TNSP Earthquake Catalogue - Eskom · 2014-07-16 · TNSP Earthquake Catalogue. F.O. Strasser & A. Mangongolo . Council of Geoscience . Report Number 2012-0166 . Rev. 0 . Confidential

TNSP Earthquake Catalogue

F.O. Strasser & A. Mangongolo

Council of Geoscience

Report Number 2012-0166 Rev. 0

Confidential

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ii

DOCUMENT APPROVAL SHEET

REFERENCE:

CGS REPORT

2012-0166

ESKOM

REVISION

0

COPY No.

TNSP Earthquake Catalogue DATE OF RELEASE:

18 January 2013

CONFIDENTIAL

REVISION DESCRIPTION OF REVISION DATE MINOR

REVISIONS

APPROVAL

AUTHORS

COMPILED BY:

COMPILED BY:

COMPILED BY: ACCEPTED BY:

F.O. STRASSER A. MANGONGOLO N. Keyser

REVIEWED BY:

ACCEPTED BY: AUTHORISED BY:

G. Graham

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Executive Summary

An earthquake catalogue has been compiled specifically for the assessment of seismic hazard at the Thyspunt site on the southern coast of South Africa in the Eastern Cape Province. The catalogue includes all known earthquakes that have occurred within the study area between 28°S and 38.5°S and between 15°E and 33°E. The catalogue was compiled using all available sources of data identified by the project participants, including historical accounts of earthquake shaking (from sources held in South African and in European archives) and instrumental recordings (from national, regional and global seismograph networks). Only tectonic earthquakes are included in the catalogue, with all events induced by mining activity and reservoir impounding removed. Epicentral locations have been reviewed in order to determine best estimate locations and associated uncertainties. Routine earthquake locations in South Africa are conducted using constrained focal depths, but for a subset of the events in the catalogue analyses have been conducted using waveform modelling of depth phases in order to estimate focal depths. These results indicate that earthquakes in South Africa generally occur within the uppermost 20km of the crust. The earthquakes are all assigned a moment magnitude, estimated from intensities for historical events and in most cases converted from other magnitude scales for instrumentally-recorded events. The adopted conversions from intensities and other magnitude scales were checked using South African data and are believed to be well suited to this region. The final catalogue indicates both how each moment magnitude was obtained and the associated uncertainty. The primary focus in compiling the catalogue was to develop a database of earthquakes that could be used as the basis for estimating recurrence rates. Once the catalogue was compiled and homogenised in terms of magnitude, declustering algorithms were applied to identify dependent events (foreshocks and aftershocks), which are retained in the final catalogue but flagged for easy identification and removal in the recurrence calculations. The final catalogue contains 2,239 earthquake events that occurred between 1690 and 2011. Almost 39% of the events are identified as being dependent, 95% of these being smaller than Mw 4.0. The remaining 1,371 independent earthquake events have moment magnitudes from 1.3 to 6.4, with 92% of the events being smaller than Mw 4.0. A mere 105 independent earthquake events of larger magnitude are included in the final catalogue. The final stage of the work was to conduct completeness analyses which included the development of models for probability of detection as a function of space and time, taking into account the statistics of the instrumental data as well as historical considerations in terms of likelihood of detection. The completeness intervals are calculated for each of the seismic source zones defined for the PSHA. The results for the ECC source zone within which the Thyspunt site is located indicate that the catalogue is complete from 1820 for events of magnitude Mw 6.5 and above and from 1910 for events of magnitude Mw 5.5 and above. Thus, the small number of events recorded in this zone reflect genuinely low levels of local seismicity.


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Table of Contents

DOCUMENT APPROVAL SHEET ............................................................................................. ii Executive Summary ................................................................................................................ iii Table of Contents .................................................................................................................... iv

Acknowledgements .................................................................................................................. 1

1. Introduction ...................................................................................................................... 3

1.1. Scope of study ............................................................................................................. 3

1.1.1. Geographic extent ................................................................................................. 3

1.1.2. Magnitude cut-off .................................................................................................. 4

1.1.3. Types of earthquakes investigated ........................................................................ 4

1.1.4. Time span covered................................................................................................ 6

1.2. Structure of report ........................................................................................................ 6

2. Data Sources .................................................................................................................... 7

2.1. Seismic monitoring in South Africa and neighbouring regions ...................................... 7

2.1.1. Royal Observatory at the Cape of Good Hope (CGH and CTO) ............................ 8

2.1.2. Union Observatory (JOH) ...................................................................................... 8

2.1.3. Cape Town University (CTO) ................................................................................ 9

2.1.4. Geological Survey (PRE, GRM, KIM, PMB, WIN) ................................................. 9

2.1.5. Bernard Price Institute (BPI) ................................................................................ 10

2.1.6. Hermanus Magnetic Observatory (HER) ............................................................. 12

2.1.7. Ceres temporary network .................................................................................... 12

2.1.8. South African National Seismograph Network (SANSN) ..................................... 12

2.1.9. Seismological stations in neighbouring countries ................................................ 13

2.2. Global seismological agencies ................................................................................... 15

2.2.1. International Seismological Summary (ISS) ........................................................ 15

2.2.2. ISC Bulletin ......................................................................................................... 15

2.2.3. NEIC bulletin ....................................................................................................... 16

2.3. Historical sources and previous catalogue compilation efforts .................................... 16

2.3.1. Local contemporary sources ............................................................................... 16

2.3.2. Early seismological compilations ......................................................................... 16

2.3.3. Wood (1913) and Finsen (1950) .......................................................................... 17

2.3.4. Sieberg (1932) .................................................................................................... 17

2.3.5. Theron (1974) ..................................................................................................... 18

2.3.6. Fernández & Gúzman (1979) .............................................................................. 18

2.3.7. De Klerk & Read (1988) ...................................................................................... 18

2.3.8. Ambraseys & Adams (1991, 1992) ...................................................................... 18


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2.3.9. Midzi et al. (1999) ............................................................................................... 19

2.3.10. Brandt et al. (2005) ............................................................................................. 19

2.3.11. Albini (2012) ........................................................................................................ 19

2.4. Macroseismic Data ..................................................................................................... 20

2.4.1. Intensity data points ............................................................................................ 20

2.4.2. Isoseismal maps ................................................................................................. 20

2.5. Studies of individual events ........................................................................................ 20

3. Epicentral Locations ...................................................................................................... 22

3.1. Historical (pre-1899) Data .......................................................................................... 23

3.1.1. Events included in Albini (2012) .......................................................................... 23

3.1.2. Other events ....................................................................................................... 29

3.2. Early Instrumental (1899-1969) Data.......................................................................... 29

3.2.1. Pre-1949 data ..................................................................................................... 29

3.2.2. 1949-1969 data ................................................................................................... 32

3.3. Ceres Sequence (1969-1971) .................................................................................... 33

3.4. Modern Instrumental (1970-2011) Data ...................................................................... 35

3.5. Treatment of Location Uncertainties ........................................................................... 37

3.5.1. Instrumental data ................................................................................................ 37

3.5.2. Macroseismic data .............................................................................................. 38

4. Depth of South African earthquakes ............................................................................. 44

4.1. Crustal Thickness....................................................................................................... 44

4.2. Routine Location Procedure and Depth ...................................................................... 45

4.3. Well-constrained instrumental depths from event-specific studies .............................. 46

4.3.1. 1969-1970 Ceres sequence ................................................................................ 46

4.3.2. 1976 Koffiefontein event ..................................................................................... 47

4.3.3. 1986 Matatiele .................................................................................................... 47

4.3.4. 1989 SA-Lesotho border ..................................................................................... 47

4.4. Additional depths determined using depths phases .................................................... 47

4.4.1. Methodology ....................................................................................................... 47

4.4.2. 2008-2011 Augrabies swarm .............................................................................. 48

4.4.3. Re-analysis of selected events recorded by the SASE array ............................... 49

4.5. Depth from macroseismic intensity observations ........................................................ 52

5. Homogenisation of Magnitudes .................................................................................... 55

5.1. Target magnitude scale and available magnitudes ..................................................... 55

5.1.1. Target magnitude ................................................................................................ 55

5.1.2. Available Mw values............................................................................................. 55

5.1.3. Other magnitude scales considered .................................................................... 56


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5.2. Conversion from local magnitude ............................................................................... 57

5.2.1. Calibration of South African local magnitude ....................................................... 57

5.2.2. Uniformisation of local magnitude values ............................................................ 60

5.2.3. Conversion from ML* to Mw .................................................................................. 62

5.3. Conversion from body-wave magnitude mb ................................................................ 67

5.4. Conversion from surface-wave magnitude MS ............................................................ 69

5.5. Conversion from Gutenberg-Richter magnitude MGR .................................................. 69

5.6. Conversion from Bulawayo magnitude mBUL ............................................................... 70

5.7. Estimation of magnitudes from intensity data ............................................................. 71

5.7.1. Events with an IDP field ...................................................................................... 71

5.7.2. Events with isoseismal maps .............................................................................. 73

5.7.3. Events for which only Imax is available .................................................................. 73

5.8. Magnitude Uncertainties............................................................................................. 74

5.8.1. Magnitude uncertainties for instrumental data ..................................................... 75

5.8.2. Magnitude uncertainties for macroseismic data ................................................... 77

5.8.3. Summary ............................................................................................................ 79

6. Catalogue declustering .................................................................................................. 80

6.1. Options for identification of dependent events ............................................................ 80

6.1.1. Window-based approaches ................................................................................. 80

6.1.2. Cluster-link models .............................................................................................. 81

6.1.3. Rate-based approaches ...................................................................................... 83

6.2. Selection of declustering approach ............................................................................ 83

6.2.1. Poissonian nature of output ................................................................................. 84

6.2.2. Calibration and parameterisation ......................................................................... 86

6.2.3. Relative performance compared to other methods .............................................. 86

6.3. Application to TNSP catalogue ................................................................................... 87

6.3.1. Subset of modern instrumental data .................................................................... 87

6.3.2. Application to the full catalogue ........................................................................... 88

6.4. Results for selected clusters ...................................................................................... 89

7. Catalogue Completeness ............................................................................................... 92

7.1. Overview of approaches available .............................................................................. 92

7.1.1. Statistical approaches ......................................................................................... 92

7.1.2. Historical approaches .......................................................................................... 93

7.1.3. Probability of detection approach ........................................................................ 93

7.1.4. Approach adopted in present study ..................................................................... 93

7.2. Historical considerations ............................................................................................ 94

7.3. Instrumental considerations ....................................................................................... 97


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7.3.1. Local networks .................................................................................................... 97

7.3.2. Global networks .................................................................................................. 99

7.4. Time intervals for completeness ............................................................................... 101

7.5. Spatial variations in completeness ........................................................................... 101

7.6. Probability of detection in space and time ................................................................ 103

8. References .................................................................................................................... 110

Appendix A: TNSP Catalogue................................................................................................ A1

Appendix B: Review Annotation Form ................................................................................. B1


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Acknowledgements

The work summarised in this report has benefited from input from many people in a number of different ways, and the final product would not have been of the same quality without these contributions. At early stages of the project, considerable input was provided in the form of advice, orientation, references and general guidance by Professor Stefan Wiemer and his colleagues at the Swiss Seismological Service at ETH, Zurich. During a working meeting held in Zurich in December 2008, a delegation from the project (Julian Bommer, Martin Brandt, Kevin Coppersmith, Erna Hattingh and Ian Saunders) enjoyed extensive interactions with the SED team and were able to gain considerable insight regarding ways to tackle issues related to the compilation and processing of the earthquake catalogue. Martin Brandt and Ian Saunders subsequently provided extensive input to this work through provision of the raw data from the CGS earthquake archives, as well as through sharing their knowledge of the history, development and current status of the national seismograph network in South Africa. In this regard, a special mention must also be made of the considerable time and effort that Prof. Andreas Rietbrock from the University of Liverpool made in helping to identify and resolve some calibration issues with several instruments in the current network. Tim Molea was particularly helpful in terms of providing access to the extensive collection of seismological data held by CGS including analogue seismograms and historical bulletins. Dr Vunganai Midzi helped with clarifications regarding data from the Bulawayo seismic network and other earthquake observatories in Africa. Thanks are due also to others who assisted with access to relevant data, including the staff at the CSIR archive in Pretoria for providing access to material from the Union Observatory. Many thanks are also due to staff at theCape Town University library for their assistance in locating and retrieving documents on South African earthquakes. Finally, archiving projects such as EUROSISMOS greatly facilitated the work undertaken by making full collections of historical seismological bulletins available online. The compilation of the historical earthquake catalogue was led and coordinated by Dr Paola Albini of INGV, Milan, who brought to this task extensive experience and unique expertise in the field of historical seismology. Dr Albini was greatly assisted in her efforts to retrieve historical accounts of earthquake effects in South Africa by Nicky Flint, particularly for Dutch and Afrikaans sources. In terms of analysing the compiled data, particularly in terms of estimating magnitudes from intensities of historical earthquakes and in de-clustering of earthquake catalogues, Dr Céline Beauval of ISTerre in Grenoble provided extensive guidance and review. Dr Beauval also provided a detailed formal review of the draft version of this report.


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Many invaluable insights into the intricacies of catalogue completeness analyses and quantification of uncertainties associated with magnitude determinations were provided by Dr Bob Youngs of AMEC. Dr Julian Bommer assisted extensively with reviewing various parts of this report at different stages, and helped to guide it through the process of completion.


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1. Introduction

This report presents the seismicity catalogue developed for the Thyspunt Nuclear Siting Project

(TNSP), a SSHAC Level 3 probabilistic hazard analysis (PSHA) for a new-build nuclear site on

the southern coast of South Africa (Bommer & Coppersmith, 2010).

1.1. Scope of study

This Section defines the scope of the catalogue compilation study in terms of geographic extent,

minimum magnitude, and type of seismicity investigated.

1.1.1. Geographic extent

The boundaries of the region for which the seismicity catalogue is compiled have to be selected

in such a way as to cover the geographic extent of the source zones that have been identified

as potential contributors to the seismic hazard at the site. In view of the very low level of seismic

activity in the vicinity of the site, the seismic sources zones considered in the preliminary

seismic source characterisation (SSC) model extend considerably beyond the 320km regulatory

radius defined in RG 1.208 (USNRC, 2007). The seismicity catalogue documented therefore

covers the region stretching from latitude -40° to -28° north, and 15° to 33° longitude east, as

illustrated in Figure 1.1.

Figure 1.1 Extent of catalogue study region.


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1.1.2. Magnitude cut-off

Although RG 1.208 (USNRC, 2007) requires a minimum magnitude of Mmin=5.0 to be

considered in the hazard calculations, a lower limit of ML ≥ 3.0 is chosen for the catalogue

development because of the greater abundance of data at lower magnitudes that provides

constraint both on spatial distribution of seismicity in South Africa and on recurrence relations.

However, below this limit the uncertainties associated with source parameters become very

large, counteracting the benefits of increasing the sample size. Small-magnitude earthquakes

have also been shown to exhibit different scaling behaviour than those in the magnitude range

of interest to the TNSP project. Finally, a prior assessment of completeness suggests that the

record becomes very incomplete below the ML 3.0 threshold except for the most recent time

period, further limiting the usefulness of data below this threshold.

1.1.3. Types of earthquakes investigated

The TNSP project is concerned exclusively with seismic hazard from tectonic sources, hence

any seismic events related to human activity, such as explosions, quarry blasts, rockbursts and

mining-related events, as well as events related to reservoir impoundment, are excluded from

the present study.

The seismic events encountered in the Southern Africa region are generally classified into the

following types (e.g., Gibowicz & Kijko, 1994):

• Tectonic events: these are earthquakes occurring naturally due to slip on seismogenic

faults; in stable continental regions, tectonic earthquakes can reach moderate-to-large

(M 6 to 7) magnitudes, although the occurrence of such events is infrequent.

• Mining-related events: these are earthquakes occurring on tectonic faults, but which

are thought to have been induced by the stress changes created by mining activities;

such events can occasionally reach moderate magnitudes (M 4 to 5). However, ground

motions from mining-related earthquakes attenuate much faster with distance than those

from tectonic earthquakes (due to higher frequency content of the motions and shallower

depth of the events), therefore these events are not expected to generate surface

ground motions of engineering significance except in the immediate vicinity of the source.

• Rockbursts and explosions: these are events directly related to mining operations

(e.g., blasting); such events are too small (M<3) to generate ground motions that could

affect engineered structures located outside the perimeter of the mine.

• Reservoir-induced events: these are events related to the impounding of large

reservoirs.


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Explosions, rockbursts and mining-related events are identified based on location and

waveform aspect as part of the routine processing procedure of seismic data at the Council for

Geoscience, and flagged by using a different fixed depth from that used for tectonic events,

hence are straightforward to eliminate. The magnitude cut-off at ML = 3.0 would eliminate the

vast majority of these events. Note that the occurrence of moderate-magnitude mining-related

events is primarily associated with deep mining activities (gold and platinum mines), which are

concentrated in the northern and central part of the country, and largely fall outside the study

region (Figure 1.2). The Free State Gold Mines region partially falls within the study region,

requiring mining-related events to be eliminated using a location-based criterion, particularly for

solutions from networks other than the South African National Network (SANSN), which may not

identify the event as anthropogenic. For convenience, the boundaries selected for the

elimination of Free State Gold Mines events are taken as a rectangular area delimited by

latitudes -28.4° to -27.6° north, longitudes 26.4° to 27.1° east, indicated as an orange rectangle

in Figure 1.2.

Figure 1.2 Location of South African gold-mining areas and Lesotho Highlands Water Project. The green triangle identifies the location of the site, the green rectangle the extent of the catalogue study region. The seismicity shown is taken from the unprocessed CGS database for the years 1620-2008.


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Another source of anthropogenic seismicity that could potentially contaminate the catalogue is

the reservoir-induced seismicity associated with the impoundment of the Katse Dam reservoir in

northern Lesotho as part of the Lesotho Highlands Water Project. Brandt (2000) investigated

this reservoir-induced seismicity and found that the largest event of this type was a magnitude

ML 3.0 event that occurred in on 3 January 1996 some 5 km upstream of the dam wall. This

event was removed manually, while the ML 3.0 cut-off removed all other reservoir-induced

events. As a result, all events discussed in the present study can be considered as being of

tectonic origin, unless explicitly stated otherwise.

1.1.4. Time span covered

The catalogue developed in the present report covers all known events in the region of study up

to and including December 2011.

1.2. Structure of report

Following this brief introduction, Chapter 2 provides an overview of the data sources used in the

catalogue compilation.

The following chapters go on to discuss the determination of source parameters. Chapter 3

deals with the catalogue compilation, focusing in particular on the selection of the preferred

origin time and epicentral location for each earthquake, as well as associated uncertainties.

Chapters 4 summarises the information available regarding earthquake hypocentral depths.

This is followed by a set of chapters providing an overview of the catalogue analysis steps

undertaken. Chapter 5 summarises the homogeneisation of the catalogue in magnitude.

Chapter 6 describes the catalogue declustering process, in which dependent events such as

foreshocks and aftershocks are removed. This is followed by an assessment of catalogue

completeness in Chapter 7.


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2. Data Sources

Seismicity catalogues are generally compiled from multiple primary data sources, often updating

and cross-checking previous compilations. The following sections discuss the sources of

information available for the extraction of earthquake parameters for the region of interest, since

these were used in the reappraisal of the source parameters of the events in the catalogue. The

nature of the information available is closely linked to the history of seismic monitoring in South

Africa and neighbouring countries, which is detailed in the following sections. This is followed by

a summary overview of historical sources and previous catalogue compilation efforts.

2.1. Seismic monitoring in South Africa and neighbouring regions

This section provides a brief historical overview of seismic monitoring in South Africa and

neighbouring regions. A map of early seismograph stations discussed in this section is shown in

Figure 2.1. Details of the histories of the individual stations are taken from the references and

materials cited, as well as the summaries by Fernández & Wright (2003) and Saunders et al.

(2008).

Figure 2.1 Location of early seismograph stations in the South African region. Yellow symbols indicate stations that were operational before 1949, red symbols those that started operating after this date. The green rectangle indicates the boundaries of the study region.


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2.1.1. Royal Observatory at the Cape of Good Hope (CGH and CTO)

From its establishment in 1820 as the first permanent scientific institution in the southern

hemisphere, the Royal Observatory of the Cape of Good Hope (ROCGH) in Cape Town

contributed to seismic monitoring by the publication of letters or notices in the few instances of

events sufficiently large to be widely felt (e.g., Maclear, 1835; Morton, 1857). A Milne instrument

(CGH) was installed at the Royal Observatory in August 1899, and the first local earthquake

recorded on 15 September 1899. Readings from this instrument are preserved in the so-called

“Shide Circulars” published by the British Association for the Advancement of Science, later to

become the International Seismic Summary (ISS). Readings were also communicated to the

German Seismological service then based in Strasbourg. The Milne instrument was upgraded

to a Milne-Shaw in late 1920. At the end of 1931, operation of the seismograph ceased and the

instrument was moved to the Department of Applied Mathematics of the University of Cape

Town, with the station code becoming CTO (see Section 2.1.3). While phase readings were

communicated regularly to international organisations throughout the operation of the

instrument, there is no record of studies dealing specifically with local or regional events. This is

not altogether surprising, since the low damping and low resolution of the instrument is not

conducive to the monitoring of such events, but would point towards the absence of any

remarkable recording from a local or regional event during the operation of the instrument.

2.1.2. Union Observatory (JOH)

A 200kg Wiechert seismograph was operated at the Union Observatory in Johannesburg

between July 1910 and April 1972. Whilst the primary focus of the seismological research

undertaken at this observatory was the monitoring of seismic activity related to gold mining

operations on the Witwatersrand, the continuous operation of this seismograph and the

collection of macroseismic information contributes valuable information to the catalogue of

South African tectonic events over this period, as detailed below.

2.1.2.1. Wood (1913)

Wood (1913) provides the first systematic catalogue of South African earthquakes, listing 44

earthquakes that occurred between 1906 and 1912. The list is based on the reports received at

the Transvaal Meteorological Department (later the Union Observatory) in Johannesburg,

focusing essentially on the eastern part of the country, since seismicity in the Cape Province

was primarily monitored at the Royal Observatory in Cape Town (see above). The study also

includes isoseismal maps for three larger events.

2.1.2.2. Finsen (1950)

The list compiled by Finsen (1950) updates the summary of Wood (1913) with dates, times,

locations and observations of felt effects of seismic events until the end of 1949. Again, this


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compilation is based on reports received by the Union Observatory in Johannesburg, hence

biased towards the east of the country, particularly for reports of smaller events only felt locally.

However, Finsen (1950) also listed historical events occurring from 1695 to 1891 inferred from

various historical sources, the vast majority of which are reported from Cape Town and localities

along the western coast of South Africa. A total of 239 events are listed in this compilation,

which is limited to events of tectonic origin.

2.1.2.3. Other materials

While the recordings of the Wiechert seismograph operated at the Union Observatory have

been lost, the complete set of log-books for this seismograph has survived, providing phase

readings and in some instances double amplitudes for larger tectonic events. While this

information is in itself insufficient to determine source parameters, it provides valuable

constraints and checks on solutions based on other types of data (teleseismic and/or

macroseismic). The log-books also include numerous newspaper clippings regarding felt effects

of larger events, which were incorporated in the assessment of macroseismic intensities

undertaken as part of the TNSP project (Albini, 2012; Midzi et al., 2012).

2.1.3. Cape Town University (CTO)

The Milne-Shaw instrument of the Royal Observatory was moved to the Department of Applied

Mathematics of the University of Cape Town, where it was operational, along with another

horizontal Milne-Shaw instrument, from about 1935 to 1947. A bulletin was published for part of

this period (Gane & Oliver, 1953), however no copies thereof could be traced. The original

recordings, however, survive and are stored as part of the Council for Geoscience’s

seismological archive. These recordings, which are in the process of being digitised to enable

more detailed analysis, were considered by Fernandez & Guzman (1979) in the development of

their historical catalogue.

2.1.4. Geological Survey (PRE, GRM, KIM, PMB, WIN)

The Geological Survey of South Africa became involved in seismic monitoring in the first part of

the 20th century through the installation the first national network of seismographs in 1949, as

well as the collection of macroseismic information.

2.1.4.1. Macroseismic monitoring

Based on the information collected from the public through postal intensity surveys and

newspaper reports, Krige (1933), Krige & Venter (1936) and Krige & Maree (1948) published

monographs including isoseismal maps of 14 events having occurred in South Africa between

1932 and 1944. This information was incorporated in the assessment of macroseismic


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intensities undertaken as part of the TNSP project (Albini, 2012; Midzi et al., 2012), and used in

the present study to determine source parameters of the events in question.

2.1.4.2. Geological Survey Network

From 1949 to 1951, short-period Benioff seismographs were installed in Kimberley (KIM in

Figure 2.1), Grahamstown (GRM), Pietermaritzburg (PMB) and Pretoria (PRE), as well as at a

station in Windhoek (Namibia, WIN). The Pretoria, Grahamstown and Windhoek stations were

upgraded in 1965 to form part of the World Wide Standard Seismograph Network (WWSSN).

Analysis of the recordings was the Bernard Price Institute of Geophysics (BPI) of the University

of the Witwatersrand in Johannesburg, as described below, with the phase readings published

as monthly bulletins. Towards the middle of 1968, a reorganisation of the South African

scientific institutions caused the suspension of the publication of the bulletins from September

1968 to July 1970 inclusive. This interruption is particularly unfortunate in view of the

occurrence of the Mw 6.2 Ceres event on 29 September 1969, which yielded a rich aftershock

sequence. The WWSSN stations at Pretoria, Grahamstown and Windhoek, however, continued

to report to international institutions such as the International Seismological Centre, so some

arrival times from this period have survived.

2.1.5. Bernard Price Institute (BPI)

An 80kg Wiechert horizontal seismograph was briefly operational at BPI from 1938 to 1939, but

was then moved to Maputo in Mozambique (Gane & Oliver, 1953), where it became operational

as station LMM in 1951 (see 2.1.9.2). BPI staff were heavily involved in research into the

seismicity associated with mining activity on the Witwatersrand and the local crustal structure

(e.g., Gane et al., 1956), but also contributed to the monitoring of tectonic seismicity through the

analysis of the data recorded on the Geological Survey network.

2.1.5.1. Geological Survey network bulletins

BPI staff were responsible for collating and analysing the data of the Geological Survey Network

for the whole period of operation of the network (1949 to 1968). The phase readings and

locations were published as a monthly bulletin, of which a whole set has survived. As noted

previously, production of the bulletins ceased in September 1968. From 1959 to 1964, the

bulletins for the Bulawayo network were produced in parallel using the same format.


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2.1.5.2. Gane & Oliver (1953) and Oliver (1956, 1970)

Based on the information compiled in the monthly bulletins of the Geological Survey network,

Gane & Oliver (1953) and Oliver (1956) listed compilations of earthquakes in the southern

African region detected by this network. These compilations cover the years 1949-1952 and

1953-1955 respectively, and were later supplemented by an unpublished list covering the years

1956-1968 (Oliver, 1970). Exact locations (i.e., epicentral coordinates) are only provided for the

subset of events for which recordings at three or more stations are available. For the other

events, the earthquake location is given only as a geographical region, sometimes

supplemented by the distance from a single station.

These catalogues also list local magnitude (ML) values for some of the larger events. Johnston

et al. (1994) stated that the values of ML listed by Gane & Oliver (1953) and Oliver (1956, 1970)

were likely to have been inferred from maximum intensity values, and for this reason discounted

them in their assessment of moment magnitudes. However, Gane & Oliver (1953) clearly

describe how these values were determined from the instrumental recordings obtained on the

short-period Benioff seismographs. Hand-written index cards detailing the published solutions,

an example of which is shown in Figure 2.2, have survived for the period 1949 to 1954, and

confirm the instrumental nature of the magnitude determinations.

Figure 2.2 Index card illustrating source parameter determination procedure used by BPI, for the 26 January 1952 Southern Sutherland District earthquake.


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2.1.6. Hermanus Magnetic Observatory (HER)

The Milne-Shaw instrument that was located at the University of Cape Town was moved to the

magnetic observatory at Hermanus at the end of 1950. The low gain of the instrument and the

noise from oceanic waves led to recordings from this instrument to be more useful for

teleseismic determinations (phase readings were reported to the ISC) than for local

determinations. Nevertheless, it contributed to the epicentral determinations for the 1969-1971

Ceres sequence (Goetz Observatory, 1972) by providing arrival-time constraints.

2.1.7. Ceres temporary network

Following the occurrence of the Mw 6.2 Ceres earthquake, a temporary network of five mobile

stations was deployed in the epicentral region (Green & Bloch, 1971). The network recorded

more than 2,000 events during its first five weeks of operation. The number of stations was later

reduced to three for operational reasons. This deployment enabled the accurate location of 125

events. Unfortunately, with the exception of the largest aftershocks, the location parameters of

these events are only provided in graphical form by Green & Bloch (1971), and therefore they

are most useful in terms of delimiting the causative source of this event. The non-inclusion of

these events in the TNSP catalogue ultimately has little impact on the final hazard, since they

are dependent events that would have been removed at the declustering stage (see Chapter 7).

2.1.8. South African National Seismograph Network (SANSN)

Following the 1969 destructive earthquake in the Tulbagh/Ceres region and the reorganisation

of the South African Astronomical Observatories, the responsibility of monitoring seismicity at a

national level fell to the Geological Survey, now the Council for Geoscience (CGS). The South

African National Seismic Network (SANSN), described in detail in Saunders et al. (2008), was

established as a network of 7 stations in 1970, and currently includes 28 permanent stations

(Figure 2.3). From 1991 onwards, analogue instruments were supplemented and eventually

replaced by digital instruments.

The data collected through the SANSN is processed by staff of the Seismology Unit of CGS and

published in the form of regular bulletins (currently issued on a quarterly basis), as well as a

yearly catalogue summarising the source parameters of all earthquakes recorded by the

SANSN. The digital database underlying these publications constitutes the primary source of

modern instrumental data for the compilation of the catalogue presented in the current report.


13

Figure 2.3 Map of the SANSN network (Saunders et al., 2008).

2.1.9. Seismological stations in neighbouring countries

As a consequence of its location at the southern tip of Africa, South Africa has few neighbour

states that are in a position to contribute readings that will help constrain locations of regional

events. A number of networks from neighbouring countries nevertheless contributed data to the

present catalogue, an overview of which is given in this section.

2.1.9.1. Goetz Observatory, Bulawayo, Zimbabwe

Outside South Africa, the main contributor of regional seismological data is the network

operated from 1959 onwards by the Goetz Observatory in Bulawayo. As shown in Figure 2.1

and Figure 2.3 this network included stations in present-day Zimbabwe (BUL, CIR, MTD, KRR),

Zambia (BHA) and Malawi (CLK). From 1959 to 1964, the data was analysed at BPI, after which

the responsibility was passed on to the Goetz Observatory. Epicentral solutions and magnitudes

were determined for both local and regional events. Figure 2.3 shows that the study region lies

on the margins of the region covered by this network.


14

Figure 2.4: Stations of the Bulawayo network (Chow et al., 1980). The green rectangle indicates the approximate extent of the region considered in the present study.

2.1.9.2. Mozambique

A station was operational at Maputo (then Lourenço Marques, LMM in Figure 2.1) from 1951

onwards. Another station of interest is the Changalane station (CNG in Figure 2.1), which was

operational from the mid-1950s onwards and regularly provided readings to the International

Seismological Centre. These stations helped constraining the locations of some of the events in

the catalogue.

2.1.9.3. Namibia

Instrumental recordings in Namibia started with the installation of the Windhoek (WIN in Figure

2.1) station in 1951. Recordings from this station were routinely incorporated into the South

African bulletins. Data recorded in Namibia continues to be exchanged with South Africa on a

regular basis to the present day.

2.1.9.4. Botswana

The permanent station in Lobatse (LBTB) near the South African border is incorporated in the

South African National Seismograph Network.

2.1.9.5. Madagascar (TAN)

Early seismographs of Italian design were installed by the Jesuits at the Geophysical

Observatory in Antananarivo (then Tananarive, TAN in Figure 2.1) in 1899 and upgraded to a 3-

component, 460 kg Mainka instrument in 1827 (Udías & Stauder, 1996) . Seismological reports

from Madagascar were included in the bulletins of the French network during colonial times, and


15

the TAN station was a regular contributor to global data listings (see Section 2.2), providing

useful constraints for a number of events in the South African region.

2.2. Global seismological agencies

In addition to local sources, information about source parameters of South African earthquakes

can be retrieved from compilations of earthquakes determined at the global scale by

international agencies. These sources are reviewed below.

2.2.1. International Seismological Summary (ISS)

The South African stations regularly contributed to the International Seismological Summary

(ISS), which constitutes one of the main sources of information for instrumentally recorded

earthquakes in the time span between its inception (1918) and the establishment of the World

Wide Standardised Seismographic Network (WWSSN) in the 1960s. The phase readings listed

in the ISS bulletins scanned and made available as part of the EUROSISMOS project were

retrieved and used in the checking of the few events in the catalogue region featuring in this

compilation. The ISS bulletins also provide the data for the re-analyses of events by Gutenberg

& Richter (1958) and Engdahl et al. (1998).

2.2.2. ISC Bulletin

The International Seismological Centre (ISC) was founded in 1964 concurrently with the

establishment of the WWSSN. Its mission was to continue the gathering of instrumental

recordings worldwide, previously undertaken by the International Seismological Summary (ISS),

in order to calculate source parameters that are well constrained.

The ISC Bulletin typically presents the source parameters calculated by the individual agencies

contributing the data, followed by a reappraised solution considering all available data

calculated by ISC staff.

For the southern Africa region, the ISC Bulletin lists source parameters from 1964 onwards,

contributed mainly by the CGS (or its predecessor, the Geological Survey) and the Goetz

Observatory at Bulawayo (BUL). The National Earthquake Information Center (NEIC) of the US

Geological Survey also contributes solutions for larger events, but these have been found to be

less well-constrained and hence less reliable than the ISC solutions as far as the southern

Africa region is concerned. Other organisations, including the Geological Survey Department of

Zambia, and the Geophysical Survey of the Russian Academy of Sciences, also occasionally


16

contribute sets of source parameters, but their solutions are generally unreliable due to the

limited number of recordings used, as well as the large distance from the source at which these

recordings were obtained. In consequence, only solutions contributed by BUL or reappraisals

by the ISC are considered in the present study as alternatives to those determined by the CGS.

2.2.3. NEIC bulletin

As noted above, most of the solutions published by the NEIC are included in the ISC bulletin.

Exceptions include the most recent data (2009-2011), for which the ISC solutions had not yet

been reviewed, but solutions were published by NEIC. Also, the determinations circulated by

the US Coast and Geodetic Survey (USCGS) contributed international teleseismic solutions in

particular for the period prior to 1964.

2.3. Historical sources and previous catalogue compilation efforts

In addition to the systematic compilations of instrumentally recorded data released by the

operating networks described above, a number of regional earthquake catalogues based on

instrumental recordings, but also on reports of felt effects, have been compiled. These cover in

particular the historical (pre-1900) and early instrumental (1900-1969) periods.

2.3.1. Local contemporary sources

A number of local contemporary reports of historical earthquakes have been collected by South

African researchers over time. These are not discussed in detail here, as they appear in

interpreted form in subsequent studies. For the region of interest, additional material of this

nature has been collected by Albini (2012), discussed below, within the TNSP project.

2.3.2. Early seismological compilations

Early seismological compilations, whether contemporaneous with the events compiled, or

collated at a later date, are the principal contributors of data up to the 1960s-1970s. An

important aspect to acknowledge is the overlap and interdependencies that exist between these

different compilations, as illustrated in Figure 2.4, reproduced from Albini (2012).


17

Figure 2.5 Relationships between early seismological compilations considered in Albini (2012). Entries in italics correspond to information pertaining to a single event or a small number of individual events, while the other entries refer to more extensive compilations.

2.3.3. Wood (1913) and Finsen (1950)

The compilations by Wood (1913) and Finsen (1950) represent a summary of the information

gathered at the Union Observatory in Johannesburg. While the compilation includes some

instrumental information, the listings are predominantly based on macroseismic information

gathered from newspaper clippings or reports sent by members of the public to the observatory,

which is presented in summary form. Finsen (1950) incorporates the earlier study by Wood

(1913) and whenever possible provides coordinates for epicentral locations and locations of

intensity observations. No magnitudes are provided.

2.3.4. Sieberg (1932)

The global compilation by Sieberg (1932) lists a number of events for the region of interest. This

compilation has been found problematic by historical seismologists (e.g., Ambraseys et al.,

1994) in that the author does not cite his primary references, and on occasions includes fake or

spurious events due to gross mislocations or limited evidence. The events listed in Sieberg

(1932) for the 20th century match the local records of Wood (1913) and Finsen (1950). Events

listed for earlier dates were reviewed, but no new events were added from this compilation

since it was found that events that were not already listed in South African sources were either

Ambraseys & Adams 1991; 1992

De Klerk & Read 1988

Fernandez & Guzman 1979

Finsen 1950

Theron 1974

Frankel 1936

Skead 1974

Krige & Venter 1933

Wood 1913

Sieberg 1932

Brandt et al. 2005

Ambraseys & Adams 1991; 1992

De Klerk & Read 1988

Fernandez & Guzman 1979

Finsen 1950

Theron 1974

Frankel 1936

Skead 1974

Krige & Venter 1933

Wood 1913

Sieberg 1932

Brandt et al. 2005


18

gross mislocations (e.g., a 1882 event “near the Cape Coast” which was in fact felt in Cape

Coast Castle near Accra, Ghana) or missing local data to support their occurrence.

2.3.5. Theron (1974)

The compilation by Theron (1974), published as part of a special publication of the Geological

Survey dedicated to the 1969 Ceres event and its aftershock sequence, is the first listing of

events compiled specifically for the Western Cape region. It includes 50 events that occurred

between 1620 and 1971, for which a description of the felt effects could be found. These

descriptions are accompanied by maximum intensity values which have been deduced from

available information. Theron (1974) also lists magnitude values, but notes that these are

deduced from intensity values. Locations are provided only in the form of geographical place

names; no epicentral coordinates are provided.

2.3.6. Fernández & Gúzman (1979)

The compilation by Fernández & Gúzman (1979) is the first catalogue systematically listing

times, epicentral coordinates and magnitudes for events in southern Africa, covering South

Africa and neighbouring countries (Namibia, Botswana, Zimbabwe, Mozambique). This

catalogue reappraises the studies described in preceding sections as well as including

additional information gathered from sources including archival records, seismological bulletins

and unpublished seismograph recordings obtained at the University of Cape Town. Epicentral

coordinates and magnitude estimates in terms of the local magnitude scale used in the routine

processing of SANSN data, ML, are listed for a majority of the events in this compilation, along

with epicentral intensity values. Alternative instrumental magnitude determinations on other

scales are not included. A significant proportion of the events have ML values determined from

the epicentral intensity I0, and the intensity values listed for events with instrumental magnitude

determinations mostly rely on the conversion relation being applied in reverse.

2.3.7. De Klerk & Read (1988)

De Klerk & Reed (1988) compiled a catalogue of newspaper reports spanning the time period

between 1806 and 1969. The study was focused predominantly on the Southern and Eastern

Cape regions. The information is presented in the form of non-interpreted newspaper clippings,

which are nevertheless grouped by earthquake event.

2.3.8. Ambraseys & Adams (1991, 1992)

Ambraseys & Adams (1991, 1992) reappraised the macroseismic and instrumental data for a

number of larger events located south of 20°N that occurred in the time period 1900-1930. The

focus is mostly on events associated with East African Rift. The analysis of the five southern

African events appears to rely on the local studies listed above, without collection of additional


19

intensity data. This study proves useful, however, in providing reappraised locations and

magnitudes based on re-examination of the limited instrumental recordings available.

2.3.9. Midzi et al. (1999)

The catalogue developed by Midzi et al. (1999) for the Eastern and Southern Africa Global

Seismic Hazard Assessment Program (GSHAP) study incorporated the South African catalogue

of Fernández & Gúzman (1979) and subsequent yearly catalogues published by the Council for

Geoscience. This listing is almost identical to the original sources considered, hence provides

no additional information for the purposes of the present study. Magnitudes are expressed

uniformly in terms of surface-wave magnitude MS, but the consistency of the conversions

applied and their applicability to the South African region have not been tested within that study.

2.3.10. Brandt et al. (2005)

The Fernández & Gúzman (1979) catalogue was updated by Brandt et al. (2005), who revised

the source parameters of historical earthquakes from the Finsen (1950) and Theron (1974), and

included several previously unlisted events based primarily on the newspaper report compilation

by De Klerk & Read (1988). Only events for which epicentral coordinates and magnitude

determinations are available have been retained in this compilation. Magnitudes are expressed

in terms of the ML scale, which in some cases were converted from magnitude values

determined using other magnitude scales. Conversions from macroseismic intensity were

performed in the same manner as in Fernández & Gúzman (1979).

2.3.11. Albini (2012)

A detailed study of the seismicity of the Southern and Eastern Cape regions was undertaken by

Albini (2012) as part of the TNSP project. This study focused in particular on the seismic history

of the region, collecting negative as well as positive evidence in order to establish historical

catalogue completeness. This study also incorporates individual studies of 15 events in the time

span 1850-1936 selected on the basis of either the proximity of their epicentral location to the

site, or, in the case of a number of larger, more distant events, their reported potential of

causing ground motions that would have been felt in the vicinity of the site. The Albini (2012)

study reviewed all previous studies listed above and thus constitutes the authoritative study for

the Southern and Eastern Cape region.


20

2.4. Macroseismic Data

2.4.1. Intensity data points

The Albini (2012) study described above is the main source of information in terms of intensity

data points (IDPs) for the historical part of the catalogue. Data for events with instrumental

source parameters were similarly compiled by Midzi et al. (1999). These compilations were

undertaken with an emphasis on uniform definition of the IDPs, both within each study and

across both studies, so that the resulting IDPs can be considered directly compatible.

2.4.2. Isoseismal maps

Isoseismal maps are maps showing contours delimiting areas of similar intensity. Since intensity

values generally decrease with distance from the epicentre due to the attenuation of seismic

waves and the size of the felt area scales with magnitude, such maps can be used to determine

the source parameters of earthquakes using empirical relations (e.g., Johnston, 1996).

Published isoseismal maps for South African events are reviewed in Midzi et al. (2012), which

describes the compilation of the intensity database for events with instrumental source

parameters used in the TNSP project.

2.5. Studies of individual events

Prior to the establishment of a seismograph network, a number of monographs about more

notable events were published by the staff of the South African Geological Survey. These

monographs focus predominantly on macroseismic information, but also present available

phase reading from the Royal Observatory (Cape Town) and Union Observatory

(Johannesburg) instruments. These publications include the monograph about the 31

December 1932 off Cape St Lucia event by Krige & Venter (1933), the monographs about the

12 and 16 January 1936 Swaziland and Fauresmith events by Krige (1936), as well as a the

Krige & Maree (1951) compilation of individual studies of 11 events having occurred in South

Africa between 1938 and 1944.

In addition to the source parameters determined as part of routine seismological monitoring,

seismological studies investigating specific events in more detail are sometimes carried out. For

the TNSP catalogue region, such studies are limited to monographs of the 1969 Ceres event

and its aftershock sequence (e.g., Green & Bloch, 1971). Most of these studies are summarised

in a special publication of the Geological Survey (van Wyk & Kent, 1974). A recent re-analysis

of the teleseismic data available for the 1969 Ceres event by Krüger et al. (2011) supplements

these studies.


21

The MSc thesis of Jensen (1991) contains monographs of three African events that have

occurred in the stable part of the continent, including the 1 July 1976 Koffiefontein event.

Similarly, a number of studies focussing predominantly on larger sub-Saharan African events

(Fairhead & Girdler, 1971; Maasha & Molnar, 1972; Fairhead & Stuart, 1982; Shudofsky, 1985;

Wagner & Langston, 1988; Foster & Jackson, 1998) or investigating the characteristics of

Stable Continental Region (SCR) earthquakes (Somerville et al., 1987; Johnston et al., 1994)

provide source parameters for the 1969 Ceres (e.g., Nowack & Boore, 1986) and 1976

Koffiefontein events.

A number of more recent studies investigate the source parameters of a few moderate South

African events (Fan & Wallace, 1995; Bowers, 1997; Brandt & Saunders, 2011), but often have

a strong focus on mining-related events.


22

3. Epicentral Locations

Using the data sources listed in Chapter 2, a catalogue was compiled using the rules outlined in

the following Sections.

In the case of multiple determinations of the source parameters (date, location and magnitude),

all possible options were reviewed and the solution considered the best constrained and/or the

best documented was retained as the preferred solution, with the remaining data informing

parameter uncertainty. This methodology was adopted in preference to a more algorithmic

approach, since the number of events with multiple solutions is relatively small, which renders

an event-by-event analysis less impractical than in the case of large datasets. Furthermore,

choice of the “best-quality” solution among different available options relies on criteria that have

been found to vary strongly from one event to another, thus hampering the development of

general rules, particularly with a limited number of events.

Note that in terms of location, this section focuses on epicentral coordinates, and hypocentral

depth is addressed separately in Section 5. Given the relatively sparse nature of the recording

network, depths of earthquakes in South Africa are not well resolved, and are in most cases

fixed in the calculations in order to obtain a more robust estimate of the epicentral coordinates.

The catalogue was divided into the following four subsets to reflect the varying nature of the

information on which the estimation of source parameters and magnitude values is based:

• Historical period: This subset includes all events reported that occurred prior to the

installation of the first seismograph in South Africa at the Royal Observatory of the Cape

of Good Hope in Cape Town in August 1899. The assessment of source parameters for

this subset is based exclusively on macroseismic data. Existing macroseismic

information was supplemented by the detailed investigation of 15 events occurring

during this period in the Southern and Eastern Cape region by Albini (2012).

• Early instrumental period: This subset includes all events reported in the study region

starting with the first instrumentally recorded South African earthquake, which occurred

in Cape Town on 15 September 1899 until the earthquake that occurred near Heidelberg

on 11 September 1969. For the first part of this period (up to 1949), instrumental

recordings mainly confirm the date and time of occurrence, and provide an approximate

location based on the distance to the recording instrument(s). A more precise location is

generally inferred from macroseismic observations. From 1949 onwards, instrumental

data becomes more plentiful with the deployment of the first South African seismological


23

network; however, locations continue to be informed or confirmed by macroseismic

information. The Albini (2012) study contributes a further 15 events to this subset of the

catalogue. Similarly, magnitude determinations are only linked to instrumental

recordings for larger events occurring during the last two decades of this period, and

based on macroseismic observations otherwise

• Ceres sequence: The Ceres sequence, defined for the purposes of this study as the 29

September 1969 mainshock and its aftershocks until and including the 28 September

1971 event, which is the last event listed in the compilation by Theron (1974). It should

be noted that this assumption is made for convenience, and does not constitute a

seismological assessment of the duration of the aftershock sequence. The events in this

subset are treated separately as they are better documented, in terms of both

instrumental and macroseismic information, than other similar-sized events from the

same period, as a result of the increased interest following the mainshock. It should

further be noted that this sequence coincides with a gap in the publication of regular

bulletins for the South African seismograph network. Locations and magnitudes are

primarily determined from instrumental data, but macroseismic observations are used to

inform the selection of source parameters among available options.

