Severn Thames Transfer Study

Final report

July 2018

Rudd AC, Bell VA, Kay AL and Davies HN

Centre for Ecology & Hydrology

Wallingford, Oxon, OX10 8BB

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Executive Summary This project, entitled “Severn Thames Transfer Study”, was commissioned to provide a more location specific analysis of concurrent droughts in the Severn and Thames river catchments for past and future climates.

The study consisted of two work packages. The first investigated the likelihood of drought occurring concurrently in two catchments; the Thames to Kingston and the Severn to Deerhurst. The second provides an analysis of river flow drought characteristics at gauged locations in the Rivers Thames and Severn. Both work packages used simulated river flows from the Grid-to-Grid (G2G) hydrological model. The datasets analysed were from model runs of the G2G with observation-based inputs and climate model inputs. The climate model runs consisted of an ensemble of 100 simulations (projections) of past and future climate.

Work package 1 found that the number of ensemble members for which the largest major drought in the Thames to Kingston also affected the Severn to Deerhurst is projected to increase into the future (considering the largest major drought in the Thames in each ensemble member). For example, the number of ensemble members projecting a major drought in both catchments that affects at least 70% of the rivers in each, is projected to increase by 56% in the near-future (2022-2049), and by 135% in the far-future (2072-2099). Thus analysis of future climate projections indicate that the largest major droughts in each ensemble member are more likely to affect both catchments.

The work package 2 analysis indicates that the number of droughts of moderate severity or greater affecting both locations (Severn to Deerhurst and Thames to Kingston) is projected to increase into the future.

For droughts that affect the Thames at Kingston but not the Severn at Deerhurst, water could potentially be transferred from the Severn to supplement flows in the Thames. However, this study found that the period of time when the Thames at Kingston is affected by drought, but the Severn at Deerhurst is not, is projected to decrease into the future, especially so for summer months. Generally, in the future there are projected to be fewer occasions when the Severn would be able to supply water to a drought-affected Thames at Kingston via a transfer scheme. For winter droughts projections indicate that there is little change in the mean period of time when Kingston is in drought but Deerhurst is unaffected, thus potential water transfers in winter months would remain as viable in the future as they are for the baseline period.

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Contents 1 Introduction ......................................................................................................... 5

1.1 Hydrological model runs ................................................................................ 5

1.2 Driving data ................................................................................................... 5

1.3 Drought identification .................................................................................... 6

2 Work packages ................................................................................................... 7

2.1 WP1: Coincident major droughts ................................................................... 7

2.2 WP2: Drought duration and intensity at specific gauged locations ................ 9

3 Results .............................................................................................................. 10

3.1 WP1: Coincident major droughts ................................................................. 10

3.2 WP2: Drought duration and intensity at specific gauged locations .............. 11

3.2.1 Observation-driven G2G run (1960-2015) ............................................ 11

3.2.2 Climate ensemble-driven G2G runs ..................................................... 14

4 Conclusions ...................................................................................................... 21

References ............................................................................................................... 24

Appendix 1: Work package schematics .................................................................... 25

Appendix 2: Work plan ............................................................................................. 26

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1 Introduction This project, entitled “Severn Thames Transfer Study”, was commissioned to provide a location specific analysis of concurrent droughts in the Severn and Thames river catchments for past and future climates.

Some background information is provided in the rest of this section, with further information on methods in Section 2, and results presented and discussed in Section 3. Section 4 provides the conclusions, including considerations and limitations.

Rudd et al. (2017) and (2018) examined historic and future droughts in Great Britain using a national-scale hydrological model, Grid-to-Grid (G2G), driven by observation-based data and regional climate model (RCM) data. This study applies the methods in Rudd et al. (2018) to G2G simulations driven by large ensembles of RCM data, to quantify potential changes in concurrent droughts in the Severn and Thames catchments.