• Modern instrumental data: This subset includes all events other than the Ceres

sequence (as defined above) recorded since the establishment of the SANSN in 1970.

Locations and magnitudes for this period are determined from instrumental data, but

macroseismic observations are used in some instances to qualify the results.

The specific assumptions made in the determination of source parameters for each subset are

detailed in the following sections.

3.1. Historical (pre-1899) Data

3.1.1. Events included in Albini (2012)

For the Eastern and Southern Cape region, the authoritative primary data source is the Albini

(2012) study, which was undertaken specifically for the TNSP project. This study contributes

individual studies of 15 events for the time period up to 1899, including seven newly identified

events. As well as adding these new events, the Albini (2012) study also highlighted a number

of doubtful events, and identified a few occurrences of fake events (i.e., observations of effects

that were ascribed to earthquakes, but on inspection were revealed to be caused by another

phenomenon, such as the meteorite blaze observed in the Bloemfontein region in June 1862).


24

For events whose occurrence was confirmed, the information is provided in the form of a field of

intensity data points (IDPs) which were analysed using third-generation techniques to determine

source parameters (location and magnitude) along with their associated uncertainties.

The MEEP2 software (Musson, 2009) is used for this purpose. This software includes

implementations of four different methods for source parameter determination:

• The Bakun & Wentworth (1997) approach, which relies on the specification of an

intensity prediction equation (IPE) giving macroseismic intensity as a function of

magnitude and distance.

• The Macroseismic Estimation of Earthquake Parameters (MEEP) approach (Musson,

2009), which combines the Kövesligethy (1907) equation with the Frankel (1994) model.

The former relates the average spacing of isoseismal contours with regional attenuation

properties, and the latter provides a physically based model allowing the estimation of

magnitude based on felt area.

• A centroid method based on the BOXER algorithm of Gasperini et al. (1999), which

determines the optimal epicentral location based on the spatial distribution of the IDPs

with the highest intensity levels.

• Finally, a method based on pairwise comparisons of IDPs, which favours epicentral

locations closer to the IDP with higher intensity.

Systematic comparisons of the first three methods were undertaken as part of the NERIES

project (Musson & Jimenez, 2008; Bakun et al., 2011). This study found that while all three

methods give consistent results for well-behaved cases, systematic differences in behaviour

may arise in the event of data limitations, such as partial datasets from offshore events. All four

methods were therefore implemented in the present study, in order to obtain an estimate of the

modelling uncertainty.

The IPE used in the Bakun & Wentworth (1997) method can be specified either on the basis of

a published IPE, or by deriving a new regionally-calibrated equation using the subset of data for

which instrumentally determined parameters are available. The latter approach is commonly

implemented in studies using the Bakun & Wentworth (1997) approach (e.g., Beauval et al.,

2010; Bakun & Scotti, 2006), but it requires a minimum number of well-documented events for

the calibration. A review by Scotti (2012) of the macroseismic intensity database for events with

instrumental source parameters compiled for this project (Midzi et al., 2012) concluded that in

the South African case, there is insufficient data to allow the derivation of a well-constrained

locally-calibrated IPE, and the use of the IPE given in Eq. (3.1), which was derived for the

French-SCR region by Bakun & Scotti (2006), was recommended.


25

( )2210log37.327.148.4 hMI wMSK +∆−+= (3.1)

where Δ is epicentral distance and h is the hypocentral depth, fixed to 10 km.

This IPE has been found by Scotti (2006) to provide good agreement with macroseismic

intensity observations not only in France, but also other SCR regions (Indian Craton, Australia).

Another advantage of this IPE, illustrated in Figure 3.1, is that it represents a central tendency

amongst available options. While the data available was insufficient to derive a calibration

specific to South Africa, the subset of macroseismic intensity data with instrumentally-

determined source parameters was used to check the performance of the Bakun & Scotti (2006)

IPE for a given intensity, as illustrated in Figure 3.2.

The MEEP approach relies on a formula first proposed by Kövesligethy (1907), implemented in

its most general form:

( )hhRekh

hRkII ii

i −++

+=− 22

102

22

100 )(loglog α (3.2)

where I0 is the epicentral intensity, Ri is the isoseismal radius for intensity Ii assuming spherical

isoseismals1, k is a parameter controlling the spacing of the isoseismals (usually between 2.0

and 4.0), and α a regional attenuation parameter (usually between 0.003 and 0.008). The k and

α parameters are set as part of the calibration. Equation (3.2) is combined with the model of

Frankel (1994), in which the radius of perceptibility is interpreted in terms of measurable

physical parameters:

CAmAnM w +

+

=

ππ 3.22log10 (3.3)

where n is geometrical spreading (taken to be 0.5), A is the felt area (often taken as the area

corresponding to intensity III and higher) in km2, C is a calibration constant and m is the factor:

βπQ

fm = (3.4)

where f is the predominant frequency of earthquake motion at the limit of the felt area (believed

to be 3 Hz), Q is the shear wave attenuation, and β is the shear-wave velocity (3.5 km/s) . In

MEEP2, the optimal epicentral location is determined by finding the location minimising the

RMS residual between observed radii (taken as the 84th percentile of the distribution of

distances of the IDPs for the intensity level considered to the tested location) and the radii

predicted from the combination of the Kövesligethy formula above with the Frankel (1994)

model. The intensity III area then leads to an estimate of magnitude using Eq. (3.3).

1 Equivalent circular radii determined based on the preservation of the area enclosed by the isoseismals are often used in practice when the shape of the isoseismals strongly deviates from a circular model.


26

The same empirical data as was considered to check the performance of the Bakun & Scotti

(2006) IPE was used to find a calibration of the Kövesligethy (1907) and Frankel (1994)

equations in the MEEP method that is compatible with the Bakun & Scotti (2006) IPE as well as

being consistent with the observed behaviour of South African intensity data (Figure 3.2). The

following parameters were adopted: Q = 800, C = 1.55, α = 0.003 and k = 2.2. The centroid and

pairwise approaches do not require additional calibration parameters for the determination of

locations, and rely on the same parameters as the MEEP approach to determine magnitudes

using the Frankel (1994) formulation.

Figure 3.1 Comparison of intensity predictions for a magnitude Mw 6.0 event from the IPEs listed in Cua et al. (2010), as well as the Indian Craton relation of Szeliga et al. (2010). For IPEs using hypocentral distance, a source depth of 10km is assumed and the equivalent epicentral distance calculated.


27

Figure 3.2 Comparison of isoseismal areas predicted by various relations with isoseismal areas determined from South African isoseismal map and IDP data.


28

One final point to note is that the implementation of the Bakun & Wentworth (1997) method in

the MEEP2 software slightly differs from the methodology proposed in the original paper, in that

the search is carried out using an adaptive grid of increasingly smaller size, rather than a fixed

size grid. Tests were carried out for a number of events with well-constrained source

parameters (e.g., Ceres 1969) comparing the results obtained from MEEP2 with those obtained

using the original formulation (implemented by Céline Beauval). A good agreement was found

for these well-constrained cases; it was also concluded that care must be exercised with the

adaptive grid search in cases where the algorithm shows convergence difficulties, as these are

less obvious to detect than on a fixed grid.

The locations determined for the pre-1899 events in the Albini (2012) study are listed in Table

3.1. These were determined on an event-by-event basis by considering the results of all four

methods implemented in MEEP2, along with a careful review of the IDPs involving Paola Albini.

Table 3.1 Individual events of the historical period studied by Albini (2012)

Date Most affected

place NIDPs Imax LatN LonE LatErr LonErr Remarks

1850-05-21 Morley 32 6-7 -32.00 28.00 0.75 1.28

1859-04-11 Colesberg 1 5 -30.72 25.10 0.25 0.25 Event newly added to catalogue.

Fixed uncertainty as single IDP.

1861-08-17 Burghersdorp 4 4 -30.85 26.50 0.59 0.29 Event newly added to catalogue

1862-06-16 Durban 3 4 -29.80 30.70 0.12 0.32

1862-06-23, 2:00 Cape Town 3 4 -33.47 18.65 0.53 0.42

1865-06-23, 2:00 Graaff-Reinet 3 3 -32.25 24.55 0.5 0.5

Insufficient data for MEEP2

analysis. Treated as local Graaff-

Reinet event with fixed

uncertainty.

1864-02-24 George 4 4 -33.75 22.75 Event newly added to catalogue

1867-02-24 Hopetown 1 3 -29.62 24.08 0.25 0.25 Event newly added to catalogue

1867-07-24 Bethany 1 4 -29.59 25.96 0.25 0.25 Event newly added to catalogue

1867-10-15 King William’s

Town 10 5 -32.95 27.60 0.36 0.36

1868-10-08 George 3 4-5 -33.75 22.75 0.29 0.45 Event newly added to catalogue

1870-02-25 Durban 2 4 -29.75 31.00 0.11 0.05 Event newly added to catalogue

1870-08-03 Harrismith 19 5-6 -28.45 29.15 0.93 1.29

1883-09-30

[Port

Elizabeth]

not confirmed

-- -- -- -- -- --

Removed from catalogue based

on negative evidence in Port

Elizabeth region. Treated as

duplicate account of Lesotho

event a few days earlier.

1895-04-09 Uitenhage 7 4 -33.40 25.45 0.73 0.77


29

3.1.2. Other events

For all other events in the study region falling into this time period, the primary source of data for

the historical dataset is the compilation by Brandt et al. (2005), which builds on work by

previous authors, and in particular updates the compilation of Fernández & Gúzman (1979) by

incorporating information that had not been available to these authors. For these events, the

epicentral coordinates of Brandt et al. (2005) are adopted. Available primary sources of data

were examined in order to assess the quality and quantity of the information on which the

assessment is based and thus inform the location uncertainty for the events concerned.

The only modification that was undertaken was the removal of the 31 October 1869 event,

which had been added by Brandt et al. (2005) based on a single newspaper report in De Klerk

& Reed (1988); additional newspaper reports gathered since the Brandt et al. (2005) study

clearly indicate that this event was subsequently related to an aerolite fall rather than an

earthquake by the Royal Observatory at the Cape of Good Hope.

3.2. Early Instrumental (1899-1969) Data

The data for the early instrumental period (1899 to 1969) can be split into two subsets, with the

split being defined by the establishment of the first national seismograph network in 1949.

3.2.1. Pre-1949 data

For the time period covering the years 1899 to 1949, the approach adopted is very similar to

that of the historical period. For larger events, macroseismic information is in some cases

supplemented by instrumental information from the two South African seismographs and early

global networks. Due to the sparse distribution of the seismograph stations as well as recording

limitations stemming from instrument characteristics, this early instrumental information is

mostly useful for confirming the occurrence of seismic events, and to provide constraints on the

magnitude, with epicentral locations still largely controlled by macroseismic data. The selection

of epicentral locations for this period was undertaken in a manner very similar to the approach

used for the historical period, as explained below.

Events for which an individual study was included in the Albini (2012) study were analysed

using the MEEP2 software; the results were combined as was done for historical events to

provide a preferred macroseismic epicentral location. This macroseismic location was used as

the preferred epicentral location for those events unless an instrumentally-determined solution

was available. The latter was only the case for the three events large enough to have a globally


30

determined solution included in the ISS summary, which include the 20 February 1912

Koffiefontein event, the 4 December 1920 south of South Africa offshore event, and the 31

December 1932 off Cape St Lucia event. The instrumental solutions of the former two events

have been reappraised by Ambraseys & Adams (1991, see Section 2.3.8), whose reanalysis

focused predominantly on early Milne instruments. Additionally, the ISS solutions were

reviewed using the arrival times listed in the ISS bulletins (available in digital format online

courtesy of the EUROSISMOS project). Since these listings are known to sometimes include

erroneous information due to issues such as phase misidentification, timing errors or

misassociation of readings with the causative event, these arrival times were examined in

terms of P-wave arrivals and S-P time differences, as well as the arrival time of the maximum

amplitude (M), which following Ambraseys & Adams (1991) was interpreted as an Airy phase of

surface waves travelling at a velocity between 2.8 and 3.0 km/s. This procedure highlighted

gross inconsistencies, and enabled the selection of a subset of reliable stations to produce a

graphical solution providing information about the level of constraint of the solution, as

illustrated in Figure 3.3 for the 1920 event.

Figure 3.3 Source-to-site distances for the 4 December 1920 offshore event based on S-P times at selected stations listed in the ISS Bulletin, compared with the ISS (green star) and Gutenberg & Richter (1956) solutions (black star).

For the 1912 Koffiefontein event, there is excellent agreement between the macroseismic

epicentre and the instrumental epicentre. For the 1920 and 1932 offshore events, the initial

position of the epicentre in the MEEP2 calculations was fixed at the preferred instrumental

location, and the maximum intensity value assessed in the calculations allowed to vary by up to

three intensity degrees from the maximum observed value, in order to acknowledge that the


31

observed IDP field does not include the epicentral area. A comparison between the well-

constrained instrumental epicentre and the macroseismic epicentres determined using MEEP2

is shown in Figure 3.4. This figure also illustrates the differences in behaviour among the

various methods implemented in MEEP2: the centroid and MEEP methods will tend to favour

an epicentral location in the vicinity of the IDPs with the highest intensity, whereas the Bakun

and pairwise methods will tend to look for a solution outside the region defined by the IDPs in

the case that the available set of IDPs deviates significantly from the ideal pattern of concentric

annular regions. This important difference in behaviour was taken into account when combining

the macroseismic solutions for the remaining events based on the Albini (2012) study, in

particular when the set of IDPs was spatially censored by the presence of a coastline or a

sparsely populated region. The resulting locations and associated uncertainties are listed in

Table 3.2.

Figure 3.4 Comparison between instrumental epicentre and the macroseismic epicentres obtained using the various methods implemented in the MEEP2 software and the set of IDPs determined by Albini (2012) for the 1932 off Cape St. Lucia earthquake. Table 3.2 Individual events of the early instrumental period studied by Albini (2012)


32

Date Most affected

place NIDPs Imax LatN LonE LatErr LonErr Remarks

1900

January

not confirmed -- -- -- -- -- -- Event not previously in catalogue.

Insufficient evidence to add

1908-09-26 Bloemfontein 25 5 -28.70 25.80 1.01 0.75

1910-10-21 Hanover 36 5-6 -30.55 24.70 0.65 0.98

1911-07-06 Oudtshoorn 1 4 -33.58 22.20

1911-07-10 Hillary 1 4 -29.83 30.95

1912-02-20 Bloemfontein 101 7 -29.50 25.00 0.25 0.25 Instrumental epicentre.

1912-11-17 Kimberley 12 5 -29.30 25.00 0.75 0.87

1916 -03-

23

not confirmed -- -- -28.90 31.70 0.25 0.25 Kept as small event since this was

originally listed in Finsen (1950)

1920-12-04 Port Elizabeth 10 4-5 -39.00 23.50 1.0 1.0 Offshore event. Preferred

instrumental location follows

Ambraseys & Adams (1991) in

preferring the ISS location over

Gutenberg & Richter (1956) as

being more consistent with available

data.

1922-10-31 De Rust 1 3-4 -33.49 22.54 0.25 0.25

1927-09-22 Xolo/Bolo 1 4 -32.38 27.63 0.25 0.25

1932-08-09 Grahamstown 39 6 -33.30 26.50 0.43 0.52

1932-12-21 Eshowe 91 6-7 -28.50 32.80 0.25 0.25 Well-constrained instrumental

solution. ISS and Gutenberg &

Richter (1956) coincide within

rounding preferences.

1933-02-25 Grahamstown 3 3 -33.45 26.70 0.15 0.18

1936-04-26 Loerie 1 5 -33.87 25.032 0.25 0.25

For all other events in the 1899-1949 time period, the epicentral locations listed in Brandt et al.

(2005) were retained. These were based predominantly on the compilation by Finsen (1950),

supplemented by macroseismic locations from the study by Krige & Maree (1951).

3.2.2. 1949-1969 data

For this time span, the locations determined by Oliver and his BPI co-workers using the five-

station Geological Survey network represent the preferred solutions for South African events

when they are available. For some events, these solutions also considered the recordings on

the Weichert seismograph at the Union Observatory in Johannesburg. The quality of the

solutions depends mainly on the number of stations available, and thus increases with the

magnitude of the event. It is noteworthy that the epicentral locations published in Gane & Oliver

(1953), Oliver (1956) and the BPI Seismological Bulletins include confirmatory macroseismic

evidence where available, and that the authors include information regarding the quality of the


33

solution. Where additional macroseismic data was available from the compilation of De Klerk &

Read (1988) or other sources investigated as part of the compilation of the intensity database

described in Midzi et al. (2012), these data were used as an additional check on the BPI

instrumental location and uncertainty estimate. This is illustrated in Figure 3.5 showing the

instrumental solution of the well-constrained 13 April 1957 Zastron District event alongside the

available macroseismic information.

Figure 3.5 Instrumental solution of the 13 April 1957 Zastron District event (from BPI Seismological Bulletin) alongside the available macroseismic information (Midzi et al., 2012).

3.3. Ceres Sequence (1969-1971)

The source parameters for the Ceres sequence are determined by combining information from

multiple sources including notably the aftershock studies by Green & Bloch (1971) and Goetz

Observatory (1972).

Green & Bloch (1971) present the results of an aftershock study carried out by the Bernard

Price Institute of Geophysics (BPI) following the deployment of a temporary local seismograph

network. As shown in Figure 3.6, the aftershocks delineate a near-vertical structure with an

orientation close to the strike of the mapped Groenhof Fault. Green & Bloch (1971) use these

results to determine the location of the mainshock (large black dot in Figure 3.6), which is

constrained within 1-2 km and hence adopted in the present study. Unfortunately, the authors


34

only provide the locations of the aftershocks in graphical format (rather than a listing of source

times and associated epicentral coordinates). As a result, it is not possible to infer aftershock

coordinates from this study except for the 6 October 1969 and 14 April 1970 aftershocks

indicated in Figure 3.6 by a small black dot and a heavy black cross, respectively.

Figure 3.6 Locations of aftershocks of the 1969 Ceres event determined from recordings on a temporary local network by Green & Bloch (1971), in map view; see Figure 4.3 for vertical cross-sections along and perpendicular to A-A.

A report by Goetz Observatory (1972) presents magnitude estimates ranging from 3.4 to 6.0 for

79 events of the Ceres sequence, from the 29 September mainshock until 6 December 1969.

Epicental locations are given for a subset of 34 of these events, which have been recorded by 4

or more stations. The locations listed are significantly different from the preliminary BUL

locations published in the ISC bulletin, and generally lie reasonably close to the area of greatest

damage during the 1969 mainshock. Finally, additional location information is provided in

Fernández & Gúzman (1979) for events without a location in Goetz Observatory (1972), as well

as a number of additional events. ISC locations have not been considered for the Ceres data as

they have been found to be in contradiction with macroseismic evidence, which indicates that all


35

larger aftershocks were felt most strongly in the Ceres-Tulbagh area. The poor location

accuracy of the ISC solutions is thought to be linked to azimuthal biases resulting from a very

uneven station distribution.

3.4. Modern Instrumental (1970-2011) Data

For the modern instrumental data, the primary source of information is the CGS database

described in Section 2.1.8. Alternative solutions determined by the Goetz Observatory in

Bulawayo (BUL) and by the International Seismological Centre (ISC) are available for most

larger events (until 1993 for BUL, until 2008 for ISC). BUL also provides a number of additional

events for the period from 1970 to 1983, for which no determinations are available from other

agencies.

In the case of multiple solutions, the preferred solution would normally be the ISC solution,

since it is calculated using additional data compared to the solutions provided by the individual

networks, and thus better constrained. ISC solutions also have the advantage of systematically

providing an estimate of the uncertainty associated with the location. However, many of the ISC

solutions are significantly at odds with the macroseismic epicentre, in particular for events in the

Ceres-Tulbagh region that occurred in the 1970s and early 1980s, for which the quality of the

location is affected by the poor azimuthal distribution of the data, which is strongly biased to the

northeast. Therefore, the following approach is adopted:

• If the ISC and CGS epicentral locations are significantly different, macroseismic

information is used to determine the more credible solution;

• If no macroseismic information is available, or if the difference in location is small, the

ISC solution is retained as it is of better quality (smaller location uncertainty and

azimuthal gap as a result of using a larger number of stations).

• In the case of inconsistent solutions, the phase data for the individual stations was

checked to determine the solution most consistent with locally applicable travel-time

curves (both in terms of P-waves and in terms of S-P intervals).

The effect on the azimuthal pattern of adding regional stations at distances greater than 15° is

illustrated in Figure 3.7. The addition of the stations of the Bulawayo network only accentuates

the azimuthal bias towards northeastern stations, simultaneously diluting the constraints

provided by close-in South African stations such as Ceres (CER) and Sutherland (SUR), and

increasing the distance to the macroseismic epicentre at Ceres. The single-network solution

using fewer stations is therefore preferred.


36

Figure 3.7 Effect on azimuthal distribution of adding regional stations at larger distances.

Figure 3.8 illustrates the testing of alternative solutions using observed and predicted travel-

times, showing the 17 August 1979 event as an example. This approach is particularly useful in

the case of large discrepancies between the multiple solutions available, which can be driven by

the anomalous behaviour of single stations, which is not necessarily obvious from the

examination of a summary statistic such as the root-mean-square residual. In the example

shown, the Smith (1999) reanalysis of the CGS routine solution (Pretoria solution) is retained as

the best-fitting solution overall.


37

Figure 3.8 Observed vs. predicted P and S-P arrival times for the 17 August 1979 Northern Cape event, for the alternative solutions calculated by various networks and authors.

3.5. Treatment of Location Uncertainties

The identification and quantification of uncertainties is a key element of seismic hazard analysis,

since knowledge of the level of confidence that can be assigned with the assessment of a

potential threat is required to guide the decision-making process. The present section presents

the scheme implemented to assess and classify the uncertainties associated with the locations

of the seismic events included in the catalogue presented in the present study.

3.5.1. Instrumental data

For determinations based on instrumental data, the quality of the location depends critically on

the number of stations, their distance to the source, as well as their azimuthal distribution. The

best-constrained solutions are obtained from dense, close-in networks surrounding the source.

With the exception of the local network deployed by Green & Bloch (1971) to record aftershocks

of the 1969 Ceres sequence, such recording conditions are generally not available for South

African earthquakes of tectonic origin, for which determinations are generally based on

determinations from fairly distant stations, with only 1 or 2 close-in stations. Additionally, the

quality of location for earthquakes occurring along coastal regions is also affected by the

absence of recording stations in the offshore region, leading to error ellipses with a high aspect

ratio between the major and minor axes.


38

Location uncertainties are routinely determined as part of the location process by CGS and ISC.

CGS provides estimates in terms of latitude and longitude error, LatErr and LonErr. ISC

provides the dimensions of the major and minor axes of an error ellipse, Smaj and Smin. The error

ellipses for the events in the current dataset are mostly oriented NS or EW, hence the CGS and

ISC location error parameters can be considered equivalent. For ease of comparison with the

uncertainties determined from macroseismic data, which are expressed as radii, equivalent

error radii are defined as follows:

LonErrLatErrErrRCGS ×= (3.1)

and

minSSErrR majISC ×= (3.2)

for the CGS and ISC data, respectively. These equivalent radii were used as estimates of the

location uncertainty. It should, however, be noted that due to lack of stations offshore the

western and southern coasts, the error driving the uncertainty assignment is the longitude error

for locations along the western coast, and latitude error along the southern coast.

For the most recent subset of instrumental data (1997 to 2011), for which no lower magnitude

cut-off was imposed, locations determined from fewer than 3 stations were not included in the

catalogue, given that these locations are azimuthally unconstrained and thus extremely

uncertain. Despite the sparse nature of the network, the improved detection thresholds of

modern seismographs limit such cases to events with very low magnitudes. The exclusion of

these events therefore has no impact on downstream applications such as the estimation of

recurrence parameters, simply reducing the noise in the spatial distribution of seismicity.

3.5.2. Macroseismic data

In a similar manner that the quality of an instrumental location depends on the instrumental

coverage, the quality of a location determined from macroseismic data depends on the detail of

the information available, as well as its spatial distribution.

3.5.2.1. Events analysed using MEEP2

For the events studied by Albini (2012) and analysed using the MEEP2 software, uncertainties

in location were assessed by considering the spatial distributions of bootstrapped epicentres

generated by the software for each of the different methods. These epicentres correspond to

the solutions that would be obtained by repeating the analysis for a sample of IDPs of the same


39

size as the original IDP set drawn with replacement from this original set. The bootstrapping

procedure is repeated 1000 times. The resulting distributions of bootstrapped epicentres are

combined with the same weights as are assigned to the various methods when determining the

preferred epicentre. These weights have been assigned on an event-by-event basis in order to

incorporate event-specific data and method limitations. Location uncertainties are then

determined based on the fractiles of the density function of the weighted differences between

bootstrapped epicentres and the best estimate epicentre. For consistency with the MEEP2

definition of isoseismals as the 84th percentile of the observed IDP-distance distribution, the

location error is defined as the equivalent radius of the 84th percentile of the spatial density

function of weighted bootstrapped epicentres. This approach is similar to the use of the fractiles

of a combined spatial density function as described in Bakun et al. (2011), but uses the MEEP2

path optimisation rather than a gridded approach.

Figure 3.9 shows the alternative epicentres obtained from the various approaches implemented

in MEEP2 for the 21 May 1850 event, along with the best estimate epicentre adopted. The

location uncertainties are developed using the bootstrapped epicentres shown in Figure 3.10. In

this example, the centroid method is given a low weight, since it is strongly affected by the

azimuthal bias of the IDP distribution.


40

Figure 3.9 Alternative epicentres provided by the various approaches implemented in the MEEP2 software and best estimate epicentre adopted in the present study for the 21 May 1850 event.


41

Figure 3.10 Bootstrapped epicentres for the various methods implemented in the MEEP2 software, for the 21 May 1850 event. The uncertainties for the TNSP catalogue are based on the spatial distributions of these bootstrapped epicentres, with event-specific weights applied to each method.

Figure 3.11 illustrates another weighting case. In this example, the Bakun method (as

implemented in MEEP2) has difficulty converging and thus predicts an offshore event with

larger magnitude than predicted by the other methods. The limited instrumental data available

do not support such a scenario, and the IDP distribution also does not exhibit the behaviour

patterns generally observed for offshore events. Therefore, the offshore solutions are given a

low weight for this event.


42

Figure 3.11 Bootstrapped epicentres for the various methods implemented in the MEEP2 software, for the 9 August 1932 event. The uncertainties for the TNSP catalogue are based on the spatial distributions of these bootstrapped epicentres, with event-specific weights applied to each method.

3.5.2.2. Events with isoseismal map

When the information is sufficient to construct a full isoseismal map, the epicentral location can

be constrained by the extent of the highest intensity isoseismal contour. However, in practice,

the assessment is often based on incomplete isoseismals (particularly for coastal locations).

The detail of the description of felt effects, or negative reports (i.e., reports that the earthquake

has not been felt at a given locality), can help in improving location quality. Although it does not

always coincide with the epicentre, confirmation of the highest observed intensity level will also


43

help in constraining the location. The classification adopted for the location uncertainties is

summarised in Table 3.3.

3.5.2.3. Events with individual IDPs

When only a few intensity reports are available, it is often ambiguous whether they correspond

to a small event felt only locally, or to a larger, more distant event for which close-in reports are

not available. This ambiguity leads to a location bias towards population centres (e.g., there

seem to be more historical events in Cape Town than in the surrounding, more sparsely

populated areas). However, in some cases, negative information can be used to confirm the

local nature of an event, thus reducing the location uncertainty. The classification adopted for

the location uncertainties is summarised in Table 3.3.

Table 3.3 Classification of location uncertainties for locations determined using macroseismic data (excluding IDP sets analysed using MEEP2). Quality Description Location uncertainty

a Observation of surface fault rupture caused by the event < 5km

b1 Location from multiple (4 or more) reasonably complete isoseismal

contours including detail in the presumed source region 5 to 10 km

c1 Location from multiple isoseismals lacking detail close to the source 10 to 20 km

c2 Location from multiple incomplete isoseismals 10 to 20 km

c3 Location from few (<4) but reasonably complete isoseismals 10 to 20 km

d1 Location from few and/or incomplete isoseismals, in combination with

isolated report regarding maximum intensity 20 to 50 km

d2 Location based on total felt area 20 to 50 km

d3 Location based on few felt effect reports, but with an indication of the

maximum extent of the felt area to support local character 20 to 50 km

d4 Location based on few felt effect reports, but with sufficient detail to

confirm local character of event 20 to 50 km

e Location based on few isolated intensity observations Unconstrained


44

4. Depth of South African earthquakes

This section summarises the current state-of-the-knowledge regarding the depths of South

African earthquakes.

4.1. Crustal Thickness

A key piece of information in the determination of seismic depths is knowledge of the

seismogenic thickness of the crust, which is limited by the overall crustal thickness, although

previous experience shows no obvious correlation between these two parameters. Kgaswane et

al. (2009) determined shear-wave profiles for 89 broadband seismic stations from the South

African Seismic Experiment (SASE) temporary array (Figure 4.1) as well as the permanent

SANSN and IRIS stations. They found crustal thicknesses falling mostly in the range of 35-45

km (Figure 4.2).

Figure 4.1 South African Seismic Experiment (SASE) temporary array used by Kgaswane et al. (2009).


45

Figure 4.2 Crustal thickness determined at SASE stations by Kgaswane et al. (2009) from joint inversion, compared to estimates from previous studies. Closed symbols highlight stations that were found to deviate significantly (> 5 km) from the 1:1 line by Kgaswane et al. (2009) due to difficulties in determining the crust-mantle boundary in the presence of complex, gradational shear-wave structure at these sites.

4.2. Routine Location Procedure and Depth

In the CGS routine location procedure, depths are fixed to default values depending on the

nature of the earthquake (h=0 km: explosion, h=2km: mining-related event, h=5km: local

tectonic event, h=10 km: regional tectonic event). This practice is due to the low station density,

resulting in insufficient numbers of close-in standard phase readings (P and S) that would be

required to constrain the location in 3 dimensions. In their discussion of location quality criteria,

Bondár et al. (1994) include the requirement of having at least one station within 30km of the

event to ensure it is at crustal depth. This condition is very rarely met by events detected by the

South African National Seismograph Network.

Bondár et al. (1994) note that “estimation of focal depth based on phase arrival times from

regional and teleseismic networks is difficult at best” since “focal depth is poorly constrained by

direct phases in these distance ranges”. This is reflected in the fact that the teleseismic

locations determined by agencies such as ISC or NEIC are also based on fixed depths. In some

cases, solutions with freely-determined depths are listed in the ISC Bulletin, however their

reliability is rather doubtful given that they include extremely large values of depth for mining

events known to occur in the upper few kilometres of the crust (e.g. an event that occurred on

11 August 1971 at 14:17 located at -26.4070°S, 27.4147°E in the Witwatersrand mining regions


46

is assigned a depth of 167.9 km), pointing to an algorithm convergence issue. Increases in the

size of the error ellipse when comparing the quality of Engdahl-Hilst-Buland (EHB, Engdahl et

al., 1998) locations with free depth to the ISC solution with fixed depth 2 also point to the

difficulty of constraining depth with limited close-in data, even when using an improved velocity

model.

The difficulty of obtaining well-constrained depth using routine procedures is further evidenced

when plotting the root-mean-square (RMS) time residual at the optimal locations, which show

little variation of the RMS over depth.

4.3. Well-constrained instrumental depths from event-specific studies

For a very small number of events, the instrumental information was sufficient to obtain a

reasonable well-constrained estimate of depth.

4.3.1. 1969-1970 Ceres sequence

The aftershocks of the 29 September 1969 Ceres event (Mw 6.2) were recorded by Green &

Bloch (1971) on a temporary local network, yielding a fairly good image of the fault rupture

plane of the main event, as well as of the fault rupture plane of the 14 April 1970 largest

aftershock (Mw 5.8), which appears to have occurred on a conjugate plane (Figure 4.3). Green

and Bloch (1971) found that these events were located at a maximum depth of 9 km, with most

of the aftershocks occurring prior to 14 April 1970 located at a depth shallower than 6.5 km.

They also found that the close-to-surface events were concentrated in the Ceres region, with

events deeper than 6.5 km only occurring at distances greater than 17 km from Ceres.

These results are in good agreement with the shallow depth (<20 km) found by Krüger et al.

(2011), who also note that the absence of depth phases provides additional evidence for a

shallow source. When reappraising the teleseismic data at CGS’s request (Storchak, 2009), ISC

could not determine a freely varying depth, but found good agreement with a fixed depth of 10

km.

2 Note that the error ellipse parameters listed for the EHB solution in the ISC bulletin appear to be in error by a factor of 10 compared to the equivalent parameters listed in the EHB bulletin (considered the authoritative version), which are of the same order of magnitude as the error ellipse parameters of the ISC solution.


47

Figure 4.3 Depth distribution of the aftershocks of 1969 Ceres earthquake located by a temporary seismograph network (Green & Bloch, 1971). Panel B shows a vertical section along A-A, and panel C a vertical cross-section perpendicular to A-A, where A-A is the least-squares plane fitted to the aftershocks as shown in Figure 3.6. Circles indicate aftershocks of the 14 April 1970 aftershock.

4.3.2. 1976 Koffiefontein event

The ISC solution for this event, for which the depth was initially determined as 28 km, was

reappraised by ISC (Storchak, 2009) following a request from CGS. The reappraised depths

range from 7 to 11 km. These values are in broad agreement with the shallow depth of 5.5 km

obtained by Jensen (1991) from body-wave inversion.

4.3.3. 1986 Matatiele

EHB determine a depth of 11.7 +/- 3.7 km for this Mw 5.3 event, at the cost of a slight increase

of the error ellipse compared to the ISC fixed depth solution. A Harvard CMT solution is

available for this event, but the centroid depth is set at the default value of 15 km.

4.3.4. 1989 SA-Lesotho border

ISC determined a depth of 6.8 km for this event, however it carries an error of +/- 22.7 km. EHB

found a depth of 7.7 km (again at the cost of an increase in terms of the error ellipse size), with

an unspecified error.

4.4. Additional depths determined using depths phases

4.4.1. Methodology

Constraints on depths calculated from instrumental recordings can be improved if depth-

sensitive phases, such as those reflected at the free surface, are considered. The idea here is

to identify these phases on the recordings and compare their arrival times with the theoretical

arrival times determined from the velocity model. The process is repeated stepping through

several values of depths, the optimal depth being the one for which the best match between

observation and synthetics is obtained.


48

Ma & Atkinson (2006) proposed a version of this method considering the arrivals of pairs of

direct phases and their surface-reflected equivalent (Pg and sPg, PmP and sPmP, and Pn and

sPn, see Figure 4).

Figure 4.4 Depth phases considered in the Ma & Atkinson (2006) approach (Ma & Eaton, 2011).

They applied this method to a set of Eastern North American events, and found that a single

station can be sufficient to constrain the event depth, as long as the depth phases can be read

clearly. The latter is a function of the source-to-site distance, with sPg typically well developed

at distances of up to ~100 km, sPmP typically well developed in the range 200-300 km, and sPn

sometimes being observable for the larger events of the dataset. The method is most commonly

applied with the PmP phase.

4.4.2. 2008-2011 Augrabies swarm

The Augrabies region in northwestern South Africa, close to the Namibian boundary, has been

experiencing seismic swarm activity in the last few years, yielding a large dataset of digital

seismograms. In addition to routine analysis, these data have been re-analysed (I. Saunders,

personal communication) using additional phases, including depth-sensitive phases such as Pn,

Pg Sn, Sg and PmP and leaving the depth unrestrained. These additional phases were identified

with the help of synthetics generated using SEISAN’s ray-tracing module, which is based on the

WKBJ algorithm (Chapman et al., 1988). The results indicate depths ranging from 3.4 to 12.1

km, and are listed in full in Table 4.1


49

Table 4.1 Depths determined for selected events of the 2008-2011 Augrabies sequence (I. Saunders, personal communications)

Date LatN LonE h (km) No of stations rms ML

2008-09-20 20:18:10.7 -28.863 20.248 6.2 4 0.3 1.4

2009-07-09 02:38:02.2 -28.835 20.217 5.3 14 0.4 3.1

2009-07-21 23:43:31.2 -28.872 20.286 7.3 10 0.3 3.0

2009-08-31 13:14:28.2 -28.956 20.401 4.0 7 0.2 2.4

2009-10-30 07:02:03.2 -28.906 20.235 6.8 6 0.1 1.8

2010-06-24 10:06:24.1 -28.664 20.500 4.3 17 0.5 3.7

2010-06-29 02:07:07.6 -28.679 20.483 5.4 9 0.9 3.3

2010-07-02 21:09:48.6 -28.507 20.359 6.5 8 0.5 2.1

2010-07-26 14:24:20.2 -28.656 20.379 10.7 21 0.6 3.7

2010-07-26 14:27:06.6 -28.708 20.411 12.1 18 0.5 3.3

2010-08-04 05:12:48.8 -28.693 20.501 11.9 9 0.5 2.4

2010-08-05 09:03:56.4 -28.728 20.468 3.4 15 0.4 3.0

2010-11-21 02:28:52.1 -28.684 20.393 6.1 17 0.6 3.7

4.4.3. Re-analysis of selected events recorded by the SASE array

The data recorded by the temporary array installed from 1997 to 1999 as part of the South

African Seismic Experiment (SASE, see Figure 4.1) was screened to identify event-station

combinations within distance ranges likely to show depth-dependent phases.

In Figure 4.5 to Figure 4.7, the methodology is shown applied to the event which occurred on 3

July 1999 at 20:53:02.5. The top trace in each figure is the trace used to pick the observed

phases, while the other traces are used to display predicted phases calculated using the TauP

program. The depth was changed from 1 to 40 km in increments of 1 km, while the epicentre

was kept fixed. At 11km, the observed T0 (PmP) and T4 (sPmP) times match the PmP and

sPmP arrival times predicted by TauP.


50

Figure 4.5 Station SA26 recording of the 3 July 1999 Koffiefontein event with actual phases read (top trace ) and arrival times predicted by Tau-P for depths between 1 and 4 km.

Figure 4.6 Same as previous figure, for source depths from 6 to 10 km.


51

Figure 4.7 Same as previous figure, for depths from 11 to 15 km. The depth of 11 km provides the best match for this waveform.

The same method was applied to 9 events occurring during the deployment of the SASE array.

The depths obtained are listed in Table 4.2. When results were available for multiple stations,

the depths values obtained were averaged to obtain the final depth value. The resulting depths

range from 5.6 to 18.6 km, with uncertainties of up to 3.0 km, for ML magnitudes ranging from

2.7 to 4.5.

Table 4.2 Depths determined by matching depth phase arrivals for 9 selected events using seismograms from the SASE array deployed 1997-1999.

Event Location LatN LonE Depth (km) ML (CGS) Strike Dip Rake

1998-04-24 11:44:05.5 Augrabies area -28.213 20.364 7.3+/-2.3 4.3 9 68 -20

1998-06-22 11:33:11.7 Three Sisters area -31.877 23.356 6.3+/-0.3 3.5 19 47 -122

1998-07-05 17:19:41.1 Lesotho -30.134 27.59 14.8+/-1.5 3 28 58 -124

1998-09-06 20:16:17 Lesotho -30.255 27.976 18.6+/-3.0 3.4 148 18 -68

1998-10-05 22:40:35.4 Fraserburg area -30.972 22.347 5.6+/-0.3 3.9 149 19 -69

1999-01-07 10:41:31.3 Koffiefontein -29.489 24.959 6.3+/-0.9 2.7 148 18 -68

1999-02-04 02:02:24.3 Koffiefontein -29.838 25.868 8.1+/-1.5 4.5 98 78 -122

1999-06-21 09:18:22 Koffiefontein -29.608 25.325 7.5+/-1.4 3.3 95 58 -152

1999-07-03 20:53:02.8 Koffiefontein -29.473 24.65 7.5+/-2.2 4.5 68 18 -155


52

4.5. Depth from macroseismic intensity observations

This section focuses on the determination of depths from macroseismic observations, which are

based on variants of a formula first proposed by Kövesligethy (1907). The basic idea, illustrated

in Figure 4.8, is that the surface projection of the 3D isoseismal contours (whose extent and

spacing is determined by the magnitude of the event as well as regional attenuation properties)

will also be affected by the depth of the event, with shallower events giving rise to higher

intensities in the epicentral region than deeper events.

Figure 4.8 Effect of depth on isoseismals (Musson & Jiménez, 2008).

In the software package MEEP2 (Musson, 2009), the depth is considered for the MEEP

approach described in Section 3.1.1 via the hypocentral depth term included in the Kövesligethy

formula given in Eq. (3.2). Once the optimal epicentral location has been determined, the depth

is optimised by stepping through depth values and investigating the effect on the RMS residual

of the isoseismal radii. Note that the depth values are capped at 20km; Musson (2009) notes

that “for ill-behaved data sets, the RMS misfit can always be reduced somewhat by increasing

the depth, so depths of exactly 20 km should be regarded as unreliable”. In applications to the

South African intensity data, the calculated depth is almost always returned as 20km. In the few

instances where this is not the case, the results are not preserved when the calibration

parameters are subjected to a perturbation, hence cannot be considered robust.

An earlier implementation of the Kövesligethy method was provided in the software MACDEP

(Musson, 1996). This method was successfully applied to the UK by Burton et al. (1985) and


53

Musson (1996), who fixed the isoseismal spacing parameter k at an average value of 3.0,

leaving only the α parameter to vary. The MACDEP implementation does not include the

Frankel model, hence does not require the additional Q and C calibration parameters; however,

it is therefore more critically dependent on the value of I0, which is generally not well known.

The software plots the RMS residual values for a grid of depth-I0 values for a given combination

of k and α parameters, as shown in Figure 4.9.

Figure 4.9 Example MACDEP run showing the trade-off between I0 and depth.

More generally, the method, similarly to the routine instrumental location procedure, is critically

dependent on the availability of IDP data close-in to provide a constraint on the value of I0, since

isoseismal radii at larger distances are relatively unaffected by depths, as illustrated in Figure

4.10, showing the isoseismal radii expected from the Bakun & Scotti (2006) French SCR

Intensity prediction equation (IPE) for different magnitude and depth combinations. This IPE has

been found to provide a good match to the isoseismal areas observed in South Africa (see

Figure 3.2) as well as the global SCR felt area-magnitude relations of Johnston (1996).

Furthermore, it falls towards the middle of the predictions of various IPEs available (see Figure

3.1), matches predictions from other SCRs (e.g. the Szeliga et al., 2010 India Craton IPE),

allows explicit specification of depth, and is well-behaved at short distances.

Note also that magnitude has a much greater impact on the expected isoseismal pattern than

depth has, which implies that it will only be possible to constrain depths in cases where

magnitude is well-constrained.


54

Figure 4.10 84th-percentile isoseismal radii predicted by the Bakun & Scotti (2006) France-SCR IPE for different assumed source depths. The predicted intensities are rounded to the nearest integer (e.g. intensity VI corresponds to predicted values between 5.5 and 6.5) . The 84th-percentile radii correspond to the 84th percentile of the distance range covered by a given intensity level.


55

5. Homogenisation of Magnitudes

For a meaningful downstream utilisation of the catalogue, it is essential that the relative sizes of

the earthquakes listed are derived in a consistent manner. The present Chapter describes the

steps undertaken in order to achieve uniform magnitude estimates for the TNSP earthquake

catalogue.

5.1. Target magnitude scale and available magnitudes

5.1.1. Target magnitude

The catalogue presented in this report has been developed in terms of moment magnitude (Mw)

for compatibility with future manipulations as part of the seismic hazard analysis, in particular to

avoid conversion issues when using modern ground-motion prediction equations (GMPEs)

formulated in terms of Mw. The use of magnitude scale that does not saturate is also important

in the selection and testing of source scaling relations.

Throughout this study, moment magnitude Mw refers to the original definition of Hanks &

Kanamori (1979)3:

𝑀𝑤 = 23𝑙𝑜𝑔10(𝑀0) – 10.7 (5.1)

where M0 is the seismic moment in dyne-cm (1 dyne-cm = 10-7 Nm).

5.1.2. Available Mw values

There are, however, only a handful of earthquakes in the catalogue for which a value of Mw has

been directly determined from the long-period part of the spectrum of available recordings

through moment tensor inversion or wave-form modelling. These are summarised in Table 5.1.

The limited number of such determinations is due to the rare occurrence of events large enough

to allow a teleseismic determination, combined with the sparse nature of the local recording

network, which usually yields insufficient data for a moment tensor inversion of local events. For

the 4 February 1999 Koffiefontein event, Brandt & Saunders (2011) determined a moment

tensor solution using waveforms recorded by a temporary array deployed as part of the South

3 Note that Hanks & Kanamori (1979) use the notation M for this parameter. Herein, the notation Mw is adopted to avoid confusion with other magnitude scales in cases where bold formatting may not be obvious.


56

African Seismic Experiment (SASE, see Figure 4.1), which provided a much denser coverage

than the permanent South African network.

Table 5.1 Events in catalogue region with direct estimates of Mw Event Mw Reference Study Type

1969-09-29 Ceres Mainshock 6.2 Krüger et al. (2011) MT from teleseismic data

1970-04-14 Ceres Aftershock 5.8 Shudofsky (1985) Body-wave inversion

1976-07-01 Koffiefontein 5.8 Jensen (1991) Body-wave inversion

1986-10-05 Matatiele region 5.3 Harvard CMT Global CMT

1999-02-04 Koffiefontein 3.8 Brandt & Saunders (2011) Regional CMT

2011-12-18 Augrabies 4.3 USGS NEIC Rapid MT (global)

Additionally, estimates of Mw have been obtained for a set of events that occurred between

2006 and 2011, for which good-quality digital recordings were selected by Rietbrock & Drouet

(2012) to perform inversions using two different inversion methods in order to derive suites of

parameters for the calibration of stochastic models considered as part of the GMC component

of the project. This dataset consisted essentially of weak-motion data, and extended beyond the

study region considered for the catalogue compilation, also including mining-related events. The

inversion process provided estimates of seismic moment M0 obtained through fitting of the

Fourier spectra of the selected records; these were converted to Mw using Eq. (5.1), the

resulting values adopted as estimates of Mw for tectonic events falling within the catalogue

compilation region. An excellent agreement was observed for the values obtained by the two

methods for common events; where Mw estimates from both methods were available, the

arithmetic mean of these values was used as the best estimate of Mw.

5.1.3. Other magnitude scales considered

For those events for which no direct estimate of Mw is available, the primary references used in

the compilation of the catalogue provide magnitudes in the following scales:

• Local magnitude, ML

• Body-wave magnitude, mb

• Surface-wave magnitude, MS

• Magnitude determined by the Goetz Observatory in Bulawayo, mBUL

Additionally, for historical events as well as a number of events from the early instrumental

period, Mw have been estimated from macroseismic intensity observations. A summary of the


57

different approaches to obtaining Mw is shown in Figure 5.1; details of the conversions are

discussed in the following sections.

Figure 5.1 Summary of different approaches to estimate Mw. See text for details of conversions.

5.2. Conversion from local magnitude

By far the greatest fractions of magnitudes requiring conversion are expressed in terms of local

magnitude, ML, which is the magnitude routinely reported by CGS and its predecessor

organisations. This magnitude scale required an additional homogenisation step to be carried

out prior to conversion, in order to avoid inconsistencies related to change in magnitude

determination practice over time. Such changes have been found to affect conversions in other

projects (e.g., USNRC, 2012) even when the magnitude under consideration was nominally

determined by the same agency using the same conventions (Figure 5.2).

5.2.1. Calibration of South African local magnitude

A succinct overview of the South African practice of magnitude determination is given by

Saunders et al. (2012), who derived the first local calibration for the local magnitude scale,

using a selection of recent (2006-2009) digital high-quality recordings from tectonic events

6 12 2

1867

7256

212

147

3

51Direct Mw estimate

Conversion from mb

Conversion from Ms

Conversion from ML* (SANSN)

Conversion from ML* (BPI)

Conversion from MBUL

Mw based on MI (3rd generation)

Mw based on MI (Isoseismals)

Mw based on MI (Io only)

Composite estimate

Mw from weak-motion Mo


58

recorded at a minimum of 5 stations. Prior to this, South African local magnitude determinations

were based on the calibration derived by Richter (1935) when first defining the local magnitude

scale, updated to the Hutton & Boore (1987) relation in 1997 when the SEISAN seismic

analysis software was adopted for routine analysis (Brandt, 1997). Both these relations were

calibrated to southern California and strictly speaking applicable only to horizontal components

measured on Wood-Anderson seismometers, while until recently the South African instruments

consisted predominantly of short-period vertical instruments. Such a situation was not

uncommon in other regions of low seismicity prior to the derivation of a locally calibrated local

magnitude scale (e.g., Wahlström, 1979; Greenhalgh & Parham, 1986), but a comparison

between the newly derived calibration of Saunders et al. (2012) and the Hutton & Boore (1987)

calibration reveals quite significant differences at larger distances (Figure 5.3).

Figure 5.2 Discrepancies between nominally identically determined magnitudes over time for CEUS, thought to be related to undocumented changes in observatory practice (USNRC, 2012).


59

Figure 5.3 Calibration of local magnitude scale in South Africa, other regions of Africa and selected SCR regions.

Additionally, while a consistency check between new and old calculation methods was

performed at the time of the switch to SEISAN (Figure 5.4), an implicit change in magnitude

assignment practice was nevertheless made as the maximum distance considered for the

calculation of station magnitudes was increased to the SEISAN default value of 1500 km.

Previous practice did not explicitly set a maximum distance; however, examination of the data

used in the magnitude determinations for individual events reveals that records at distances

greater than 750 km were rarely included.

Pre-1997 distance cut-off for ML calculation

Post-1997 distance cut-off for ML calculation (SEISAN)


60

Figure 5.4 Consistency check between new and old SA ML values performed after adoption of the SEISAN seismic analysis software for routine analysis (Brandt, 1997). The equation describes the best linear fit to the data, shown as a solid black line; the 1:1 line is shown as a grey dashed line. This difference in practice, combined with the distance-dependent discrepancy between

assumed and actual attenuation, is likely to lead to significant complications in the derivation of

a conversion to moment magnitude. The decision was therefore taken to uniformly recalculate

all locally determined ML values using the new calibration of Saunders et al. (2012), and to

determine a conversion relation to Mw using this recalibrated local magnitude ML*.

5.2.2. Uniformisation of local magnitude values

The uniformisation of the local magnitudes was carried out using the distance correction

function recently derived by Saunders et al. (2012):

06.20006.0)(log159.1)(log 10010 −+=− RRA (5.2)

where R is the hypocentral distance in km. The recalibrated local magnitude, denoted ML*

herein to differentiate it from the published values of local magnitude, is thus given by:


61

06.20006.0)(log159.1)(log)(log)(log 101001010* −++=−= RRAAAM L (5.3)

where A is the maximum trace amplitude, in nm, of a vertical Wood-Anderson standard

seismometer normalised to have a static magnification of 1, and R is the hypocentral distance in

km.

The maximum trace amplitudes A were determined from available phase data, applying the

appropriate instrument corrections. From 1997 onwards, the database is fully digital, hence

recalibration was performed directly using Eq. (5.3). Prior to this date, phase data is listed in

hard copy seismological bulletins. These are in the process of being digitized, however this

process is not yet complete, nor has the resulting electronic version been quality-checked yet.

Therefore, the recalibration was undertaken by retrieving phase data for tectonic events within

the study region from the hard-copy bulletins. In view of the effort involved, a listed minimum

magnitude of ML = 3.0 (prior to recalibration) was imposed. For the earliest phase of SANSN

operation, the amplitudes listed were the maximum double-amplitudes measured on the records,

rather than the instrument-corrected ground-motion amplitudes listed in later years. For these, a

gain correction was applied; while not exact, this approach represents a reasonable

approximation in the case of short-period analogue instruments.

Finally, to correct the ML values determined for the first, pre-SANSN network by Oliver and his

BPI co-workers, a correction based on the distance to the contributing recording stations was

applied to the listed magnitudes in order to correct for the difference in attenuation between the

Richter (1935) and Saunders et al. (2012) calibrations, maintaining the instrument corrections

as applied by Gane & Oliver (1953).

To illustrate the effects of this recalibration, a comparison between the old ML values and

recalibrated ML* values is shown in Figure 5.5 for the 2000-2011 subset of the TNSP catalogue,

as well as the high-quality datasets selected from the 2006-2011 data by A. Rietbrock and S.

Drouet for use in the weak-motion inversions (Rietbrock & Drouet, 2012). Note that the latter

two datasets include events outside the boundaries used for the TNSP catalogue, as well as

mining-related events. These three overlapping datasets show a consistent pattern of the

correction increasing with increasing magnitude. This trend is expected, since magnitude

determinations from larger events consider more distant stations, for which the effect of

correcting the attenuation function will be more pronounced (Figure 5.3).


62

Figure 5.5 Comparison between old and recalibrated ML values.

5.2.3. Conversion from ML* to Mw

The uniformly recalibrated local magnitude values ML* for events with an estimate of Mw (either

from direct calculation or from an estimate of M0) are plotted in Figure 5.4, along with a number

of published conversion relations. Data for 4 mining-related events with ML* ≥ 4.0 (i.e. large

enough to be related to slippage on geological faults) are also plotted in view of the paucity of

data. The available South African data is insufficient to derive a conversion relation through

regression that would span the whole magnitude range of interest. Regression is nevertheless

possible for the small-magnitude data with Mw based on M0 estimates obtained from fitting

weak-motion data. The slopes obtained from these regressions (0.62 for the Rietbrock data and

0.69 for the Drouet data) are in good agreement with the slopes of 0.6 to 0.8 found in other

relations derived from data in a comparable magnitude range (Figure 5.6 and Table 5.2), which

are typically similarly derived using Mw obtained through spectral fitting of weak-motion data. At

larger magnitudes, the limited data available supports the 1:1 scaling between ML and Mw that

would be expected theoretically (Deichmann, 2006; Scherbaum, 2012). Unlike other regions,

there does not appear to be any constant offset from this slope, which is most probably related

to regional differences in the calibration of ML.

Differences in scaling in the ML-Mw relationship between small and moderate magnitudes have

been observed in other regions, and are generally addressed by using a nonlinear functional

form for the conversion relation. A quadratic function of magnitude has been found to provide a


63

good fit across the whole magnitude range under consideration by Grünthal et al. (2009) for a

compilation of data from Central, Eastern and Northern Europe. However, in view of the

consistency with linear models of different slopes at small and moderate magnitudes, the South

African data follows more closely the pattern of the Swiss ECOS-09 catalogue data presented in

Goertz-Allmann et al. (2011), where linear relations at small and moderate magnitudes are

linked with a quadratic functional form to bridge intermediate magnitudes (Figure 5.7. and Table

5.2).

Figure 5.6 ML-Mw relation adopted in the present study.

Figure 5.7 Mw-ML residuals for the Swiss ECOS-09 catalogue data, with Mw determined using various methods (Goertz-Allmann et al., 2011).


64

In the present dataset, there is a clear discrepancy between the trends indicated by Mw values

obtained from spectral fitting of weak-motion data, and those obtained from moment tensor

inversion, for ML* values around 4.0. The moment-tensor based data are deemed more reliable

estimates of Mw, and are therefore given preference in the determination of the conversion

relation. This in turn requires to ignore the larger Mw values from spectral fitting, for which the

regression is limited to points with ML* ≤ 2.5 and performed on values averaged over 0.1

magnitude unit wide bins in order to minimise the effects of varying sample size with magnitude.

A 1:1 scaling is imposed for ML* ≥ 4.0. The quadratic part of the conversion relation is then

derived to link this to the 1:1 scaling observed for ML* ≥ 4.0. The equations for the resulting

relation, shown as a dark pink line in Figure 5.6, are thus given by:

𝑀𝑤 = 0.5631𝑀𝐿 + 0.9265 𝑓𝑜𝑟 𝑀𝐿 ≤ 2.5

𝑀𝑤 = 0.1942 𝑀𝐿2 − 0.1518𝑀𝐿 + 1.5 𝑓𝑜𝑟 2.5 ≤ 𝑀𝐿 ≤ 4.0 (5.4)

𝑀𝑤 = 𝑀𝐿 𝑓𝑜𝑟 𝑀𝐿 ≥ 4.0

Due to the lack of a constant offset, the intermediate-magnitude kink in the relation is more

pronounced, leading to a fairly strong non-linear behaviour for ML* ≤ 4.0. In the absence of

reliable Mw values in this intermediate magnitude range, it is difficult to ascertain whether such

strong non-linearity is genuine. Various physical explanations have been suggested for this

non-linear behaviour, including the breakdown of self-similar scaling and an interpretation as a

scaling artefact due to the difficulty of reliably determining the corner frequency fc of the

spectrum at small magnitudes, notably because of the kappa filter (Scherbaum, 2012).

Whatever the cause of the non-linearity, it is likely to bias the estimation of recurrence

parameters, therefore events with moment magnitudes Mw smaller than 4.0 will not be used in

this estimation, following the recommendations in USNRC (2012).


65

Table 5.2 Conversion relations between ML and Mw Reference Equation Region N1 ML range Mw method Notes

Goertz-Allmann et

al. (2009)

3.04085.0253.0327.142

985.0594.022

−=>+++=≤≤

+=<

LwL

LLwL

LwL

MMMMMMM

MMM

Switzerland ~1000+

(multiple

methods)

0.1 to 5.5 Multiple methods

Grünthal et al.

(2009) 53.0646.00376.0 2 ++= LLw MMM

Central, Eastern and

Northern Europe

221 -0.8 to 6.2 Mixed Supersedes Stromeyer et al.

(2004) equation.

New data (mostly Swiss) fills gap

between ML 3.5 and 5.0.

σ is a function of ML

Edwards et al.

(2008) 58.071.0 += Lw MM

United Kingdom 273 2.0 to 4.7

Drouet et al.

(2008) NaSSw

LDGw

MMMM

Re)05.0(93.0)17.0(02.0)05.0(95.0)19.0(27.0

±+±−=±+±−=

France (Alps &

Pyrenees)

2.9 to 5.2

2.4 to 5.3

Joint inversion

Miao & Langston

(2007) 8170.07603.0 += Lw MM

Central United States 27 3.6 to 5.3

Castello et

al.(2007) 20.1)4.0(79.0

92.10)06.0(18.1)( 0

+±=+±=

Lw

L

MMMMLog

Italy 101 3.5 to 5.8 Regional centroid

moment tensors

Clinton et al.

(2006)

)18.06.2()056.0(36.0*)13.07.1()04.0(66.0)12.03.1()034.0(64.0)097.08.0()024.0(8.0

±+±=±+±=±+±=±+±=

Lw

Lw

Lw

Lw

MMCQualityMMCQualityMMBQuality

MMAQuality

Southern California A: 281

B: 212

C:1226

C*:733

3.0 to 6.5

2.8 to 4.7

2.5 to 5.9

2.5 to 5.2

Automatic regional

moment tensor


66

Table 5.2 continued. Reference Equation Region N1 ML range Mw method Notes

Allen et al.(2006) 34.1016.1)( 0 += LMMLog Southwestern

Western

Australia

69 1.8 to 4.8

Allen et al.(2004) 83.064.0 += Lw MM Southeastern

Australia

93 1.6 to 5.0

Grünthal &

Wahlström

(2003); Stromeyer

et al. (2004)

2)11.0(046.0)08.0(56.0)11.0(67.0 LLw MMM ±+±+±= Central Europe 161 -0.8 to 6.2 Mixed

Muço et al.

(2002) 898.198317.0)( 0 += LMMLog

Albania 51 2.2 to 4.5

Wahlström &

Grünthal (2000) 2.128.006.0 2 ++= LLw MMM

Fennoscandia 350 2.0 to 5.2 Modified from Kim et al. (1989);

same data used.

Papazachos et al.

(1997) 58.097.0 += Lw MM

Greece 169 4.5 to 6.0 Mixed

Uhrhammer et al.

(1996) )131.0050.0()020.0(997.0 ±−±= Lw MM

California 3.6 to 6.8 Broadband waveform

inversion.

Thio & Kanamori

(1995) 5.1/)1.16)(( 0 −= MLogM L

Southern

California

180 3.2 to 6.5 Same relation found by

Thatcher & Hanks (1973)

Bollinger et al.

(1993) 17.1436.0059.0 2 ++= LLw MMM

Western United

States

Parameterised as given by

Grünthal & Wahlström (2003);

Kim et al. (1989) LMMLog 01.193.16)( 0 +=

Baltic Shield 350 2 to 5.2 Inversion of Fourier

spectra

1 Number of ML-Mw pairs used


67

5.3. Conversion from body-wave magnitude mb

For a small number of events in the catalogue, teleseismic body-wave magnitudes have been

calculated by ISC and/or NEIC (or its predecessors). Most of these are comparatively poor

determinations from a very limited number of stations (often only 1 or 2 African stations at

regional distances, such as Lwiro and Bangui), and dating back to the early to mid-1970s, when

mb determinations across agencies did not follow uniform conventions. The ISC determinations

are generally preferred as being based on a larger number of stations, but these are also not

without problems. In particular, the mb value of 5.6 for the 1969 Ceres mainshock (Mw 6.2)

appears to be affected by saturation. An alternative explanation for the low mb value of this

event could be a complex rupture mechanism, in which case the mb value could reflect the size

of an asperity, rather than integrating wave contributions from the whole source as other

magnitude definitions, such as MS, would do (Gupta & Rostagi, 1972).

For a fraction of the events for which mb was determined, a moment magnitude value is also

available (Figure 5.8). In view of the very extreme scarcity of the data from tectonic events, mb-

Mw pairs from four mining events were examined in an attempt to expand the dataset. However,

even at the low resolution afforded by the data, the mining-related data exhibit a different

behaviour, hence will not be considered further. The available mb-Mw data are compared with

the published conversion relations of Johnston et al. (1994) and Johnston (1996) for global SCR,

as well as the global relation of Scordilis (2006), all of which are shown beyond their range of

applicability in Figure 5.8. Note that this comparison plot of available data vs. existing mb-Mw

relations is used not so much to select the most appropriate mb-Mw relation (which is precluded

by the paucity of the data), but simply as a check that imported relations are not in contradiction

with the very limited number of local data available. The Johnston (1996) relation de facto

supersedes the Johnston et al. (1994) relation, which does not fit the limited data available at all.

Out of the three relations available, the Johnston (1996) relation appears to be the best-

behaved, since the strong departure from a 1:1 relation for the Scordilis (2006) relation is

controlled by the choice of functional form, rather than by data constraints. The Johnston (1996)

relation is therefore tentatively chosen for the conversion.

As a check on the consistency with the conversion relation for local magnitude, the estimates of

Mw obtained from applying the Johnston (1996) relation to available mb values from ISC is

plotted against the relevant ML* values and superimposed on the ML*-Mw data (Figure 5.9). The

results display a large scatter, which is not altogether surprising giving that this is a two-step

conversion, and that conversion relations based on global datasets, such as the ones

considered here, tend to exhibit significant scatter.


68

Figure 5.8 Comparison of mb-Mw data in study region with available conversion relations

Figure 5.9 Consistency check between ML-Mw conversion and mb-Mw conversion.


69

Nevertheless, within the resolution of the data, a reasonable fit is observed, but again, there

appear to be issues for magnitudes with ML* between 3.0 and 4.0. These issues are likely to be

caused by the unconstrained behaviour of the conversion relation when extrapolated beyond its

intended limits of applicability. The difficulty to constrain data in this magnitude range again

suggests the exclusion of these data from any downstream calculations, regardless of other

considerations such as completeness.

5.4. Conversion from surface-wave magnitude MS

The conversion from surface-wave magnitude MS is included here mainly for the sake of

completeness, since for the modern instrumental area, estimates of this magnitude are only

available for:

• Events large enough to have a Mw estimate (Ceres 1969, Koffiefontein 1976), thus not

requiring conversion; these generally support the Mw=MS scaling assumed for larger

events in published conversion relations (e.g., Scordilis, 2006)

• Events too small to generate substantial surface-waves, for which the MS value is based

on 1 or 2 stations only and appears to be abnormally small compared to the body-wave

magnitude, which is found to be considerably better constrained.

Thus, the issue of conversion from MS is limited to those values determined from early

instrumental recordings on intermediate-period instruments by Ambraseys & Adams (1991) for

the 20 February 1912 Koffiefontein (MS = 6.2) and 4 December 1920 offshore (MS 6.4)

earthquakes. Ambraseys & Adams (1991) state that they use the Prague formula in their

calculations, therefore the resulting values should be directly comparable to modern

instrumental MS determinations.

5.5. Conversion from Gutenberg-Richter magnitude MGR

The exact calculation method of the Gutenberg-Richter remains unknown, however it is

generally considered to be close to the surface-wave magnitude MS, with some authors finding

that the MGR values need to be reduced by 0.2 magnitude units in order to reconcile early

instrumental and modern seismicity rates. A comparison between the MGR values and re-

evaluated MS values of the sub-Saharan African events studied by Ambraseys & Adams (1991)

supports the observation that MGR values for this region sometimes deviate significantly from re-

evaluated values.


70

In the current catalogue, this conversion is solely required for one event in the intensity

database, namely the 31 December 1932 event off Cape St Lucia. While there is close to no

data available to constrain the conversion relation, the event itself is well-documented, with a

reasonably well-constrained epicentral location. The plentiful macroseismic data supports a

smaller magnitude than the value of 6¾ listed by Gutenberg & Richter (1958). The Mw value for

this event is therefore determined as a composite estimate of 6.3 +/- 0.3 by considering the

range of magnitude values that would be consistent with the epicentral location and observed

macroseismic intensity field, as well as the instrumental amplitude recorded on the Union

Observatory seismograph in Johannesburg.

5.6. Conversion from Bulawayo magnitude mBUL

The final instrumental magnitude scale for which a conversion is required is the magnitude

calculated by the Goetz Observatory in Bulawayo based on the data registered by the network

of stations located in present-day Zimbabwe, Zambia and Malawi. This conversion concerns

events that occurred in the late 1960s and early 1970s, in particular the foreshock-aftershock

sequence of the 1969 Ceres earthquake, for which no other reliable estimate of magnitude is

available.

The Bulawayo magnitude is close to an mbLg magnitude (Nuttli, 1973) since it is nominally

calculated based on the A/T ratio. However, for events in South Africa, Chen et al. (1980) note

that T is difficult to determine and therefore a value T = 1.0s is assumed, which effectively

makes the magnitudes determined by this institution comparable to local magnitudes. As shown

in Figure 5.2, the distance correction term implemented at the time is found to be very similar to

that of Saunders et al. (2012), therefore these magnitudes are considered to be equivalent to

ML* as described previously. Note that the ML values given by Fernandez (1974) for a number

of events of the Ceres sequence also use the Bulawayo distance corrections, and are therefore

also considered directly equivalent to ML*.

In the late 1970s and early 1980s, the calibration of the Bulawayo magnitudes was revised to

match the mb estimates provided by NEIC. This was not necessarily an improvement, given that

early NEIC mb values for southern Africa have been found to be frequently unreliable (e.g.,

Johnston et al., 1994). However, this update does not affect the present study given that by that

time, local magnitudes from the SANSN represent the preferred magnitude option for events in

the study region.


71

5.7. Estimation of magnitudes from intensity data

5.7.1. Events with an IDP field

For events for which a set of IDPs is available, magnitudes are estimated using the third-

generation algorithms implemented in the MEEP2 software (Musson, 2009), as discussed

previously in Section 3.1.1. While there are four algorithms for location, the magnitude

determinations use one of two methods:

• The implementation of the Bakun & Wentworth (1997) method in the MEEP2 software

uses a predefined IPE (in this case, Bakun & Scotti, 2006) to determine the best-

estimate magnitude;

• The three other methods use the calibration of the Frankel (1994) formula to determine

magnitude.

Note that in some badly-behaved cases, the Bakun & Wentworth (1997) method has difficulty to

converge and the critical-path implementation in MEEP2 software then tends to move the

epicentre away from the data (e.g., offshore) and increase the magnitude of the event. This is

equivalent to the grid search not finding a good fit and ending up in a corner of the originally

specified grid in the original Bakun & Wentworth (1997) approach. In such cases, preference is

given to the magnitude estimates from the other methods, although it is acknowledged that the

lack of convergence of the Bakun & Wentworth (1997) points to insufficient data to constrain a

solution, hence the uncertainties associated with alternative methods are high.

The performance of the methods is illustrated in Figure 5.10 using the events analysed by Midzi

et al. (2012) that also have an instrumental determination of magnitude, with Mw estimated as

described in the previous section. The uncertainty bars for MI reflect the standard deviation of

the bootstrap solutions obtained for each approach using the MEEP2 software, while the Mw

uncertainties are those listed in the catalogue (or similarly determined for events falling outside

the catalogue region), as discussed in Section 5.8. These plots show, in general, a good

agreement between the intensity magnitude MI and the instrumental Mw estimate, with the

exception of cases where the Bakun algorithm does not converge.

As a result, the intensity magnitude values MI determined from calculations using the MEEP2

software are taken as directly equivalent to Mw. This is also consistent with the fact that both the

Frankel (1994) formula and the Bakun & Scotti (2006) IPE are formulated in terms of Mw.


72

Figure 5.10 Intensity magnitudes obtained from using the different methods implemented in the MEEP2 software compared with instrumentally determined magnitudes. The uncertainty bars for MI reflect the standard deviation of the bootstrap solutions obtained for each approach using the MEEP2 software, while the Mw uncertainties are those listed in the catalogue (or similarly determined).


73

5.7.2. Events with isoseismal maps

In the case of events without an instrumental magnitude or IDP field but for which an isoseismal

map is available, the intensity magnitude is determined based on the equivalent areas

calculated from the isoseismal contours, in combination with the relevant equations from

Johnston (1996). These are compatible both with the calibration used in the MEEP software,

and with the Johnston (1996) equation used when only a single point of intensity is available.

The magnitude estimates from multiple isoseismals are then averaged using the variance-

weighted approach described in Johnston et al. (1994). For incomplete isoseismal contours, an

equivalent area is computed from the azimuth-averaged radius (calculated using the best

estimate epicentral location). This approach is described in more detail in the intensity database

report (Midzi et al., 2012).

5.7.3. Events for which only Imax is available

The magnitudes listed in the Brandt et al. (2005) catalogue for the historical period have been

inferred from the maximum observed intensity value, following the same approach as in

Fernández & Gúzman (1979). In both cases, the conversion was carried out using the empirical

relation of Gutenberg & Richter (1954):

0.132

0 += IM L (5.5)

where ML is the Richter magnitude (local magnitude calibrated to southern California), and I0 is

the macroseismic intensity at the source. This conversion is now considered to be superseded

by more recent relations, notably the relation proposed by Johnston (1996):

( ) 2maxmax010 0244.0481.036.19log IIM ++= (5.6)

where M0 is the seismic moment of the event, in dyne-cm, which can be converted to moment

magnitude using Eq. (5.1).

The maximum observed intensity Imax is often used as a proxy for I0, although in cases of sparse

data coverage this value tends to be smaller than the true value of I0. In the case of strong site

effects, Imax might also be higher than I0. In the present dataset, the locations from which Imax

values have been reported for the historical and early instrumental period overlap to a large

extent with the locations considered in the Albini (2012) and Midzi et al. (2012) studies, which,


74

with very few and notable exceptions such as coastal sites, have been found to be devoid of

strong site effects. As a result, the magnitudes determined through this methodology are

considered lower bound estimates.

The values of Imax listed by Brandt et al. (2005) have been checked against Fernández &

Gúzman (1979) as well as the primary sources used in both compilations (e.g., Theron, 1974).

The originally assigned value of Imax has been retained in each case, except when there is clear

evidence that the Brandt et al. (2005) value is an update based on the incorporation of

additional evidence (e.g., from De Klerk & Read, 1988). When the listed value is given as two

intensity levels (e.g., Imax III-IV), the arithmetic mean of the magnitude values obtained for each

level was adopted, although it is acknowledged that such cases reflect uncertainty as to the Imax

value, rather than defining intermediate half-degrees of intensity.

5.8. Magnitude Uncertainties

Given the limited amount of data available for the vast majority of the magnitude determination,

as well as the significant uncertainties associated with the conversions to moment magnitude,

the specification of the uncertainties associated with the magnitude values is an essential

component of the catalogue. The hierarchical approach of Johnston et al. (1994), reproduced in

Table 5.3, was used as a guide for the determination of uncertainties. For most conversions, the

uncertainty values determined for the global SCR dataset by Johnston et al. (1994) can be

treated as lower bound estimates for the uncertainties encountered in the TNSP catalogue.

There are, however, the following two exceptions to this rule:

• The conversion uncertainty for the regional set of uniformly recalibrated ML* values

considered in this study is expected to be lower than the uncertainty determined by

Johnston et al. (1994) for an inhomogeneous global set of ML values, and comparable to

the conversion uncertainty for the mbLg magnitude.

• The magnitude uncertainties determined from the Albini (2012) IDP sets analysed using

MEEP2 are expected to be lower than the values quoted for isoseismal contours by

Johnston et al. (1994) for well-behaved datasets, since the IDPs have been uniformly

reappraised and a more objective estimation technique is used.

The detailed assessment of magnitude uncertainties for the TNSP catalogue is discussed in the

following sections.


75

5.8.1. Magnitude uncertainties for instrumental data

5.8.1.1. Direct estimates of Mw

For the small number of events for which a direct estimate of Mw is available (Table 5.1), a

magnitude uncertainty of 0.16 magnitude units is assigned following USNRC (2012).

5.8.1.2. Conversions from M0

For Mw values obtained from M0 values obtained through the weak-motion inversions of

Rietbrock & Drouet (2012), the magnitude uncertainty is set at 0.2 magnitude units, following

Johnston et al. (1994).

Table 5.3 Magnitude uncertainties determined by Johnston et al. (1994) Category Description Assigned

Quality

Estimated Uncertainty of

M

1a Instrumental M0 (spectra, waveform matching,

inversion)

A ± 0.20

1b M0 from field observations A ± 0.25

2a Weighted average of mb, MS B ± 0.25

2b Teleseismic (20s) MS B ± 0.25

2c Teleseismic (1s) mb B ± 0.30

2d Instrumental mbLg B ± 0.30

2e MGR (Gutenberg & Richter, 1956) ≈ MS (not “class d”) B ± 0.30

3a Isoseismal areas: average of 3-6 contour areas C ± 0.35

3b Isoseismal areas: average of 1-2 contour areas C ± 0.35

4a Direct ML-log(M0) regression C1 ± 0.40

4b Regional mb, MS (non-ISC/NEIS) C1 ± 0.40

4c ML regressed to mb/MS then to M0 C1 ± 0.40

4d MGR (Gutenberg & Richter, 1956), “class d” C1 ± 0.40

5a Magnitude based on intensity equated to mb, MS, mbLg D ± 0.50

5b Mw estimated from quoted isoseismal areas or radii D ± 0.50

6 Mw from number of recording stations D1 ± 0.60

7 Mw estimated from I0 only. X ± 1.00

8 Mw assigned by judgment Z ± 1.20

5.8.1.3. Conversions from mb

For Mw estimates obtained from mb using the Johnston (1996) equation, the magnitude

uncertainty is set to the standard deviation associated with this equation, namely 0.26

magnitude units.


76

5.8.1.4. Conversion from MS and MGR

As noted previously in Sections 5.4 and 5.5, conversions from MS and MGR are limited to larger

events of the early instrumental period, for which macroseismic data provides additional

constraints. For the MS values reappraised by Ambraseys & Adams (1991) for the 20 February

1920 Koffiefontein and the 4 December 1920 offshore events, the uncertainty is set at 0.25

magnitude units since these values are considered equivalent to a teleseismic MS value. The

MGR value of 6.75 for the 31 December 1932 Off Cape St Lucia event has been revised

downwards based on the macroseismic data; the uncertainty is therefore assigned in the same

manner as for other events analysed using MEEP2 (see Section 5.8.2.1).

5.8.1.5. Conversion from ML*

Magnitudes obtained from the SANSN local magnitude consider the event-specific uncertainty

in the determination of the regionally recalibrated ML*, σML*, defined as the standard deviation

taken across the individual recalibrated station ML values, as well as the conversion uncertainty

from ML* to Mw, which is defined as follows:

𝜎𝑀𝑤=𝑓(𝑀𝐿∗) = 0.2 𝑓𝑜𝑟 𝑀𝐿

∗ ≤ 2.5

𝜎𝑀𝑤=𝑓(𝑀𝐿∗) = 0.2 +

0.11.5

(𝑀𝐿∗ − 2.5) 𝑓𝑜𝑟 2.5 ≤ 𝑀𝐿

∗ ≤ 4.0 (5.7)

𝜎𝑀𝑤=𝑓(𝑀𝐿∗) = 0.3 𝑓𝑜𝑟 𝑀𝐿

∗ ≥ 4.0

The total uncertainty for the resulting Mw estimate is then given by:

𝜎𝑀𝑤 = ��𝜎𝑀𝑤=𝑓(𝑀𝐿∗)�

2 + �𝜎𝑀𝐿∗�2 (5.8)

The standard deviation for this conversion was fixed to 0.2 at small magnitudes based on the

dispersion of the weak-motion data (see above); at larger magnitudes, the standard deviation is

set to a larger value (0.3) in view of the lower level of constraint available. This value is selected

such as to encompass the available empirical data.

For the earlier BPI ML data, the ML* recalibration is more uncertain due to the lack of information

regarding the detailed assumptions of the calculation process employed, and therefore the

uncertainty on the resulting Mw value is set to 0.6. Again, this value is selected so as to envelop

alternative determinations for the limited data available, and to be slightly higher than the later,

better documented MBUL values.


77

5.8.1.6. Conversion from MBUL

The values converted from MBUL have been assigned an uncertainty of 0.5. The rationale behind

this assignment is that based on the definition of this magnitude, associated uncertainties are

expected to be slightly higher than those for a regional mb scale.

5.8.2. Magnitude uncertainties for macroseismic data

5.8.2.1. Albini (2012) IDP sets analysed using MEEP2

For the magnitudes obtained from the IDP sets determined by Albini (2012), uncertainties were

determined on an event-by-event basis by considering the uncertainties obtained from the

bootstrapping process. Although four different methodologies have been implemented in

MEEP2, the magnitude calculations for the centroid and pairwise solutions are essentially using

the same methodology as the MEEP method, hence the assessment was made by combining

the magnitude estimates from the MEEP method with that of the Bakun method, taking into

account the fact that the Bakun method tends to move events away from the IDP set and to

larger magnitudes in cases of convergence difficulties. External constraints from instrumental

recordings and the overall felt area were also used to determine bounds on the values

assessed. Thus, the resulting values, summarised in Table 5.4 for the historical period and

Table 5.5 for the early instrumental period, are to be interpreted as the best estimates and

range of values assessed from all available information for the events under consideration.

Table 5.4 Magnitudes and associated uncertainties for events of the historical period studied by Albini (2012) analysed using the MEEP2 software

Date Most affected place Mw Uncertainty

1850 May 21 Morley (EC) 5.7 0.4

1859 April 11 Colesberg (NC) 3.7 0.8

1861 August 17 Burghersdorp (EC) 4.6 0.7

1862 June 16 Durban (KN) 4.2 0.5

1862 June 23, h 2:00 Cape Town (WC) 4.6 0.5

1864 February 24 George (WC) 4.1 0.5

1867 February 24 Hopetown (NC) 3.0 0.8

1867 July 24 Bethany (FS) 3.1 0.8

1867 October 15 King William’s Town 5.1 0.5

1868 October 8 George (WC) 4.1 0.8

1870 February 25 Durban (KN) 3.3 0.8

1870 August 3 Harrismith (FS) 5.5 0.5

1895 April 9 Uitenhage (EC) 4.1 0.5


78

Table 5.5 Magnitudes and associated uncertainties for events of the early instrumental period studied by Albini (2012) analysed using the MEEP2 software

Date Most affected

place Mw Uncertainty Remarks

1908 September 26 Bloemfontein (FS) 5.5 0.5

1910 October 21 Hanover (NC) 5.7 0.5

1911 July 6 Oudtshoorn (WC) 3.1 0.8

1911 July 10 Hillary (KN) 3.1 0.8

1912 February 20 Bloemfontein (FS) 6.2 0.25 Instrumental magnitude, confirmed by

macroseismic data

1912 November 17 Kimberley (NC) 5.5 0.4

1920 December 4 Port Elizabeth (EC) 6.4 0.3 Instrumental magnitude, confirmed by

macroseismic data

1922 October 31 De Rust (WC) 3.0 0.8

1927 September 22 Xolo/Bolo (EC) 3.1 0.8

1932 August 9 Grahamstown (EC) 5.7 0.35 Instrumental constraints

1932 December 31 Eshowe (KN) 6.3 0.3 Location fixed to best instrumental

solution.

Composite magnitude determination

1933 February 25 Grahamstown (EC) 3.2 0.8

1936 April 26 Loerie (EC) 3.4 0.8

5.8.2.2. Magnitudes from isoseismals

For the few events for which the magnitude determination was based on isoseismals, the

uncertainties of the Johnston (1996) equations were averaged using the variance-weigthed

approach described in Johnston et al. (1994).

5.8.2.3. Magnitudes from I0

Events for which the magnitude was determined solely on the basis of I0 were assigned a

magnitude uncertainty of 1.0 following Johnston et al. (1994). Part of the reason for assigning a

large uncertainty to such events is the aforementioned ambiguity regarding the validity of the

assumption that the available maximum observed value of intensity is indeed the epicentral

value I0.


79

5.8.3. Summary

Figure 5.11 shows a summary of the magnitude uncertainties for events with Mw ≥ 2.0 in the

TNSP catalogue. These uncertainties are large in comparison to those encountered in

catalogues with more plentiful instrumental data (e.g., USNRC, 2012). The paucity of well-

constrained Mw values that can be used to constrain conversions is likely to remain in place for

some time given the low seismicity levels and sparse nature of the recording network.

Macroseismic reports contribute a significant proportion of the database. For these events, the

large uncertainties could in some cases be reduced by carrying out detailed investigations of

individual events, in particular gathering additional IDPs for events for which the magnitude is

currently estimated based on I0 only.

Figure 5.11 Distribution of magnitude uncertainties in TNSP catalogue

Finally, it should be noted that since the magnitude uncertainties for the TNSP catalogue have

in most cases been obtained from the consideration of external constraints, rather than direct

regression analysis, they are in general not directly equivalent to the regression based standard

deviations used in methods to correct biases resulting from magnitude uncertainties in

recurrence calculations (e.g., USNRC, 2012).


80

6. Catalogue declustering

The present catalogue is used primarily for the estimation of seismicity recurrence parameters

to characterise the various seismic sources comprising the SSC model. In view of the limited

number of earthquakes available, the analysis is limited to time-independent models and

therefore the usual assumption of a Poissonian distribution is made to characterise earthquake

occurrences in time. Under this assumption, the rate parameter of the Poissonian distribution

characterises the long-term rate of seismicity.

This assumption requires events to occur independently from one another, therefore events

whose occurrence is causally linked to that of other events, such as foreshocks and aftershocks,

which effectively represent short-term perturbations of seismicity rate, need to be removed from

the catalogue prior to undertaking the rate calculations. This is done through the use of

algorithms identifying dependent events, often called declustering algorithms, for which

available options are reviewed in the next section. The ZMAP catalogue analysis package

(Wiemer, 2001) is used for practical implementation of these routines.

6.1. Options for identification of dependent events

Options for identifying dependent events fall into three main categories:

(i) window-based approaches (Section 6.1.1), which as their name indicates, identify

dependent events based on spatio-temporal windows;

(ii) cluster-link approaches (Section 6.1.2), such as the frequently used Reasenberg (1985)

algorithm, which link sequences of events into clusters considering multiple levels of

dependencies;

(iii) rate-based and stochastic approaches (Section 6.1.3), which essentially consider

deviations from the long-term background rate and/or the Poissonian distribution

assumption.

6.1.1. Window-based approaches

The simplest and longest-established method for declustering is the windows-based method of

Gardner & Knopoff (1974) based on earlier efforts by Knopoff & Gardner (1972). This method

essentially consists in defining magnitude-dependent windows in space and time around each

event of the catalogue. If an event falls into the spatio-temporal window of another, the two


81

events are members of the same cluster. Once all events have been assigned to clusters or

found to be independent, the largest event in each cluster is labelled as the mainshock of the

cluster, and all events within its spatio-temporal window as dependent events. The latter are

then deleted to obtain the declustered catalogue. Note that events falling within the window of a

secondary event but not of the event labelled as mainshock, are not deleted in this approach.

The spatio-temporal windows of the Gardner & Knopoff (1974) approach were originally derived

empirically from southern Californian data. They are nevertheless often applied to other

geographical regions, and have also been used for declustering global catalogues (e.g.,

Shearer & Stark, 2012). Grünthal (1986) independently derived alternative windows using

Central European data. As shown in Figure 6.1 these remain close to the Gardner & Knopoff

(1974) windows, with the consequence that applying these two algorithms often produces very

similar results. Updated windows developed for California by Uhrhammer (1986), however, are

significantly different (Figure 6.1).

Figure 6.1 Magnitude-dependent distance and time window sizes for the Gardner & Knopoff (1974), Grünthal (1986) and Uhrhammer (1986) declustering algorithms, as implemented in ZMAP (van Stiphout et al., 2012).

6.1.2. Cluster-link models

Cluster-link models, such as the widely used Reasenberg (1985) algorithm, group events into

the same cluster as long as they fall within the window of any event that is already in the cluster.

This allows the inclusion of higher-level dependencies (e.g., aftershocks of aftershocks), which


82

could be missed in a simple windowing approach, as illustrated in Figure 6.2. Another feature of

cluster-link approaches is that the clusters grow with the number of events analysed.

The Reasenberg (1985) algorithm requires the specification of several calibration parameters,

which are listed in Table 6.1, alongside the default values provided in the ZMAP implementation

of this algorithm, which correspond to empirical values determined for California.

Figure 6.2 Schematic illustration of the difference between window-based and cluster-link approaches (Tibi et al., 2011): windows-based approaches may miss events such as E2 which are in the window of an aftershock E1, but fall outside the window of the mainshock M.

Table 6.1 Calibration parameters for Reasenberg (1985) algorithm, alongside their default values as implemented in ZMAP.

Parameter Description ZMAP Default

Value τmin Lower bound on interaction time window, in days 1 τmax Upper bound on interaction time window, in days 10

p Empirical decay factor of the modified Omori law 0.95

Xk Multiplicative factor on maximum event magnitude by which XMEFF is raised during a cluster

0.5

XMEFF Effective lower magnitude cut-off for the catalog 1.5

Rfact Scaling factor for spatial interaction zone (Reasenberg’s Q factor)

10

Epicentral error Error on epicentral location, in km 1.5 Depth error Error on depth, in km 2.0

The Reasenberg (1985) algorithm is often implemented with these default parameters, even for

regions other than Central California. This choice may not always be appropriate for other

regions, since these parameters may depend on catalogue quality and completeness. A recent

study by Ebel (2009) found that Omori-law parameters determined for aftershock sequences for

a number of SCR areas were in good agreement with each other, as well as being similar to

those of California aftershock sequences. However, Tibi et al. (2011) noted, amongst other


83

difficulties in application, the sensitivity of the Reasenberg (1985) algorithm to the choice of the

upper bound of the interaction time window, and proposed an alternative cluster-link model that

is less reliant on subjective decisions by the analyst, in which the time links are based on a

simple magnitude-dependent function, rather than on Poisson probability. However, their

method remains sensitive to catalogue-specific parameters, such as the minimum cut-off

magnitude, as well as location errors in terms of epicentral location and depth. The latter can be

significant (or even unknown) in the case of very sparse catalogues, such as the one under

consideration in this study.

6.1.3. Rate-based approaches

As part of the EPRI-SOG project, Veneziano & Van Dyck (1985) developed a method to thin out

all the events contributing to deviations from the background rate; this approach has recently

been implemented in the CEUS SSC project (USNRC, 2012). A similar concept was proposed

by Zhuang et al. (2002) under the name of stochastic declustering; for each event, this

approach estimates the probability of being a background or a triggered event, by making use

of the thinning operation for point processes. Hainzl et al. (2006) similarly used stochastic point-

process simulations to classify events as mainshocks or aftershocks and obtain non-parametric

estimates of the background seismicity rate based on the inter-event time distribution. Again,

declustering can be implemented as a thinning procedure by splitting the dataset such that the

rate of mainshocks matches the background rate determined from the observed inter-event

times. As noted by van Stiphout et al. (2012), the Hainzl et al. (2006) approach is not

conditioned on magnitude, hence the event designated as mainshock is not necessarily the

largest of a given cluster.

6.2. Selection of declustering approach

The various approaches to identification of dependent events reviewed above may give

different results in terms of the identity and proportion of dependent events identified (Figure

6.3). This in turn may have implications for seismic hazard analysis, if the estimation of the long-

term rate of seismicity is biased.

An important fact to acknowledge is that not all of these approaches have been developed with

the aim of removing dependent events prior to rate calculations for seismic hazard analysis,

therefore their performance in terms of returning a declustered catalogue from which unbiased

estimates of recurrence parameters can be obtained also varies. The identification of

dependent events has also been found to be an important factor in the understanding and


84

forward-modelling of the earthquake process. As a result, some of the methods listed above

(e.g., Reasenberg, 1985) are more targeted at the identification of aftershocks for the purpose

of keeping them to study the connections between events, rather than getting rid of them as

noise affecting the estimation of the background rate. One consequence of this is that these

methods may keep more data in the “declustered” catalogue, which may also deviate from the

Poissonian model. Methods such as the rate-thinning approach of Veneziano & Van Dyck

(1985), on the other hand, were developed specifically with seismic hazard applications in mind.

6.2.1. Poissonian nature of output

In view of the downstream use of the declustered catalogue, namely the estimation of

recurrence parameters assuming a Poissonian process (the latter being a key assumption for

time-independent seismic hazard analysis), the ability of the selected algorithm to provide a

declustered catalogue that follows the Poissonian model is critical. While some of the algorithms

reviewed above are specifically designed to meet this condition (e.g., Hainzl et al., 2006), others,

in particular Reasenberg (1985), have been found to be in violation of this assumption even in

cases where calibration should not be an issue (Hainzl et al., 2006; van Stiphout et al., 2012;

Luen & Stark, 2012).

Figure 6.3 shows a comparison of the results of various declustering algorithms applied by van

Stiphout et al. (2012) to a test catalogue, namely the ANSS catalogue in the California CSEP

testing region (Schorlemmer & Gerstenberger, 2007) between 1981 and 2010. The top panel

shows the cumulative number of M ≥ 3.5 events for the non-delcustered catalogue and the

declustered catalogues obtained using several declustering algorithms. For the Reasenberg

(1985) and Gardner & Knopoff (1974) approaches, uncertainties and parameters were varied

using 1000 simulated declusterings. The lines plotted correspond to the 5th and 95th percentiles

from this exercise. The bottom panel shows the results of a chi-squared test of the Poissonian

assumption. For each method, the dashed arrow labelled “boundary value” indicates the 5%

significance level of being Poissonian. If the computed chi-squared statistics of the time

distribution of the events of a given catalogue falls to the left of the boundary value, the

distribution of events can be considered Poissonian. This figure clearly shows that the

background seismicity obtained using the Reasenberg (1985) algorithm does not follow a

Poissonian distribution for either the standard parameters (developed for California) or indeed

most other parameters considered. A similar conclusion was reached by Hainzl et al. (2006),

who found that the Reasenberg (1985) algorithm systematically overestimated the percentage

of mainshocks specified in simulations based on a Poissonian model of background seismicity

combined with a magnitude-dependent Omori-law type aftershock behaviour.


85

The results presented in Figure 6.3 further show that variations of up to +/-10% in the

parameters of the Gardner & Knopoff (1974) model make little difference to the results, which

are found to be in good agreement with the Poissonian assumption. It should be noted that a

10% variation is relatively small, given the uncertainty on the length of the spatio-temporal

windows.

An excellent agreement is also observed between the Gardner & Knopoff (1974) results and the

stochastic approach of Zhuang et al. (2005). Figure 6.3 also illustrates the difficulty in choosing

between the algorithms that do satisfy the Poissonian assumption, for which absolute numbers

of events vary by a factor of 2.

Figure 6.3 Comparison of several algorithms for the identification and removal of dependent events (van Stiphout et al., 2012). See text for details.


86

6.2.2. Calibration and parameterisation

Most of the methods described above require the specification of parameters that have typically

been derived empirically for a specific catalogue and a given geographic region. This raises the

issue of whether this calibration can be considered universal and applied to other regions, or

whether locally derived parameters may be required. In the context of seismic hazard analysis,

this may need to be considered, since the improvement in methodology may be counter-acted

by increased epistemic uncertainty regarding the parameters. This is particularly an issue in

cases where empirical data available for calibration are very sparse, as is the case here.

The Gardner & Knopoff (1974) approach has been widely used outside of California, and found

to provide reasonable results even when the windows have not been calibrated to local data.

The similarity between the independently derived Grünthal (1985) and the original Gardner &

Knopoff (1974) windows, as well as the good performance of the Gardner & Knopoff (1974)

algorithm when applied at a global scale (Shearer & Stark, 2012) further point to the fact that

the spatio-temporal windows required in this approach are not strongly region-dependent. This

may be related to the previously noted fact that the method itself does not appear to be strongly

influenced by variations in its parameters (Figure 6.3; van Stiphout et al., 2012).

Finally, the number of data points required for a specific method to operate in a stable manner

also needs to be considered. Some of the methods listed above subdivide the data in subsets

(e.g. magnitude bins in Hainzl et al., 2006), making it difficult to obtain stable estimates for very

sparse datasets.