1.1 Hydrological model runs The Grid-to-Grid model is a national-scale hydrological model that provides estimates of river flows on a 1km x 1km grid across Britain (Bell et al. 2009). G2G performs well for a wide variety of catchments across Great Britain, particularly those with natural flow regimes as the model formulation does not currently account for artificial influences such as abstractions and discharges (Bell at al. 2009). It has been used to investigate the potential impact of climate change on flooding (Bell et al. 2012; Bell et al. 2016) and low flows (Kay et al. 2018), and has recently been shown to perform well during periods of low flows and for drought identification (Rudd et al. 2017). G2G requires as input gridded time series of precipitation and potential evaporation (PE) (Section 1.2).

This study uses two sets of G2G simulations from the NERC-funded project MaRIUS: Managing the Risks, Impacts and Uncertainties of droughts and water Scarcity (www.mariusdroughtproject.org);

• observation-driven (1960-2015) (Bell et al. 2018a)

• RCM ensemble-driven (Bell et al. 2018b), for three time-slices o baseline (BS; 1975-2004); o near-future (NF; 2020-2049); o far-future (FF; 2070-2099).

It also uses observed flows from the National River Flow Archive (NRFA, nrfa.ceh.ac.uk).

1.2 Driving data The observation-driven G2G simulations use:

• 1km x 1km grids of daily rainfall (CEH-GEAR: Keller et al. 2015, Tanguy et al. 2016),

• Monthly PE data on a 40km grid (MORECS: Hough and Jones 1997).

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MORECS provides observation-based monthly estimates of PE (or “potential evapotranspiration”) from well-watered short grass (Penman-Monteith; Monteith, 1965). These PE estimates are copied to each of the corresponding 1km x 1km boxes of the hydrological model grid, and both PE and rainfall are divided equally down to the 15-minute model time-step (Bell et al. 2009, 2016).

The RCM ensemble-driven G2G simulations use precipitation and PE from the MaRIUS Weather@Home2 (WAH2) RCM dataset (http://catalogue.ceda.ac.uk/uuid/0cea8d7aca57427fae92241348ae9b03). The WAH2 system uses volunteer computing time to do large numbers of runs of the HadRM3P RCM nested in the HadAM3P atmospheric global climate model (Guillod et al. 2018). Data are available for historical and future periods (listed above) and the future periods use the RCP8.5 emissions scenario (Riahi et al. 2011).

A simple bias-correction scheme was applied to precipitation (Guillod et al. 2018). PE was derived from other WAH2 meteorological variables using the Penman-Monteith scheme (Monteith, 1965). Guillod et al. (2018) provides further information on the estimation of PE using WAH2 data.

For use in the G2G hydrological model, the WAH2 precipitation and PE data are re-projected from the 0.22° (~25km) rotated lat-lon RCM grid to the UK national grid. Following re-projection, spatially distributed weights based on standard average annual rainfall patterns are used to provide a non-uniform distribution of precipitation for every 1km x 1km G2G grid-cell within each RCM box (Bell et al. 2007). Note that the WAH2 RCM assumes 360-day years (twelve 30-day months).

1.3 Drought identification Droughts are identified using the threshold level method (Yevjevich, 1967; Hisdal et al. 2004) with the standardisation method previously developed by Rudd et al. (2017) for use with G2G model output. This procedure, summarised below, is applied to time series of G2G-simulated monthly mean river flow to identify droughts, and their characteristics.

The drought identification and characterisation procedure is as follows: A drought event is assumed to start when the river flow falls below a threshold, and continues until the threshold is exceeded again. Here the threshold is the long-term mean monthly flow from the years 1975-2004 (i.e. baseline period), thus removing the seasonality in hydrological response.

The procedure is as follows:

Step 1: Remove the long-term monthly mean flow, Xmon (1975-2004) from the monthly mean time series, X.

anomaly = X - Xmon

Step 2: Where the anomaly is negative (i.e. a deficit) calculate the duration, intensity and severity of that deficit (Figure 1).

(i) drought intensity — the deficit (m3s-1); (ii) drought duration — the length of time in deficit (months); and (iii) drought severity — duration multiplied by mean drought intensity.

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Figure 1: Schematic showing drought characteristics (duration, intensity, severity).

To allow comparison of drought characteristics for different locations the time series of flow “anomalies” can be standardised (Peters et al. 2003) by dividing by the standard deviation of mean monthly flow, σmon, also from the years 1975-2004. Thus a “drought” is defined as the period of time for which the variable is below normal, i.e. a deficit.