6.2.3. Relative performance compared to other methods

Even though seismic hazard analysis may address the epistemic uncertainty regarding the

optimal method to use by combining the results obtained from different approaches in a logic-

tree framework, it may not be desirable in practice to consider as alternatives catalogue

processing methods that give almost identical results in terms of recurrence.

Furthermore, for a catalogue such as the one under consideration here, with relatively few

events, a relatively high detection threshold due to the sparse nature of the network, the

potential added value from using more sophisticated approaches may not necessarily

materialise (i.e. the dependent events in the catalogue are “obvious” foreshocks and

aftershocks that will be picked up by any of the approaches available).


87

The recent CEUS SSC project (USNRC, 2012) considered both the rate-thinning approach of

Veneziano & Van Dyck (1985) and the Gardner & Knopoff (1974) window-based approach in

declustering the project catalogue. The results in Table 6.2 show that both approaches lead to

almost identical results. A similarly good agreement between the Gardner & Knopoff (1974)

approach and the stochastic approach of Zhueng et al. (2002) has been found for the California

catalogue analysed by van Stiphout et al. (2012; Figure 6.3).

Table 6.2 Comparison of EPRI (1988) and Gardner & Knopoff (1974) declustering approaches for the CEUS catalogue (USNRC, 2012). E[M] is the expected value of moment magnitude.

E[M] Magnitude Range

Number of earthquakes in E[M] Magnitude Range

Entire Catalogue Independent earthquakes

using Veneziano & Van Dyck (1985) approach

Independent Earthquakes using Gardner & Knopoff

(1974) approach 2.9-3.6 2333 1787 1865 3.6-4.3 696 554 530 4.3-5.0 204 168 155 5.0-5.7 44 36 33 5.7-6.4 13 13 13 6.4-7.1 4 4 3 7.1-7.8 3 2 0 7.8-8.3 1 1 1

6.3. Application to TNSP catalogue

This has been explored using the three window-based declustering algorithms implemented in

the ZMAP seismicity analysis package (Wiemer, 2001), namely the Gardner & Knopoff (1974),

Grünthal (1986) and Uhrhammer (1986). Rate-based and cluster-link based models have not

been explored in view of the aforementioned practical issues relating to calibration and dataset

splitting.

6.3.1. Subset of modern instrumental data

For the evaluation of the catalogue completeness and the derivation of a regional b-value, the

subset of the catalogue corresponding to modern instrumental data (1972-2011) from the

SANSN was studied in more detail. This subset of 1917 events with Mw ranging from 1.27 to

5.80 was selected in order to avoid potential issues related to the uncertainties related to

magnitude conversion, which are expected to be considerable for the pre-1971 data in view of

the heavy reliance on macroseismic information and data from other networks.


88

As a preliminary step, the sensitivity to the choice of declustering algorithm was examined by

applying the three window-based declustering algorithms implemented in ZMAP. The results of

this analysis are summarised in Table 7.3. Examination of the resulting seismicity maps reveals

that the Gardner & Knopoff (1974) and Grünthal (1986) algorithms give very similar results,

removing around 40-45% of the events and picking up all of the events that would a priori be

considered to form part of a foreshock/aftershock sequence or a seismic swarm. In contrast, the

Uhrhammer (1986) algorithm only labels 7% of events as dependent events, and does not

appear to detect some of the “obvious” dependent events. From this analysis it is concluded

that the Uhrhammer (1986) algorithm does not appear appropriate for the catalogue under

investigation, and that there is no significant difference between applying the Gardner & Knopoff

(1974) and Grünthal (1986) algorithms.

Table 6.3 Results of applying the declustering algorithms of Gardner & Knopoff (1974), Grünthal (1986) and Uhrhammer (1986) to the modern SANSN data subset (1972-2011) of the TNSP catalogue. Gardner & Knopoff

(1974) Grunthal (1986) Uhrhammer (1986)

Number of clusters 104 106 59

Number of events

removed

770 892 148

Percentage of events

removed

40.17% 46.53% 7.72%

Number of remaining

events

1147 1025 1769

Percentage cluster

seismic moment w.r.t.

total seismic moment

3.47 % 4.54% .07%

Remarks Picks up Ceres,

Koffiefontein, Augrabies,

Lesotho, Kokstad and

Leeu-Gamka

Very similar to GK74 Picks up Augrabies, some

Koffiefontein, some

Lesotho, no Ceres

(mainshock not included in

this subset). Seems not

severe enough.

6.3.2. Application to the full catalogue

Based on the discussion in preceding sections, the Gardner & Knopoff (1974) algorithm is

applied to the full TNSP catalogue. The results are shown in Figure 7.4. Cluster-link models

such as Reasenberg (1985) and more sophisticated models such as rate-thinning and


89

stochastic models were not considered as it would be problematic to calibrate such models with

confidence with the limited data available. Also, for the cluster-link models, the deviation from

the Poissonian model and related overestimation of the proportion of mainshocks may

adversely affect the recurrence calculation by reducing even further the influence of the already

very sparse moderate-to-large events.

Figure 6.4 Results of applying the Gardner & Knopoff (1974) declustering algorithm to the TNSP catalogue. The source zones shown correspond to the preliminary TNSP SSC model.

6.4. Results for selected clusters

The declustering results using the Gardner & Knopff (1974) algorithm are examined in more

detail for events in the Ceres and Koffiefontein regions, defined for this exercise as square

regions of 1 degree extent centred on the largest mainshock. The Ceres region thus

corresponds to the region delimited by latitudes 32.8° to 33.8° S and longitudes 18.7° to 19.7° E.

Similarly, the Koffiefontein region corresponds to the region delimited by latitudes 29.0° to 30.0°

S and longitudes 24.5° to 25.5° E.


90

Figure 6.5 Gardner & Knopoff (1974) declustering algorithm results for events in the Ceres region.

The results for post-1900 data are shown in Figure 6.5 for Ceres and Figure 6.6 for Koffiefontein.

These results show that the Gardner & Knopoff (1974) algorithm is efficient at detecting the

immediate aftershocks of larger events, but otherwise considers events to be independent

unless they occur very closely in space and time.


91

Figure 6.6 Gardner & Knopoff (1974) declustering algorithm results for events in the Koffiefontein region.


92

7. Catalogue Completeness

In addition to the removal of dependent events through declustering, the catalogue used for the

calculation of seismicity rates also needs to be assessed in terms of its completeness. An

earthquake catalogue can be said to be complete above a given magnitude Mc (magnitude of

completeness) over a period Tc (period of completeness) if all earthquakes with magnitudes

equal or greater to MC that have occurred during the period TC in the region covered by the

catalogue are listed in the catalogue. If any of these events are missing, the catalogue is said to

be incomplete. Catalogue incompleteness needs to be taken into account in the recurrence

calculations, since failure to do so may result in biased estimation of seismicity rates and b-

values, and thus may affect the final hazard results.

7.1. Overview of approaches available

A variety of approaches are available to address the issue of catalogue completeness. These

are reviewed in the following sections, before the approach adopted in the present study is

described. For a given magnitude level, completeness can vary significantly in both time and

space, due to factors related to earthquake detection capabilities for the instrumental part of the

data, as well as factors related to reporting practices and record survival for the historical part of

the data.

7.1.1. Statistical approaches

Most commonly, catalogue completeness is determined through statistical analysis of the

(declustered) earthquake catalogue, typically by considering the evolution of the cumulative

number of events against time. Under the assumption of a Poisson distribution, the cumulative

rate of events should remain constant in time, hence variations in this rate can be interpreted as

pointing to incompleteness. In such approaches, the periods of completeness for different

magnitude intervals are inferred by looking for breaks in slope on a linear plot of cumulative rate

against time (e.g., Beauval, 2003). Alternatively, the deviation with respect to the theoretical

value of 0.5 (on a log-log plot) of the cumulative number of events accumulated from the most

recent date on can be investigated (Stepp, 1972).

An alternative approach, known as the maximum curvature approach (Wiemer & Wyss, 2000)

relies on the self-similarity implied by the adherence of empirical data to the Gutenberg-Richter

(GR) relation. Recurrence plots showing both the incremental and the cumulative number of


93

events against magnitude usually show a deviation from the theoretical GR relation at lower

magnitude. The transition from GR to non-GR behaviour is accompanied by a change in

curvature for both curves, hence the name of the method. Magnitudes of completeness based

on maximum curvature have been found to give values that fall slightly below the actual

magnitude of completeness, which would be expected from the shape of the curve.

7.1.2. Historical approaches

Stucchi et al. (2009) provide an overview of the historical approach to completeness, insisting in

particular on the importance of the assessment of the quality of available documentation, as

well as the importance of negative evidence of earthquakes. The major advantage of this type

of approach, which was implemented in the Albini (2012) study performed specifically for the

TNSP project, is that it explicitly assesses the meaning of lack of reports of earthquakes, which

purely statistical approaches can only ascribe to incompleteness.

7.1.3. Probability of detection approach

Schorlemmer & Woessner (2008) present an approach based on the probabilities of detection

of events at single stations, expressed as functions of magnitude and distance that are

calibrated using data from past events. These station-specific probabilities of detection are then

combined to estimate regional magnitudes of completeness by assessing the probability of

events of a given magnitude going undetected. An alternative probability of detection approach

was considered in the USNRC (2012) study, where the probabilities of detection were

determined through a maximum-likelihood fit to spatially gridded data.

7.1.4. Approach adopted in present study

A probability of detection approach leading to equivalent periods of completeness, similar to

that used in the CEUS SSC project, is adopted here, for the following reasons:

• Rather than eliminating data below the threshold of completeness, this type of approach

allows to preserve all available data, correcting for missing data by adjusting the period

of completeness accordingly. This is a desirable feature in view of the very limited

number of data available.

• A probability of detection approach can incorporate within a uniform, quantitative

framework different types of information, both qualitative and quantitative, from a variety

of sources pertaining to both the historical and instrumental parts of the catalogue.


94

• Unlike purely statistical approaches, this type of approach can incorporate the negative

evidence gathered in the historical study by Albini (2012), as well as information

regarding the historical evolution of the recording network.

In view of the significant contribution of historical, qualitative information to the overall

knowledge available for assessing catalogue completeness, the values for the probability of

detection were developed deterministically for the historical part of the catalogue. Values based

on statistical analysis of the data were used for the modern instrumental part of the catalogue.

This approach differs somewhat from that adopted in the CEUS SSC (USNRC, 2012) study,

which relies more heavily on the data by determining spatially varying maximum-likelihood

values for the probabilities of detection by fitting the catalogue data. While the data-fitting

aspect of this method was not deemed appropriate for the present study in view of the data

limitations, the underlying principle of probabilities of detection increasing in a monotonic

manner with time and with magnitude was maintained, in particular to constrain the transition

between the historical and modern instrumental parts of the catalogue.

7.2. Historical considerations

For the historical part of the catalogue, the assessment of the catalogue completeness

essentially boils down to answering the following questions:

• Would an earthquake of magnitude M be noticed?

• If so, how likely is it that a record of this event was made?

• Assuming that such a record was made, how likely is it to have survived to the present

day and to been considered in the catalogue compilation?

Taken in the negative, this series of questions also addresses the interpretation of negative

evidence, i.e. the likelihood that the absence of records of earthquakes genuinely reflects an

absence of seismicity.

Answers to the question above will be strongly dependent on location, being influenced by

factors such as population density and historical developments in terms of recording. As part of

the TNSP project, a detailed historical study of the Eastern Cape region has been undertaken

by Albini (2012), which explicitly addresses completeness issues in terms of historical

completeness as described in Section 7.1.2.

The Albini (2012) developed a set of intensity data points spanning predominantly the eastern

part of the catalogue region. This focus was to a large extent deliberate, to compensate for the

western bias of the existing catalogue. A second consideration was the desire to capture all


95

events of interest that could potentially have been felt in the vicinity of the Thyspunt site, hence

the focus was predominantly on the southern and eastern Cape regions, for which negative as

well as positive evidence was studied (Figure 7.2). The Albini (2012) study thus was able to

develop seismic histories at a number of localities shown in Figure 7.3. Based on the analysis of

the data in its historical context, Albini (2012) concludes that these histories are complete to at

least the intensity VI-VII level for the time period 1820-1936.

Figure 7.1 Intensity data points collected by Albini (2012), covering the period 1820-1936. The area enclosed by the dashed rectangle is shown in more detail in the next figure.

Figure 7.2 Detail of the study region of Albini (2012). This region was assessed for negative, as well as positive evidence of earthquakes.


96

Figure 7.3 Localities for which a seismic history was developed by Albini (2012). The numbers indicate the number of records available for each locality.

In view of the schedule constraints of the project, this study focused on events identified as

having the potential of being felt at Thyspunt, and thus does not cover the full area of catalogue

study, which extends well beyond the 320 km radius prescribed by US NRC (2007; Figure 1.1).

Whilst a detailed historical study of the full catalogue region is beyond the scope of this report,

the next paragraph attempts to summarise a few salient historical facts that were considered in

the development of the probability of detection values.

Prior to the early 1800s, the catalogue is based on earthquake reports emanating exclusively

from the immediate vicinity of Cape Town. From about 1800 onwards, the spatial scale of

reporting expands northwards and eastwards, notably through the establishment of mission

stations keeping continuous records, as well as the development of a local press. Reports from

travellers also become more plentiful. The establishment of the Cape Observatory provided a

scientific institution with some interest in earthquake phenomena. This is, however, counter-

balanced by multiple wars and unrests leading to complex patterns of population migration and

the possible destruction of records. Additionally, less hospitable areas, such as mountainous

regions and the arid Karoo region, remain sparsely populated to this day. In terms of

earthquake detection, similar patterns persist until the early 1900s, when the first seismographs

are installed and earthquake monitoring becomes a routine task.


97

7.3. Instrumental considerations

Instrumental considerations for completeness revolve primarily around the development of a

local seismographic network, as well as the evolution of the relative quality of coverage by

global seismograph networks.

7.3.1. Local networks

As discussed in Section 2.1, instrumental recording in South Africa started with the installation

of a Milne instrument in Cape Town in 1899, followed by an (undamped) Wiechert instrument in

Johannesburg in 1910. Continuous records have survived for the latter, but not the former. This

was followed by the establishment of a 5-station short-period network in 1949, which was

expanded to the modern SANSN from 1971 onwards. From 1949 onwards, the instruments

were suitable for the monitoring of local seismicity, the undamped character of the older

instruments rendering them more useful for regional and teleseismic monitoring.

The detection capability of the Geological Survey network that was in operation from 1949 to

1968 can be qualitatively assessed by examining the list of events that this network was

capable of locating. For this application, events that are large enough to have independently

constrained locations (from global networks or good-quality macroseismic intensity data) are

particularly useful. In 1952, a sequence of events occurred in the Okavango region of northern

Botswana, with the mainshock being recorded teleseismically. The Geological Survey recorded

both this mainshock and a significant number of aftershocks, at distances of up to 1000 km from

the stations of the network. While some scatter was observed in the location of the smaller

foreshocks and aftershocks, the quality of location can still be considered fair. From this it can

be inferred that events situated at a similar distance to the stations of the network, but to the

south, would have also been detected and locatable.

As part of the preliminary catalogue analysis undertaken to obtain a regional b-value to be used

in the recurrence calculations, the data from the modern instrumental period (SANSN) was

analysed using seismic analysis software ZMAP. The maximum curvature method was used in

combination with three different declustering algorithms to assess the value of the magnitude of

completeness Mc. The results are summarised in Table 7.1 and Table 7.2 for two different

values of the lower limit magnitude considered in the catalogue used for the assessment.

Results for a cut-off magnitude Mw = 3.0 show a certain degree of instability, whereas the

results for a cut-off magnitude Mw = 3.5 give consistent results across the range of declustering

algorithms considered, with values of MC in the range 3.8 to 4.1 depending on the method

considered. A number of method-dataset combinations are not stable enough to provide a

result.


98

Analysis of the subset of 1997-2011 data (for which the lower magnitude cut-off is controlled by

the detection capability of the network) in terms of the evolution of MC vs. time provides the

following results: Mc~2.0 from 1997, Mc~1.9 from 2003, Mc~1.8 from 2007. These results are

consistent with the analysis of the full SANSN catalogue by Brandt (2011).

Table 7.1 Magnitude of completeness assessment using the maximum curvature method as implemented in ZMAP for modern instrumental catalogue (1972-2011), limiting the data to magnitudes Mw 3.0 and above.

E(M)>=3.0 Gardner & Knopoff (1975)

Grünthal (1986) Uhrhammer (1986)

Max. curv b 0.8 +/- 0.18 0.65 +/-0.04 0.68 +/-0.05

a 4.81 4.18 4.37

a (annual) 3.21 2.58 2.78

Mc 3.8+/-0.22 3.2 +/-0.06 3.2 +/-0.06

Mc90% b 1.04 +/-0.00 0.79 +/- 0.0 -

a 5.88 4.79 -

a (annual) 4.28 3.19 -

Mc 4.0 +/- 0.32 3.3 +/-0.48 -

Mc95% b 0.89 +/- 0.29 - -

a 5.21 - -

a (annual) 3.61 - -

Mc 3.8+/-0.27 - -

Best of Max

curv., Mc90%,

Mc95%

b 0.91 +/-0.28 0.7 +/-0.21 0.76+/-0.22

a 5.28 4.42 4.74

a (annual) 3.69 2.82 3.14

Mc 3.9 +/-0.27 3.2 +/-0.35 3.3 +/-0.4


99

Table 7.2 Same as previous table, except using a lower limit on magnitude of Mw 3.5 E(M)>=3.5 Gardner & Knopoff

(1975) Grunthal (1986) Uhrhammer (1986)

Max. curv b 0.86 +/- 0.24 0.8 +/- 0.23 0.81+/-0.18

a 5.09 4.8 4.9

a (annual) 3.49 3.21 3.3

Mc 3.8+/-0.25 3.8 +/-0.22 3.7 +/-0.19

Mc90% b 1.1 +/-0.00 1.07 +/- 0.00 1.11 +/-0

a 6.15 6.02 6.21

a (annual) 4.56 4.43 4.61

Mc 4.1 +/- 0.28 4.1 +/- 0.25 4.1+/-0.17

Mc95% b - - -

a - - -

a (annual) - - -

Mc - - -

Best of Max

curv., Mc90%,

Mc95%

b 0.91 +/-0.27 0.89 +/0.26 0.86+/-0.22

a 5.28 5.19 5.15

a (annual) 3.68 3.59 3.55

Mc 3.9 +/-0.25 3.9 +/-0.28 3.8+/-0.24

7.3.2. Global networks

In terms of coverage by global networks, the extent of the oceans surrounding South Africa has

to be taken into account, since they severely limit the opportunity of nearby instruments (Figure

7.4). Regular communication between the South African institutions in charge of the instruments

and international seismological organisations existed throughout the history of instrumental

recording (i.e. from about 1899 onwards).. The inclusion of events in global compilations such

as the International Seismic Summary therefore mostly reflects the geographical distribution of

triggered stations. Locations of early instrumental events (pre-1949) heavily rely on “local”

stations (Cape Town, Johannesburg, Mauritius, Tananarive; see Section 2.1); a good azimuthal

coverage requires recordings from stations in South America, as well as from Indian Ocean

stations


100

Figure 7.4 Seismograph stations operational before 1920 (Schweitzer & Lee, 2003) and currently (NEIC international station registry), showing the coverage of South Africa relative to global coverage.

From the establishment of the WWSSN onwards, the whole of the catalogue region is well

covered by global networks. Participation of the South African stations in these networks means

that the actual magnitude of completeness is likely to be slightly lower than the nominal global

magnitude of completeness of these networks, which also considers offshore regions

corresponding to network gaps. Based on the threshold values reported by agencies such as

ISC and NEIC, as well as studies of the regional variations (Figure 7.5), it seems reasonable to

assume that the TNSP catalogue is complete at least down to Mw 4.5 from 1964 onwards.

Figure 7.5 Global values for completeness of ISC mb values (Willemann, 1999).


101

7.4. Time intervals for completeness

Based on the knowledge of earthquake reporting and monitoring in the region described above, the time intervals listed in Table 7.3 were determined. These intervals correspond to dates delimiting periods for which the probability of detection is expected to remain uniform. Table 7.3 Time intervals for catalogue completeness analysis Interval Dates Justification 1 1650-1819 Only scattered information, almost exclusively from Cape Town region 2 1820-1899 Eastern Cape covered by Albini (2012) study; improved records across remainder of

study region 3 1900-1909 Milne seismograph installed in Cape Town. Macroseismic reports collected across the

country. Eastern Cape covered by Albini (2012) study. 4 1910-1936 Undamped Wiechert seismograph and continuous monitoring in Johannesburg. Eastern

Cape still covered by Albini (2012) study. 5 1937-1949 No longer covered by Albini (2012) study. Data mainly from Johannesburg-based sources

(Finsen, 1950; Krige & Maree, 1951) or global compilations. 6 1950-1963 Short-period Benioff network installed (Gane & Oliver, 1953). Continuous monitoring ,

bulletins available 7 1964-1968 Early WWSSN period. Local network continues as before. 8 1969-1971 Bulletin production stopped due to reorganisation of South African scientific institutions,

but recording continues. Ceres sequence. Heavy reliance on Bulawayo data collection and analysis

9 1972-1979 Early SANSN, still very sparse. 10 1980-1996 SANSN mostly analogue, but network densifies. 11 1997-2002 Transition to SEISAN and digital recording 12 2003-2006 Digital upgrade of the network 13 2007-2011 Modern, fully digital network

7.5. Spatial variations in completeness

Spatial variations in completeness affect predominantly the historical part of the catalogue. In

particular, there is a significant difference in level of information available between the region

studied by Albini (2012), and the remainder of the catalogue study region. This prompted the

assessment of the region implicitly covered by the completeness threshold of intensity VI given

in the Albini (2012) study. This was done by using the same intensity prediction equation

(Bakun & Scotti, 2006) as for the development of the intensity-based seismic source parameters

(Section 5.7), and determining, for various magnitudes, the regions in which an earthquake

could have originated that would have generated ground motions with an intensity of VI or more

in at least one of the localities for which a seismic history was developed by Albini (2012).

Figure 7.6 shows that for Mw = 7.0, the disks delimiting these areas overlap, thus enabling the

definition of a special region corresponding to the Albini (2012) study. For smaller magnitudes

(Figure 7.7), the disks no longer cover the whole of the special region, implying that there are

locations at which an earthquake of the specified magnitude could have occurred without

generating intensities above the intensity completeness threshold at any of the localities for

which a seismic history is available. This information will be translated into probabilities of


102

detection by considering the relative areas covered, but also taking into account that the

localities, rather than being points, have a finite spatial extent (i.e. reporting is likely to include

intensities above the completeness threshold occurring in the immediately surrounding districts).

Figure 7.6 Interpretation of Albini (2012) intensity completeness results using the Bakun & Scotti (2006) intensity prediction equation. Each circle is centered on a locality with a known seismic history shows the area where a magnitude Mw 7.0 event could have occurred causing an intensity VI at the locality in question.

Figure 7.7 Same as previous figure, but for magnitude 6.0 events.

1

2 3

4 5

6

7 8

9

10

1112

MMIc = VI Bakun & Scotti (2006) R = 150 km Mc =7.0

15.0° E 17.5° E 20.0° E 22.5° E 25.0° E 27.5° E 30.0° E 32.5° E

35.0° S

32.5° S

30.0° S

1

2 3

4 5

6

7 8

9

10

1112

MMIc = VI Bakun & Scotti (2006) R = 65 km Mc =6.0

15.0° E 17.5° E 20.0° E 22.5° E 25.0° E 27.5° E 30.0° E 32.5° E

35.0° S

32.5° S

30.0° S


103

For the remainder of the catalogue region falling outside the area analysed in detail by Albini

(2012), a distinction needs to be made between (i) onshore and offshore areas, since reports

from offshore earthquakes are invariably removed from the epicentral region of the earthquake;

(ii) the well-documented Cape Town region, and the rest of the country. Combining this

information leads to the definition of the regions of uniform information quality shown in Figure

7.8, superimposed on the source zones of the preliminary TNSP SSC model.

Figure 7.8 Zones of uniform information quality in completeness assessment for the historical part of the catalogue.

7.6. Probability of detection in space and time

The information regarding the completeness of the instrumental and historical parts of the

catalogue is combined in the form of magnitude-dependent probabilities of detection, which are

subsequently used to estimate equivalent periods of completeness.

Since subsequent recurrence calculations requiring these periods of completeness are to be

undertaken for each source zone individually, the probability of detection values are determined

on a zone-by-zone basis. For a given magnitude bin and date, these values represent, the

answer to the question: how likely is an event of this magnitude to appear in the catalogue? The

assignment of the values takes into account differences in the quality of the information

available, using average values across the zone. The results for the five source zones depicted

in Figure 7.8 are listed in Table 7.4 to Table 7.8. These tables also show the equivalent period

of completeness for each magnitude interval Mi, which is obtained by summing the actual

periods multiplied by the probability of detection:


104

𝑇𝐸𝑖𝑗(𝑀𝑖) = �𝑝𝐷(𝑀𝑖,𝑇𝑗𝑗

) (7.1)

where pD(Mi,Tj) is the probability of detection corresponding to interval Mi and period Tj.

In the present study, the pD values were determined as values that are representative of the

average probability of detection across the source zones considered in the SSC model, rather

than being assessed separately for each sub-region defined by the intersection of the

completeness zones and seismic source zones (as in Johnston et al., 1994 or USNRC, 2012).

This simplification was made to avoid further splitting up the datasets used for the recurrence

calculations for the individual source zones, which are characterised by extremely low

earthquake counts. Additionally, the probability of detection approach inherently includes some

spatial averaging in the determination of the probabilities of detection. Therefore, these

probabilities of detection have been determined directly as average values applicable for the

areas delimited by the source zone boundaries. For the ECC host zone, this leads to some

uncertainty regarding the completeness results offshore. This uncertainty cannot be resolved

through empirical calibration due to data paucity. Therefore, this uncertainty has been

addressed in the SSC logic-tree by including a branch considering the effect of this uncertainty

on the ECC seismicity rate via the application of a scaling ratio linked to the ratio of the offshore

area to the total ECC area.

The equivalent periods of completeness (derived using the probability of detection approach)

are used in the recurrence calculations (e.g., in the Weichert (1980) approach) in combination

with the total counts for each magnitude interval (i.e. without applying the completeness

censoring that is used in the traditional completeness interval approach) in the same way that

completeness-censored counts are used with actual completeness intervals. The replacement

of the completeness-censoring step by the pD approach enables the preservation of a more

comprehensive set of moderate-to large events, which is a desirable feature when dealing with

very sparse data. Details of this approach can be found in the CEUS SSC (USNRC, 2012)

report.


105

Table 7.4 Probability of detection and equivalent period values for Extended Continental Crust (ECC) source zone.

Tj 170 80 10 27 14 14 5 3 8 17 6 4 5 363

J96(Imax) Mi 1650-1819 1820-1899 1900-1909 1910-1936 1937-1949 1950-1963 1964-1968 1969-1971 1972-1979 1980-1996 1997-2002 2003-2006 2007-2011 TEij

Not felt 2.0-2.5 0 0 0 0 0 0.3 0.3 0.2 0.4 0.5 0.8 0.9 1 31

<II 2.5-3.0 0 0 0.1 0.1 0.1 0.3 0.5 0.5 0.7 0.8 0.9 1 1 47

III 3.0-3.5 0 0.3 0.3 0.3 0.3 0.5 0.7 0.7 0.8 0.9 1 1 1 89

IV 3.5-4.0 0.1 0.5 0.5 0.5 0.5 0.7 0.8 0.8 0.9 1 1 1 1 138

V 4.0-4.5 0.3 0.7 0.7 0.7 0.7 0.9 0.9 0.9 1 1 1 1 1 203

VI 4.5-5.0 0.3 0.7 0.7 0.8 0.8 1 1 1 1 1 1 1 1 209

VII 5.0-5.5 0.5 0.8 0.8 0.9 0.9 1 1 1 1 1 1 1 1 256

VIII 5.5-6.0 0.5 0.9 0.9 1 1 1 1 1 1 1 1 1 1 269

>VIII 6.0-6.5 0.5 0.9 1 1 1 1 1 1 1 1 1 1 1 270

>VIII 6.5-7.0 0.7 1 1 1 1 1 1 1 1 1 1 1 1 312

>VIII 7.0-7.5 0.8 1 1 1 1 1 1 1 1 1 1 1 1 329

>VIII 7.5-8.0 0.9 1 1 1 1 1 1 1 1 1 1 1 1 346


106

Table 7.5 Probability of detection and equivalent period values for Syntaxis (SYN) source zone.

Tj 170 80 10 27 14 14 5 3 8 17 6 4 5 363

J96(Imax) Mi 1650-1819 1820-1899 1900-1909 1910-1936 1937-1949 1950-1963 1964-1968 1969-1971 1972-1979 1980-1996 1997-2002 2003-2006 2007-2011 TEij

Not felt 2.0-2.5 0 0 0 0 0 0.3 0.3 0.2 0.4 0.5 0.8 0.9 1 31

<II 2.5-3.0 0 0 0.1 0.1 0.1 0.3 0.5 0.5 0.7 0.8 0.9 1 1 47

III 3.0-3.5 0 0.3 0.3 0.3 0.3 0.5 0.7 0.7 0.8 0.9 1 1 1 89

IV 3.5-4.0 0.1 0.5 0.5 0.5 0.5 0.7 0.8 0.8 0.9 1 1 1 1 138

V 4.0-4.5 0.3 0.7 0.7 0.7 0.7 0.9 0.9 0.9 1 1 1 1 1 203

VI 4.5-5.0 0.3 0.7 0.7 0.8 0.8 1 1 1 1 1 1 1 1 209

VII 5.0-5.5 0.5 0.8 0.8 0.9 0.9 1 1 1 1 1 1 1 1 256

VIII 5.5-6.0 0.7 0.9 0.9 1 1 1 1 1 1 1 1 1 1 303

>VIII 6.0-6.5 0.9 0.9 1 1 1 1 1 1 1 1 1 1 1 338

>VIII 6.5-7.0 1 1 1 1 1 1 1 1 1 1 1 1 1 363

>VIII 7.0-7.5 1 1 1 1 1 1 1 1 1 1 1 1 1 363

>VIII 7.5-8.0 1 1 1 1 1 1 1 1 1 1 1 1 1 363


107

Table 7.6 Probability of detection and equivalent period values for Karoo (KAR) zone.

Tj 170 80 10 27 14 14 5 3 8 17 6 4 5 363

J96(Imax) Mi 1650-1819 1820-1899 1900-1909 1910-1936 1937-1949 1950-1963 1964-1968 1969-1971 1972-1979 1980-1996 1997-2002 2003-2006 2007-2011 TEij

Not felt 2.0-2.5 0 0 0 0 0 0.3 0.3 0.2 0.4 0.5 0.8 0.9 1 31

<II 2.5-3.0 0 0 0.1 0.1 0.1 0.3 0.5 0.5 0.7 0.8 0.9 1 1 47

III 3.0-3.5 0 0.1 0.3 0.3 0.3 0.5 0.7 0.7 0.8 0.9 1 1 1 73

IV 3.5-4.0 0.1 0.3 0.5 0.5 0.5 0.7 0.8 0.8 0.9 1 1 1 1 122

V 4.0-4.5 0.2 0.4 0.6 0.7 0.7 0.9 0.9 0.9 1 1 1 1 1 161

VI 4.5-5.0 0.3 0.5 0.7 0.8 0.8 0.9 1 1 1 1 1 1 1 191

VII 5.0-5.5 0.4 0.7 0.8 0.9 0.9 1 1 1 1 1 1 1 1 231

VIII 5.5-6.0 0.5 0.8 0.9 1 1 1 1 1 1 1 1 1 1 261

>VIII 6.0-6.5 0.5 0.9 1 1 1 1 1 1 1 1 1 1 1 270

>VIII 6.5-7.0 0.7 1 1 1 1 1 1 1 1 1 1 1 1 312

>VIII 7.0-7.5 0.8 1 1 1 1 1 1 1 1 1 1 1 1 329

>VIII 7.5-8.0 0.9 1 1 1 1 1 1 1 1 1 1 1 1 346


108

Table 7.7 Probability of detection and equivalent period values for Cedarville-Koffiefontein (CK) zone.

Tj 170 80 10 27 14 14 5 3 8 17 6 4 5 363

J96(Imax) Mi 1650-1819 1820-1899 1900-1909 1910-1936 1937-1949 1950-1963 1964-1968 1969-1971 1972-1979 1980-1996 1997-2002 2003-2006 2007-2011 TEij

Not felt 2.0-2.5 0 0 0 0 0 0 0.3 0.6 0.7 0.8 0.9 1 1 37

<II 2.5-3.0 0 0 0 0 0 0.3 0.5 0.7 0.8 0.9 1 1 1 46

III 3.0-3.5 0 0.1 0.2 0.3 0.5 0.6 0.7 0.8 0.9 1 1 1 1 79

IV 3.5-4.0 0 0.1 0.3 0.5 0.6 0.7 0.8 0.9 1 1 1 1 1 89

V 4.0-4.5 0 0.2 0.4 0.6 0.7 0.8 0.9 1 1 1 1 1 1 105

VI 4.5-5.0 0.1 0.2 0.5 0.7 0.8 0.9 1 1 1 1 1 1 1 129

VII 5.0-5.5 0.2 0.3 0.5 0.8 0.9 1 1 1 1 1 1 1 1 159

VIII 5.5-6.0 0.3 0.5 0.8 0.9 1 1 1 1 1 1 1 1 1 199

>VIII 6.0-6.5 0.4 0.7 0.9 1 1 1 1 1 1 1 1 1 1 236

>VIII 6.5-7.0 0.5 0.8 1 1 1 1 1 1 1 1 1 1 1 262

>VIII 7.0-7.5 0.7 0.9 1 1 1 1 1 1 1 1 1 1 1 304

>VIII 7.5-8.0 0.9 1 1 1 1 1 1 1 1 1 1 1 1 306


109

Table 7.8 Probability of detection and equivalent period values for Namaqua (NAM) zone.

Tj 170 80 10 27 14 14 5 3 8 17 6 4 5 363

J96(Imax) Mi 1650-1819 1820-1899 1900-1909 1910-1936 1937-1949 1950-1963 1964-1968 1969-1971 1972-1979 1980-1996 1997-2002 2003-2006 2007-2011 TEij

Not felt 2.0-2.5 0 0 0 0 0 0 0.3 0.5 0.6 0.7 0.8 0.9 0.9 33

<II 2.5-3.0 0 0 0 0 0 0.3 0.5 0.6 0.7 0.8 0.9 0.9 1 42

III 3.0-3.5 0 0.1 0.2 0.3 0.5 0.6 0.7 0.8 0.9 0.9 1 1 1 77

IV 3.5-4.0 0 0.1 0.3 0.5 0.6 0.7 0.8 0.9 0.9 1 1 1 1 89

V 4.0-4.5 0 0.2 0.4 0.6 0.7 0.8 0.9 1 1 1 1 1 1 105

VI 4.5-5.0 0.1 0.2 0.5 0.7 0.8 0.9 1 1 1 1 1 1 1 129

VII 5.0-5.5 0.2 0.3 0.5 0.8 0.9 1 1 1 1 1 1 1 1 159

VIII 5.5-6.0 0.3 0.5 0.8 0.9 1 1 1 1 1 1 1 1 1 199

>VIII 6.0-6.5 0.4 0.7 0.9 1 1 1 1 1 1 1 1 1 1 236

>VIII 6.5-7.0 0.5 0.8 1 1 1 1 1 1 1 1 1 1 1 262

>VIII 7.0-7.5 0.7 0.9 1 1 1 1 1 1 1 1 1 1 1 304

>VIII 7.5-8.0 0.9 1 1 1 1 1 1 1 1 1 1 1 1 306


110

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A1

Appendix A: TNSP Catalogue

The column headings in the table below are defined as follows:

• YY: Year of the earthquake origin time (in UTC)

• MM: Month of the earthquake origin time (in UTC)

• DD: Day of the earthquake origin time (in UTC)

• Hr: Hours of the earthquake origin time (in UTC)

• Mn: Minutes of the earthquake origin time (in UTC)

• Sc: Seconds of the earthquake origin time (in UTC)

• LatN: Latitude of earthquake epicentre (°N)

• LonE: Longitude of earthquake epicentre (°E)

• Mw: Final moment magnitude assigned to the earthquake

• MwU: Uncertainty in the determination of Mw

• MwC: Origin of the final Mw value:

0. Direct Mw estimate (from moment tensor or waveform inversion) 1. Conversion from mb 2. Conversion from Ms 3. Conversion from SANSN ML after recalibration to ML* 4. Conversion from MBUL 5. Mw based on MI from 3rd generation methods implemented in MEEP2 6. Mw based on MI from isoseismals 7. Mw based on MI based on I0 only 8. Composite estimate combining multiple data types 9. Mw from weak-motion M0 30. Conversion from SANSN ML after recalibration to ML*

• Decl.: Outcome of chosen de-clustering algorithm, whereby DEP indicates that the

earthquake has been identified as a dependent event (foreshock, aftershock or simply

not the largest member of a cluster/sequence)


A2

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 1690 0 0 -33.900 18.400 3.7 1 7 DEP 1695 10 4 17 -33.900 18.400 3.7 1 7 1696 1 11 -33.900 18.400 3.5 1 7 1739 9 5 -33.900 18.400 3.5 1 7 1749 8 27 -33.900 18.400 3.3 1 7 1766 7 14 -34.200 18.500 4.2 1 7 1806 1 0 -28.800 23.200 4.2 1 7 DEP 1809 12 4 20 8 -34.000 18.400 5.8 0.6 8 1809 12 28 -33.900 18.400 3.7 1 7 DEP 1810 1 29 -33.900 18.400 3.3 1 7 DEP 1810 4 11 1 -33.900 18.400 3.7 1 7 DEP 1810 12 26 -34.100 19.500 3.3 1 7 1811 1 7 4 -33.900 18.400 3.3 1 7 1811 6 2 7 -33.900 18.400 5.2 1 7 1811 6 19 8 -33.900 18.400 4.5 1 7 DEP 1819 4 14 3 -30.300 18.100 4.0 1 7 1819 6 24 -32.900 18.800 3.3 1 7 1826 0 0 -33.000 18.000 3.7 1 7 DEP 1826 4 14 5 -33.900 18.400 3.3 1 7 1835 11 11 1 48 -33.900 18.400 4.0 1 7 1850 5 21 20 30 -32.000 28.000 5.7 0.4 5 1854 8 20 9 0 -29.700 31.000 3.7 1 7 1857 8 14 21 30 -33.500 19.000 5.1 0.6 7 1859 9 4 -30.720 25.097 3.7 0.8 5 1860 6 15 -29.900 31.000 3.7 1 7 1860 9 21 -29.600 30.400 3.7 1 7 1861 8 17 -30.850 26.500 4.6 0.7 5 1862 6 16 14 0 -29.800 30.700 4.2 0.5 5 1862 6 23 2 0 -33.470 18.650 3.7 1 5 1862 6 23 5 0 -32.250 24.550 3.0 1 7 1864 2 24 -33.750 22.750 4.1 0.5 5 1867 2 24 -29.617 24.083 3.0 0.8 5 1867 7 24 -29.594 25.961 3.1 0.8 5 1867 10 15 10 15 -32.950 27.600 5.1 0.5 7 1869 11 23 17 50 -30.000 17.200 3.7 1 7 1870 2 25 -29.750 31.000 3.3 0.8 5 1870 8 3 13 20 -28.450 29.150 5.5 0.5 5 1871 4 15 17 58 -32.100 28.300 3.7 1 7 1871 9 30 6 30 -29.900 31.000 2.9 1 7 1876 10 14 -31.600 28.800 2.9 1 7 1882 4 28 -29.700 17.900 3.7 1 7 1883 9 26 8 45 -29.750 31.000 3.3 1 7 1884 2 19 22 24 -28.700 24.700 3.3 1 7 1884 7 11 17 40 -30.600 21.400 3.3 1 7 1885 5 10 21 41 -33.900 18.400 3.3 1 7 1895 4 9 -33.400 25.450 4.1 0.5 5 1898 8 11 19 20 -29.700 31.100 3.3 1 7 1899 9 15 10 23 -33.900 18.400 4.5 1 7 1902 5 28 21 45 -33.900 18.400 4.2 1 7 1903 7 9 10 6 -33.900 18.400 3.7 1 7 1903 8 3 -29.400 25.000 4.2 1 7 1905 8 19 10 0 -29.100 25.500 3.3 1 7 1905 11 28 -30.500 29.400 3.7 1 7 1905 12 1 -30.500 29.400 3.7 1 7 DEP 1907 3 20 19 45 -29.900 30.300 3.3 1 7 1908 8 18 3 0 -29.000 26.000 4.2 1 7


A3

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 1908 9 26 21 7 -28.700 25.800 5.5 0.5 5 1908 12 30 0 20 -29.700 17.900 3.7 1 7 1909 3 19 -29.300 21.100 3.3 1 7 1909 4 15 -30.700 30.000 3.7 1 7 1909 8 16 20 15 -29.600 24.000 3.7 1 7 1910 10 21 18 42 -30.550 24.700 5.7 0.5 5 1911 7 6 20 15 -33.583 22.200 3.1 0.8 5 1911 7 10 -29.833 30.950 3.1 0.8 5 1912 2 20 13 3 -29.500 25.000 6.2 0.25 2 1912 4 19 18 0 -29.700 25.100 3.7 1 7 DEP 1912 11 16 23 43 -29.300 25.000 5.5 0.4 5 DEP 1913 6 15 -29.600 24.100 3.3 1 7 1913 9 17 -30.500 29.400 3.7 1 7 1914 2 6 12 35 -29.000 31.700 3.3 1 7 DEP 1914 2 16 23 50 -29.000 31.700 4.0 1 7 1914 3 31 12 45 -28.700 31.900 3.7 1 7 1914 5 19 8 47 -29.200 24.600 3.7 1 7 1914 6 14 2 0 -29.300 31.300 3.3 1 7 1914 6 20 4 3 -28.200 20.000 3.3 1 7 1916 3 24 12 35 -28.900 31.700 3.3 1 7 1917 4 11 4 5 -28.900 31.700 3.7 1 7 1917 4 25 16 18 -28.000 31.000 3.7 1 7 1917 9 3 6 30 -29.700 25.400 3.3 1 7 1917 9 9 15 23 -28.000 31.000 3.7 1 7 1917 9 20 3 39 -28.000 31.000 3.3 1 7 DEP 1918 9 25 0 30 -28.800 20.600 3.7 1 7 1919 1 13 12 0 -31.400 19.800 3.3 1 7 1919 5 14 21 50 -28.000 31.000 3.3 1 7 DEP 1919 5 15 -28.000 31.000 3.7 1 7 1919 6 24 4 14 -30.500 29.400 3.3 1 7 1919 11 7 18 52 -28.000 31.000 3.7 1 7 1920 1 31 17 0 -29.300 31.300 3.3 1 7 1920 3 7 8 10 -28.000 31.000 3.3 1 7 1920 4 3 16 57 -28.000 31.000 3.7 1 7 1920 4 12 23 24 -28.000 31.000 3.3 1 7 DEP 1920 5 8 16 0 -30.500 29.400 3.3 1 7 1920 8 13 7 5 -33.900 18.500 3.3 1 7 1920 9 10 3 41 -30.500 29.400 3.7 1 7 1920 10 15 6 40 -30.500 29.400 3.3 1 7 1920 12 4 5 52 -39.000 23.500 6.4 0.3 2 1921 1 22 4 55 -30.500 29.400 4.2 1 7 1921 2 19 0 0 -31.600 18.700 3.7 1 7 1921 3 16 0 10 -30.000 25.000 3.7 1 7 1921 3 23 0 0 -29.800 25.300 3.3 1 7 1921 8 13 0 0 -30.500 29.400 4.0 1 7 1921 10 9 13 20 -33.300 19.100 4.5 1 7 1921 12 15 19 44 -29.200 16.900 3.3 1 7 1922 1 3 0 0 -33.300 19.100 3.7 1 7 1922 3 20 22 30 -30.500 29.400 4.2 1 7 1922 3 21 3 26 -28.000 31.000 3.7 1 7 1922 5 8 22 43 -28.000 31.000 3.3 1 7 1922 9 18 0 0 -30.500 29.400 3.7 1 7 1922 10 31 0 0 -33.490 22.535 3.0 0.8 5 1923 1 12 1 45 -29.400 25.000 3.3 1 7 1923 3 1 0 23 -30.500 25.500 3.7 1 7 1923 3 29 19 10 -28.000 31.000 4.2 1 7 1923 8 7 17 27 -30.500 29.400 3.3 1 7 1924 2 22 5 40 -34.000 18.400 3.3 1 7


A4

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 1924 3 6 9 56 -30.500 29.400 3.7 1 7 1924 10 28 10 45 -30.500 29.400 3.3 1 7 1925 8 6 2 28 -31.000 22.100 3.7 1 7 1925 8 25 11 0 -29.600 24.100 3.3 1 7 1925 9 3 0 0 -30.500 29.400 3.5 1 7 1926 8 11 0 0 -33.400 18.400 3.5 1 7 1927 3 10 4 5 -28.400 32.300 3.7 1 7 1927 9 22 20 30 -32.380 27.632 3.1 0.8 5 1928 7 10 16 30 -30.400 27.700 3.3 1 7 1928 11 15 5 45 -28.900 31.500 3.7 1 7 1929 6 24 15 45 -28.900 31.700 3.7 1 7 1929 12 28 2 15 -30.500 29.400 3.7 1 7 1930 4 24 5 25 -30.500 29.400 3.7 1 7 1930 5 14 0 38 -28.900 31.700 3.3 1 7 1930 7 20 1 5 -30.200 30.000 4.2 1 7 1931 11 20 6 45 -28.900 18.200 3.7 1 7 1932 5 25 0 0 -29.300 30.000 3.3 1 7 1932 6 30 20 25 -30.500 29.400 3.7 1 7 1932 8 9 0 56 -33.300 26.500 5.7 0.35 5 1932 12 31 6 32 -28.500 32.800 6.3 0.3 8 1933 2 25 16 56 -33.450 26.700 3.2 0.8 5 DEP 1935 2 20 17 15 -28.700 31.900 3.3 1 7 1936 1 16 9 38 -29.800 25.300 4.7 1 7 1936 4 26 18 45 -33.870 25.032 3.4 0.8 5 1936 9 18 8 45 -28.400 32.300 3.3 1 7 1937 2 25 20 0 -30.400 29.000 3.3 1 7 1937 8 19 14 0 -33.400 18.400 3.3 1 7 1937 11 1 18 29 -28.700 16.900 3.7 1 7 1938 1 21 4 0 -30.500 29.400 3.7 1 7 1938 9 4 13 25 -32.400 28.700 3.3 1 7 1938 10 25 5 45 -28.200 28.700 3.7 1 7 1940 2 29 23 40 -28.600 28.200 4.2 1 6 1940 8 28 14 35 -30.000 30.500 3.3 1 7 1940 9 19 14 30 -28.600 31.400 3.3 1 7 1940 9 29 0 0 -30.800 30.200 3.5 1 7 1940 10 13 13 45 -32.500 24.000 4.2 1 7 1940 10 24 19 54 -30.000 30.500 3.3 1 7 1940 10 26 17 30 -29.500 25.200 3.3 1 7 1940 10 27 0 0 -29.500 25.200 3.3 1 7 DEP 1940 11 10 0 0 -33.300 26.700 3.3 1 7 1941 10 23 18 30 -31.000 17.700 4.2 1 7 1942 11 1 4 50 -31.100 30.500 5.2 1 6 1942 12 0 0 -31.100 30.200 3.3 1 7 DEP 1943 11 24 22 45 -30.000 23.000 4.2 1 7 1944 8 28 0 0 -32.500 22.500 3.3 1 7 1944 11 12 10 55 -29.000 27.700 4.2 1 7 1947 2 27 10 19 -32.800 17.800 3.5 1 7 1947 5 8 5 13 -28.600 32.100 3.7 1 7 1948 2 3 4 29 -29.100 30.600 4.0 1 7 1948 9 25 1 45 -30.300 29.900 4.0 1 7 1950 2 5 7 59 -31.200 29.800 3.1 0.6 30 1950 9 30 16 56 -30.500 18.000 4.3 0.6 30 1950 11 19 0 0 -34.000 18.000 3.3 1 7 1951 1 19 6 15 -29.500 24.500 2.9 0.6 30 1951 6 13 14 8 -31.900 23.200 3.9 0.6 30 1951 9 16 16 33 -33.000 22.500 3.7 0.6 30 1952 1 26 6 54 -32.900 20.500 3.9 0.6 30 DEP 1952 1 26 17 18 -32.900 20.500 3.5 0.6 30 DEP


A5

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 1952 1 26 19 10 -32.900 20.500 3.3 0.6 30 DEP 1952 1 27 11 9 -32.900 20.500 4.0 0.6 30 DEP 1952 1 27 16 20 -33.000 20.500 4.3 0.6 30 DEP 1952 1 28 2 35 -33.000 20.500 2.8 0.6 30 DEP 1952 1 28 16 41 -32.900 20.500 4.4 0.6 30 1952 1 28 17 10 -32.900 20.500 3.9 0.6 30 DEP 1952 1 29 13 48 -32.900 20.500 3.6 0.6 30 DEP 1952 2 1 6 11 -32.900 20.500 4.0 0.6 30 DEP 1952 2 26 0 0 -34.000 20.400 3.3 1 7 1952 3 25 8 18 -30.000 28.300 2.7 0.6 30 1952 5 13 12 59 -32.900 20.500 3.2 0.6 30 1952 6 11 19 26 -30.100 29.800 3.4 0.6 30 1952 8 30 16 10 -30.000 27.500 2.7 0.6 30 1952 9 7 4 56 -29.000 28.000 3.0 0.6 30 1952 9 23 17 48 -33.300 27.200 1.7 0.6 30 DEP 1952 9 23 17 50 -33.300 27.200 1.8 0.6 30 1952 9 23 19 46 -30.000 29.000 2.4 0.6 30 1952 10 14 2 37 -29.800 27.000 3.7 0.6 30 1952 12 1 1 24 -30.500 29.500 2.1 0.6 30 1953 1 3 2 16 -30.500 27.500 2.6 0.6 30 DEP 1953 1 3 3 37 -30.500 27.500 2.6 0.6 30 DEP 1953 1 6 0 57 -30.500 27.500 2.9 0.6 30 DEP 1953 1 6 4 56 -30.500 27.500 2.7 0.6 30 DEP 1953 1 15 1 17 -30.500 27.500 4.1 0.6 30 1953 1 15 1 34 -30.500 27.500 2.6 0.6 30 DEP 1953 1 15 16 43 -30.500 27.500 2.7 0.6 30 DEP 1953 1 15 17 14 -30.500 27.500 2.8 0.6 30 DEP 1953 1 15 20 43 -30.500 27.500 3.2 0.6 30 DEP 1953 1 16 3 40 -30.500 27.500 3.1 0.6 30 DEP 1953 1 16 4 12 -30.500 27.500 2.5 0.6 30 DEP 1953 1 16 5 43 -30.500 27.500 2.9 0.6 30 DEP 1953 1 20 5 47 -33.300 26.500 2.3 0.6 30 1953 1 21 6 11 -30.500 27.500 3.2 0.6 30 DEP 1953 1 24 11 33 -30.500 27.500 2.8 0.6 30 DEP 1953 1 24 20 4 -30.500 27.500 3.6 0.6 30 DEP 1953 1 24 20 16 -30.500 27.500 2.8 0.6 30 DEP 1953 1 28 1 27 -30.500 27.500 2.7 0.6 30 DEP 1953 1 30 11 33 -30.500 27.500 3.9 0.6 30 DEP 1953 2 5 18 14 -30.500 27.000 2.6 0.6 30 1953 2 26 9 14 -30.000 21.000 3.4 0.6 30 1953 3 25 23 28 -30.300 28.500 2.7 0.6 30 1953 5 1 1 7 -29.000 17.000 4.6 0.6 30 1953 6 17 5 9 -30.000 28.500 3.0 0.6 30 1953 7 29 20 51 -30.500 28.000 2.8 0.6 30 1953 8 15 9 54 -30.500 28.500 2.3 0.6 30 1953 8 31 19 48 -30.000 26.500 2.3 0.6 30 1953 11 5 21 1 -30.500 24.000 2.4 0.6 30 DEP 1953 11 5 21 5 -30.500 24.000 2.5 0.6 30 1954 1 6 15 35 -30.000 26.500 3.5 0.6 30 1954 2 9 23 3 -29.500 25.000 2.4 0.6 30 1954 11 18 1 29 -28.200 27.200 3.6 0.6 30 1955 5 20 6 23 -29.333 25.333 4.5 0.6 30 1955 10 28 13 17 -29.500 25.500 3.2 0.6 30 1956 6 26 9 9 -30.000 26.000 2.9 0.6 30 1956 6 29 19 50 -28.300 31.300 2.2 0.6 30 1956 7 13 14 12 -30.300 29.700 3.4 0.6 30 1956 10 23 21 21 -31.200 22.200 2.6 0.6 30 1957 4 13 21 54 -30.500 27.200 4.9 0.6 30


A6

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 1957 4 23 13 23 -30.300 27.200 4.1 0.6 30 DEP 1957 9 20 3 38 -34.000 18.200 3.3 1 7 1957 9 30 0 0 -34.000 18.200 3.3 1 7 DEP 1958 2 10 18 54 -29.300 28.200 3.0 0.6 30 1958 2 11 15 50 -29.300 28.200 3.0 0.6 30 DEP 1960 8 29 7 35 -33.400 19.300 4.0 1 7 1963 8 27 0 48 -33.100 19.000 4.7 1 7 1963 9 17 23 40 -33.300 19.300 4.0 1 7 1964 2 21 0 0 -34.100 18.000 3.7 1 7 1964 6 9 20 1 -29.000 25.000 4.0 0.6 30 1965 9 28 14 45 -33.900 22.000 4.0 1 7 1966 2 18 11 42 -29.500 25.000 2.8 0.6 30 1966 2 22 4 36 -29.000 28.000 3.7 0.5 4 1966 3 1 0 4 -34.100 18.000 3.7 1 7 1966 6 18 5 21 -29.300 29.300 4.2 0.6 30 1966 6 20 2 22 -28.300 31.000 2.9 0.6 30 1966 7 31 20 2 -30.000 19.000 4.2 0.5 4 1966 8 25 1 27 -28.400 19.300 3.6 0.5 4 1967 4 13 18 13 -29.700 29.000 3.2 0.6 30 1967 6 16 14 51 -30.400 18.400 4.3 0.5 4 1967 6 16 18 59 -30.200 27.600 3.5 0.5 4 1967 7 12 22 36 -30.000 20.000 3.6 0.5 4 1967 8 9 23 10 -31.300 23.300 3.5 0.5 4 1967 8 23 12 41 -29.700 30.000 3.7 0.5 4 1968 1 9 9 54 -29.800 28.300 3.1 0.5 4 1968 1 11 19 50 -30.300 28.500 3.9 0.5 4 1968 1 12 1 0 -33.170 23.600 4.9 0.26 1 1968 2 13 15 29 -29.400 27.100 2.9 0.5 4 1968 2 24 2 23 -30.200 20.000 3.5 0.5 4 1968 3 19 12 0 -29.900 28.300 3.0 0.5 4 1968 8 31 13 13 -29.600 25.900 4.4 0.5 4 1968 9 27 12 42 -29.000 25.000 3.2 0.5 4 1968 12 5 0 48 -29.000 26.500 3.1 0.5 4 1969 1 29 14 50 -30.400 27.600 3.0 0.5 4 1969 2 17 15 38 -28.000 24.000 2.9 0.5 4 1969 6 5 22 17 -29.900 30.300 3.2 0.5 4 1969 9 11 21 45 -34.000 21.000 4.8 1 8 1969 9 29 9 2 -33.200 19.200 3.6 0.5 4 DEP 1969 9 29 17 22 -33.100 19.300 3.3 0.5 4 DEP 1969 9 29 20 3 -33.278 19.210 6.2 0.2 0 1969 9 29 20 44 -33.200 19.200 3.9 0.5 4 DEP 1969 9 29 20 54 -33.200 19.400 3.3 0.5 4 DEP 1969 9 29 21 19 -33.200 19.100 3.2 0.5 4 DEP 1969 9 29 21 30 -33.100 19.400 3.3 0.5 4 DEP 1969 9 29 21 37 -33.100 19.400 3.3 0.5 4 DEP 1969 9 29 21 43 -33.400 19.300 3.3 0.5 4 DEP 1969 9 29 21 48 -33.400 19.400 3.7 0.5 4 DEP 1969 9 29 23 34 -33.000 19.100 4.3 0.5 4 DEP 1969 9 30 1 58 -33.300 19.200 3.9 0.5 4 DEP 1969 9 30 4 20 -33.300 19.200 3.9 0.5 4 DEP 1969 9 30 7 6 -33.300 19.200 3.9 0.5 4 DEP 1969 9 30 9 48 -33.100 19.000 4.2 0.5 4 DEP 1969 9 30 11 40 -33.400 19.200 4.5 0.5 4 DEP 1969 9 30 15 29 -33.100 19.400 3.7 0.5 4 DEP 1969 10 1 4 19 -33.500 19.400 4.1 0.5 4 DEP 1969 10 3 14 12 -33.200 19.100 4.1 0.5 4 DEP 1969 10 3 17 23 -33.400 19.200 4.7 0.5 4 DEP 1969 10 5 5 1 -33.400 19.300 5.1 0.26 1 DEP


A7

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 1969 10 6 22 5 -33.300 19.000 4.1 0.26 1 DEP 1969 10 8 17 53 -32.200 19.200 3.7 0.5 4 1969 10 10 18 34 -33.302 19.208 4.8 0.5 4 DEP 1969 10 11 21 4 -33.200 19.000 4.1 0.5 4 DEP 1969 11 5 19 2 -33.400 19.400 5.5 0.3 1 DEP 1969 11 6 20 5 -33.300 19.100 4.3 0.5 4 DEP 1969 11 8 9 35 -33.300 19.000 3.7 0.5 4 DEP 1969 11 8 12 23 -33.300 19.200 4.3 0.5 4 DEP 1969 11 9 1 42 -33.500 19.400 4.6 0.5 4 DEP 1969 11 9 3 57 -33.300 19.200 3.5 0.5 4 DEP 1969 11 9 11 38 -33.300 19.200 4.3 0.5 4 DEP 1969 11 9 20 46 -33.300 19.300 4.6 0.5 4 DEP 1969 11 10 5 6 -33.300 19.700 4.3 0.26 1 DEP 1969 11 12 14 25 -33.300 19.700 3.3 0.5 4 DEP 1969 11 19 13 24 -33.200 19.200 3.6 0.5 4 DEP 1970 4 6 10 59 -32.900 19.800 4.0 0.5 4 DEP 1970 4 14 19 8 -33.343 19.311 5.6 0.2 0 DEP 1970 4 14 19 23 -32.900 19.200 4.6 0.5 4 DEP 1970 4 14 20 36 -32.800 19.800 4.1 0.5 4 1970 4 14 21 6 -32.900 19.200 4.2 0.5 4 DEP 1970 4 16 22 15 -33.000 19.000 4.1 0.5 4 DEP 1971 9 28 17 1 -33.000 19.500 4.6 0.5 4 1972 1 22 10 37 -32.6512 31.5141 2.9 0.78 3 1972 2 13 1 55 -29.3000 27.2000 2.7 0.29 3 1972 3 9 8 29 -31.7962 25.0491 3.3 0.26 3 1972 7 19 17 35 -31.7530 25.3701 3.5 0.35 3 1972 9 21 23 26 -29.5306 25.6487 4.5 0.42 3 1973 1 12 5 27 -33.3270 19.1030 4.0 0.41 3 1973 4 22 2 9 -30.8038 27.6508 3.1 0.26 3 1974 10 11 12 3 -31.3000 24.2000 4.4 0.33 3 1974 12 19 9 17 -33.2940 19.2500 3.3 0.33 3 DEP 1974 12 23 17 23 -33.2000 19.3000 3.5 0.40 3 1975 1 5 17 48 -32.3700 23.3430 3.6 0.40 3 1975 1 8 0 1 -29.1078 29.7970 2.7 0.53 3 1975 1 16 3 48 -30.6222 30.8140 2.7 0.33 3 1975 5 14 0 17 -29.5000 25.1000 3.5 0.33 3 DEP 1975 6 8 18 32 -29.4455 25.2087 4.3 0.49 3 1975 6 10 0 11 -29.5460 24.9847 2.3 0.28 3 DEP 1975 8 10 15 42 -30.2751 27.8002 3.7 0.45 3 1976 6 4 12 34 -30.9251 29.9076 4.1 0.50 3 1976 7 1 11 24 -29.5084 25.1669 5.8 0.16 0 1976 7 1 12 43 -29.6000 25.0000 3.1 0.26 3 DEP 1976 7 1 16 6 -29.5000 25.0000 3.2 0.30 3 DEP 1976 7 1 16 40 -29.6000 25.1000 2.8 0.35 3 DEP 1976 7 1 19 0 -29.3081 24.8938 3.3 0.34 3 DEP 1976 7 2 18 25 -29.5000 25.1000 3.0 0.32 3 DEP 1976 7 3 20 51 -29.6000 25.2000 2.7 0.45 3 DEP 1976 7 5 15 4 -29.2104 24.8018 3.1 0.28 3 1976 7 6 17 36 -29.3182 24.9497 3.4 0.43 3 DEP 1976 7 15 1 46 -29.4312 25.0911 3.9 0.42 3 DEP 1976 7 20 18 17 -30.7000 26.1000 3.4 0.39 3 1976 7 26 17 54 -29.5365 22.9708 3.2 0.41 3 1976 8 19 16 15 -29.8531 22.2062 4.2 0.40 3 1976 9 4 6 10 -29.4084 24.9889 3.0 0.25 3 DEP 1976 9 4 12 30 -29.5004 24.9793 2.4 0.42 3 DEP 1976 10 17 11 42 -29.5000 24.9000 2.7 0.34 3 DEP 1976 11 26 17 35 -29.4572 24.9987 3.1 0.35 3 DEP 1977 3 2 4 54 -33.4810 19.4930 5.0 0.38 3


A8

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 1977 3 2 10 56 -33.3000 19.5000 3.7 0.34 3 DEP 1977 4 28 23 26 -33.2000 19.1000 3.4 0.37 3 1977 6 7 20 19 -33.3000 19.3000 4.7 0.40 3 DEP 1977 7 10 22 8 -29.4900 25.1100 3.0 0.30 3 DEP 1977 11 22 17 20 -28.1800 28.8400 3.1 0.70 3 1978 2 28 19 33 -29.5863 25.0928 3.0 0.34 3 1978 4 11 15 51 -33.4000 19.3000 2.0 0.20 3 1978 6 2 11 16 -29.5089 25.1060 3.6 0.30 3 1978 7 27 23 30 -29.4000 31.4000 3.1 0.25 3 DEP 1978 12 27 17 30 -28.0953 28.4543 3.5 0.40 3 1979 2 21 10 59 -29.6000 21.0000 5.0 0.41 3 1979 3 12 16 27 -29.5500 24.8900 3.1 0.29 3 1979 6 16 6 36 -29.5300 25.1400 3.0 0.46 3 1979 8 4 9 30 -29.4896 21.0578 4.3 0.46 3 1979 8 7 9 22 -28.7690 20.4210 4.2 0.49 3 1979 8 11 4 0 -29.4000 20.6000 4.4 0.46 3 1979 8 17 1 9 -29.9850 21.5390 4.1 0.38 3 1980 4 25 22 13 -30.32 23.29 2.7 0.43 3 1980 10 22 10 25 -29.600 24.600 3.3 0.42 3 1981 3 20 22 46 -30.720 21.950 3.2 0.45 3 1981 4 7 14 53 -30.910 30.220 3.1 0.32 3 1981 8 24 1 27 -33.340 19.040 4.4 0.40 3 1981 11 5 20 19 -29.950 27.370 3.6 0.38 3 1981 11 18 3 32 -28.250 31.840 3.9 0.37 3 1982 5 9 7 7 -29.600 27.060 3.0 0.30 3 1982 11 3 7 57 -33.340 19.250 3.0 0.29 3 1982 11 18 13 45 -29.410 27.560 3.6 0.42 3 1982 12 2 20 45 -30.730 21.870 3.3 0.36 3 1983 2 22 16 26 -29.187 27.927 4.4 0.47 3 1983 2 24 6 46 -33.490 18.850 4.5 0.34 3 1983 2 24 14 54 -30.770 23.440 3.3 0.33 3 1983 6 21 19 45 -32.380 29.580 3.6 0.38 3 1983 7 31 0 35 -31.190 24.250 3.5 0.45 3 1983 9 5 0 33 -29.470 25.030 4.2 0.64 3 1983 9 9 3 5 -29.540 24.900 2.8 0.28 3 DEP 1983 11 2 23 16 -30.060 25.790 3.2 0.34 3 1983 12 30 16 57 -29.820 27.270 3.8 0.40 3 1984 8 5 22 23 -30.210 26.130 2.9 0.34 3 1985 4 10 11 20 -29.260 25.010 4.1 0.45 3 DEP 1985 4 30 19 6 -29.130 20.050 4.0 0.36 3 1985 5 8 11 35 -29.410 24.870 4.7 0.26 1 1985 5 9 16 10 -29.400 24.810 4.3 0.44 3 DEP 1985 5 27 12 26 -29.370 25.100 2.7 0.32 3 DEP 1985 8 26 12 31 -29.270 19.940 4.5 0.42 3 1985 8 31 6 3 -30.100 27.130 2.9 0.29 3 1985 11 21 0 56 -29.460 24.170 3.9 0.40 3 1985 12 3 18 59 -29.910 25.570 2.7 0.35 3 1985 12 11 10 17 -29.770 28.020 3.4 0.35 3 1986 3 23 5 3 -29.410 24.920 3.5 0.38 3 1986 7 29 19 13 -29.630 27.500 3.2 0.44 3 1986 7 30 19 43 -30.870 28.290 2.6 0.29 3 1986 8 5 18 3 -28.200 28.100 2.8 0.38 3 1986 9 13 11 5 -30.890 23.780 3.4 0.37 3 1986 10 5 18 53 -30.529 28.841 5.3 0.16 0 1986 10 6 10 4 -30.030 28.610 2.8 0.30 3 1986 10 13 1 42 -30.260 27.690 3.3 0.36 3 1986 12 29 6 42 -29.980 27.610 2.8 0.43 3 1987 2 14 6 21 -29.490 24.780 4.0 0.38 3


A9

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 1987 3 5 22 24 -33.010 17.620 2.9 0.50 3 1987 4 21 22 20 -29.720 19.820 3.4 0.34 3 1987 4 26 20 9 -29.960 19.640 4.2 0.36 3 DEP 1987 4 27 6 52 -29.960 19.730 4.5 0.37 3 1987 6 8 16 39 -30.010 27.130 3.1 0.39 3 1987 8 1 18 43 -30.350 28.340 4.4 0.45 3 1987 8 1 19 39 -30.600 28.130 3.4 0.35 3 1987 8 26 6 31 -29.480 25.040 3.2 0.36 3 1987 9 26 17 5 -30.300 18.620 3.6 0.38 3 1987 10 2 17 46 -30.060 22.220 2.9 0.25 3 1987 10 13 18 58 -29.580 25.430 3.1 0.37 3 1987 10 24 11 45 -30.630 29.010 4.3 0.34 3 1987 11 15 13 58 -29.520 25.160 4.6 0.39 3 1987 12 11 1 49 -29.500 19.800 3.1 0.35 3 1988 2 12 17 54 -30.280 28.570 4.4 0.55 3 1988 2 12 19 30 -30.150 28.370 4.2 0.40 3 DEP 1988 2 16 23 5 -29.240 25.250 3.1 0.35 3 1988 8 5 5 0 -29.460 19.960 3.4 0.37 3 1988 8 20 8 43 -29.420 30.100 3.7 0.34 3 1988 9 16 10 2 -29.520 27.570 3.1 0.25 3 1988 9 21 22 40 -31.030 28.700 2.6 0.44 3 1988 9 22 12 57 -30.610 28.890 3.0 0.34 3 1989 2 17 8 22 -29.030 20.510 3.1 0.33 3 1989 2 23 6 50 -28.080 26.020 3.2 0.30 3 1989 2 28 20 55 -30.820 28.230 3.1 0.37 3 1989 3 14 10 26 -30.070 28.670 2.9 0.26 3 1989 3 15 2 24 -30.030 29.040 2.8 0.41 3 1989 4 30 9 39 -30.560 29.010 3.0 0.38 3 1989 5 15 18 2 -31.510 28.490 3.2 0.39 3 1989 6 17 2 55 -29.740 27.140 3.8 0.34 3 1989 6 19 17 55 -29.890 27.180 3.1 0.28 3 DEP 1989 8 21 19 57 -29.480 30.830 4.0 0.34 3 1989 9 4 2 35 -29.100 27.580 3.2 0.29 3 1989 9 29 6 16 -30.640 28.430 4.8 0.26 1 1989 9 29 17 37 -30.602 28.702 3.1 0.29 3 DEP 1989 10 2 15 2 -29.980 28.050 3.7 0.32 3 1989 11 6 4 59 -29.230 25.320 4.0 0.38 3 1990 3 22 17 35 -28.06 30.56 3.2 0.42 3 1990 5 1 15 15 -29.82 27.70 3.8 0.40 3 1990 8 21 23 20 -30.25 28.87 2.9 0.49 3 1990 10 16 8 26 -29.94 25.27 2.8 0.36 3 1991 1 25 17 55 -30.09 22.51 3.3 0.67 3 1991 6 3 14 13 -33.45 19.24 2.4 0.20 3 1991 6 18 17 12 -29.97 22.47 3.3 0.40 3 1991 6 24 12 34 -30.09 18.68 3.4 0.35 3 1991 6 29 15 12 -30.69 28.51 3.6 0.43 3 1991 7 26 12 42 -30.01 29.19 3.5 0.40 3 1991 8 11 22 12 -29.94 18.35 3.7 0.32 3 1991 8 17 23 41 -29.48 22.06 3.3 0.30 3 1991 9 17 5 26 -29.92 26.18 2.6 0.41 3 1991 10 31 13 36 -33.35 19.16 4.8 0.38 3 1992 2 16 2 28 -28.33 17.42 3.6 0.45 3 1992 10 24 1 46 -30.02 25.41 2.8 0.37 3 1992 11 2 10 55 -31.34 23.63 3.1 0.35 3 1992 11 19 8 32 -30.39 25.10 3.8 0.41 3 1993 3 11 20 5 -29.53 18.34 4.7 0.40 3 1993 6 3 4 45 -29.67 17.97 3.7 0.41 3 1993 7 31 22 38 -29.60 27.71 3.7 0.41 3


A10

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 1993 10 11 14 6 -28.48 30.67 3.3 0.30 3 1993 11 20 9 20 -29.68 28.86 3.1 0.33 3 1994 1 9 17 1 -29.50 30.20 3.6 0.35 3 1994 1 27 5 26 -30.82 28.86 3.2 0.42 3 1994 3 22 18 44 -29.58 28.86 3.2 0.39 3 1994 4 8 17 21 -30.60 30.89 3.2 0.37 3 1994 4 18 21 4 -28.15 28.90 2.9 0.41 3 1994 6 10 4 29 -30.06 29.61 2.9 0.30 3 1994 7 19 9 9 -29.52 25.35 3.0 0.37 3 1994 9 13 5 11 -30.39 29.12 3.1 0.37 3 1994 12 31 22 9 -30.41 20.87 4.7 0.38 3 1995 2 8 23 26 -29.73 27.55 3.6 0.50 3 1995 2 11 17 37 -30.46 30.27 3.2 0.43 3 1995 2 27 8 15 -29.58 18.51 3.4 0.38 3 1996 2 4 20 52 -29.65 18.10 3.2 0.28 3 1996 4 26 9 31 -29.55 17.87 3.7 0.37 3 1996 5 24 3 1 -30.08 27.37 3.0 0.41 3 1996 6 20 1 27 -29.58 25.20 2.8 0.40 3 1996 6 30 10 28 -28.18 29.84 3.2 0.35 3 1996 7 21 1 16 -30.38 27.47 2.8 0.61 3 1996 8 22 16 16 -30.45 27.64 2.7 0.29 3 1996 9 15 20 37 -30.05 19.24 5.0 0.42 3 1996 10 10 2 1 -29.205 30.229 2.7 0.23 3 1996 10 22 20 25 -30.500 29.074 2.9 0.40 3 1996 12 27 11 7 -31.018 30.459 3.0 0.46 3 1997 7 25 1 59 -29.379 27.789 2.8 0.24 3 1997 10 19 8 56 -28.358 31.830 2.8 0.46 3 1998 4 24 11 44 -28.214 20.367 3.4 0.32 3 1998 6 22 11 33 -31.877 23.356 3.0 0.24 3 1998 6 22 11 36 -28.486 28.890 2.3 0.20 3 1998 7 5 17 19 -29.730 26.258 2.6 0.24 3 1998 7 12 7 6 -30.682 27.311 3.3 0.26 3 1998 7 15 22 53 -30.080 24.409 2.6 0.37 3 1998 8 11 9 38 -29.359 27.690 2.5 0.24 3 1998 8 28 9 11 -28.204 22.510 2.4 0.33 3 1998 10 2 12 22 -28.364 25.903 2.2 0.23 3 1998 10 5 22 40 -30.267 20.510 3.1 0.79 3 1999 1 7 10 41 -29.527 25.348 2.7 0.61 3 1999 2 4 2 2 -29.760 25.704 4.3 0.26 0 1999 2 14 19 46 -30.221 29.367 3.7 0.44 3 1999 2 19 11 45 -30.120 27.032 2.4 0.21 3 1999 6 21 9 18 -29.581 25.302 2.8 0.52 3 1999 7 3 20 53 -29.292 24.630 4.2 0.30 3 1999 11 15 4 56 -30.594 26.474 2.6 0.45 3 2000 3 8 17 4 -28.28 17.959 3.0 0.25 3 2000 6 11 19 37 -31.359 29.851 3.6 0.55 3 2000 6 25 2 33 -29.33 27.312 2.8 0.37 3 2000 7 12 3 46 -32.327 23.799 2.9 0.66 3 2000 7 13 13 17 -29.521 28.023 2.3 0.20 3 2000 7 21 23 34 -29.691 27.274 2.6 0.22 3 2000 8 27 19 34 -28.874 19.737 2.9 0.27 3 2000 10 3 21 54 -30.263 28.241 2.7 0.25 3 DEP 2000 10 3 21 54 -30.135 28.156 2.7 0.23 3 2000 10 6 3 28 -29.811 24.256 2.2 0.20 3 2000 10 9 11 33 -29.54 24.779 2.1 0.20 3 2000 11 6 8 8 -30.457 25.108 2.3 0.20 3 2000 11 6 8 8 -30.302 25.787 2.3 0.22 3 2000 11 24 18 10 -28.533 28.562 3.3 0.66 3


A11

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2000 11 24 18 10 -28.53 28.57 2.8 0.24 3 DEP 2000 11 24 18 10 -28.543 28.499 3.0 0.34 3 DEP 2001 3 24 20 40 -29.831 18.982 4.0 0.43 3 2001 4 6 19 42 -29.529 19.565 4.4 0.26 1 2001 4 6 20 58 -28.349 19.927 3.7 0.45 3 2001 8 20 0 4 -30.399 29.577 2.5 0.28 3 2001 9 1 22 5 -33.735 23.991 3.2 0.35 3 2001 9 21 19 21 -30.647 27.134 2.3 0.35 3 2001 10 28 22 48 -33.871 22.443 3.9 0.37 3 2002 1 8 5 32 -29.416 24.159 4.2 0.26 1 DEP 2002 1 8 5 32 -29.267 24.126 4.6 0.26 1 2002 1 27 21 50 -29.812 27.644 4.5 0.26 1 2002 1 27 22 9 -29.576 27.492 4.2 0.37 3 DEP 2002 2 14 23 59 -29.203 18.538 3.8 0.29 3 2002 4 11 12 58 -32.818 28.123 3.5 0.91 3 2002 6 25 3 3 -29.908 27.041 2.9 0.27 3 2002 6 28 3 18 -28.084 31.099 3.2 0.27 3 2003 5 4 2 58 -29.509 25.3 2.4 0.25 3 2003 5 4 4 19 -29.614 24.938 2.1 0.28 3 2003 5 8 21 26 -29.852 24.617 2.3 0.56 3 2003 5 19 7 0 -33.8 18.67 2.8 1.12 3 2003 5 19 7 1 -32.851 19.664 2.7 1.15 3 2003 7 2 23 46 -29.812 27.125 2.5 0.31 3 DEP 2003 7 4 13 17 -30.003 27.097 2.8 0.38 3 2003 7 4 14 10 -30 27.044 2.6 0.31 3 DEP 2003 7 7 23 39 -29.844 27.033 2.5 0.22 3 DEP 2003 7 11 3 3 -30.186 26.937 2.3 0.26 3 2003 7 15 20 35 -28.524 28.579 2.8 0.43 3 2003 8 30 16 34 -28.279 28.265 3.2 0.29 3 2003 9 3 7 36 -31.547 23.82 3.4 1.58 3 2003 9 3 16 3 -28.085 28.528 3.2 0.48 3 2003 9 28 8 10 -30.811 24.2 2.2 0.20 3 2003 9 30 0 50 -30.104 19.904 2.7 0.22 3 2003 10 3 2 2 -29.77 27.452 3.1 0.46 3 2003 10 17 21 52 -30.186 27.723 2.3 0.38 3 2003 10 22 21 36 -28.732 24.997 2.7 0.75 3 2003 11 1 2 44 -30.397 28.154 2.6 0.59 3 2003 11 10 17 0 -30.293 25.698 2.3 0.26 3 2003 11 10 18 37 -33.226 19.149 2.8 0.24 3 2003 11 12 0 15 -30.555 27.703 2.5 0.50 3 2003 11 12 12 35 -29.446 27.677 2.5 0.53 3 2003 12 6 17 25 -28.563 26.354 2.5 0.47 3 2003 12 10 1 26 -30.317 27.671 3.2 0.26 3 2003 12 12 19 44 -33.179 19.226 3.5 0.27 3 2003 12 12 19 44 -31.221 18.343 2.5 0.21 3 2004 4 12 11 34 -29.353 24.941 2.6 0.28 3 2004 5 7 18 32 -32.084 30.356 3.2 0.39 3 2004 5 15 13 18 -28.955 29.917 2.0 0.40 3 2004 6 17 18 19 -28.775 20.131 2.2 0.26 3 2004 6 19 16 32 -29.994 27.192 2.7 0.46 3 2004 6 20 10 53 -31.006 25.97 2.7 0.53 3 2004 7 6 13 43 -29.926 21.819 2.0 0.94 3 2004 8 9 7 39 -31.303 19.669 2.6 0.35 3 2004 8 19 12 46 -29.828 20.189 1.8 0.23 3 2004 8 21 4 31 -29.876 18.99 1.9 0.54 3 2004 8 31 5 55 -30.248 21.737 2.0 0.36 3 2004 9 3 11 33 -28.314 23.031 2.4 1.36 3 2004 9 3 13 14 -28.801 23.082 2.7 0.88 3


A12

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2004 9 6 13 47 -28.836 22.887 2.3 0.38 3 2004 9 7 15 57 -29.612 22.682 1.9 0.20 3 2004 9 15 10 56 -28.766 22.909 2.8 1.47 3 2004 9 16 10 45 -30.071 20.976 2.9 1.72 3 2004 9 18 18 5 -30.744 21.137 2.3 0.25 3 2004 9 25 0 38 -28.419 23.466 2.5 1.46 3 2004 9 25 7 19 -29.18 19.88 1.9 0.26 3 2004 10 10 5 30 -32.712 18.187 3.2 0.58 3 2004 10 27 10 21 -33.253 19.046 3.6 0.28 3 2004 11 3 10 14 -29.651 21.61 1.8 0.37 3 2004 11 30 5 57 -29.495 24.999 4.3 0.44 3 2005 1 7 16 25 -29.961 27.314 3.5 0.28 3 2005 1 9 21 16 -29.526 25.093 3.4 0.45 3 DEP 2005 1 17 11 52 -31.243 20.687 2.8 0.52 3 2005 4 4 23 21 -30.008 19.881 2.5 0.22 3 2005 4 11 12 33 -33.412 21.978 2.4 0.39 3 2005 4 16 16 5 -29.748 27.339 2.6 0.36 3 2005 5 18 7 0 -29.544 28.213 3.0 0.43 3 2005 5 18 8 54 -29.762 27.824 2.7 0.56 3 2005 5 20 0 44 -29.422 27.576 2.3 0.66 3 2005 6 11 10 6 -29.811 19.788 2.3 0.31 3 2005 6 23 0 33 -30.196 29.698 2.6 0.33 3 2005 7 1 10 11 -31.411 21.181 2.4 0.27 3 2005 7 3 8 1 -28.16 28.818 2.0 0.21 3 2005 7 9 3 49 -29.742 26.383 2.9 0.35 3 2005 8 22 6 38 -30.317 20.114 2.1 0.20 3 2005 8 23 15 23 -29.543 25.132 2.9 0.55 3 2005 9 1 10 30 -30.253 25.945 2.3 0.23 3 2005 9 7 12 43 -29.749 27.197 2.2 0.20 3 2005 9 11 21 51 -31.63 22.058 2.0 0.21 3 2005 9 19 22 21 -29.474 24.904 2.5 0.32 3 2005 10 13 12 40 -29.507 24.906 2.3 0.46 3 2005 10 17 12 6 -32.915 19.201 1.7 0.57 3 2005 10 19 11 0 -28.026 21.179 2.3 0.39 3 2005 10 20 0 30 -30.188 18.443 2.1 0.29 3 2005 10 25 21 33 -29.312 22.159 2.2 0.48 3 2005 11 3 16 58 -30.121 19.681 2.3 0.47 3 2005 11 25 14 53 -29.217 20.9 2.3 0.46 3 2005 12 2 3 55 -29.033 25.056 2.0 0.21 3 2005 12 6 13 43 -33.213 26.035 2.6 0.26 3 2005 12 9 5 15 -29.249 23.945 2.1 0.34 3 2005 12 18 8 51 -30.113 18.067 2.2 0.24 3 2005 12 23 11 29 -32.255 21.041 1.9 0.22 3 2006 1 18 11 43 -29.845 26.203 2.2 0.47 3 2006 1 26 10 16 -30.606 23.527 2.7 0.62 3 2006 1 26 23 56 -29.417 25.03 2.1 0.37 3 DEP 2006 1 29 10 1 -29.516 25.058 2.3 0.43 3 2006 2 4 0 18 -28.291 30.951 2.1 0.33 3 2006 2 26 1 39 -29.953 26.643 2.5 0.31 3 2006 3 30 14 22 -29.531 18.553 1.9 0.23 3 2006 4 6 18 48 -30.646 21.797 1.7 0.25 3 2006 4 11 20 53 -30.772 25.881 2.9 0.34 3 2006 4 14 3 39 -28.737 23.93 2.0 0.21 3 2006 4 14 18 6 -30.169 19.752 2.1 0.33 3 2006 4 29 20 48 -32.417 22.221 2.3 0.34 3 2006 5 17 16 51 -29.774 28.519 2.0 0.26 3 2006 5 29 22 44 -28.04 31.27 3.1 0.29 3 2006 5 31 19 36 -32.609 21.332 1.6 0.33 3


A13

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2006 6 2 7 51 -29.422 24.35 2.4 0.36 3 2006 6 11 19 51 -30.275 24.618 2.1 0.27 3 2006 6 13 9 13 -30.209 29.523 2.3 0.44 3 2006 6 19 3 34 -30.481 19.904 1.7 0.20 3 2006 6 22 1 43 -30.037 28.58 1.9 0.30 3 2006 6 24 4 25 -29.1618 33.1616 4.2 0.26 1 2006 6 25 15 39 -30.7 18.956 1.8 0.21 3 2006 7 11 17 10 -33.347 19.416 1.7 0.20 3 2006 7 11 17 10 -33.299 19.398 1.6 0.20 3 DEP 2006 7 13 15 7 -29.825 18.683 1.8 0.45 3 2006 7 25 1 2 -29.031 23.483 1.7 0.38 3 2006 7 28 10 50 -30.461 22.415 2.1 0.37 3 2006 7 28 18 3 -30.237 19.303 1.7 0.21 3 2006 7 29 12 8 -30.147 23.354 1.7 0.53 3 2006 7 31 16 42 -29.501 26.929 2.1 0.33 3 2006 8 7 1 18 -29.564 25.033 2.4 0.28 3 2006 8 23 4 56 -29.033 20.449 1.9 0.23 3 2006 8 28 18 11 -29.395 27.402 2.1 0.37 3 2006 8 31 1 35 -30.038 28.194 2.0 0.27 3 2006 8 31 3 59 -29.807 19.433 2.1 0.42 3 2006 9 1 18 24 -29.017 20.309 1.8 0.23 3 2006 9 9 8 18 -32.739 25.412 1.9 0.21 3 2006 9 10 2 39 -28.55 21.747 2.1 0.32 3 2006 9 11 11 30 -34.053 19.196 1.7 0.60 3 2006 9 17 6 50 -31.182 20.341 2.0 0.24 3 2006 9 21 19 57 -28.082 24.365 2.0 0.32 3 2006 9 22 3 16 -29.763 25.294 2.0 0.30 3 2006 9 23 5 14 -28.352 19.817 2.0 0.29 3 2006 9 24 15 27 -29.989 26.682 2.1 0.25 3 2006 9 24 21 19 -30.281 21.849 2.6 0.32 3 2006 9 27 21 53 -33.396 18.933 2.9 0.28 3 2006 9 29 10 33 -28.166 27.299 1.7 0.25 3 2006 10 1 3 35 -33.226 19.156 2.2 0.20 3 2006 10 4 10 23 -29.063 22.986 1.9 0.69 3 2006 10 4 18 8 -33.078 30.102 2.6 0.32 3 2006 10 6 14 9 -29.068 28.496 2.0 0.33 3 2006 10 11 2 17 -33.22 19.169 1.9 0.20 3 2006 10 12 2 3 -28.332 26.001 1.7 0.28 3 2006 10 14 12 23 -28.944 29.122 1.8 0.23 3 2006 10 16 11 2 -33.57 19.148 2.1 0.51 3 2006 10 19 10 10 -28.944 29.035 2.0 0.31 3 2006 10 20 13 57 -30.096 24.04 2.1 0.67 3 2006 11 1 14 5 -32.938 18.951 1.6 0.70 3 2006 11 1 16 16 -28.45 29.742 1.9 0.34 3 2006 11 4 7 13 -30.386 20.956 1.7 0.34 3 2006 11 4 12 56 -28.425 28.978 1.9 0.33 3 2006 11 5 20 2 -31.588 31.349 1.9 0.26 3 2006 11 6 2 48 -30.645 19.637 2.0 0.31 3 2006 11 7 14 30 -28.978 28.901 1.8 0.22 3 2006 11 10 0 21 -29.878 28.67 1.8 0.34 3 2006 11 12 5 48 -32.05 23.138 1.8 0.28 3 2006 11 12 12 19 -29.868 27.839 2.4 0.40 3 2006 11 12 15 46 -29.685 28.25 1.7 0.34 3 2006 11 13 13 56 -29.02 28.817 1.7 0.23 3 2006 11 16 10 7 -29.543 26.676 2.0 0.27 3 2006 11 16 16 3 -29.547 24.192 1.9 0.44 3 2006 11 17 9 2 -29.434 32.957 3.1 0.35 3 2006 11 24 12 19 -28.55 26.337 2.0 0.41 3


A14

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2006 11 25 0 0 -33.522 23.724 2.2 0.24 3 2006 11 27 20 5 -30.008 27.885 2.1 0.29 3 2006 11 29 1 50 -29.703 19.53 1.9 0.26 3 2006 12 4 4 25 -32.055 26.139 1.8 0.26 3 2006 12 8 10 31 -29.994 27.764 1.9 0.37 3 2006 12 8 19 21 -30.036 27.573 2.1 0.35 3 2006 12 10 3 41 -31.792 28.787 2.4 0.28 3 2006 12 22 9 21 -29.524 22.914 2.1 0.52 3 2006 12 23 15 4 -28.862 27.241 1.6 0.28 3 2006 12 24 3 4 -30.218 29.807 2.2 0.30 3 2006 12 24 19 27 -28.552 27.064 1.5 0.39 3 2006 12 26 17 42 -33.744 21.38 1.8 0.21 3 2006 12 28 19 58 -29.786 17.982 2.0 0.22 3 2007 1 3 6 26 -30.817 19.256 2.2 0.31 3 2007 1 3 17 29 -32.258 23.603 2.4 0.20 9 2007 1 5 13 48 -32.89 18.845 1.7 0.55 3 2007 1 6 11 53 -32.536 23.654 1.9 0.22 3 2007 1 8 2 48 -33.262 19.447 1.9 0.24 3 2007 1 8 8 19 -32.015 21.322 2.0 0.31 3 2007 1 8 14 45 -28.929 27.364 1.5 0.35 3 2007 1 9 13 8 -28.87 29.488 1.8 0.22 3 2007 1 12 11 12 -28.977 31.811 2.3 0.21 3 2007 1 13 22 46 -30.029 27.245 1.8 0.39 3 2007 1 15 20 39 -29.96 27.665 1.6 0.26 3 2007 1 16 20 23 -30.361 28.266 1.7 0.32 3 DEP 2007 1 17 12 11 -29.051 25.559 1.8 0.37 3 2007 1 17 19 50 -30.239 28.298 2.0 0.34 3 DEP 2007 1 17 21 41 -30.575 28.263 1.6 0.28 3 DEP 2007 1 19 6 38 -30.579 28.286 1.7 0.33 3 2007 1 19 8 24 -29.851 28.425 1.7 0.26 3 2007 1 19 8 35 -30.25 28.25 2.0 0.34 3 DEP 2007 1 19 9 7 -30.192 28.325 1.8 0.37 3 DEP 2007 1 19 9 28 -30.15 28.312 1.9 0.29 3 DEP 2007 1 19 10 49 -30.192 28.302 2.2 0.31 3 DEP 2007 1 19 17 47 -30.238 28.255 2.0 0.33 3 DEP 2007 1 19 19 1 -30.295 28.334 2.0 0.38 3 DEP 2007 1 19 21 23 -29.939 18.345 1.9 0.69 3 2007 1 20 1 42 -30.042 28.302 2.0 0.32 3 2007 1 20 4 31 -30.201 28.253 1.9 0.41 3 DEP 2007 1 20 5 59 -30.186 28.287 1.9 0.24 3 DEP 2007 1 20 8 4 -30.258 28.409 1.8 0.31 3 DEP 2007 1 20 11 35 -30.311 28.398 2.1 0.32 3 DEP 2007 1 20 12 40 -30.279 28.199 2.4 0.29 3 DEP 2007 1 20 16 10 -30.037 28.078 1.8 0.39 3 2007 1 20 20 45 -30.23 28.355 2.1 0.30 3 DEP 2007 1 21 0 7 -30.349 28.232 2.0 0.35 3 DEP 2007 1 21 20 59 -29.868 28.302 2.0 0.32 3 DEP 2007 1 21 1 35 -32.76 17.895 1.9 0.48 3 2007 1 21 5 6 -30.173 28.307 1.9 0.36 9 DEP 2007 1 21 5 23 -30.224 28.16 2.4 0.20 3 2007 1 21 9 18 -30.804 28.246 1.8 0.27 3 2007 1 21 16 21 -30.282 28.233 2.1 0.35 3 DEP 2007 1 21 16 23 -30.19 28.285 2.0 0.30 3 DEP 2007 1 21 16 25 -30.215 28.217 2.0 0.30 3 DEP 2007 1 21 16 37 -30.485 28.044 1.9 0.20 3 2007 1 22 0 38 -30.388 28.148 1.7 0.43 3 DEP 2007 1 22 21 10 -28.864 19.744 1.9 0.44 3 2007 1 24 0 4 -29.65 18.412 1.7 0.58 3