Step 3: Repeat steps 1 and 2 for the standardised anomaly by dividing by the long-term monthly standard deviation (1975-2004)

standardised anomaly = (X - Xmon)/σmon

Step 4: Select only the deficits where the standardised severity is greater than or equal to the severity thresholds in Table 1 (severity thresholds used in Rudd et al 2017 and 2018).

(i) standardised drought severity — duration multiplied by mean standardised drought intensity (standardised deficit).

Table 1 Severity thresholds used to identify moderate- and major-threshold droughts.

2 Work packages The work packages follow that of the proposal, contained in Appendix 2.

2.1 WP1: Coincident major droughts

Sub-catchment selection

The Severn at Deerhurst (NRFA station number 54110) and the Thames at Kingston (39001) have been selected and agreed on (Figure 2).

Severity

Moderate-threshold Major-threshold

River flow 4 8

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Figure 2: Catchment outlines for the Severn at Deerhurst (54110) and the Thames at Kingston (39001), and region outlines for the Severn and Thames UKCP09 river basins1.

Drought identification

The drought identification algorithm from Rudd et al. (2017) (Section 1.3) was adapted to identify droughts in the Thames to Kingston and the Severn to Deerhurst catchments. The analysis was carried out for all 100 members of the WAH2 ensemble for three time-slices (baseline, 1977-2004; near-future, 2022-2049; far-future 2072-2099). The analyses are applied to 28-year time-slices, neglecting the first two years to allow for hydrological model spin up (Rudd et al., 2017).

For the catchment-wide analysis undertaken for WP1 drought severity is a standardised quantity to allow catchments in two regions to be compared directly. The severity thresholds (applied to the standardised severity) identified by Rudd et al. (2017) (Table 1) allow simulated droughts to be classified as major or moderate. The analysis in WP1 is for droughts of major severity or greater.

Dataset: MaRIUS-G2G-WAH2-monthly, Bell et al. (2018a).

Analyse the coincidence of droughts

Rudd et al (2018) investigated the likelihood of drought occurring concurrently in adjacent UKCP09 regions, Thames and Severn, and how this might change in the future. In this study the regions have been refined to those of two catchments, Kingston and Deerhurst (Figure 2).

1 http://ukclimateprojections.metoffice.gov.uk/23216

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First, droughts are identified using the method outlined in Section 1.3. Then the number of river pixels with severity equal to or above the major drought threshold (Table 1) in the catchment to Kingston are counted to estimate the drought extent (length of river classified as major drought). The drought event with the largest extent in the Thames to Kingston catchment is then selected for each ensemble member for that time-slice as shown in Figure A1 in Appendix 1. If for a particular ensemble member there are two events in the Thames to Kingston with the same extent, then the one with the largest extent in the Deerhurst catchment is selected. This method will thus identify the droughts that could have the greatest effect on whether there is water available for a transfer from Deerhurst to the Thames.

For example: if there are two droughts in an ensemble member that affect 90% of the river in the Kingston catchment, but the first event affects 60% of the Deerhurst catchment and the second affects 65%, then the second event is selected.

For each of the largest droughts in the Thames to Kingston the number of ensemble members that simulate a drought in the Deerhurst catchment at the same time for a given percentage coverage are considered. This provides an estimate of the probability of both catchments experiencing the largest major drought at the same time, and is repeated for each time-slice. Results are presented in Section 3.1.

2.2 WP2: Drought duration and intensity at specific gauged locations

Identify droughts for a flow record in the Thames and in the Severn

For each gauging station (Thames to Kingston 39001 and Severn to Deerhurst 54110) location, drought time series are identified (Section 1.3) using the monthly mean flow for the climate ensemble-driven and the observation-driven G2G simulations. However, a comparable analysis with observed flows could not be carried out because although the Kingston observed monthly river flows are available from January 1883 to present day, for Deerhurst (54110) only 17 years of observed flows are available (Dec 1995 – Aug 2012). There are also periods of missing data within the Deerhurst monthly record (e.g. in 2007 and 2011).