A15

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2007 1 24 20 32 -30.184 27.817 1.9 0.35 3 2007 1 24 22 23 -30.108 28.283 2.3 0.30 3 DEP 2007 1 25 0 17 -29.898 28.385 1.9 0.24 3 2007 1 25 1 24 -30.22 28.221 2.2 0.35 3 DEP 2007 1 25 13 55 -28.679 27.269 2.1 0.70 3 2007 1 25 18 8 -30.349 28.22 2.0 0.25 3 DEP 2007 1 25 18 30 -30.338 28.296 1.8 0.25 3 DEP 2007 1 26 13 54 -29.87 28.018 1.9 0.44 3 2007 1 26 21 36 -30.342 28.287 1.7 0.39 3 DEP 2007 1 27 3 26 -30.089 28.423 1.9 0.33 3 2007 1 29 3 23 -30.202 28.204 1.9 0.40 3 2007 1 31 6 30 -34.16 19.982 2.2 0.46 3 2007 1 31 15 35 -33.537 19.434 1.5 0.20 3 2007 2 1 11 22 -32.902 18.79 1.7 0.65 3 2007 2 2 10 54 -32.963 22.184 2.1 0.27 3 2007 2 5 2 18 -30.155 29.43 2.3 0.27 3 2007 2 8 14 29 -29.609 17.251 1.8 0.34 3 2007 2 8 17 38 -29.124 27.977 1.7 0.40 3 2007 2 9 11 47 -30.006 28.302 1.8 0.48 3 2007 2 15 14 8 -33.661 18.722 1.8 0.72 3 2007 2 18 21 39 -29.53 24.546 1.4 0.32 3 DEP 2007 2 19 1 29 -29.526 24.601 1.7 0.22 3 2007 2 22 15 39 -33.649 19.067 2.0 0.20 3 2007 2 24 17 36 -29.868 27.325 2.2 0.29 3 2007 2 25 13 1 -28.636 26.284 1.8 0.51 3 2007 2 27 20 53 -32.183 28.245 1.9 0.25 3 2007 3 1 14 31 -28.081 29.658 2.0 0.34 3 2007 3 2 4 18 -29.569 28.442 2.5 0.86 3 2007 3 4 2 45 -29.876 27.456 2.1 0.34 3 2007 3 5 4 7 -30.803 18.863 1.5 0.55 3 2007 3 6 10 42 -30.227 28.169 2.4 0.20 9 2007 3 6 15 40 -33.57 19.466 1.9 0.20 3 2007 3 7 8 58 -30.46 18.636 1.5 0.48 3 2007 3 10 2 37 -29.088 18.292 1.8 0.70 3 2007 3 14 1 43 -30.789 18.88 1.5 0.73 3 2007 3 25 19 43 -32.705 17.938 2.0 0.29 3 2007 3 29 10 24 -30.429 29.843 2.1 0.38 3 2007 3 30 12 23 -32.917 18.802 1.9 0.82 3 2007 3 31 11 41 -33.14 17.747 2.0 0.23 3 2007 4 1 0 29 -30.23 27.409 1.8 0.32 3 2007 4 1 8 59 -29.95 22.292 1.6 0.28 3 2007 4 5 15 1 -29.452 27.829 1.8 0.39 3 2007 4 9 11 0 -29.816 26.793 3.4 0.32 3 2007 4 12 13 1 -29.114 28.59 1.9 0.30 3 2007 4 21 12 15 -28.805 28.794 1.8 0.26 3 2007 4 22 4 20 -29.931 28.252 1.8 0.30 3 2007 4 22 13 11 -29.581 30.504 2.0 0.41 3 2007 4 22 22 7 -30.221 17.817 1.4 0.69 3 2007 4 22 22 28 -30.545 27.745 1.9 0.27 3 2007 4 23 17 45 -33.454 19.311 2.1 0.20 3 2007 4 30 3 58 -30.471 27.551 1.8 0.32 3 2007 4 30 14 48 -29.832 18.339 1.6 0.71 3 2007 5 1 5 30 -30.071 23.549 1.5 0.22 3 2007 5 1 7 5 -30.312 27.625 1.8 0.33 3 2007 5 1 8 9 -32.79 22.094 2.1 0.29 3 2007 5 2 22 19 -30.523 24.6 1.7 0.48 3 2007 5 4 5 37 -29.428 28.07 1.7 0.31 3 2007 5 4 8 36 -29.531 24.553 1.7 0.24 3


A16

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2007 5 7 4 53 -30.158 18.88 1.9 0.48 3 2007 5 9 13 6 -29.164 28.62 1.9 0.22 3 2007 5 11 12 8 -30.104 28.203 2.1 0.37 3 DEP 2007 5 11 12 29 -29.998 28.267 2.3 0.41 3 2007 5 11 19 28 -30.65 28.142 1.9 0.42 3 2007 5 11 19 50 -30.314 28.177 1.8 0.32 3 DEP 2007 5 12 1 45 -30.287 28.171 2.1 0.28 3 2007 5 12 3 41 -30.227 28.171 1.7 0.48 3 DEP 2007 5 12 7 11 -30.264 28.192 2.0 0.37 3 DEP 2007 5 15 4 4 -30.018 27.772 2.1 0.27 3 DEP 2007 5 15 8 42 -30.148 27.74 2.1 0.23 3 2007 5 15 14 51 -29.733 28.433 2.1 0.48 3 2007 5 21 19 44 -29.899 27.358 2.1 0.26 3 DEP 2007 5 24 19 36 -29.954 27.499 2.3 0.25 3 2007 5 25 19 7 -30.331 19.04 2.0 0.38 3 2007 5 27 3 26 -29.775 29.496 2.0 0.36 3 2007 6 3 22 58 -30.187 28.569 2.8 0.27 3 2007 6 9 8 8 -34.259 19.715 1.5 0.20 3 2007 6 9 8 29 -30.036 27.001 1.6 0.41 3 2007 6 9 14 31 -28.584 28.611 1.7 0.42 3 2007 6 13 21 57 -29.051 27.739 2.3 0.38 3 2007 6 22 8 4 -29.369 24.79 1.6 0.21 3 2007 6 22 14 22 -28.749 29.949 2.3 0.28 3 2007 6 24 5 26 -30.862 18.849 2.2 0.32 3 2007 6 26 9 52 -28.039 30.863 2.0 0.89 3 2007 7 1 7 28 -28.661 18.013 2.1 0.26 3 2007 7 1 16 21 -29.246 27.487 1.6 0.21 3 2007 7 2 15 27 -33.833 18.649 1.7 0.87 3 2007 7 5 1 13 -29.429 25.026 1.3 0.35 3 2007 7 6 17 20 -28.754 26.187 1.7 0.21 3 2007 7 8 5 25 -29.197 27.131 1.7 0.47 3 2007 7 10 15 53 -28.79 26.361 1.8 0.46 3 2007 7 11 17 17 -29.727 27.323 1.9 0.55 3 2007 7 15 11 44 -30.503 27.69 2.0 0.21 3 2007 7 20 22 8 -29.816 20.499 1.9 0.24 3 2007 7 30 13 37 -29.721 18.7 1.8 0.22 3 2007 8 18 15 39 -29.839 19.241 2.2 0.31 3 2007 8 19 6 53 -35.465 19.096 1.6 0.20 3 2007 8 20 19 17 -30.389 24.652 3.0 0.39 3 2007 9 1 13 34 -29.197 28.553 1.8 0.33 3 2007 9 5 14 36 -31.163 22.868 2.0 0.20 3 2007 9 5 19 9 -31.596 19.231 2.1 0.36 3 2007 9 6 7 41 -28.049 30.214 2.4 0.60 3 2007 9 8 7 20 -33.351 19.441 2.0 0.20 3 2007 9 9 4 40 -29.957 26.447 1.8 0.41 3 2007 9 9 10 24 -29.814 19.301 2.1 0.27 3 2007 9 15 3 15 -29.36 27.692 1.9 0.37 3 2007 9 17 16 21 -29.556 25.009 1.9 0.28 3 2007 9 17 16 45 -33.362 19.443 1.6 0.20 3 2007 9 17 20 3 -29.928 18.781 3.1 0.35 3 2007 9 18 14 59 -33.855 20.168 2.3 0.37 3 2007 9 20 10 32 -29.96 28.934 2.2 0.33 3 2007 9 21 22 26 -30.252 28.934 2.2 0.28 3 2007 9 26 12 28 -28.906 29.019 2.0 0.32 3 2007 9 29 12 58 -29.692 27.624 1.7 0.24 3 2007 9 30 14 35 -30.333 18.853 1.9 0.22 3 2007 10 1 4 36 -30.03 27.246 2.0 0.38 3 2007 10 3 21 32 -29.888 28.53 1.9 0.46 3


A17

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2007 10 6 14 29 -29.674 29.595 2.2 0.39 3 2007 10 12 9 17 -28.301 18.315 2.0 0.20 3 2007 10 12 15 24 -30.038 27.565 2.3 0.24 3 2007 10 19 14 39 -28.932 28.936 2.0 0.45 3 2007 10 19 15 17 -28.617 31.193 2.4 0.40 3 2007 10 20 21 18 -30.271 19.746 1.8 0.22 3 2007 10 23 21 51 -31.189 20.348 1.9 0.22 3 2007 10 27 2 58 -30.279 24.525 1.4 0.20 3 2007 10 27 5 42 -32.507 24.653 2.3 0.20 9 2007 10 27 22 49 -32.64 24.818 1.9 0.30 3 DEP 2007 10 28 1 18 -32.662 24.771 1.9 0.29 3 2007 10 30 14 34 -30.3 19.259 2.5 0.24 3 2007 10 31 13 55 -30.109 29.313 2.3 0.23 3 2007 11 1 7 47 -30.634 20.509 2.0 0.28 3 2007 11 3 9 3 -32.794 22.023 3.8 0.34 3 2007 11 5 14 17 -29.509 24.967 1.7 0.24 3 2007 11 11 19 13 -29.776 27.441 1.7 0.29 3 2007 11 14 5 20 -29.516 25.215 2.0 0.30 3 2007 11 18 14 14 -32.068 20.749 2.0 0.31 3 2007 11 18 15 5 -29.31 22.061 1.8 0.26 3 2007 11 22 22 18 -30.738 19.236 1.8 0.22 3 2007 12 2 3 53 -28.412 19.6 1.8 0.21 3 2007 12 3 12 27 -30.122 27.343 2.1 0.28 3 2007 12 4 14 28 -29.489 27.977 2.0 0.55 3 2007 12 6 15 0 -29.916 27.494 1.9 0.45 3 2007 12 7 2 55 -29.906 28.382 2.0 0.37 3 2007 12 11 15 37 -30.173 29.55 2.1 0.25 3 2007 12 13 9 32 -29.751 26.112 2.1 0.33 3 2007 12 14 7 42 -29.585 24.453 1.7 0.22 3 2007 12 14 13 12 -28.91 28.545 1.9 0.31 3 2007 12 18 2 53 -30.026 27.303 2.1 0.37 3 2007 12 20 2 35 -32.095 26.085 1.8 0.25 3 2007 12 20 9 7 -31.29 28.892 2.0 0.33 3 2007 12 21 17 16 -30.272 25.805 2.1 0.26 3 2007 12 22 8 16 -30.287 27.354 1.8 0.37 3 2007 12 24 0 17 -28.437 26.393 1.7 0.26 3 2007 12 24 1 41 -29.456 19.641 1.9 0.22 3 2007 12 26 11 2 -29.96 29.503 3.0 0.34 3 2007 12 26 13 14 -29.976 29.585 2.0 0.36 3 DEP 2007 12 26 11 8 -29.954 29.474 2.3 0.28 3 DEP 2008 1 4 13 33 -29.332 28.843 2.2 0.29 3 2008 1 4 19 6 -29.527 25.33 1.9 0.40 3 2008 1 8 9 5 -28.831 28.688 2.0 0.50 3 2008 1 14 22 48 -29.757 27.218 2.1 0.27 3 2008 1 14 23 19 -29.466 27.705 1.8 0.52 3 2008 1 19 8 53 -30.257 25.259 1.9 0.20 3 2008 1 23 12 12 -28.015 30.31 2.0 0.52 3 2008 1 26 9 42 -29.99 27.672 2.3 0.28 3 2008 1 26 12 36 -30.586 19.112 1.9 0.25 3 2008 1 27 13 53 -28.759 28.681 1.9 0.37 3 2008 1 28 20 43 -28.467 28.876 1.9 0.48 3 2008 1 31 18 3 -30.358 28.948 1.9 0.20 3 2008 2 2 14 58 -29.65 27.92 1.8 0.37 3 2008 2 3 16 23 -29.167 27.156 2.1 0.31 3 2008 2 5 23 51 -30.68 30.436 2.0 0.24 3 2008 2 6 7 28 -29.507 27.725 1.9 0.42 3 2008 2 14 3 49 -30.166 27.502 1.9 0.22 3 2008 2 19 20 15 -29.52 18.284 2.8 0.28 3


A18

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2008 2 21 1 1 -35.625 25.561 2.5 0.53 3 2008 2 26 13 27 -32.835 18.862 1.5 0.58 3 2008 2 28 4 16 -28.726 30.898 2.9 0.37 3 2008 3 3 15 44 -28.305 17.857 2.3 0.22 3 2008 3 4 2 38 -29.901 24.717 1.8 0.32 3 2008 3 11 13 15 -30.12 27.379 2.2 0.28 3 2008 3 11 21 4 -30.157 19.907 2.1 0.35 3 2008 3 14 4 12 -29.053 23.506 1.7 0.59 3 2008 3 15 5 21 -29.566 25.2 1.9 0.28 3 2008 3 16 15 0 -30.384 27.436 1.9 0.63 3 2008 3 16 17 20 -29.792 27.486 2.0 0.34 3 2008 3 17 21 43 -32.869 22.063 1.9 0.25 3 2008 3 18 19 28 -29.853 27.472 1.9 0.31 3 DEP 2008 3 22 3 56 -29.964 28.466 2.0 0.26 3 2008 3 25 17 13 -32.422 31.258 2.2 0.26 3 2008 3 29 14 46 -29.6 19.798 1.8 0.26 3 2008 3 29 16 46 -30.416 27.885 1.7 0.28 3 2008 4 4 12 13 -29.141 27.999 2.2 0.26 3 2008 4 5 13 26 -29.031 28.868 1.7 0.20 3 2008 4 6 18 12 -30.449 21.107 1.7 0.24 3 2008 4 9 18 33 -29.815 27.471 1.9 0.30 3 2008 4 11 13 28 -29.047 28.937 2.0 0.56 3 2008 4 12 0 28 -29.334 24.786 1.8 0.45 3 2008 4 15 12 42 -34.095 18.591 1.8 0.28 3 2008 4 17 0 5 -30.526 20.271 2.2 0.22 3 2008 4 21 9 55 -33.219 19.384 1.5 0.32 3 2008 4 21 15 10 -33.558 19.527 1.8 0.34 3 2008 4 22 6 41 -30.028 26.809 2.2 0.32 3 2008 4 23 13 6 -32.884 18.791 1.6 0.52 3 2008 4 24 14 35 -28.736 29.136 2.0 0.47 3 2008 4 27 2 2 -31.864 23.244 2.2 0.26 3 2008 4 27 11 5 -29.485 27.758 1.6 0.24 3 2008 4 28 7 45 -29.172 28.272 1.7 0.25 3 2008 4 28 8 15 -33.163 19.331 1.8 0.28 3 2008 5 13 15 52 -33.514 18.84 1.7 0.28 3 2008 5 19 9 16 -29.966 18.957 2.0 0.20 3 2008 5 21 8 55 -29.058 28.827 2.0 0.46 3 2008 5 31 13 25 -29.773 27.39 1.9 0.29 3 2008 6 1 12 53 -29.709 27.689 1.8 0.30 3 2008 6 1 17 56 -30.355 23.281 2.2 0.23 3 2008 6 9 11 11 -29.922 27.636 2.0 0.21 3 2008 6 11 19 58 -29.737 26.436 2.2 0.25 3 2008 6 15 2 12 -30.121 28.323 2.0 0.25 3 2008 6 19 3 17 -29.965 27.171 2.0 0.36 3 2008 6 21 1 34 -30.159 27.298 2.0 0.27 3 2008 6 26 2 47 -28.947 27.278 1.7 0.40 3 2008 6 26 20 59 -28.878 19.343 2.2 0.26 3 2008 6 27 4 24 -30.022 19.609 1.6 0.41 3 2008 6 28 0 29 -28.901 20.245 1.9 0.21 3 2008 6 30 6 6 -29.909 27.852 2.0 0.37 3 2008 7 9 15 1 -29.465 21.902 2.1 0.40 3 2008 7 13 17 36 -33.21 21.88 1.8 0.34 3 2008 7 18 3 53 -28.756 23.739 1.5 0.36 3 2008 7 20 5 30 -29.8 19.803 2.0 0.21 3 2008 7 23 19 58 -30.03 18.624 1.7 0.23 3 2008 8 1 16 1 -30.381 28.923 2.4 0.20 9 2008 8 2 8 35 -31.896 24.852 1.6 0.33 3 2008 8 4 17 50 -30.398 29.779 2.1 0.27 3


A19

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2008 8 5 1 12 -28.132 24.012 1.6 0.20 9 2008 8 8 22 30 -29.14 31.299 2.3 0.20 9 2008 8 10 9 52 -30.01 28.276 1.8 0.23 3 2008 8 11 11 41 -32.604 17.607 2.4 0.20 9 2008 8 14 3 22 -30.371 20.986 1.9 0.20 9 2008 8 14 14 50 -33.001 18.817 1.9 0.20 3 2008 8 14 18 38 -30.079 25.74 2.1 0.20 9 2008 8 23 13 42 -29.323 23.053 2.0 0.22 3 2008 8 24 19 57 -33.381 19.599 2.1 0.26 3 2008 8 25 20 25 -32.794 22.059 2.3 0.20 9 2008 8 25 20 32 -32.763 22.025 2.1 0.20 9 DEP 2008 8 25 22 17 -29.271 24.807 1.7 0.40 3 2008 8 26 18 22 -30.599 18.419 1.9 0.20 9 2008 8 27 13 7 -29.991 18.18 1.9 0.20 9 2008 8 30 15 16 -30.324 25.824 2.1 0.20 9 2008 9 2 22 25 -30.509 20.402 2.1 0.20 9 2008 9 8 14 33 -30.425 19.527 2.3 0.23 3 2008 9 8 23 51 -30.595 29.727 2.0 0.38 3 2008 9 10 19 17 -32.946 17.825 2.3 0.33 3 2008 9 11 10 28 -29.7 18.283 1.8 0.33 3 2008 9 12 12 44 -28.206 29.186 1.9 0.28 3 2008 9 12 23 54 -30.42 19.493 2.0 0.27 3 DEP 2008 9 13 22 44 -30.839 19.032 1.6 0.22 3 2008 9 15 1 56 -29.82 18.079 1.9 0.24 3 2008 9 17 20 3 -29.819 26.595 2.3 0.20 9 2008 9 20 20 18 -28.844 20.249 1.8 0.34 3 2008 9 22 2 8 -29.971 18.728 2.0 0.28 3 2008 9 26 16 59 -30.048 28.146 1.8 0.37 3 2008 9 27 10 35 -28.982 18.458 1.9 0.30 3 2008 9 28 12 38 -29.017 28.837 1.8 0.25 3 2008 9 30 11 21 -29.951 20.462 2.1 0.29 3 2008 10 3 22 22 -30.373 17.638 1.8 0.37 3 2008 10 4 8 59 -29.278 28.45 2.2 0.20 9 2008 10 4 11 18 -32.937 17.805 2.1 0.36 3 2008 10 6 8 8 -30.214 27.443 1.7 0.36 3 2008 10 9 16 51 -32.887 22.153 2.3 0.20 9 2008 10 13 4 14 -30.563 19.435 1.7 0.22 3 2008 10 13 14 37 -28.722 29.137 1.8 0.33 3 2008 10 14 21 3 -30.564 20.543 1.7 0.24 3 2008 10 15 9 27 -29.032 28.808 1.9 0.25 3 2008 10 17 12 21 -30.103 27.478 2.3 0.30 3 2008 10 19 21 13 -28.923 19.705 2.6 0.25 3 2008 10 20 5 32 -29.533 24.865 2.0 0.20 9 2008 10 23 14 28 -28.911 29.058 1.8 0.29 3 2008 10 25 3 1 -30.229 26.645 1.8 0.27 3 2008 10 26 5 25 -29.857 19.392 1.9 0.26 3 2008 10 30 6 20 -28.573 28.962 2.0 0.28 3 DEP 2008 10 30 7 32 -28.582 28.938 2.1 0.20 9 2008 10 30 11 25 -28.593 28.959 2.1 0.29 3 DEP 2008 10 30 13 30 -28.558 29.032 1.9 0.26 3 DEP 2008 11 3 7 17 -30.133 27.678 1.7 0.41 3 2008 11 6 11 26 -32.977 18.694 1.8 0.46 3 2008 11 7 2 19 -32.978 17.785 2.0 0.27 3 2008 11 9 0 33 -29.587 27.695 1.8 0.22 3 2008 11 10 6 45 -29.814 28.227 1.8 0.23 3 2008 11 15 2 27 -28.193 18.352 1.9 0.22 3 2008 11 19 10 5 -31.654 24.499 2.8 0.30 3 2008 11 20 3 58 -31.538 20.033 1.7 0.36 3


A20

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2008 11 20 13 5 -31.889 22.4 2.0 0.47 3 2008 11 20 21 2 -29.485 24.528 2.2 0.22 3 2008 11 26 14 0 -29.338 28.37 1.7 0.24 3 2008 12 1 13 58 -29.127 28.693 1.9 0.23 3 2008 12 3 10 50 -31.275 28.24 2.3 0.20 9 2008 12 14 18 8 -29.898 28.157 1.8 0.28 3 2008 12 16 0 36 -29.648 18.512 1.9 0.34 3 2008 12 16 2 47 -30.254 21.27 1.9 0.24 3 2008 12 20 6 3 -28.738 32.82 2.8 0.26 3 2008 12 23 5 20 -29.743 18.776 1.9 0.23 3 2008 12 28 5 21 -32.525 25.208 2.3 0.24 3 2009 1 3 15 35 -29.496 27.975 2.1 0.23 3 2009 1 4 3 33 -32.873 22.056 1.8 0.20 9 2009 1 7 13 51 -37.68 31.559 2.5 0.32 3 2009 1 8 5 4 -28.721 32.662 3.0 0.30 3 2009 1 10 7 22 -30.828 26.14 2.1 0.20 9 2009 1 24 10 50 -32.073 18.868 2.0 0.27 3 2009 1 24 16 39 -32.677 17.741 1.7 0.21 3 2009 1 25 0 43 -30.159 21.284 1.8 0.31 3 2009 1 27 10 42 -30.22 29.283 2.9 0.30 3 2009 1 28 3 39 -28.624 18.536 2.6 0.33 3 DEP 2009 1 28 4 27 -28.582 18.591 3.3 0.41 3 2009 2 1 8 49 -33.241 19.037 1.8 0.24 3 2009 2 9 10 8 -28.619 28.935 1.9 0.46 3 2009 2 9 19 6 -28.412 28.833 1.8 0.24 3 2009 2 14 11 49 -32.513 19.732 1.4 0.24 3 2009 2 14 21 40 -33.225 19.1 2.4 0.40 3 2009 2 18 9 41 -29.792 18.992 1.9 0.21 3 2009 3 8 3 23 -33.157 21.843 2.0 0.20 9 2009 3 8 21 10 -32.728 20.252 2.7 0.32 3 2009 3 13 21 55 -29.154 27.387 2.1 0.20 9 2009 3 17 12 15 -33.647 20.873 2.2 0.20 9 2009 3 20 0 37 -33.403 19.356 2.2 0.38 3 2009 4 7 2 53 -29.961 27.49 1.8 0.27 3 2009 4 10 10 17 -33.56 18.275 1.8 0.52 3 2009 4 15 14 15 -29.501 27.983 1.9 0.25 3 2009 4 21 10 22 -29.831 18.882 2.1 0.29 3 2009 5 7 0 43 -30.31 18.136 2.0 0.21 3 2009 5 13 0 55 -30.096 19.069 1.7 0.48 3 2009 5 20 16 30 -30.266 20.459 1.8 0.21 3 2009 5 20 22 44 -29.651 27.685 3.0 0.31 3 2009 5 21 4 3 -28.631 28.986 3.0 0.32 3 DEP 2009 5 21 4 3 -28.635 28.975 3.1 0.34 3 2009 5 22 7 40 -28.597 29.004 2.2 0.20 9 DEP 2009 5 25 20 57 -29.655 17.843 2.0 0.25 3 2009 5 29 15 24 -28.222 29.622 1.9 0.40 3 2009 5 30 7 26 -29.026 29.209 1.7 0.28 3 2009 6 8 0 8 -32.836 22.068 2.3 0.20 9 2009 6 11 22 23 -29.429 24.924 1.7 0.27 3 2009 6 13 3 52 -30.172 18.087 1.9 0.59 3 2009 6 25 6 13 -29.716 27.844 2.0 0.20 9 2009 6 27 2 23 -29.057 27.51 1.8 0.41 3 2009 6 29 16 12 -32.16 23.118 2.0 0.27 3 2009 6 30 21 35 -30.102 19.443 1.8 0.22 3 2009 7 5 0 3 -30.93 29.288 2.4 0.29 3 2009 7 9 2 38 -28.857 20.198 2.7 0.28 3 2009 7 9 10 9 -28.776 20.142 2.0 0.23 3 DEP 2009 7 9 10 20 -28.883 20.28 2.0 0.24 3 DEP


A21

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2009 7 10 21 7 -28.818 20.184 2.1 0.24 3 DEP 2009 7 13 12 53 -29.496 19.806 3.5 0.30 3 2009 7 13 18 0 -34.57 18.252 2.3 0.27 3 2009 7 21 20 51 -30.107 25.863 2.0 0.20 9 2009 7 21 23 43 -28.868 20.278 2.6 0.26 3 2009 7 24 12 49 -28.581 17.461 2.1 0.46 3 2009 7 26 14 38 -29.036 28.829 2.2 0.28 3 2009 7 28 17 50 -28.613 28.923 1.9 0.21 3 DEP 2009 7 28 21 35 -28.633 28.946 1.9 0.20 9 2009 7 28 20 30 -28.679 28.865 1.7 0.20 9 DEP 2009 7 30 1 52 -28.875 19.639 2.5 0.25 3 2009 7 31 11 28 -28.747 28.791 1.8 0.20 3 2009 8 1 19 27 -30.204 29.393 2.0 0.20 9 2009 8 3 5 59 -29.866 28.089 2.3 0.20 9 2009 8 4 6 7 -29.929 19.365 1.9 0.21 3 2009 8 10 2 39 -30.093 27.401 1.8 0.39 3 2009 8 10 19 31 -30.043 28.157 1.9 0.25 3 2009 8 11 4 30 -32.794 22.049 2.9 0.29 3 2009 8 14 11 36 -29.51 19.768 2.0 0.24 3 2009 8 19 17 10 -32.831 22.117 1.9 0.20 9 DEP 2009 8 22 10 10 -33.298 19.471 1.8 0.81 3 2009 8 22 12 0 -29.14 28.784 1.8 0.52 3 2009 8 24 23 12 -31.816 18.244 2.0 0.20 9 2009 8 31 13 14 -28.932 20.384 2.3 0.22 3 2009 9 3 6 33 -32.849 22.046 2.8 0.27 3 2009 9 5 13 58 -28.862 29.433 2.0 0.24 3 2009 9 6 17 27 -30.355 27.622 1.7 0.42 3 2009 9 7 13 56 -28.943 29.179 1.8 0.25 3 2009 9 21 13 58 -29.049 28.999 2.0 0.30 3 2009 9 22 1 23 -32.734 31.336 2.4 0.29 3 2009 9 23 8 13 -30.301 29.585 2.2 0.30 3 2009 9 26 8 42 -29.577 25.088 1.9 0.20 9 2009 9 27 14 9 -28.779 20.149 2.1 0.27 3 2009 10 7 16 36 -30.27 29.378 2.5 0.30 3 2009 10 11 4 47 -29.976 28.455 2.0 0.20 9 2009 10 13 7 38 -30.201 18.514 2.0 0.22 3 2009 10 14 14 7 -29.005 29.049 1.8 0.26 3 2009 10 15 22 36 -29.131 29.474 2.2 0.24 3 2009 10 16 18 32 -31.278 20.705 2.9 0.33 3 DEP 2009 10 16 18 35 -31.297 20.67 3.2 0.36 3 2009 10 17 2 14 -31.279 20.762 2.6 0.32 3 DEP 2009 10 17 18 26 -30.76 19.059 1.9 0.25 3 2009 10 18 19 49 -32.97 22.191 1.8 0.30 3 2009 10 24 2 21 -29.491 24.658 1.8 0.26 3 2009 10 24 12 21 -32.284 25.905 1.8 0.28 3 2009 10 28 17 29 -29.914 27.558 1.9 0.26 3 2009 10 30 7 2 -28.904 20.237 1.9 0.30 3 2009 10 30 13 54 -29.092 28.736 2.0 0.26 3 2009 11 1 3 23 -31.587 21.409 1.8 0.33 3 2009 11 4 1 28 -30.198 19.005 1.7 0.32 3 2009 11 4 22 14 -31.572 24.943 2.7 0.37 3 2009 11 5 12 39 -32.843 22.152 3.5 0.38 3 2009 11 5 16 8 -29.709 29.056 2.3 0.46 3 2009 11 7 9 57 -32.856 22.057 2.3 0.33 3 DEP 2009 11 7 23 9 -32.854 21.986 1.9 0.34 3 DEP 2009 11 8 13 36 -28.945 28.932 2.0 0.36 3 2009 11 13 5 36 -30.22 18.849 2.5 0.25 3 2009 11 16 5 43 -30.892 18.768 2.1 0.37 3


A22

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2009 11 18 17 57 -29.164 28.869 2.2 0.40 3 2009 11 22 14 16 -29.096 28.702 2.0 0.36 3 2009 11 22 21 57 -29.71 26.699 1.7 0.34 3 2009 12 1 13 44 -32.693 31.421 3.1 0.34 3 2009 12 2 13 55 -29.165 28.633 2.1 0.20 3 2009 12 2 17 9 -33.085 18.266 2.6 0.35 3 2009 12 3 13 57 -29.853 28.859 1.8 0.48 3 2009 12 8 1 9 -30.103 27.65 2.1 0.30 3 2009 12 8 23 21 -32.788 22.135 3.6 0.37 3 2009 12 9 14 32 -28.9 28.959 2.0 0.26 3 2009 12 9 17 6 -32.626 22.113 2.0 0.26 3 DEP 2009 12 9 22 4 -30.801 24.407 1.7 0.26 3 2009 12 11 12 8 -31.616 18.429 1.9 0.42 3 2009 12 16 0 43 -32.648 31.205 2.8 0.28 3 2010 1 12 20 39 -30.025 28.903 1.8 0.57 3 2010 1 17 12 26 -28.849 29.297 2.0 0.23 3 2010 1 19 7 56 -29.18 28.736 1.9 0.39 3 2010 1 23 20 49 -29.851 27.759 1.5 0.28 3 2010 1 29 13 50 -30.123 29.555 2.1 0.27 3 2010 1 30 12 25 -28.831 29.186 1.9 0.55 3 2010 2 12 4 34 -30.155 27.382 2.5 0.20 9 2010 2 12 5 51 -29.997 27.491 2.0 0.29 3 2010 2 16 12 20 -28.861 26.837 2.3 0.20 9 2010 2 19 7 23 -28.497 20.045 2.1 0.24 3 2010 2 24 1 7 -30.179 28.485 2.4 0.20 9 2010 3 1 14 1 -28.941 28.907 1.8 0.26 3 2010 3 3 13 1 -30.493 30.999 2.7 0.33 3 2010 3 10 23 28 -34.66 19.126 2.1 0.71 3 2010 3 11 15 6 -30.364 25.995 2.8 0.40 3 2010 3 20 12 16 -29.548 28.077 1.8 0.63 3 2010 3 23 14 1 -29.671 27.572 2.0 0.36 3 2010 3 28 0 0 -30.257 29.446 2.1 0.41 3 2010 3 28 14 38 -29.393 27.675 2.2 0.30 3 2010 3 29 8 54 -34.161 18.329 2.4 0.30 3 2010 4 4 10 27 -29.573 27.076 1.7 0.46 3 2010 4 8 6 39 -29.46 19.787 2.6 0.28 3 2010 4 10 8 51 -29.019 20.929 1.8 0.40 3 2010 4 15 13 41 -30.071 27.891 2.2 0.55 3 2010 4 18 9 59 -30.153 27.82 2.1 0.38 3 DEP 2010 4 21 11 28 -29.567 18.325 2.4 0.21 3 2010 4 22 12 36 -29.453 19.89 2.2 1.30 3 2010 4 28 0 19 -32.99 17.807 1.9 0.28 3 2010 5 5 16 33 -28.795 20.221 1.8 0.21 3 2010 5 5 18 3 -29.033 27.136 2.0 0.20 9 2010 5 9 1 50 -30.03 29.447 2.0 0.26 3 2010 5 9 17 21 -30.487 28.351 1.9 0.35 3 2010 5 12 8 11 -28.804 26.44 1.7 0.21 3 2010 5 12 15 26 -28.735 26.878 1.8 0.29 3 2010 5 12 23 21 -29.643 28.039 1.7 0.29 3 DEP 2010 5 13 20 22 -33.305 19.443 2.0 0.26 3 2010 5 15 5 5 -29.75 28.041 2.3 0.20 9 2010 5 18 13 32 -32.454 17.783 2.1 0.23 3 2010 5 20 2 33 -29.252 27.755 2.4 0.20 9 2010 5 20 13 25 -33.195 26.717 1.9 0.42 3 2010 5 22 16 44 -33.073 22.518 1.7 0.32 3 2010 5 25 1 14 -29.787 25.591 2.1 0.20 9 2010 5 27 10 12 -28.821 26.363 1.9 0.33 3 2010 6 6 18 23 -28.883 28.395 1.8 0.27 3


A23

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2010 6 7 1 53 -30.031 30.133 2.0 0.41 3 2010 6 13 6 37 -29.001 27.029 2.0 0.20 9 2010 6 14 15 59 -28.037 24.509 1.7 0.22 3 2010 6 15 2 18 -29.767 26.377 1.8 0.23 3 2010 6 15 3 43 -30.321 29.682 2.0 0.25 3 2010 6 19 18 59 -29.995 27.064 2.4 0.29 3 2010 6 20 21 15 -28.648 20.466 1.8 0.21 3 DEP 2010 6 21 1 17 -28.682 20.435 2.1 0.32 3 2010 6 22 22 53 -28.717 22.118 2.3 0.33 3 2010 6 24 10 6 -28.721 20.804 3.2 0.45 3 2010 6 24 10 20 -28.507 19.004 2.3 0.22 3 2010 6 24 11 2 -30.154 21.533 1.9 0.25 3 2010 6 24 16 39 -28.217 20.046 2.4 0.26 3 DEP 2010 6 25 20 41 -28.831 23.598 2.0 0.29 3 2010 6 29 2 7 -28.38 20.014 2.8 0.32 3 2010 7 1 4 3 -28.686 26.77 2.1 0.44 3 2010 7 2 14 32 -29.108 28.444 1.9 0.30 3 2010 7 2 21 9 -28.55 20.437 2.1 0.28 3 2010 7 4 1 14 -28.618 20.346 1.8 0.31 3 DEP 2010 7 13 12 21 -28.715 20.43 2.4 0.30 3 2010 7 15 10 32 -29.823 18.72 2.1 0.61 3 2010 7 19 15 3 -28.877 25.819 2.0 0.92 3 2010 7 24 12 4 -33.342 22.022 2.2 0.25 3 2010 7 26 14 24 -28.79 20.406 3.5 0.40 3 2010 7 26 14 27 -28.632 20.328 3.2 0.33 3 DEP 2010 7 26 19 43 -28.745 20.452 2.1 0.22 3 DEP 2010 8 4 5 12 -28.991 20.63 2.3 0.31 3 2010 8 5 9 3 -28.572 20.365 2.9 0.28 3 DEP 2010 8 8 19 59 -28.409 20.315 2.3 0.30 3 2010 8 10 3 14 -33.382 19.29 2.0 0.20 3 2010 8 20 11 1 -29.737 17.321 1.8 0.33 3 2010 8 20 16 31 -29.541 21.339 1.9 0.21 3 2010 8 20 16 40 -28.354 20.261 1.9 0.22 3 2010 8 23 23 38 -29.981 18.783 2.1 0.42 3 2010 8 25 5 11 -28.771 20.17 2.1 0.23 3 2010 8 25 12 14 -29.616 23.036 2.4 0.47 3 2010 8 25 14 11 -31.699 18.518 1.7 0.20 3 2010 8 25 14 15 -30.327 20.671 1.9 0.30 3 2010 8 25 14 26 -30.739 30.137 2.3 0.28 3 2010 8 26 22 25 -28.379 20.355 2.0 0.29 3 2010 8 30 1 37 -33.173 19.516 1.9 0.32 3 2010 9 2 20 15 -28.378 20.309 1.9 0.23 3 2010 9 9 20 21 -28.787 20.445 2.0 0.33 3 2010 9 10 4 49 -32.233 20.256 2.0 0.36 3 2010 9 17 12 20 -28.003 30.333 2.1 0.30 3 2010 9 17 15 55 -29.142 18.412 2.1 0.31 3 2010 9 18 11 2 -30.403 25.274 2.1 0.20 3 2010 9 18 14 3 -28.159 29.317 1.9 0.23 3 2010 9 25 5 44 -28.334 20.381 1.8 0.32 3 2010 9 27 3 28 -33.342 22.197 2.1 0.69 3 2010 9 29 1 18 -33.312 19.405 1.7 0.25 3 2010 10 2 17 12 -33.067 18.006 1.9 0.31 3 2010 10 4 19 34 -28.634 20.317 1.9 0.26 3 DEP 2010 10 5 18 54 -28.991 20.462 1.9 0.31 3 2010 10 7 0 52 -28.558 20.425 2.9 0.31 3 2010 10 7 1 52 -28.814 20.448 2.2 0.23 3 DEP 2010 10 8 13 16 -28.78 20.577 2.2 0.21 3 2010 10 14 10 48 -28.012 30.248 2.2 0.35 3


A24

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2010 10 15 16 32 -30.499 21.073 2.4 0.20 9 2010 10 15 16 32 -30.563 21.042 2.3 0.25 3 DEP 2010 10 31 2 26 -30.876 23.617 2.0 0.26 3 2010 11 1 15 19 -30.608 21.095 2.9 0.41 3 2010 11 1 15 25 -28.961 27.43 1.9 0.34 3 2010 11 3 17 45 -30.349 27.669 2.4 0.20 9 2010 11 12 17 46 -29.211 25.079 2.0 0.26 3 2010 11 13 11 17 -28.272 29.267 2.3 0.33 3 2010 11 14 12 58 -28.802 20.5 1.9 0.22 3 DEP 2010 11 14 16 55 -28.368 20.401 2.0 0.67 3 2010 11 14 18 49 -29.178 29.422 2.1 0.35 3 2010 11 14 21 26 -30.289 27.726 2.1 0.20 9 2010 11 15 7 22 -29.176 19.149 2.5 0.23 3 2010 11 15 14 12 -28.821 20.43 1.7 0.23 3 DEP 2010 11 15 22 48 -32.469 17.914 1.7 0.45 3 2010 11 17 11 53 -30.11 28.152 2.4 0.36 3 2010 11 17 14 9 -28.797 20.448 2.8 0.31 3 DEP 2010 11 17 15 20 -28.573 20.327 2.2 0.33 3 DEP 2010 11 18 2 50 -28.84 20.491 3.1 0.28 3 2010 11 21 2 28 -28.567 20.367 3.8 0.37 3 2010 11 23 1 37 -28.547 20.316 1.8 0.28 3 DEP 2010 12 4 16 25 -28.99 29.11 2.1 0.48 3 2010 12 5 5 2 -30.774 25.959 2.0 0.20 9 2010 12 5 20 49 -28.379 20.287 2.3 0.27 3 DEP 2010 12 9 8 51 -28.619 20.332 2.6 0.24 3 DEP 2010 12 16 4 0 -28.728 20.425 3.6 0.34 3 DEP 2010 12 19 3 44 -31.168 19.114 1.7 0.24 3 2010 12 23 23 52 -29.753 18.727 1.8 0.36 3 2010 12 25 9 57 -28.69 20.454 1.9 0.24 3 DEP 2010 12 25 16 29 -28.693 20.452 1.7 0.26 3 DEP 2010 12 25 16 58 -28.691 20.408 2.3 0.24 3 DEP 2010 12 25 17 59 -28.728 20.416 2.0 0.21 3 DEP 2010 12 25 18 29 -28.733 20.476 3.0 0.29 3 DEP 2010 12 25 19 43 -28.771 20.459 2.0 0.22 3 DEP 2010 12 25 21 6 -28.68 20.34 2.3 0.25 3 DEP 2010 12 25 23 28 -28.732 20.442 3.5 0.34 3 DEP 2010 12 26 12 19 -28.741 20.418 2.1 0.24 3 DEP 2010 12 26 19 10 -28.715 20.417 1.9 0.22 3 DEP 2010 12 27 17 17 -28.747 20.388 2.2 0.23 3 DEP 2010 12 27 22 50 -28.782 20.443 1.9 0.23 3 DEP 2010 12 28 0 38 -28.743 20.452 3.4 0.33 3 DEP 2010 12 28 19 9 -28.652 20.457 2.4 0.29 3 DEP 2010 12 29 9 33 -28.762 20.46 2.2 0.25 3 DEP 2010 12 30 11 20 -28.651 20.376 2.1 0.23 3 DEP 2010 12 30 11 45 -28.827 20.468 2.2 0.28 3 DEP 2011 1 1 9 15 -28.647 20.382 2.8 0.25 3 DEP 2011 1 1 9 58 -28.675 20.355 1.7 0.23 3 DEP 2011 1 2 12 52 -28.699 20.477 2.9 0.27 3 DEP 2011 1 4 2 10 -30.115 21.624 1.9 0.21 3 2011 1 4 11 41 -28.789 20.498 3.5 0.41 3 DEP 2011 1 4 13 6 -28.709 20.457 2.3 0.27 3 DEP 2011 1 6 6 22 -28.787 20.54 2.3 0.37 3 DEP 2011 1 6 15 5 -28.649 20.368 2.1 0.26 3 DEP 2011 1 6 15 38 -28.788 20.487 2.4 0.36 3 DEP 2011 1 7 12 56 -28.634 20.362 4.0 0.47 3 DEP 2011 1 7 15 58 -30.608 20.47 2.1 0.22 3 2011 1 7 21 0 -28.771 20.439 2.9 0.29 3 DEP 2011 1 8 0 8 -28.487 20.321 1.8 0.33 3 DEP


A25

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 1 8 2 59 -28.69 20.359 1.9 0.22 3 DEP 2011 1 8 19 57 -28.703 20.496 2.5 0.27 3 DEP 2011 1 8 20 33 -28.633 20.369 2.1 0.28 3 DEP 2011 1 9 3 40 -28.584 20.356 2.3 0.29 3 DEP 2011 1 9 12 35 -28.636 20.457 2.1 0.25 3 DEP 2011 1 10 4 55 -28.718 20.459 2.2 0.28 3 DEP 2011 1 10 6 48 -28.533 20.355 2.3 0.22 3 DEP 2011 1 10 7 15 -28.546 20.373 2.4 0.26 3 DEP 2011 1 11 4 29 -28.418 20.323 1.9 0.31 3 2011 1 11 5 14 -28.608 20.379 2.0 0.29 3 DEP 2011 1 11 5 31 -28.779 20.424 2.8 0.34 3 DEP 2011 1 11 9 47 -28.754 20.522 2.0 0.28 3 DEP 2011 1 11 19 8 -28.566 20.328 2.0 0.24 3 DEP 2011 1 11 20 43 -28.659 20.391 2.1 0.21 3 DEP 2011 1 12 0 9 -28.654 20.429 2.9 0.30 3 DEP 2011 1 12 6 14 -28.69 20.348 4.2 0.47 3 DEP 2011 1 13 0 32 -28.705 20.376 2.0 0.26 3 DEP 2011 1 13 14 19 -28.513 20.332 2.3 0.33 3 DEP 2011 1 13 14 26 -28.783 20.497 2.0 0.24 3 DEP 2011 1 13 17 36 -28.749 20.445 4.1 0.36 3 DEP 2011 1 14 19 54 -28.7 20.488 2.2 0.30 3 DEP 2011 1 14 20 56 -28.701 20.436 2.6 0.32 3 DEP 2011 1 15 2 6 -28.795 20.539 1.8 0.27 3 DEP 2011 1 15 6 47 -28.832 20.44 2.1 0.26 3 DEP 2011 1 15 8 55 -28.5 20.316 2.3 0.27 3 DEP 2011 1 15 9 12 -28.607 20.309 2.5 0.37 3 DEP 2011 1 15 13 14 -28.758 20.514 2.0 0.28 3 DEP 2011 1 15 19 27 -28.796 20.514 2.1 0.28 3 DEP 2011 1 16 0 44 -28.729 20.481 1.9 0.51 3 DEP 2011 1 16 20 2 -28.885 20.187 2.5 0.25 3 DEP 2011 1 16 0 45 -28.456 20.364 1.8 0.24 3 DEP 2011 1 16 1 41 -28.791 20.497 1.9 0.29 3 DEP 2011 1 16 2 7 -28.753 20.493 2.8 0.30 3 DEP 2011 1 16 7 50 -28.792 20.49 2.4 0.58 3 DEP 2011 1 16 16 58 -28.701 20.448 2.1 0.31 3 DEP 2011 1 17 0 3 -28.86 20.596 2.2 0.24 3 DEP 2011 1 17 6 36 -28.805 20.533 2.2 0.28 3 DEP 2011 1 17 8 51 -28.753 20.476 2.1 0.31 3 DEP 2011 1 17 15 12 -28.825 20.501 2.1 0.31 3 DEP 2011 1 17 19 54 -28.816 20.388 2.3 0.30 3 DEP 2011 1 18 2 58 -28.779 20.332 2.4 0.25 3 DEP 2011 1 18 3 2 -28.719 20.458 2.1 0.31 3 DEP 2011 1 18 16 26 -28.598 20.417 2.1 0.41 3 DEP 2011 1 18 17 33 -28.753 20.483 2.5 0.29 3 DEP 2011 1 19 3 40 -28.668 20.452 2.2 0.30 3 DEP 2011 1 19 3 49 -28.932 20.594 3.7 0.52 3 2011 1 19 12 4 -28.781 20.474 2.1 0.35 3 DEP 2011 1 19 21 38 -28.754 20.465 2.3 0.28 3 DEP 2011 1 20 18 3 -28.795 20.538 2.3 0.26 3 DEP 2011 1 20 19 17 -28.461 20.148 2.1 0.27 3 2011 1 20 23 5 -28.625 20.491 2.2 0.41 3 DEP 2011 1 20 23 9 -28.683 20.366 2.6 0.66 3 DEP 2011 1 21 9 2 -28.645 30.547 2.8 0.37 3 2011 1 21 19 26 -28.768 20.43 1.9 0.33 3 DEP 2011 1 21 20 0 -28.579 20.467 2.0 0.58 3 DEP 2011 1 22 0 43 -28.73 20.43 2.1 0.36 3 DEP 2011 1 22 2 18 -28.6 20.353 1.9 0.24 3 DEP 2011 1 22 2 34 -28.763 20.448 2.7 0.32 3 DEP


A26

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 1 22 2 35 -28.595 20.352 3.0 0.32 3 DEP 2011 1 22 3 26 -28.709 20.495 2.0 0.26 3 DEP 2011 1 22 4 15 -28.358 20.267 1.9 0.27 3 DEP 2011 1 22 4 39 -28.562 20.304 1.9 0.26 3 DEP 2011 1 22 6 56 -28.646 20.271 2.2 0.36 3 DEP 2011 1 22 11 16 -28.645 20.366 2.1 0.25 3 DEP 2011 1 22 14 54 -28.337 20.239 2.1 0.35 3 DEP 2011 1 22 15 56 -28.551 20.438 1.9 0.40 3 DEP 2011 1 22 16 18 -28.646 20.417 2.2 0.44 3 DEP 2011 1 22 19 46 -28.505 20.382 1.9 0.53 3 DEP 2011 1 22 20 26 -28.589 20.446 1.9 0.48 3 DEP 2011 1 22 20 55 -28.423 20.26 1.9 0.24 3 DEP 2011 1 22 23 15 -28.774 20.489 2.1 0.28 3 DEP 2011 1 22 23 26 -28.484 20.287 1.8 0.40 3 DEP 2011 1 22 23 44 -28.781 20.469 1.8 0.40 3 DEP 2011 1 23 5 19 -28.722 20.425 2.1 0.29 3 DEP 2011 1 23 7 41 -28.688 20.416 2.0 0.25 3 DEP 2011 1 23 8 45 -28.619 20.38 2.3 0.25 3 DEP 2011 1 23 9 14 -29.996 19.679 2.1 0.38 3 2011 1 23 9 58 -28.373 20.334 1.9 0.53 3 2011 1 23 15 42 -28.671 20.337 2.1 0.28 3 DEP 2011 1 23 20 44 -28.647 20.389 3.3 0.32 3 DEP 2011 1 23 21 13 -28.592 20.42 2.1 0.34 3 DEP 2011 1 23 21 15 -28.595 20.427 2.1 0.27 3 DEP 2011 1 23 22 21 -28.472 20.374 1.9 0.26 3 DEP 2011 1 24 3 27 -28.483 20.34 1.7 0.40 3 DEP 2011 1 24 10 33 -28.978 20.609 2.5 0.30 3 DEP 2011 1 24 16 0 -28.655 20.481 1.8 0.31 3 DEP 2011 1 25 2 39 -28.759 20.426 4.4 0.32 3 2011 1 25 7 36 -28.617 20.349 2.3 0.27 3 DEP 2011 1 26 5 13 -28.45 20.333 1.9 0.27 3 DEP 2011 1 26 7 6 -28.688 20.507 1.9 0.27 3 DEP 2011 1 26 17 46 -28.634 20.352 2.1 0.42 3 DEP 2011 1 27 0 57 -28.601 20.377 2.0 0.25 3 DEP 2011 1 27 1 20 -28.104 20.105 1.9 0.32 3 2011 1 27 20 24 -28.686 20.499 1.8 0.26 3 DEP 2011 1 28 1 29 -28.511 20.361 3.2 0.37 3 DEP 2011 1 29 1 30 -28.749 20.485 2.2 0.38 3 DEP 2011 1 29 16 6 -28.552 20.327 2.5 0.30 3 DEP 2011 1 29 18 38 -28.666 20.409 2.3 0.39 3 DEP 2011 1 29 20 45 -28.436 20.304 1.9 0.26 3 DEP 2011 1 30 4 26 -28.672 20.391 2.5 0.27 3 DEP 2011 1 30 5 18 -28.376 20.319 2.9 0.30 3 2011 1 30 7 55 -28.618 20.341 2.4 0.28 3 DEP 2011 1 30 9 2 -28.723 20.381 1.8 0.29 3 DEP 2011 1 30 16 8 -28.684 20.408 2.1 0.29 3 DEP 2011 1 30 17 9 -28.685 20.463 2.0 0.27 3 DEP 2011 1 30 19 48 -28.161 20.156 1.7 0.28 3 2011 1 30 20 0 -28.732 20.446 1.7 0.23 3 DEP 2011 1 31 7 12 -28.748 20.491 2.4 0.41 3 DEP 2011 1 31 10 6 -30.314 18.73 2.0 0.24 3 2011 1 31 15 48 -28.595 20.32 2.2 0.28 3 DEP 2011 1 31 23 38 -28.745 20.443 1.9 0.23 3 DEP 2011 2 1 0 30 -28.818 20.444 1.6 0.24 3 DEP 2011 2 1 6 58 -28.882 20.59 2.6 0.33 3 DEP 2011 2 1 7 27 -28.722 20.427 2.2 0.28 3 DEP 2011 2 1 7 30 -28.82 20.573 2.1 0.26 3 DEP 2011 2 1 10 15 -28.822 20.439 1.8 0.24 3 DEP


A27

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 2 1 10 57 -28.658 20.367 2.1 0.30 3 DEP 2011 2 1 14 58 -28.879 20.625 2.3 0.33 3 DEP 2011 2 1 17 19 -28.671 20.477 2.6 0.32 3 DEP 2011 2 1 20 2 -28.937 20.629 1.7 0.20 3 DEP 2011 2 1 20 47 -28.77 20.514 2.1 0.24 3 DEP 2011 2 2 5 45 -30.413 26.162 1.9 0.51 3 2011 2 3 6 32 -28.563 20.42 3.1 0.47 3 DEP 2011 2 3 17 57 -28.583 20.445 2.7 0.60 3 DEP 2011 2 4 15 18 -28.618 20.417 2.6 0.46 3 DEP 2011 2 4 18 18 -28.623 20.378 1.6 0.22 3 DEP 2011 2 4 18 33 -28.666 20.491 1.8 0.24 3 DEP 2011 2 4 22 27 -28.713 20.38 1.8 0.23 3 DEP 2011 2 4 23 38 -28.703 20.389 2.4 0.31 3 DEP 2011 2 5 2 43 -28.688 20.391 1.6 0.29 3 DEP 2011 2 5 5 47 -28.878 20.577 3.0 0.41 3 DEP 2011 2 5 7 21 -28.726 20.422 1.6 0.29 3 DEP 2011 2 5 8 14 -28.69 20.378 2.2 0.32 3 DEP 2011 2 5 8 22 -28.697 20.414 3.6 0.43 3 DEP 2011 2 5 12 43 -29.105 24.912 2.2 0.25 3 2011 2 5 17 12 -28.688 20.347 1.9 0.23 3 DEP 2011 2 5 20 17 -28.709 20.399 1.6 0.31 3 DEP 2011 2 5 23 52 -28.721 20.465 1.7 0.23 3 DEP 2011 2 6 1 21 -28.751 20.451 1.7 0.20 3 DEP 2011 2 6 2 16 -28.82 20.395 2.1 0.34 3 DEP 2011 2 6 3 28 -28.689 20.368 1.5 0.23 3 DEP 2011 2 6 5 9 -28.638 20.356 2.3 0.32 3 DEP 2011 2 6 23 47 -28.782 20.438 1.8 0.37 3 DEP 2011 2 7 0 52 -28.571 20.044 1.9 0.27 3 2011 2 7 3 35 -28.679 20.373 2.0 0.27 3 DEP 2011 2 7 6 38 -28.716 20.399 2.1 0.26 3 DEP 2011 2 7 6 40 -28.503 20.411 2.0 0.28 3 DEP 2011 2 7 15 27 -28.685 20.396 2.1 0.35 3 DEP 2011 2 8 12 55 -28.718 20.39 2.5 0.28 3 DEP 2011 2 8 20 17 -28.552 20.353 2.2 0.35 3 DEP 2011 2 9 2 44 -33.128 17.697 2.3 0.27 3 2011 2 9 6 24 -28.74 20.444 2.2 0.27 3 DEP 2011 2 9 13 22 -28.79 20.54 3.4 0.39 3 DEP 2011 2 9 23 22 -28.482 20.038 1.7 0.25 3 DEP 2011 2 10 0 24 -28.792 20.517 2.1 0.27 3 DEP 2011 2 10 19 1 -28.746 20.387 2.4 0.25 3 DEP 2011 2 11 7 52 -28.773 20.493 3.4 0.37 3 DEP 2011 2 11 7 58 -28.757 20.444 3.1 0.37 3 DEP 2011 2 11 11 28 -28.708 20.456 1.7 0.21 3 DEP 2011 2 11 11 28 -29.194 20.877 1.7 0.32 3 2011 2 11 11 57 -28.649 20.462 2.0 0.25 3 DEP 2011 2 11 11 58 -29.068 20.781 1.8 0.21 3 DEP 2011 2 11 18 41 -28.625 20.365 1.8 0.26 3 DEP 2011 2 12 4 52 -28.741 20.408 1.7 0.33 3 DEP 2011 2 12 4 53 -28.666 20.455 1.6 0.32 3 DEP 2011 2 12 5 54 -28.703 20.315 1.6 0.34 3 DEP 2011 2 12 10 44 -28.761 20.383 1.6 0.25 3 DEP 2011 2 12 11 15 -28.685 20.379 1.8 0.29 3 DEP 2011 2 13 1 46 -28.859 20.394 1.9 0.32 3 DEP 2011 2 13 4 19 -28.758 20.41 1.6 0.39 3 DEP 2011 2 13 5 20 -32.03 19.905 2.1 0.24 3 2011 2 13 7 32 -28.656 20.368 1.8 0.56 3 DEP 2011 2 13 13 32 -28.655 20.339 2.4 0.34 3 DEP 2011 2 13 14 26 -28.756 20.422 1.9 0.38 3 DEP


A28

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 2 13 22 39 -28.715 20.382 1.6 0.30 3 DEP 2011 2 13 23 45 -30.787 21.103 2.1 0.28 3 2011 2 14 5 21 -29.218 20.953 2.1 0.34 3 2011 2 14 10 13 -28.847 20.452 2.1 0.24 3 DEP 2011 2 14 14 12 -28.714 20.366 2.0 0.24 3 DEP 2011 2 14 17 19 -28.783 20.465 2.3 0.27 3 DEP 2011 2 14 17 46 -28.707 20.38 1.7 0.26 3 DEP 2011 2 15 5 17 -28.607 20.396 2.2 0.35 3 DEP 2011 2 15 7 27 -28.688 20.397 2.3 0.27 3 DEP 2011 2 16 9 7 -28.558 20.348 2.2 0.35 3 DEP 2011 2 17 12 26 -28.717 20.402 2.3 0.25 3 DEP 2011 2 17 23 19 -28.687 20.376 2.2 0.35 3 DEP 2011 2 18 23 48 -28.855 20.568 1.8 0.22 3 DEP 2011 2 20 0 5 -28.802 20.431 1.9 0.25 3 DEP 2011 2 20 0 23 -28.771 20.429 1.8 0.31 3 DEP 2011 2 20 2 56 -28.742 20.415 2.0 0.26 3 DEP 2011 2 20 17 48 -28.688 20.366 2.5 0.35 3 DEP 2011 2 21 10 47 -28.815 20.426 2.1 0.33 3 DEP 2011 2 21 21 19 -28.799 20.495 4.0 0.51 3 DEP 2011 2 23 3 11 -28.71 20.376 1.8 0.33 3 DEP 2011 2 23 17 8 -28.719 20.382 2.3 0.31 3 DEP 2011 2 24 7 21 -29.736 27.065 2.3 0.26 3 2011 2 24 9 39 -28.709 20.387 1.9 0.28 3 DEP 2011 2 24 9 41 -29.169 20.818 1.7 0.38 3 DEP 2011 2 24 9 43 -28.69 20.385 1.7 0.29 3 DEP 2011 2 24 20 21 -28.727 20.256 1.6 0.26 3 DEP 2011 2 24 20 23 -28.774 20.389 2.0 0.32 3 DEP 2011 2 25 0 36 -28.644 20.462 1.7 0.30 3 DEP 2011 2 25 6 30 -29.157 20.775 1.9 0.34 3 2011 2 25 9 46 -28.693 20.333 1.8 0.38 3 DEP 2011 2 25 11 32 -28.738 20.363 1.7 0.33 3 DEP 2011 2 25 12 40 -32.863 22.135 2.7 0.25 3 2011 2 25 18 15 -29.606 19.87 1.7 0.21 3 2011 2 25 20 22 -28.713 20.396 1.6 0.42 3 DEP 2011 2 26 15 2 -28.742 20.397 1.7 0.30 3 DEP 2011 2 26 17 35 -29.245 20.763 1.6 0.41 3 DEP 2011 2 27 0 32 -28.808 20.333 1.6 0.36 3 DEP 2011 2 27 1 26 -28.776 20.417 1.5 0.38 3 DEP 2011 2 27 20 16 -28.685 20.402 1.7 0.35 3 DEP 2011 2 27 21 3 -28.646 20.365 1.5 0.32 3 DEP 2011 3 1 3 23 -28.91 20.542 3.1 0.28 3 DEP 2011 3 1 6 17 -28.637 20.372 1.6 0.36 3 DEP 2011 3 1 6 36 -28.659 20.254 1.7 0.30 3 DEP 2011 3 1 8 38 -28.716 20.408 1.7 0.27 3 DEP 2011 3 1 12 3 -28.688 20.382 1.7 0.33 3 DEP 2011 3 1 12 11 -28.733 20.419 1.6 0.34 3 DEP 2011 3 1 13 59 -29.638 20.07 1.9 0.27 3 2011 3 1 16 9 -28.59 20.376 2.0 0.34 3 DEP 2011 3 1 18 58 -28.773 20.464 1.6 0.33 3 DEP 2011 3 1 21 51 -28.741 20.43 1.6 0.69 3 DEP 2011 3 1 22 34 -29.122 20.678 1.7 0.33 3 2011 3 2 4 39 -28.566 20.402 2.1 0.26 3 DEP 2011 3 2 4 40 -28.577 20.524 2.0 0.47 3 DEP 2011 3 2 5 45 -28.467 20.278 1.9 0.30 3 DEP 2011 3 2 8 26 -28.801 20.528 2.1 0.28 3 DEP 2011 3 3 7 30 -28.77 20.44 2.1 0.37 3 DEP 2011 3 4 0 20 -28.652 20.378 1.6 0.34 3 DEP 2011 3 4 0 48 -28.681 20.388 1.6 0.24 3 DEP


A29

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 3 5 2 15 -28.662 20.373 1.8 0.30 3 DEP 2011 3 5 2 29 -28.81 20.451 1.6 0.25 3 DEP 2011 3 5 3 12 -28.563 20.317 1.7 0.42 3 DEP 2011 3 5 7 40 -28.464 20.348 2.0 0.42 3 DEP 2011 3 5 12 47 -28.656 20.423 1.8 0.36 3 DEP 2011 3 5 21 51 -28.668 20.399 1.9 0.35 3 DEP 2011 3 6 8 44 -28.676 20.436 1.8 0.36 3 DEP 2011 3 6 8 57 -28.649 20.591 1.8 0.48 3 DEP 2011 3 6 10 51 -28.699 20.508 2.7 0.26 3 DEP 2011 3 6 11 27 -30.086 28.818 2.0 0.37 3 2011 3 6 12 15 -29.351 20.896 1.8 0.32 3 2011 3 6 15 12 -28.667 20.542 1.9 0.61 3 DEP 2011 3 6 15 46 -28.601 20.419 1.9 0.45 3 DEP 2011 3 6 20 55 -28.653 20.389 1.5 0.28 3 DEP 2011 3 6 21 2 -28.705 20.466 1.5 0.32 3 DEP 2011 3 6 23 53 -28.771 20.512 2.2 0.30 3 DEP 2011 3 7 0 56 -28.607 20.415 1.7 0.58 3 DEP 2011 3 7 1 58 -28.569 20.4 1.6 0.40 3 DEP 2011 3 7 2 9 -29.758 21.915 1.9 0.25 3 2011 3 8 0 26 -28.588 20.352 1.8 0.37 3 DEP 2011 3 8 0 36 -28.593 20.359 1.7 0.40 3 DEP 2011 3 8 1 51 -28.687 20.43 1.6 0.31 3 DEP 2011 3 8 7 43 -28.631 20.479 2.3 0.49 3 DEP 2011 3 8 15 10 -28.63 20.401 2.1 0.34 3 DEP 2011 3 8 16 51 -28.541 20.244 2.1 0.36 3 DEP 2011 3 9 2 36 -28.91 20.654 1.5 0.39 3 DEP 2011 3 9 2 46 -29.029 20.699 1.7 0.31 3 2011 3 9 8 52 -28.635 20.432 3.3 0.47 3 DEP 2011 3 9 9 3 -28.565 20.413 2.0 0.36 3 DEP 2011 3 9 12 42 -28.764 20.464 1.9 0.21 3 DEP 2011 3 9 20 9 -30.955 30.241 2.1 0.21 3 2011 3 10 22 52 -28.582 20.475 1.8 0.65 3 DEP 2011 3 10 22 59 -28.691 20.381 1.6 0.49 3 DEP 2011 3 11 2 46 -28.645 20.468 1.9 0.60 3 DEP 2011 3 11 17 57 -30.479 24.555 2.0 0.26 3 2011 3 11 23 33 -28.748 20.407 1.7 0.37 3 DEP 2011 3 11 23 58 -28.758 20.509 3.6 0.43 3 DEP 2011 3 13 4 56 -29.644 19.741 1.7 0.39 3 2011 3 14 8 18 -28.789 20.45 1.7 0.61 3 DEP 2011 3 14 10 51 -28.651 20.461 1.8 0.46 3 DEP 2011 3 15 13 24 -29.237 20.867 1.9 0.30 3 2011 3 15 16 35 -28.726 20.523 2.1 0.33 3 DEP 2011 3 15 17 31 -28.656 20.406 1.7 0.31 3 DEP 2011 3 15 17 48 -28.545 20.448 1.8 0.49 3 DEP 2011 3 15 20 37 -29.233 20.908 1.6 0.45 3 DEP 2011 3 16 15 3 -29.161 28.745 1.8 0.22 3 2011 3 16 18 3 -28.525 20.368 2.2 0.34 3 DEP 2011 3 16 18 12 -28.558 20.413 2.0 0.33 3 DEP 2011 3 16 18 34 -28.448 20.329 2.0 0.27 3 2011 3 16 18 42 -28.528 20.293 2.0 0.27 3 DEP 2011 3 16 23 54 -28.524 20.297 1.8 0.20 3 DEP 2011 3 17 4 43 -28.55 20.352 1.9 0.26 3 DEP 2011 3 17 6 46 -28.648 20.418 1.7 0.58 3 DEP 2011 3 17 16 3 -29.111 20.736 1.7 0.35 3 2011 3 17 21 44 -28.783 20.462 2.2 0.29 3 DEP 2011 3 17 21 57 -28.88 20.568 1.6 0.37 3 DEP 2011 3 17 22 4 -28.559 20.405 2.0 0.38 3 DEP 2011 3 17 22 46 -28.491 20.309 1.8 0.36 3 DEP


A30

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 3 18 0 29 -28.691 20.406 2.2 0.36 3 DEP 2011 3 18 4 21 -28.678 20.465 1.9 0.26 3 DEP 2011 3 18 4 32 -29.266 21.067 1.7 0.33 3 2011 3 18 7 17 -29.679 24.542 2.1 0.21 3 2011 3 18 13 40 -28.619 20.472 1.7 0.31 3 DEP 2011 3 18 20 42 -32.069 24.745 2.7 0.30 3 2011 3 18 21 12 -28.626 20.32 1.9 0.31 3 DEP 2011 3 19 2 58 -28.589 20.267 2.1 0.23 3 DEP 2011 3 19 16 2 -28.548 20.423 1.8 0.29 3 DEP 2011 3 19 20 17 -28.478 20.333 2.4 0.31 3 DEP 2011 3 19 23 25 -28.601 20.378 1.7 0.32 3 DEP 2011 3 19 23 26 -28.658 20.538 1.9 0.42 3 DEP 2011 3 20 2 9 -28.628 20.398 1.6 0.30 3 DEP 2011 3 20 6 43 -28.524 20.518 1.9 0.30 3 DEP 2011 3 20 6 55 -28.548 20.377 1.7 0.32 3 DEP 2011 3 20 15 25 -28.699 20.424 1.6 0.35 3 DEP 2011 3 20 21 25 -30.619 19.029 1.8 0.36 3 2011 3 21 13 4 -28.66 20.393 2.0 0.37 3 DEP 2011 3 21 20 53 -29.901 27.352 2.3 0.32 3 2011 3 22 2 57 -28.661 20.443 2.0 0.36 3 DEP 2011 3 22 2 59 -28.688 20.456 2.8 0.29 3 DEP 2011 3 22 2 59 -28.987 20.889 2.7 0.34 3 2011 3 22 3 26 -28.557 20.43 1.7 0.74 3 DEP 2011 3 22 19 4 -28.73 20.449 1.5 0.44 3 DEP 2011 3 23 4 10 -28.642 20.484 1.8 0.23 3 DEP 2011 3 23 20 33 -31.587 28.704 2.2 0.31 3 2011 3 24 2 45 -28.789 20.205 1.8 0.33 3 DEP 2011 3 25 2 17 -28.456 20.385 1.8 0.63 3 DEP 2011 3 25 21 6 -28.476 20.318 2.0 0.53 3 DEP 2011 3 25 23 21 -29.262 21.182 1.6 0.52 3 2011 3 26 1 51 -28.712 20.455 1.7 0.27 3 DEP 2011 3 26 18 23 -29.307 20.749 1.6 0.48 3 2011 3 27 6 55 -28.653 20.459 1.7 0.38 3 DEP 2011 3 27 22 30 -28.703 20.5 2.0 0.26 3 DEP 2011 3 28 6 44 -28.92 20.658 1.7 0.32 3 DEP 2011 3 29 0 6 -28.579 20.418 1.7 0.48 3 DEP 2011 3 29 6 40 -28.472 20.291 1.8 0.40 3 DEP 2011 3 29 10 47 -28.543 20.402 1.8 0.36 3 DEP 2011 3 29 11 54 -28.55 20.476 1.7 0.36 3 DEP 2011 3 29 12 52 -28.674 20.517 1.9 0.25 3 DEP 2011 3 29 17 46 -28.561 20.455 1.7 0.38 3 DEP 2011 3 29 18 36 -28.573 20.458 1.7 0.36 3 DEP 2011 3 29 21 43 -28.643 20.411 1.7 0.35 3 DEP 2011 3 31 2 23 -28.564 20.436 1.6 0.58 3 DEP 2011 3 31 5 24 -28.716 20.444 2.0 0.27 3 DEP 2011 3 31 5 32 -28.706 20.386 1.6 0.33 3 DEP 2011 3 31 20 16 -28.531 20.432 1.8 0.56 3 DEP 2011 3 31 20 36 -28.728 20.424 1.9 0.31 3 DEP 2011 4 2 3 5 -28.795 20.475 2.0 0.32 3 DEP 2011 4 3 2 28 -28.632 20.354 1.6 0.45 3 DEP 2011 4 3 3 33 -29.823 19.722 1.8 0.24 3 2011 4 3 19 45 -28.762 20.374 2.4 0.30 3 DEP 2011 4 3 20 4 -28.634 20.427 1.7 0.29 3 DEP 2011 4 5 2 36 -28.698 20.374 2.0 0.32 3 DEP 2011 4 5 22 12 -28.411 20.288 2.2 0.26 3 2011 4 6 10 1 -29.063 28.953 1.8 0.46 3 2011 4 6 18 22 -28.828 20.495 2.0 0.25 3 DEP 2011 4 6 23 34 -28.747 20.46 4.1 0.43 3


A31

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 4 6 23 56 -28.745 20.403 2.0 0.20 3 DEP 2011 4 7 0 17 -28.647 20.444 2.2 0.20 3 DEP 2011 4 7 8 42 -28.715 20.405 2.3 0.35 3 DEP 2011 4 7 9 34 -28.749 20.394 1.9 0.20 3 DEP 2011 4 7 18 43 -28.558 20.423 1.7 0.31 3 DEP 2011 4 9 11 38 -28.724 20.416 1.9 0.34 3 DEP 2011 4 9 18 40 -28.664 20.439 1.5 0.44 3 DEP 2011 4 10 10 36 -28.749 20.41 1.6 0.32 3 DEP 2011 4 12 11 35 -30.23 24.036 2.2 0.24 3 2011 4 12 12 16 -28.711 20.425 1.8 0.32 3 DEP 2011 4 12 16 58 -28.883 20.441 1.5 0.25 3 DEP 2011 4 12 18 45 -28.724 20.435 2.0 0.25 3 DEP 2011 4 13 2 53 -29.042 20.6 1.9 0.37 3 2011 4 14 2 52 -28.789 20.41 1.6 0.33 3 DEP 2011 4 14 5 1 -28.625 20.441 2.4 0.31 3 DEP 2011 4 14 5 18 -28.655 20.441 2.0 0.31 3 DEP 2011 4 14 6 33 -28.729 20.354 1.7 0.30 3 DEP 2011 4 15 2 6 -28.498 20.335 2.0 0.28 3 DEP 2011 4 15 2 19 -28.646 20.435 1.8 0.66 3 DEP 2011 4 15 4 16 -28.679 20.465 1.8 0.20 3 DEP 2011 4 16 3 27 -29.157 20.814 1.7 0.33 3 2011 4 16 17 19 -28.652 20.443 2.4 0.33 3 DEP 2011 4 18 5 26 -28.662 20.336 1.9 0.35 3 DEP 2011 4 19 0 13 -28.717 20.389 1.6 0.41 3 DEP 2011 4 19 6 36 -28.713 20.368 1.7 0.65 3 DEP 2011 4 19 16 35 -28.777 20.159 1.7 0.27 3 2011 4 19 17 6 -28.715 20.394 1.7 0.29 3 DEP 2011 4 19 19 31 -29.952 28.044 2.2 0.34 3 2011 4 19 21 5 -29.947 28.071 2.0 0.57 3 DEP 2011 4 20 1 5 -29.209 20.887 1.5 0.33 3 2011 4 20 3 17 -28.733 20.474 1.8 0.40 3 DEP 2011 4 20 8 39 -28.635 20.461 2.5 0.37 3 DEP 2011 4 20 9 35 -28.66 20.447 1.8 0.39 3 DEP 2011 4 20 19 50 -28.688 20.417 1.8 0.29 3 DEP 2011 4 21 13 20 -28.633 20.484 2.7 0.32 3 DEP 2011 4 21 14 3 -28.154 28.899 2.1 0.33 3 2011 4 22 0 57 -30.505 26.304 2.0 0.34 3 2011 4 22 2 48 -28.634 20.446 1.7 0.32 3 DEP 2011 4 23 7 37 -29.937 19.018 1.9 0.78 3 2011 4 23 11 32 -28.84 20.333 1.7 0.27 3 DEP 2011 4 23 20 35 -28.631 20.455 2.3 0.34 3 DEP 2011 4 23 23 23 -28.609 20.437 1.6 0.22 3 DEP 2011 4 24 3 16 -28.734 20.398 1.6 0.49 3 DEP 2011 4 24 7 52 -28.649 20.425 1.8 0.33 3 DEP 2011 4 24 13 27 -28.733 20.415 1.5 0.37 3 DEP 2011 4 24 15 13 -28.756 20.41 1.9 0.31 3 DEP 2011 4 24 16 46 -28.662 20.486 1.7 0.30 3 DEP 2011 4 24 17 8 -28.689 20.386 1.6 0.37 3 DEP 2011 4 24 22 36 -29.887 28.065 2.0 0.32 3 2011 4 26 8 31 -28.69 20.43 1.7 0.30 3 DEP 2011 4 26 12 6 -28.623 20.428 2.1 0.34 3 DEP 2011 4 27 8 30 -28.662 20.515 1.8 0.20 3 DEP 2011 4 28 6 41 -30.274 30.806 2.4 0.27 3 2011 4 28 22 32 -28.749 20.418 2.1 0.29 3 DEP 2011 4 28 23 24 -28.69 20.364 1.8 0.75 3 DEP 2011 4 29 17 46 -28.679 20.448 1.6 0.42 3 DEP 2011 4 30 17 6 -28.697 20.416 1.7 0.23 3 DEP 2011 5 2 18 0 -28.768 20.456 1.7 0.44 3 DEP


A32

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 5 2 18 55 -29.272 21.098 1.7 0.50 3 2011 5 2 19 17 -28.531 20.49 1.6 0.32 3 DEP 2011 5 2 21 48 -28.648 20.43 1.7 0.58 3 DEP 2011 5 3 2 45 -28.553 20.386 1.7 0.58 3 DEP 2011 5 3 3 8 -29.334 21.021 1.6 0.48 3 DEP 2011 5 3 4 15 -28.725 20.583 1.8 0.29 3 DEP 2011 5 3 4 30 -29.23 20.885 1.5 0.32 3 2011 5 3 4 33 -28.892 20.637 1.7 0.25 3 DEP 2011 5 3 7 26 -29.297 21.159 1.7 0.41 3 DEP 2011 5 3 8 4 -28.759 20.386 1.9 0.34 3 DEP 2011 5 3 19 45 -28.447 16.077 2.1 0.21 3 2011 5 3 20 2 -28.248 16.251 2.3 0.24 3 2011 5 4 9 59 -28.461 20.386 3.2 0.61 3 2011 5 4 12 42 -28.79 20.365 2.2 0.45 3 DEP 2011 5 4 12 44 -28.243 16.474 3.1 0.31 3 2011 5 4 14 29 -28.736 20.407 1.8 0.21 3 DEP 2011 5 4 17 16 -28.283 30.803 1.8 0.27 3 2011 5 5 10 6 -28.452 20.354 2.6 0.53 3 DEP 2011 5 5 10 11 -28.809 20.359 3.6 0.36 3 DEP 2011 5 5 10 38 -28.543 19.982 2.6 0.28 3 2011 5 5 10 59 -28.748 20.469 2.2 0.31 3 DEP 2011 5 5 11 37 -28.478 20.301 1.9 0.58 3 DEP 2011 5 5 11 45 -28.737 20.405 2.6 0.53 3 DEP 2011 5 6 5 57 -28.807 20.358 1.7 0.26 3 DEP 2011 5 6 23 12 -29.173 20.879 1.6 0.40 3 DEP 2011 5 7 9 53 -28.608 20.47 3.3 0.37 3 DEP 2011 5 7 9 54 -28.755 31.534 2.2 0.25 3 2011 5 7 15 14 -28.682 20.437 1.9 0.29 3 DEP 2011 5 7 15 18 -28.569 20.452 1.6 0.23 3 DEP 2011 5 8 0 0 -29.198 20.822 1.8 0.40 3 2011 5 8 17 20 -28.732 20.401 1.9 0.29 3 DEP 2011 5 8 22 53 -28.674 20.445 1.8 0.20 3 DEP 2011 5 9 1 48 -28.706 20.467 1.7 0.20 3 DEP 2011 5 9 10 40 -28.693 20.44 1.7 0.22 3 DEP 2011 5 9 22 36 -28.959 20.655 1.8 0.31 3 2011 5 9 23 45 -28.801 20.704 1.7 0.86 3 DEP 2011 5 10 23 5 -29.702 19.721 1.8 0.74 3 2011 5 11 0 20 -28.734 20.407 2.0 0.44 3 DEP 2011 5 11 0 43 -28.534 20.437 1.9 0.55 3 DEP 2011 5 11 0 48 -28.694 20.435 2.0 0.38 3 DEP 2011 5 11 20 1 -28.588 20.435 1.9 0.53 3 DEP 2011 5 11 20 6 -28.756 20.398 1.9 0.45 3 DEP 2011 5 12 0 1 -28.693 20.428 1.7 0.65 3 DEP 2011 5 12 1 1 -28.61 20.414 1.7 0.45 3 DEP 2011 5 12 14 49 -29.136 20.762 1.7 0.36 3 2011 5 12 15 31 -28.4 20.316 1.8 0.43 3 DEP 2011 5 12 20 13 -28.693 20.547 1.6 0.25 3 DEP 2011 5 13 9 31 -29.569 21.254 1.6 0.23 3 2011 5 13 15 31 -28.651 20.49 1.7 0.21 3 DEP 2011 5 13 15 40 -28.636 20.435 2.2 0.38 3 DEP 2011 5 14 2 7 -28.603 20.369 1.5 0.28 3 DEP 2011 5 14 7 13 -28.866 20.504 2.0 0.31 3 DEP 2011 5 14 7 28 -28.48 20.543 1.7 0.25 3 DEP 2011 5 14 10 43 -28.169 22.783 2.1 0.39 3 2011 5 14 14 10 -32.78 22.139 4.2 0.36 3 2011 5 14 16 26 -28.756 20.493 3.7 0.41 3 DEP 2011 5 14 18 36 -28.558 20.425 1.6 0.39 3 DEP 2011 5 14 19 9 -28.463 20.347 1.7 0.41 3 DEP


A33

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 5 14 19 45 -28.559 20.359 2.0 0.39 3 DEP 2011 5 14 21 48 -28.575 20.475 1.7 0.39 3 DEP 2011 5 14 22 40 -28.349 20.482 1.8 0.44 3 DEP 2011 5 14 23 14 -28.574 20.43 1.9 0.42 3 DEP 2011 5 14 23 51 -28.662 20.575 1.8 0.69 3 DEP 2011 5 14 23 57 -28.603 20.451 1.6 0.44 3 DEP 2011 5 15 0 13 -28.638 20.549 1.6 0.20 3 DEP 2011 5 15 1 59 -28.574 20.47 1.7 0.80 3 DEP 2011 5 15 3 5 -28.554 20.458 1.8 0.38 3 DEP 2011 5 15 3 9 -29.285 20.998 1.6 0.35 3 2011 5 15 3 28 -28.598 20.406 1.6 0.44 3 DEP 2011 5 15 3 40 -28.537 20.488 1.7 0.67 3 DEP 2011 5 15 4 56 -28.586 20.447 1.9 0.62 3 DEP 2011 5 15 11 50 -28.618 20.361 1.6 0.54 3 DEP 2011 5 15 16 5 -28.467 20.335 1.7 0.32 3 DEP 2011 5 15 17 4 -28.661 20.478 1.6 0.41 3 DEP 2011 5 15 22 40 -28.491 20.358 1.7 0.63 3 DEP 2011 5 16 0 29 -28.605 20.444 1.7 0.67 3 DEP 2011 5 16 2 17 -28.581 20.928 1.7 0.42 3 2011 5 16 8 32 -29.671 19.747 2.3 0.24 3 2011 5 16 16 27 -28.897 20.264 1.8 0.21 3 DEP 2011 5 16 17 6 -28.82 20.241 1.6 0.41 3 DEP 2011 5 17 14 2 -28.286 23.332 1.9 0.20 3 2011 5 17 19 34 -28.584 20.366 1.7 0.26 3 DEP 2011 5 18 6 7 -28.02 30.35 2.2 0.35 3 2011 5 18 12 57 -29.854 20.321 1.9 0.48 3 2011 5 19 0 44 -28.705 20.512 1.9 0.21 3 DEP 2011 5 19 12 22 -28.675 20.426 2.0 0.33 3 DEP 2011 5 19 16 10 -28.636 20.466 1.6 0.49 3 DEP 2011 5 19 16 55 -28.707 20.437 1.6 0.30 3 DEP 2011 5 19 18 27 -28.665 20.555 1.7 0.33 3 DEP 2011 5 20 0 14 -28.732 20.441 1.6 0.38 3 DEP 2011 5 20 2 48 -28.695 20.548 1.8 0.36 3 DEP 2011 5 20 9 0 -29.271 20.978 1.7 0.32 3 2011 5 20 17 45 -28.893 20.214 1.9 0.42 3 2011 5 21 12 28 -29.111 28.397 1.8 0.20 3 2011 5 22 0 44 -28.466 20.174 1.8 0.46 3 2011 5 22 0 44 -28.701 20.418 1.9 0.32 3 DEP 2011 5 22 9 26 -28.739 20.405 2.0 0.37 3 DEP 2011 5 22 10 35 -28.651 20.531 2.0 0.20 3 DEP 2011 5 22 15 22 -28.562 20.432 1.7 0.32 3 DEP 2011 5 23 1 35 -28.627 20.406 2.1 0.36 3 DEP 2011 5 23 2 33 -32.722 22.201 2.5 0.29 3 DEP 2011 5 23 18 35 -28.675 20.432 2.0 0.36 3 DEP 2011 5 23 18 37 -28.445 20.41 1.7 0.29 3 DEP 2011 5 23 18 44 -28.438 20.424 1.9 0.48 3 DEP 2011 5 23 18 45 -29.423 21.353 1.8 0.30 3 2011 5 23 19 27 -28.722 20.429 1.5 0.54 3 DEP 2011 5 23 21 57 -28.532 20.415 1.8 0.51 3 DEP 2011 5 24 7 5 -29.629 26.775 2.2 0.51 3 2011 5 24 19 9 -28.596 20.433 1.8 0.47 3 DEP 2011 5 25 15 53 -28.671 20.447 1.6 0.41 3 DEP 2011 5 25 19 21 -28.518 20.346 1.7 0.50 3 DEP 2011 5 25 19 22 -28.67 20.549 1.8 0.31 3 DEP 2011 5 25 19 32 -28.675 20.432 1.8 0.21 3 DEP 2011 5 25 23 1 -28.628 20.541 1.8 0.23 3 DEP 2011 5 26 2 3 -29.234 20.974 1.6 0.49 3 2011 5 26 2 16 -28.65 20.4 1.9 0.80 3 DEP


A34

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 5 27 3 50 -28.414 20.365 1.9 0.53 3 2011 5 27 4 2 -28.812 20.341 2.5 0.35 3 2011 5 27 4 25 -28.718 20.395 2.7 0.36 3 2011 5 27 5 5 -28.575 20.445 2.0 0.39 3 DEP 2011 5 27 16 29 -28.627 20.485 1.9 0.30 3 DEP 2011 5 27 18 31 -28.581 20.447 1.8 0.53 3 DEP 2011 5 27 20 19 -28.695 20.405 2.1 0.34 3 DEP 2011 5 28 3 4 -28.599 20.423 1.8 0.56 3 DEP 2011 5 28 9 20 -28.806 20.463 1.7 0.61 3 DEP 2011 5 29 4 24 -28.637 20.436 1.6 0.43 3 DEP 2011 5 29 4 29 -28.763 20.343 2.0 0.36 3 DEP 2011 5 29 8 3 -28.497 20.426 1.8 0.52 3 DEP 2011 5 29 8 5 -28.748 20.409 2.3 0.32 3 DEP 2011 5 29 8 5 -28.626 20.44 2.3 0.42 3 DEP 2011 5 29 8 20 -29.085 20.78 1.8 0.48 3 2011 5 29 9 46 -28.893 20.84 1.7 0.76 3 2011 6 1 10 32 -28.722 20.427 2.0 0.35 3 DEP 2011 6 1 10 47 -28.756 20.405 1.9 0.26 3 DEP 2011 6 1 12 44 -28.716 20.419 1.9 0.26 3 DEP 2011 6 1 14 53 -28.551 20.435 2.0 0.37 3 DEP 2011 6 1 16 8 -28.491 20.421 1.8 0.20 3 DEP 2011 6 4 3 35 -28.725 20.489 1.7 0.23 3 2011 6 4 8 18 -28.623 20.435 2.1 0.31 3 DEP 2011 6 5 23 33 -32.969 22.063 2.3 0.24 3 DEP 2011 6 6 6 57 -28.899 20.269 1.7 0.47 3 DEP 2011 6 7 4 33 -30.309 28.205 2.2 0.33 3 2011 6 7 7 25 -28.625 20.433 2.4 0.41 3 DEP 2011 6 7 19 38 -28.949 20.25 2.0 0.42 3 2011 6 8 21 44 -28.786 20.149 1.7 0.27 3 2011 6 10 13 46 -28.6 20.476 2.2 0.29 3 DEP 2011 6 10 14 11 -28.676 20.445 1.8 0.43 3 DEP 2011 6 10 23 12 -28.626 20.452 2.2 0.31 3 DEP 2011 6 11 0 7 -28.716 20.442 2.0 0.27 3 DEP 2011 6 12 2 6 -28.726 20.462 2.8 0.42 3 2011 6 12 4 24 -28.777 20.381 1.8 0.24 3 DEP 2011 6 12 8 28 -28.696 20.471 2.5 0.28 3 DEP 2011 6 12 8 50 -28.682 20.496 2.3 0.24 3 DEP 2011 6 13 10 9 -28.665 20.455 2.7 0.36 3 DEP 2011 6 14 0 48 -28.715 20.379 1.8 0.30 3 DEP 2011 6 14 7 54 -28.742 20.413 2.0 0.32 3 DEP 2011 6 14 17 52 -28.698 20.493 1.9 0.28 3 DEP 2011 6 14 21 24 -28.771 20.395 1.8 0.35 3 DEP 2011 6 15 1 41 -28.664 20.378 1.9 0.29 3 DEP 2011 6 16 9 43 -29.154 20.796 1.8 0.37 3 2011 6 18 6 29 -28.732 20.437 1.9 0.65 3 DEP 2011 6 19 6 35 -28.653 20.411 1.8 0.56 3 DEP 2011 6 19 8 32 -29.081 28.688 2.0 0.27 3 2011 6 20 5 30 -32.77 22.274 2.3 0.40 3 DEP 2011 6 20 10 12 -28.501 20.348 1.8 0.36 3 DEP 2011 6 20 20 49 -28.619 20.295 1.8 0.60 3 DEP 2011 6 22 1 42 -28.758 20.392 2.2 0.34 3 DEP 2011 6 22 16 19 -28.687 20.418 2.2 0.36 3 2011 6 22 16 42 -28.693 20.419 1.8 0.32 3 DEP 2011 6 22 19 12 -28.751 20.407 1.9 0.32 3 DEP 2011 6 22 19 33 -28.715 20.244 1.7 0.24 3 DEP 2011 6 22 19 55 -28.742 20.411 1.6 0.39 3 DEP 2011 6 22 21 2 -28.57 20.437 3.1 0.45 3 DEP 2011 6 22 21 10 -28.618 20.456 3.4 0.38 3


A35

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 6 22 21 30 -28.548 20.426 1.7 0.39 3 DEP 2011 6 22 21 38 -28.693 20.409 2.2 0.40 3 DEP 2011 6 22 21 45 -28.725 20.4 2.0 0.30 3 DEP 2011 6 23 4 35 -28.702 20.394 1.8 0.34 3 DEP 2011 6 23 4 40 -28.748 20.39 2.2 0.33 3 DEP 2011 6 23 7 30 -28.531 20.362 1.7 0.40 3 DEP 2011 6 23 8 16 -28.717 20.425 2.0 0.34 3 DEP 2011 6 23 14 57 -29.221 28.579 1.7 0.33 3 2011 6 24 0 28 -28.583 20.357 1.8 0.66 3 DEP 2011 6 24 2 50 -28.755 20.375 2.0 0.70 3 DEP 2011 6 25 13 38 -30.167 17.9 3.3 0.39 3 2011 6 25 21 45 -28.426 20.494 1.7 0.38 3 DEP 2011 6 25 22 18 -28.563 20.365 1.8 0.42 3 DEP 2011 6 25 23 1 -28.696 20.381 1.8 0.40 3 DEP 2011 6 25 23 36 -28.423 20.307 1.9 0.47 3 DEP 2011 6 25 23 46 -28.604 20.374 1.8 0.48 3 DEP 2011 6 26 1 42 -28.841 20.311 1.8 0.37 3 DEP 2011 6 26 6 57 -28.75 20.408 1.9 0.36 3 DEP 2011 6 29 15 53 -29.096 28.807 2.0 0.24 3 2011 6 30 7 24 -28.033 29.953 2.2 0.37 3 2011 6 30 22 0 -31.067 18.119 2.3 0.21 3 2011 7 1 7 8 -31.374 20.128 2.0 0.26 3 2011 7 1 7 51 -28.556 20.456 1.8 0.46 3 DEP 2011 7 1 9 6 -28.786 20.532 1.7 0.34 3 DEP 2011 7 2 0 24 -28.665 20.453 1.8 0.44 3 DEP 2011 7 2 5 13 -28.287 20.226 1.9 0.30 3 2011 7 2 6 14 -28.721 20.383 2.0 0.29 3 DEP 2011 7 2 6 16 -28.591 20.482 1.8 0.30 3 DEP 2011 7 2 6 58 -28.609 20.622 1.9 0.23 3 DEP 2011 7 2 7 47 -28.566 20.463 1.9 0.34 3 DEP 2011 7 2 11 35 -28.67 20.444 2.3 0.58 3 DEP 2011 7 2 11 42 -28.597 20.447 1.9 0.59 3 DEP 2011 7 3 20 3 -29.22 20.996 1.8 0.71 3 2011 7 4 14 36 -28.7 20.464 1.8 0.25 3 DEP 2011 7 5 1 7 -29.243 20.9 1.6 0.37 3 DEP 2011 7 6 0 30 -30.132 29.442 2.1 0.26 3 DEP 2011 7 6 4 48 -28.483 20.284 1.9 0.35 3 DEP 2011 7 6 9 39 -30.285 29.365 2.2 0.24 3 2011 7 6 11 2 -28.038 30.165 2.2 0.27 3 2011 7 10 19 30 -28.593 20.41 2.3 0.43 3 DEP 2011 7 10 19 38 -28.416 20.352 1.9 0.26 3 DEP 2011 7 13 10 0 -32.363 27.338 2.1 0.77 3 2011 7 15 18 13 -28.828 19.413 1.8 0.69 3 2011 7 16 8 27 -28.893 20.197 2.7 0.24 3 2011 7 16 8 47 -28.916 20.29 2.0 0.23 3 DEP 2011 7 16 9 31 -28.956 20.25 1.6 0.23 3 DEP 2011 7 17 23 40 -28.518 20.425 1.6 0.58 3 DEP 2011 7 18 5 31 -28.821 20.221 1.9 0.55 3 DEP 2011 7 18 15 23 -28.643 22.409 2.1 0.57 3 2011 7 19 0 53 -28.801 20.26 1.8 0.53 3 DEP 2011 7 19 19 51 -28.52 20.453 1.7 0.37 3 DEP 2011 7 20 0 40 -28.727 20.524 2.0 0.20 3 2011 7 20 1 5 -28.748 20.379 1.8 1.15 3 DEP 2011 7 20 1 9 -28.636 20.46 2.0 0.75 3 2011 7 20 1 29 -28.587 20.561 1.9 0.70 3 DEP 2011 7 20 18 38 -28.449 17.028 1.8 0.41 3 2011 7 21 1 3 -29.237 19.179 1.7 0.62 3 2011 7 21 6 30 -28.742 20.44 1.6 0.67 3 DEP


A36

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 7 21 6 38 -28.762 20.408 1.6 0.62 3 DEP 2011 7 21 16 20 -33.533 17.34 2.3 0.62 3 2011 7 24 15 37 -28.7 20.456 2.1 0.64 3 2011 7 25 22 1 -30.692 18.151 1.9 0.38 3 2011 7 26 21 30 -28.707 20.471 1.9 0.36 3 DEP 2011 7 27 1 58 -28.723 20.533 1.8 0.63 3 DEP 2011 7 28 19 50 -29.195 20.862 1.5 0.65 3 2011 7 28 19 58 -28.601 20.31 1.9 0.76 3 2011 7 30 14 52 -28.999 28.908 1.8 0.24 3 2011 7 31 19 8 -29.807 20.572 2.1 0.64 3 2011 7 31 20 48 -31.246 24.678 2.2 0.92 3 2011 8 1 20 12 -28.833 21.33 2.0 0.46 3 2011 8 1 23 39 -28.858 20.12 1.8 0.67 3 DEP 2011 8 2 10 18 -28.88 29.039 1.9 0.33 3 2011 8 3 19 33 -28.838 20.188 1.9 0.61 3 2011 8 4 9 58 -29.485 28.045 1.9 0.27 3 2011 8 5 2 27 -28.664 20.343 1.8 0.72 3 2011 8 7 20 22 -30.078 21.051 2.2 0.56 3 2011 8 8 3 57 -28.29 20.489 1.9 0.75 3 2011 8 9 9 58 -28.957 28.964 2.0 0.25 3 2011 8 9 10 10 -28.228 25.142 2.1 0.93 3 2011 8 9 10 57 -31.1 22.973 2.4 0.58 3 2011 8 10 12 19 -30.012 21.378 2.2 0.56 3 2011 8 10 12 20 -28.297 29.085 2.1 0.27 3 2011 8 10 17 11 -28.736 20.389 1.9 0.26 3 DEP 2011 8 10 17 14 -28.739 20.356 1.9 0.30 3 DEP 2011 8 10 18 36 -28.643 20.409 1.8 0.82 3 DEP 2011 8 10 18 38 -28.755 20.373 1.8 0.77 3 DEP 2011 8 12 1 0 -30.18 18.918 1.9 0.92 3 2011 8 12 13 45 -28.197 28.371 2.6 0.72 3 2011 8 13 13 58 -29.028 28.871 1.8 0.24 3 2011 8 13 14 38 -29.916 21.273 2.0 0.50 3 DEP 2011 8 13 18 5 -29.032 21.151 2.2 0.50 3 2011 8 13 18 23 -29.084 20.684 1.7 0.88 3 2011 8 13 18 26 -28.648 20.346 1.6 0.85 3 DEP 2011 8 13 18 51 -30.913 18.268 2.7 0.69 3 2011 8 13 18 52 -28.619 20.469 2.2 0.66 3 DEP 2011 8 13 18 53 -29.802 19.219 2.1 0.71 3 2011 8 13 19 33 -28.446 20.36 2.9 0.65 3 2011 8 13 19 42 -28.585 20.354 2.0 0.81 3 DEP 2011 8 13 19 46 -28.671 20.603 2.0 0.64 3 DEP 2011 8 13 19 47 -28.637 20.485 2.1 0.81 3 DEP 2011 8 13 19 47 -28.707 20.94 2.0 1.34 3 2011 8 13 19 48 -29.909 18.717 2.2 1.07 3 2011 8 13 19 53 -28.614 20.575 2.0 0.33 3 DEP 2011 8 13 20 17 -28.566 20.609 1.9 0.54 3 DEP 2011 8 13 20 20 -28.699 20.549 2.1 0.68 3 2011 8 13 21 13 -28.701 20.436 2.3 0.65 3 2011 8 13 23 3 -28.682 20.388 2.1 0.72 3 DEP 2011 8 14 12 23 -28.741 20.416 2.0 0.65 3 DEP 2011 8 14 12 47 -28.724 20.409 2.0 0.68 3 DEP 2011 8 17 4 31 -28.805 20.427 2.1 0.76 3 DEP 2011 8 17 22 53 -30.184 27.633 2.0 0.50 3 2011 8 20 19 3 -28.796 20.536 1.9 1.09 3 DEP 2011 8 22 16 39 -28.759 20.558 2.2 0.68 3 DEP 2011 8 22 18 40 -28.713 20.42 2.2 0.65 3 DEP 2011 8 22 21 29 -30.237 28.268 1.8 0.40 3 2011 8 24 3 17 -28.681 20.545 2.0 0.32 3 DEP


A37

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 8 25 15 2 -29.673 29.31 2.0 0.21 3 2011 8 25 15 23 -30.971 20.472 2.1 0.65 3 2011 8 26 1 4 -28.697 20.411 2.1 0.61 3 DEP 2011 8 26 2 26 -28.62 20.43 2.1 0.59 3 2011 8 26 18 56 -28.606 20.271 1.8 0.78 3 2011 8 27 1 0 -28.751 20.565 2.8 0.44 3 2011 8 27 4 20 -28.617 20.454 2.0 0.61 3 DEP 2011 8 27 4 17 -28.691 20.41 2.2 0.77 3 DEP 2011 8 27 17 8 -28.595 20.431 2.1 0.66 3 DEP 2011 8 27 17 42 -28.654 20.426 2.0 0.56 3 DEP 2011 8 27 18 25 -28.683 20.44 2.1 0.56 3 DEP 2011 8 27 22 6 -28.608 20.447 2.2 0.22 3 DEP 2011 8 29 12 6 -30.129 23.567 2.2 0.23 3 2011 8 29 17 14 -28.612 20.46 1.8 0.68 3 DEP 2011 8 29 21 27 -28.66 20.468 2.0 0.69 3 DEP 2011 9 1 3 47 -28.957 26.786 2.0 0.49 3 2011 9 2 23 43 -30.113 17.262 2.2 0.62 3 2011 9 3 8 19 -29.798 26.57 1.9 0.31 3 2011 9 3 20 1 -28.896 30.591 1.8 0.39 3 2011 9 4 3 1 -32.079 20.819 2.2 0.61 3 2011 9 4 12 13 -30.25 27.998 2.2 0.32 3 2011 9 5 18 44 -29.232 20.9 1.8 1.03 3 2011 9 5 21 37 -28.667 20.471 1.9 0.71 3 DEP 2011 9 5 21 48 -28.616 20.429 1.7 0.69 3 DEP 2011 9 5 22 1 -31.912 20.98 2.2 0.68 3 2011 9 5 22 5 -28.601 20.166 1.8 0.21 3 DEP 2011 9 5 22 37 -28.502 20.375 1.9 0.52 3 2011 9 5 22 55 -28.617 20.471 2.3 0.34 3 2011 9 5 23 3 -28.586 20.217 1.9 0.37 3 2011 9 5 23 21 -28.614 20.492 2.0 0.71 3 DEP 2011 9 5 23 23 -28.698 20.422 2.3 0.58 3 DEP 2011 9 5 23 30 -28.636 20.442 2.0 0.56 3 DEP 2011 9 5 23 41 -28.602 20.434 1.9 0.55 3 DEP 2011 9 6 1 34 -28.658 20.452 1.9 0.56 3 DEP 2011 9 6 1 46 -28.697 20.437 2.2 0.54 3 DEP 2011 9 6 14 40 -28.444 20.376 1.9 0.33 3 DEP 2011 9 6 22 11 -28.71 20.433 2.1 0.56 3 DEP 2011 9 7 0 2 -28.793 20.149 1.9 0.78 3 2011 9 9 4 28 -28.663 20.454 1.9 0.20 3 DEP 2011 9 9 4 37 -28.645 20.478 1.9 0.20 3 DEP 2011 9 10 9 59 -28.905 28.69 1.7 0.24 3 2011 9 11 22 43 -28.729 20.358 2.0 0.78 3 2011 9 11 23 25 -28.562 20.465 2.2 0.79 3 2011 9 12 2 0 -28.503 20.409 2.0 0.46 3 DEP 2011 9 12 2 0 -28.805 20.379 1.8 0.32 3 DEP 2011 9 12 2 3 -28.652 20.462 2.0 0.75 3 DEP 2011 9 12 6 30 -28.752 20.424 1.7 0.31 3 DEP 2011 9 12 6 38 -28.568 20.448 2.0 0.26 3 DEP 2011 9 14 21 19 -28.779 20.533 1.7 0.50 3 DEP 2011 9 16 0 18 -28.728 20.419 2.0 0.71 3 2011 9 16 15 10 -28.59 20.45 1.9 0.79 3 DEP 2011 9 16 18 36 -28.572 20.537 1.9 0.65 3 2011 9 17 1 23 -30.114 19.156 2.0 0.69 3 2011 9 18 10 56 -28.619 20.461 1.7 0.20 3 DEP 2011 9 19 23 6 -28.649 20.416 2.0 0.54 3 2011 9 20 6 37 -30.501 27.399 1.8 0.25 3 2011 9 22 19 26 -28.794 17.825 2.4 0.67 3 2011 9 24 1 39 -28.695 20.445 2.3 0.55 3


A38

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 9 25 17 44 -28.635 20.459 1.7 0.84 3 DEP 2011 9 26 16 38 -28.64 20.457 2.1 0.69 3 DEP 2011 9 26 19 32 -30.387 28.367 2.0 0.49 3 2011 9 26 23 56 -28.634 20.463 2.0 0.69 3 DEP 2011 9 29 12 18 -28.815 20.357 1.5 0.47 3 DEP 2011 9 29 18 12 -28.761 20.372 1.8 0.81 3 DEP 2011 9 29 21 22 -29.626 27.355 1.8 0.50 3 2011 9 30 6 58 -28.692 20.465 2.0 0.21 3 DEP 2011 10 1 10 11 -28.64 20.464 2.2 0.46 3 2011 10 1 12 40 -28.662 20.46 1.7 0.20 3 DEP 2011 10 1 20 16 -28.783 20.392 1.9 0.57 3 DEP 2011 10 1 23 52 -28.687 20.394 1.9 0.56 3 DEP 2011 10 2 1 48 -28.836 20.618 1.9 0.42 3 2011 10 2 3 27 -28.684 20.438 1.8 0.69 3 DEP 2011 10 2 8 26 -29.011 28.783 1.9 0.22 3 2011 10 2 18 28 -28.69 20.384 1.9 0.61 3 DEP 2011 10 4 10 6 -29.134 28.794 1.6 0.23 3 DEP 2011 10 4 20 9 -30.971 21.032 1.8 0.25 3 DEP 2011 10 6 2 15 -28.72 20.427 1.8 0.48 3 2011 10 6 9 44 -28.796 20.585 1.7 0.32 3 2011 10 6 9 55 -28.772 20.417 1.6 0.20 3 DEP 2011 10 6 11 8 -29.745 23.63 2.0 0.34 3 2011 10 6 21 23 -30.983 21.04 2.0 0.25 3 2011 10 7 7 23 -29.092 26.157 2.4 0.27 3 2011 10 8 22 0 -28.674 20.232 1.9 0.58 3 2011 10 8 22 7 -28.747 20.43 1.9 0.52 3 DEP 2011 10 8 22 47 -28.878 20.45 2.1 0.49 3 2011 10 9 4 9 -28.615 20.447 1.9 0.48 3 DEP 2011 10 9 5 55 -28.623 20.682 2.0 0.83 3 2011 10 9 6 41 -28.719 20.438 1.9 0.54 3 DEP 2011 10 9 6 42 -28.669 20.435 2.0 0.54 3 DEP 2011 10 9 7 14 -28.71 20.4 1.9 0.54 3 DEP 2011 10 9 7 52 -31.034 21.149 2.0 0.59 3 DEP 2011 10 9 9 40 -34.297 15.529 2.3 0.50 3 2011 10 9 10 9 -29.059 28.791 1.9 0.28 3 2011 10 10 12 18 -31.236 19.106 2.0 0.62 3 2011 10 10 14 11 -29.143 28.656 1.7 0.24 3 2011 10 11 0 13 -33.503 19.478 1.9 0.77 3 2011 10 13 13 30 -29.072 29.057 1.8 0.31 3 2011 10 13 15 32 -29.609 20.363 1.9 0.60 3 2011 10 14 13 1 -29.725 23.944 2.1 0.60 3 2011 10 16 2 42 -32.435 19.946 1.4 0.28 3 2011 10 17 0 19 -28.689 20.459 1.8 0.57 3 DEP 2011 10 17 1 11 -30.508 25.136 1.9 0.46 3 2011 10 17 1 55 -28.736 20.46 2.0 0.49 3 DEP 2011 10 17 9 18 -28.78 20.383 2.1 0.69 3 DEP 2011 10 17 12 14 -28.74 20.402 2.0 0.76 3 DEP 2011 10 17 15 43 -28.741 20.355 2.0 0.63 3 DEP 2011 10 17 16 6 -28.762 20.34 1.9 0.44 3 DEP 2011 10 17 16 16 -28.768 20.374 2.0 0.69 3 DEP 2011 10 17 16 32 -28.714 20.431 2.0 0.93 3 DEP 2011 10 17 16 29 -28.574 20.512 1.8 0.47 3 DEP 2011 10 17 16 30 -28.564 20.441 1.8 0.56 3 DEP 2011 10 17 17 3 -28.773 20.347 1.8 0.41 3 DEP 2011 10 17 17 41 -28.744 20.364 1.9 0.78 3 DEP 2011 10 17 18 8 -30.898 20.191 2.3 0.54 3 2011 10 17 18 19 -30.973 20.203 2.0 0.52 3 DEP 2011 10 17 19 21 -29.905 19.231 1.9 0.58 3


A39

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 10 17 20 10 -28.43 20.029 1.8 0.85 3 2011 10 17 21 55 -28.795 20.412 2.2 0.64 3 DEP 2011 10 17 23 41 -28.652 20.417 2.4 0.63 3 2011 10 18 7 13 -28.698 20.401 2.2 0.42 3 DEP 2011 10 18 18 33 -28.946 16.93 2.0 0.33 3 2011 10 18 21 54 -28.752 17.654 2.4 0.70 3 2011 10 20 15 18 -29.481 22.767 2.0 0.25 3 2011 10 21 0 41 -28.606 20.407 1.8 0.56 3 DEP 2011 10 21 12 32 -29.001 21.684 2.3 0.42 3 2011 10 22 2 5 -28.694 20.541 1.8 0.62 3 DEP 2011 10 22 9 25 -28.304 28.352 2.0 0.38 3 2011 10 22 4 16 -28.76 20.466 1.5 0.29 3 DEP 2011 10 22 23 37 -28.259 27.837 2.0 0.57 3 2011 10 23 2 39 -28.564 20.463 2.1 0.82 3 DEP 2011 10 23 2 38 -28.642 20.472 2.1 0.80 3 DEP 2011 10 23 2 30 -28.611 20.416 2.1 0.55 3 DEP 2011 10 23 16 31 -30.307 27.556 2.1 0.50 3 2011 10 24 0 49 -30.775 26.12 2.3 0.36 3 2011 10 26 12 24 -29.039 28.084 1.7 0.32 3 2011 10 27 8 10 -30.619 26.821 2.1 0.49 3 2011 10 27 20 32 -28.671 20.417 1.8 0.99 3 2011 10 28 5 34 -28.425 27.237 1.8 0.28 3 2011 10 30 23 29 -29.143 27.766 1.9 0.41 3 2011 11 3 5 29 -29.586 24.852 1.9 0.55 3 2011 11 4 14 10 -28.723 25.106 2.0 0.34 3 2011 11 5 13 44 -28.621 20.414 2.0 0.30 3 2011 11 6 2 36 -30.585 27.815 1.7 0.30 3 2011 11 6 10 24 -29.074 28.904 1.8 0.24 3 2011 11 6 15 53 -30.027 28.331 1.7 0.40 3 2011 11 6 21 52 -29.334 20.485 1.9 0.59 3 2011 11 7 21 12 -28.689 20.429 1.9 1.01 3 DEP 2011 11 7 21 26 -28.618 20.407 1.9 0.67 3 DEP 2011 11 8 4 44 -28.638 20.418 1.9 0.52 3 DEP 2011 11 9 3 56 -28.969 25.692 1.9 0.93 3 2011 11 9 8 46 -28.678 20.422 1.7 0.33 3 2011 11 9 12 27 -30.611 28.98 2.2 0.23 3 2011 11 10 15 39 -30.884 23.793 2.0 0.57 3 2011 11 12 21 39 -28.712 20.427 1.7 0.21 3 DEP 2011 11 12 23 8 -28.552 20.227 2.4 0.50 3 2011 11 13 1 33 -28.676 20.416 2.7 0.42 3 2011 11 13 16 29 -29.836 28.575 1.6 0.52 3 2011 11 14 12 38 -29.835 26.526 1.8 0.36 3 2011 11 16 11 34 -30.173 29.031 2.5 0.28 3 2011 11 16 16 5 -28.714 28.772 1.8 0.51 3 2011 11 17 11 39 -28.527 20.206 1.9 0.28 3 DEP 2011 11 17 20 3 -30.244 29.621 2.0 0.22 3 2011 11 17 22 4 -28.377 20.428 1.6 0.35 3 2011 11 20 0 15 -28.72 20.445 1.6 0.38 3 DEP 2011 11 21 23 11 -28.662 20.432 1.8 0.23 3 DEP 2011 11 21 23 17 -28.573 20.452 1.9 1.13 3 DEP 2011 11 21 23 35 -28.656 20.446 2.2 0.54 3 2011 11 22 0 52 -28.679 20.392 1.9 0.36 3 DEP 2011 11 22 6 21 -29.235 23.481 2.0 0.43 3 2011 11 23 14 17 -29.145 28.69 1.8 0.35 3 2011 11 29 1 42 -28.824 20.17 2.0 0.61 3 2011 11 29 5 41 -29.034 20.408 2.9 0.53 3 2011 12 2 17 5 -30.019 20.446 2.2 0.33 3 2011 12 6 18 31 -28.873 20.213 2.0 0.20 3


A40

YY MM DD Hr Mn Sc LatN LonE Mw MwU MwC Decl. 2011 12 7 18 52 -30.038 28.22 2.0 0.25 3 2011 12 7 21 24 -29.508 21.081 1.9 0.33 3 2011 12 8 19 28 -32.793 17.802 2.8 0.54 3 2011 12 9 2 50 -28.562 20.383 1.7 0.50 3 2011 12 12 14 27 -28.566 22.85 1.9 0.37 3 2011 12 15 3 25 -28.214 20.014 1.8 0.22 3 2011 12 15 5 45 -29.769 21.902 2.2 0.48 3 2011 12 15 16 33 -30.353 29.074 2.3 0.24 3 2011 12 18 13 28 -29.383 20.637 2.5 0.51 3 2011 12 18 14 23 -28.585 20.272 2.7 0.24 3 2011 12 18 18 7 -28.474 20.489 4.3 0.16 0 2011 12 19 2 37 -28.665 20.463 2.4 0.55 3 DEP 2011 12 19 4 45 -28.564 20.285 2.2 0.34 3 DEP 2011 12 19 5 43 -28.681 20.101 2.0 0.29 3 2011 12 19 20 35 -30.035 27.525 1.7 0.27 3 2011 12 20 7 4 -28.532 20.438 2.1 0.38 3 DEP 2011 12 20 18 6 -28.559 20.396 2.3 0.34 3 DEP 2011 12 21 21 45 -31.327 21.607 2.2 0.32 3 2011 12 22 4 42 -28.712 20.412 1.9 0.36 3 DEP 2011 12 22 13 24 -28.511 20.419 2.1 0.30 3 DEP 2011 12 23 7 51 -29.683 18.475 3.0 0.52 3 2011 12 23 8 7 -29.563 18.457 2.6 0.49 3 DEP 2011 12 26 19 49 -28.459 20.368 1.9 0.30 3 DEP 2011 12 27 2 39 -28.738 17.443 2.3 0.25 3 2011 12 27 2 43 -28.757 20.389 2.0 0.20 3 DEP 2011 12 27 3 56 -29.171 20.998 2.5 0.68 3 2011 12 27 4 12 -28.748 20.354 2.4 0.36 3 DEP 2011 12 28 16 18 -30.168 28.183 2.2 0.44 3 2011 12 28 23 36 -28.522 20.444 1.9 0.24 3 DEP 2011 12 29 3 2 -28.511 20.413 2.0 0.35 3 DEP 2011 12 29 3 1 -28.656 20.426 2.0 0.39 3 DEP 2011 12 29 4 5 -28.515 20.367 2.2 0.42 3 DEP 2011 12 29 10 49 -28.406 20.349 2.0 0.30 3 DEP 2011 12 29 12 1 -28.575 20.385 2.3 0.52 3 DEP 2011 12 30 15 0 -29.174 28.882 2.1 0.22 3 2011 12 30 17 38 -28.549 20.401 2.3 0.43 3 DEP 2011 12 31 14 57 -28.621 20.44 1.9 0.34 3 DEP

TECHNICAL REPORT REVIEW ANNOTATION FORM

Rev. 0 REFERENCE: CGS/TP10/FM02

as contained in CGS report 2010-0171

ISSUE DATE: 20 December 2010


B1

Appendix B: Review Annotation Form

2. Project #:

3. Report ID:

CGS

Report

number or

filename:

Report Number 2012-0166 Rev.: 0

4. Author(s) Name(s) F.O. Strasser and A.

Mangongolo Organisation/Unit NGG (CGS)

The referenced document is submitted for your review. Please return the completed form to the Project Administrator [email protected]

Organization/Department: Designated Reviewer: Reviewer Signature/Date:

(Upon completion of review)

Céline Beauval

Comment Comments and Recommendations: Resolution:

# Type*

1. Epicentral locations, historical and early

instrumental data

Three 3rd generation methods have been

tested for deriving magnitude and location

estimates from intensity data points

(IDPs). This ensures that uncertainties are

taken into account properly.

- The report is a synthesis of the

work done, however examples of the

results obtained for the historical events

(using IDPs provided by P. Albini) for the

three 3rd generation methods could be

displayed. There is only one example

shown (Fig. 3.4), and the bootstrap results

reflecting the uncertainty on the

determination are not included in the

Additional examples of the 3rd generation

methods, including bootstrap results, are now

included in Section 3.5.2.1.

mailto:[email protected]






B2

figure (§ 3.5.2.1). The report could include

a few examples.

- Tables 3.1 and 3.2: would it be

possible to include a column for the

uncertainty on the location (radius of the

84th percentile of the spatial density

function, p. 34-35)?

The suggested column for location uncertainty

has now been added to Tables 3.1 and 3.2.

2. Homogenization of magnitude:

Among others, the efforts performed to

improve the homogeneity of the local

magnitude must be underlined, which

implied going back to the database and

the phase data.

- §5.2.2. : Would it be possible to

add a graphic of newly calibrated ML

versus previous ML, in order to have an

idea of the corrections applied (like Fig.

5.3 by Brandt, 1997)?

- Would it be possible to say, in the

unified earthquake catalog, before the

homogenization in MW, how many events

are described by each magnitude type

(original ML, corrected ML, MW, mb, MS,

mBUL ..)?

- The two paragraphs p. 55 need

some clarifications:

o “in the present dataset, there is a

clear discrepancy between the MW values

A figure showing the newly calibrated ML scale

versus the previously used ML scale has now

been added to Section 5.2.2 with some

accompanying text. Note that the recalibration

includes the combined effects of two factors: (i)

adoption of an attenuation relation calibrated to

South Africa instead of the previously used

southern California relations, and (ii)

homogeneous calculation procedures (notably

in terms of cut-off distance and treatment of

outliers).

A breakdown of the data by original magnitude

scale available has been added to this section

as Figure 5.1. Note that events with magnitude

determinations other than ML generally have

multiple magnitude values other than Mw

available.

The first sentence quoted for p.55 attempts to

make the point that the moment-tensor data

(deemed to provide a more reliable estimate of

Mw because of the approach used), although






B3

obtained from spectral fitting of weak-

motion data, and those obtained from

moment tensor inversion, for ML values

around 4.0” => there is only 1 event with

MW 4.0 (Koffiefontein) and 3-4 events

with ML 3.8-4.0 obtained from spectral

fitting?

o If you ignore the data with ML >

2.5 based on doubtful reliability, how do

you justify trusting in the data with ML

<2.5? Please explain.

sparse at the lower magnitudes, shows no

indication of a deviation from 1:1 scaling. The

spectral fitting data, however, shows a clear

deviation from this scaling relation, hence the

observation about the discrepancy. The reason

this is linked to shortcomings in the spectral

fitting approach has to do with the scaling of the

stress parameter. The Mw value calculated

using the seismic moment Mo obtained from

spectral fitting relies heavily on the model

selected for the stress parameter (Δσ) and, to a

lesser extent, other parameters of the model.

The determination of these parameters is driven

by the bulk of the data, which in this case is

contributed by small-magnitude, weak-motion

data. There is now plentiful evidence that the

(apparent) scaling of Δσ is not the same for

weak-motion data and for strong-motion data

(see for example the discussion in the Rietbrock

et al. (2013) UK stochastic GMPE paper or in

the Stafford & Bommer (2012) TNSP white

paper on Δσ]). This also explains why the data

with ML<2.5 is considered reliable (the

stochastic parameters are well-constrained by

the data from this datatset and the scaling is

consistent with observations from other

datasets covering similar magnitude ranges),

whereas the reliability of the stochastic

parameters and applicability of the Δσ scaling

model degrades towards the edges of the

dataset.

Rietbrock, A., F. Strasser & B.Edwards (2013). A stochastic

ground-motion model for the UK. Bulletin of the

Seismological Society of America 103(1), in press.

Stafford, P.J. & J.J. Bommer (2012). Overvew of

approaches to derive GMPEs in low seismicity regions






B4

o Instead of a quadratic relation for

connecting the two different slopes, would

a simple linear segment be enough

(considering the data available)?

o Last sentence: “Whatever the

cause of the non-linearity, it is likely to

bias the estimation of recurrence

parameters, therefore with magnitudes

smaller than 4.0 will not be used in this

estimation” => magnitudes smaller than

4.0 will not be used in which step?

- Conversion from body-wave

magnitude mb

o There are 5 events with mb_ISC

and 4 events with mb_NEIC, which

represent an extremely restricted dataset.

When larger datasets are available (see

Scordilis 2006 or other publications), the

dispersion is large in MW versus mb plots.

(stochastic, hybrid-empirical, reference empirical). TNSP

GMC White Paper, May 2012.

The reviewer is absolutely correct in pointing

out that a linear segment is likely to be sufficient

to link the two slopes, and that the empirical

data available is so sparse that it does not

provide any constraints on the functional form to

use. The quadratic form was adopted based on

precedent (Grünthal & Wahlströhm, 2003;

Grünthal et al., 2009; ECOS-09 Swiss

catalogue), and also because it allows a

somewhat smoother transition from one branch

to another than a linear branch. However, as

noted in the following bullet point, this

discussion is mostly academic, since the lack of

data to constrain conversions for Mw<4.0

renders this magnitude range uninformative for

recurrence calculations.

As noted above, data from magnitudes lower

than 4.0 will not be included in the recurrence

calculations, since the lack of constraint on the

conversion relations renders them uninformative

in terms of seismicity rate calculations (i.e. the

data are more likely to introduce bias in the

calculation of this rate than to provide additional

information about it).

We note the reviewer’s reservations regarding

the quality of the mb-Mw data. We fully share

these reservations, as documented in the

report. The plot of available data vs. existing

mb-Mw relations is used not so much to select

the most appropriate mb-Mw relation (which is

precluded by the paucity of the data), but simply

as a check that imported relations are not in






B5

Therefore I would not use this local data

to choose the MW - mb relation. It is ok to

superimpose the data to existing relations,

but not to conclude too much on the fit to

the conversion relations.

o How many events in the catalog

have a unique magnitude estimate mb?

o Text p. 59 and Fig. 5.7: for events

with magnitudes ML between 3 and 4, for

which MW was obtained through spectral

fitting, there is no way the estimate of MW

can be improved? Using other methods

better adapted to this magnitude range?

What do the authors Rietbrock and Drouet

think about this issue?

contradiction with the very limited number of

local data available. The text has been

amended to reflect this more clearly. This

uncertainty also motivates the additional check

performed (and documented in the report in Fig

5.7 and accompanying text) comparing the ML-

Mw data for Mw values converted from mb with

other ML-Mw data.

There are no events for which mb is the only

available magnitude estimate, an alternative

estimate (either ML or MBUL) is always available.

Poorly constrained mb values (from 1 or 2

stations at regional distances) are not used if a

well-constrained local magnitude is available

instead.

Improving the estimates of Mw for events with

ML magnitudes between 3.0 and 4.0 is currently

hampered by the paucity of the data available,

which make it difficult to constrain the physical

parameters involved in the spectral fitting, in

particular the scaling of the stress parameter Δσ

in this magnitude range. Additional regional

moment tensor such as presented by Brandt &

Saunders (2011), if available, could also provide

valuable constraints in this magnitude range,

however, the derivation of such solutions is also

severely hampered by data limitations (a stable

solution requires a good azimuthal distribution

as well as a sufficient number of recordings

relatively near to the source, conditions that are

difficult to meet in South Africa given the very

sparse nature of the permanent seismograph






B6

o In Fig. 5.7, the magnitudes MW

obtained by applying the Johnston (1996)

conversion equation appear to be quite

scattered, but this is expected (again, see

Scordilis 2006 or other publications for an

evaluation of the dispersion in such plots).

network).

This observation is noted and has been

incorporated into the accompanying text. We

fully agree with the reviewer that a large

dispersion is not surprising, particularly for

relations such as Johnston (1996) and Scordilis

(2006) that are based on global data. Also, this

is a two-step conversion, which will tend to

increase the scatter.

3. Estimation of magnitudes from intensity

data

- The first § p. 63 is referring to the

Bakun and Wentworth (1997) method?

- please say how the uncertainty on

the magnitude has been evaluated in the

caption of Fig. 5.8.

- Fig. 5.8: I would advise to

distinguish the ‘MEEP’ code package from

the ‘MEEP’ method for estimating

magnitude and location, as the package

contains 3 other methods (B&W, Boxer,

Pairwise), otherwise it is confusing.

We thank the reviewer for spotting this

amibiguity. It is indeed the Bakun and

Wentworth (1997) method that is referred to

here. The text has been amended to clarify this.

The uncertainty bars for MI reflect the standard

deviation of the bootstrap solutions obtained for

each approach using the MEEP2 software,

while the Mw uncertainties are those listed in

the catalogue (or similarly determined).As

suggested, the caption of Fig 5.8 (now 5.10)

has been updated to clarify this. Note that the

uncertainties on the instrumental magnitude

have been added to this figure.

We fully agree with the reviewer that there is a

potential for confusion here. We have tried to

distinguish between the software package as a

whole and the MEEP magnitude-location

estimation method by referring to them as the

MEEP2 software package and MEEP method,

respectively. The text has been reviewed and

amended where necessary to resolve any






B7

Should the x-axis label be ‘MW’ ?

- When the B&W 1997 algorithm

does not converge, it is an indication that

the intensity data available for this

earthquake might not be sufficient for

reliably estimate location/magnitude

reliably (i.e. estimates provided by the

methods Boxer and MEEP for the same

earthquake are bearing large

uncertainties).

- §5.7.2 : please say what happens

if the isoseismal map is incomplete (e.g.

coastal event).

- P. 64 : Imax can also be higher

than the epicentral intensity, in case of

strong site effects.

remaining ambiguities.

We thank the reviewer for spotting this error.

The axis labels in this figure (now numbered

5.10) have been corrected.

We note the reviewer’s comments, and the

consequences in terms of uncertainty for the

other methods when the B&W 1997 algorithm

does not converge. This observation has now

been incorporated into the text.

We thank the reviewer for spotting this

omission. For incomplete isoseismal contours,

an equivalent area is computed from the

azimuth-averaged radius (calculated using the

best estimate epicentral location). This

approach is described in more detail in the

intensity database report (Midzi et al., 2012).

The text has been updated to incorporate this

explanation and cross-reference.

This observation is noted, and has been

incorporated into the text as an additional

caveat. In practice, however, there is no way to

separate between such a case and the case

where Imax genuinely represents epicentral

intensity. This is taken into account in the very

large value of magnitude uncertainty (1

magnitude unit) assigned to magnitude values

determined on the sole basis of Imax.

4. Magnitude uncertainties

- for Mw values obtained from Mo

The Mw estimates provided by S. Drouet were






B8

values (weak-motion inversions), can the

authors Rietbrock and Drouet provide an

estimate for the uncertainty on the Mw,

rather than using the values proposed in

Johnston (1996) ?

- Conversions from mb: this

standard deviation fixed to 0.26 is the

minimum bound of the uncertainty,

assuming that the conversion equation is

adapted to the region. Considering the

uncertainty on the choice of the equation,

which is very large, the uncertainty might

be much higher.

- Conversions from ML : how do

you fix the standard deviation 0.2 and

0.3?

- The specific implementation of

given with uncertainty estimates, those provided

by A. Rietbrock were given without. Note that

the full datasets used by these authors

extended beyond the catalogue region and

included a large proportion of mining-related

events. The (simple arithmetic) average of the

standard deviations from the full Drouet dataset

(0.22) is very close to the value of 0.2 proposed

by Johnston (1996), which reflects the

uncertainty associated with this type of method

in general.

We agree with the reviewer that the uncertainty

regarding the mb-Mw relation is very large,

particularly given the limited amount of data

available to test it. However, we find that the

argument put forward by the reviewer for an

increased uncertainty would be more relevant in

the case an mb-Mw relation calibrated to another

region (say, CEUS) had been imported. The

relations considered here are global

relationships and thus already incorporate the

region-to-region uncertainty by considering a

mixed dataset.

The standard deviation for this conversion was

fixed to 0.2 at small magnitudes based on the

dispersion of the weak-motion data (see above);

at larger magnitudes, the standard deviation is

set to a larger value (0.3) in view of the lower

level of constraint available. This value is

selected such as to encompass the available

empirical data. The text has been updated to

include these clarifications.

The reviewer correctly notes that the MEEP2






B9

the MEEP2 software to carry out the grid

search implies that less epicenter

locations are tested than in the original

B&W method. Do you think that this is

impacting the size of the uncertainty

contours (underestimating the uncertainty

on the location)?

- p. 67: “taking into account the fact

that the B&W method tends to move

events away from the IDP set and to

larger magnitudes in cases of

convergence difficulties” : the text gives

the impression that in these cases, the

other methods are providing the reliable

solutions, while the B&W method is

unable to provide a solution. Caution is

required here. The Boxer method is based

on a barycenter-type estimation of the

location/magnitude, a solution is always

proposed, even a wrong solution. B&W

cannot provide a solution if too few data is

available, the other methods can, but then

the solutions can be highly unreliable and

in any case need critical assessment.

Please try to re-word the paragraph so

software implementation slightly deviates from

the original B&W method in its implementation

(MEEP2 uses a path-based approach with a

gradually reducing grid size rather than a fixed

grid). Based on the comparisons shown for

instance in Bakun et al. (2011) as well as the

Musson & Jimenez (2008) NERIES report, as

well as the patterns exhibited by the

bootstrapped locations, we find no reason to

conclude that this modification leads to an

artificial reduction of the location uncertainty.

For well-behaved problems, the path-based

approach focuses on the “better” solutions, and

the untested locations on a regular grid would

contribute little to the location uncertainty. For

less well-behaved problems, paths in multiple

directions are created, which increases the

location uncertainty.

We take on board the reviewer’s comment,

which again is likely to be related to the

aforementioned difference in implementation

between the original and MEEP2 B&W

methods, since the latter also always provides a

result, leading to the described behaviour. The

text has been updated to reflect that this is a

specificity of the MEEP2 implementation, rather

than a general feature of the B&W approach.

We fully agree with the reviewer that a critical

assessment of all solutions is required for each

of the events, particularly in the case of very

limited datasets such as those considered here.

Therefore, as explained in the report, the

various solutions have been assessed for each

event individually, also taking into account

additional, more qualitative information about

individual IDPs as well as the overall data






B10

that these shortcomings are mentioned

and that the limits of the methods are

transparently explained.

- Magnitude uncertainties for the

earthquakes analyzed using MEEP2 :

would it be possible to include in the

report the uncertainties obtained for the

earthquakes of the historical and early

instrumental part of the catalog (e.g. in a

Table)? Are you using the bootstrap also

for estimating uncertainty on the

magnitude?

pattern (discussed with Paola Albini in Grenoble

in May 2012). As suggested, the paragraph has

been reworded to include a discussion of the

limitations of the various methods, and clarify

the approach used.

As suggested, a summary of the magnitude

uncertainties for the earthquakes analysed with

the MEEP2 software has been added to this

section, in the form of Tables 5.4 and 5.5. As

explained in the text, in view of the data

limitations described above and in the text, the

magnitude uncertainties are not directly based

on the bootstrapping results, but combine this

information with any other constraints available

on the possible magnitude of the event (i.e.

limits on earthquake size based on instrumental

recordings and/or detection/non-detection

considerations). Additionally, the magnitude

uncertainties are cross-checked across the

various events analysed to ensure that

differences in data quality are taken into

account in a meaningful and consistent manner.

5. Declustering the earthquake catalog

A wide range of methods is discussed and

this is greatly appreciated.

- “An important fact to acknowledge

is that not all of these approaches have

been developed with the aim of removing

dependent events prior to rate

calculations for SHA, therefore their

performance in terms of returning a

declustered catalog from which unbiased

estimates of recurrence parameters can

be obtained also varies” => I am not sure I

understand what the authors mean here.

You are referring to which of methods

As noted by the reviewer, there is no unique

way of identifying clusters in events in a

catalogue. The point we were trying to make

here is that the definition of the clusters is not

unique either, with some applications putting

more emphasis on the causal relations between

events, whereas others focus more on the

effects the declustering algorithm has on the

seismicity rate. These differences in objective

need to be considered when assessing the

applicability of the various approaches in the






B11

listed previously? It does not matter if the

author who derived a technique for

identifying clustered events was then

using the catalog in an SHA study or not?

There is not a unique technique for

identifying clustered events in a catalog,

this is still a research topic. Therefore the

impact of the selected declustering

method on the recurrence parameters

should always be evaluated.

- “some of the methods listed

above (e.g. Reasenberg 1985) are more

targeted at the identification of aftershocks

for the purpose of keeping them to study

the connections between events, rather

than getting rid of them as noise affecting

the estimation of the background rate.” =>

again, I don’t really see the point here.

Reasenberg (1985) proposes an algorithm

to identify clustered events, and the

performance of the algorithm should not

be judged on the basis that Reasenberg

(1985) did not use the declustered catalog

for SHA.

- “this figure clearly shows that the

background seismicity obtained using the

Reasenberg (1985) algorithm does not

follow a Poissonian distribution for either

of the standard parameters” => Based on

my experience of the Reasenberg (1985)

algorithm, I would be more careful with the

conclusions from the Van Stiphout et al.

(2012) document. Another way of

evaluating the performances of a

declustering algorithm is to analyze in

detail, for each earthquake sequence, the

events identified as clustered with respect

context of seismic hazard analysis. We agree

with the reviewer that it is not the intrinsic merits

of a given method that are in question (i.e. a

method can be very efficient in providing

insights into causal relations between

earthquakes linked in terms of physical

processes responsible for their generation), but

their relative performance in terms of providing

recurrence parameters.

Again, the point made here is that it is not only

the declustering approaches that are not

unique, but the very definition of the groups of

earthquakes described as clusters. We fully

agree with the reviewer that the fact that the

Reasenberg (1985) algorithm was not derived

for PSHA does not in itself represent a

limitation, however it raises the issue of

applicability of this approach to situations other

than the one for which it was derived.

We note with interest the reviewer’s

reservations regarding the conclusions from the

Van Stiphout et al. (2012) document, as well as

the feedback about the good performance of the

Reasenberg (1985) algorithm in both high- and

low-seismicity regions. We agree that the

analysis of individual earthquake sequences

provides valuable insights into the performance

of declustering algorithms when considering any

given catalogue. We would also like to stress

that we do not question the ability of the

Reasenberg (1985) algorithm to identify

aftershock sequences – there is no question






B12

to the entire earthquake catalog (in time

and in space). My experience in different

regions, low seismicity and high seismicity

regions, is that the Reasenberg algorithm

is rather well identifying aftershocks

sequences. The conclusions of Van

Stiphout et al. (2012) are based on an

analysis on the Californian catalog, can

they be extended to all catalogs?

- A 10% variation on the time and

space windows in the Gardner and

Knopoff (1974) algorithm corresponds to a

rather small variability, given the

that all the events identified by this algorithm as

being aftershocks are indeed aftershocks of the

mainshock. However, there appear to be events

that remain in a Reasenberg-declustered

catalogue that would be eliminated by a

window-based approach; this leads to

cumulative number of earthquake curves that

still exhibit some vertical steps (i.e. they stil

include short-term perturbations of the long-

term seismicity rate). In our assessment, this

might lead to biases estimates of this long-term

rate, and probably represents the cause for the

observed deviation from Poissonian behavior.

We concede that the Van Stiphout et al. (2012)

analysis is limited to the southern California

catalogue, however also note that this

catalogue is very similar to that used in the

original Reasenberg (1985) study, which

removes the issue of applicability/calibration of

the Reasenberg parameters. Note that similar

results to those shown in the Van Stiphout

figure have been found independently by Luen

& Stark (2012). The results shown by Tibi et al.

(2011), who consider catalogues for regions

outside California also show deviation from

Poissonian behaviour, hence we stand by our

assessment that the application of this algorithm

is likely to lead to problems in the present

application. As noted in the report, this is

compounded by practical difficulties in obtaining

stable and reliable calibration parameters for

this method.

We note this comment, which has now been

incorporated in the text.






B13

uncertainty on the length of these

windows, so it is not surprising that results

are not changing much.

- I disagree with the justifications

for selecting only algorithms relying on

spatio-temporal windows (I disagree with

the judgements on the Reasenberg

method), but I am Ok with the decision of

using only these methods. The important

point is that several windows in space and

time are tested to evaluate the impact of

these decisions on the final declustered

catalog. The width of these windows

should ideally be calibrated from

earthquake sequences in the region under

study, which is not possible given the

paucity of the data.

- As the Gardner and Knopoff

(1974) parameters are very close to the

Grunthal (1986), the same percentage of

clustered events is identified. To take into

account the uncertainty in the declustering

step, I advise to use another declustering

algorithm, relying on different hypothesis

and bearing different shortcomings, or to

use a different set of time and space

windows.

For the justifications regarding the use of the

Reasenberg algorithm, see above. Given that

we are in agreement with the reviewer on the

difficulty of applying the Reasenberg method

due to calibration issues, we have recast the

text to put more emphasis on this practical

consideration. We note the reviewer’s comment

regarding the necessity to test multiple windows

in space and time (also addressed in the next

point). As noted by the reviewer, the data

available is insufficient to provide a region-

specific calibration. This is addressed in Section

6.2.2.

Since the Gardner & Knopoff (1974) and

Grünthal (1986) parameters have been

obtained independently from each other for

different geographic regions, the fact that the

window parameters are almost identical is, in

our opinion, significant, as is the good

performance of Gardner & Knopoff (1974) when

used at a global scale. We agree with the

reviewer that ideally, another declustering

algorithm should be used as an alternative,

however find it difficult to find such an

alternative that would work with the current

dataset. Inspection of the results from the

Uhrhammer (1986) algorithm show that these

windows do not work, and it is unclear how

other spatio-temporal windows could be

selected. Also, given the overall paucity of

moderate-to-large magnitude data, it is not clear






B14

- “cluster-link models such as

Reasenberg (1985) were not considered

as it would be problematic to calibrate

such models with confidence with the

limited data available” => the problem is

the same for calibrating the windows in

time and space required in the Gardner

and Knopoff (1974) and Grunthal (1986)

methods.

- “the poor results of this type of

algorithm in terms of returning a

declustered catalog that is Poissonian” =>

Again, I would not generalized the

conclusions of Van Stiphout et al. (2012).

In conclusion: the decision of using only

methods based on spatial and time

windows is fine, but I think that two

different sets of windows should be used

in South Africa, to reflect the uncertainty

on these parameters.

Note : complementary to Figures 6.5 and

6.6, that would be even more informative

to add the corresponding plots of

distribution of earthquake epicenters in

space, highlighting the events identified as

clustered events, with respect to the rest

of the catalog.

what differences could arise that would have a

significant impact on the seismicity rate

calculations without giving “strange” declustered

catalogues.

We agree with the reviewer that no method is

free from calibration issues, however the impact

of these issues will depend on the number of

parameters to calibrate, as well as to the

sensitivity of the results to this calibration. This

explains our conclusion that calibration is more

of an issue for cluster-link method, since there

are more parameters to calibrate and the results

are more sensitive to them.

Noted. This comment has already been

responded to above.

Noted. This comment has already been

responded to above.

We thank the reviewer for this excellent

suggestion. The figures have been updated

accordingly.

6. Catalog completeness: the work done is

significant. The historical work (Albini

We thank the reviewer for this positive

feedback.






B15

2012) is integrated.

7. Please explain how the probabilities are

attributed to intensity intervals and time

periods in Table 7.4 to 7.8

As explained in the report, the probabilities of

detection are assigned from a composite

consideration of all the information available:

(i) for instrumental data, probabilities of detection of 1.0 are assigned for data in the complete part of the catalogue (determined using traditional approaches to catalogue completeness;

(ii) for historical data, probabilities of detection are set to zero for the part of the catalogue for which it is known that no information is available;

(iii) in all other cases, the probability of detection is assessed subjectively by considering the information available (location of settlements, availability/completeness of seismic histories, location of seismograph stations, network detection threshold, intensity attenuation). The listed probabilities of detection (pD) for each bin are the best estimate answers to the question: for time period X, how likely it is that an event in magnitude bin Y has been recorded in the catalogue? (In some cases, the assessment also considered the probability 1- pD of missing the event).

The following rules were applied as

additional constraints:

(i) pD needs to increase with increasing magnitude

(ii) pD needs to increase with time (except in case of known network/recording shortcomings)

Finally, a cross-check between the pD values

determined for adjacent zones was performed

in order to avoid inconsistencies across

boundaries.

8. The text is clearly detailing all the

information available for assessing the

completeness, however is it not clear how

you combine the completeness zones with

The approach used here is based on the

approach of Veneziano and Van Dyck (1985)

described in Johnston et al. (1994). In this

approach, the completeness zones are derived






B16

the seismic source zones (p. 91)? What is

true for part of the seismic source zone is

extended to the whole source zone?

independently from the source zones, and

recurrence results computed separately for the

subzones defined by the intersection of the

completeness zones with the source zones.

This approach was initially considered for the

South African catalogue, but rejected in view of

the already very limited number of earthquake

counts in each magnitude interval for the

individual source zones, which make a further

subdivision of these zones impractical.

Additionally, the probability of detection

approach inherently includes some spatial

averaging in the determination of the

probabilities of detection. Therefore, these

probabilities of detection have been determined

directly as average values applicable for the

areas delimited by the source zone boundaries.

For the ECC host zone, this leads to some

uncertainty regarding the completeness results

offshore. This uncertainty cannot be resolved

through empirical calibration due to data

paucity. Therefore, this uncertainty has been

addressed in the SSC logic-tree by including a

branch considering the effect of this uncertainty

on the ECC seismicity rate via the application of

a scaling ratio linked to the ratio of the offshore

area to the total ECC area.The corresponding

text in the report has been amended to reflect

this more clearly.

9. - Please say how the “equivalent”

period of completeness can be interpreted

and used in the rates calculations.

The equivalent periods of completeness

(derived using the probability of detection

approach) are used in the recurrence

calculations (e.g. the Weichert (1980) approach)

in combination with the total counts for each

magnitude interval (i.e. without applying the

completeness censoring that is used in the

traditional completeness interval approach) in






B17

the same way that completeness-censored

counts are used with actual completeness

intervals. Details of this approach can be found

in the CEUS SSC (2012) report. The text of the

report has been updated to explain this more

clearly.

Concur with comment resolution, review complete.

_______________________________________

Reviewer Signature Date

Comments Resolved By:

____________________________________

Report Author(s) Signature Date

*Type: E – Editorial, addresses word processing errors that do not adversely impact the validity of the

results/findings/conclusions of the report.

O – Optional, comment resolution would provide clarification, but does not impact the validity of the


M – Mandatory, comment shall be resolved; reviewer identifies impact on the validity of the


Documents

TNSP Earthquake Catalogue - Eskom · 2014-07-16 · TNSP Earthquake Catalogue. F.O. Strasser & A. Mangongolo . Council of Geoscience . Report Number 2012-0166 . Rev. 0 . Confidential