For the location-specific analysis undertaken for WP2 both the drought severity and standardised drought severity are considered (Section 1.3). The severity thresholds (applied to the standardised severity) identified by Rudd et al. (2017) (Table 1) allow simulated droughts to be classified as major or moderate. Standardising in this way enables a fair comparison between Kingston and Deerhurst sites, and removes the impact of the relative magnitude of flows in each river. The analysis in WP2 is for droughts of moderate severity or greater.

For the drought analysis, as in Rudd et al. (2017, 2018) no pooling of droughts (combining multiple droughts) has been applied. In order to cover a complete drought (i.e. into deficit and out again) the algorithm searches for positive and negative anomalies. The first 2 years of each G2G simulation are neglected due to spin up, unless the first month of the simulation is a deficit in which case the algorithm searches up to one year back in time to find the start of the drought. If the start cannot be found in these 12 months then the algorithm searches forward for the first positive anomaly and the analysis begins there.

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For example: If the anomaly (X-Xmon) is positive in Jan 1975 then the drought analysis starts from Jan 1975. If it is negative then the algorithm checks Dec 1974, Nov 1974, Oct 1974 … (up to one year) until it finds a positive value. Then the drought analysis starts from the date of the positive value. If no positive values are found in 1974 the drought analysis starts from the date of the first positive value after Jan 1975.

Similarly, if a drought does not terminate by the end of the time period (negative anomaly at the end date) then the previous positive value is identified as the end date of the analysis.

Dataset: MaRIUS-G2G-MORECS-monthly, Bell et al. (2018a).

Dataset: MaRIUS-G2G-WAH2-monthly, Bell et al. (2018b).

Calculate the duration and intensity of river flow droughts at the gauging station locations

The mean, standard deviation and maximum of drought duration and intensity (maximum deficit) were analysed for the ensemble-driven and observation-driven simulations (Sections 3.2.1 and 3.2.2).

Investigate how often flows at the Thames gauge are in drought but flows at the Severn gauge are not

By comparing the months when flows for the Thames at Kingston are in drought and flows for the Severn at Deerhurst are not, the percentage of time, time of year and duration of such events was analysed (Section 3.2.1 and 3.2.2 and Figure A2 in Appendix 1).

3 Results

3.1 WP1: Coincident major droughts

Considering the largest major drought in the Thames in each ensemble member, the number of ensemble members simulating this drought in both the Severn to Deerhurst and Thames to Kingston catchments at the same time is projected to increase into the future (Table 2). The table indicates that the number of ensemble members projecting a major drought in both catchments that affects at least 70% of the rivers in each, is projected to increase by 56% in the near-future, and by 135% in the far-future.

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Table 2 Number of ensemble members (out of 100) projecting a major drought in the Severn to Deerhurst and the Thames to Kingston catchments (considering the largest major drought for the Thames to Kingston catchment).

Time-slice Minimum % coverage of each region*

60% 70% 80% 90%

Baseline (1977-2004) 34 23 17 9

Near-Future (2022-2049) 44 36 30 12

Far-Future (2072-2099) 61 54 44 28

*Considering only river points with a catchment area ≥ 50km2

3.2 WP2: Drought duration and intensity at specific gauged locations

Results that follow are for droughts of moderate severity or greater.

3.2.1 Observation-driven G2G run (1960-2015)

Before identifying droughts from the observation-driven G2G simulation, the performance of G2G for simulating monthly mean flows for the Thames at Kingston and the Severn at Deerhurst is assessed. This is achieved by comparing the G2G river flow simulations to the observed river flow time series from the NRFA. The performance assessment uses the model efficiency criterion (NSE) of Nash and Sutcliffe (1970) and two variations of the NSE, one for assessing low flows through the use of logarithms (NSElog) and the other for assessing the mid-range of flows, with the use of the square root (NSEroot). Specifically, the efficiency scores are defined as

−

−−=

2

2

)(

)(1

tt

tt

QQ

MQNSE

( )( )

−

−−=

2

2

1

tt

tt

QQ

MQNSEroot

+−+

+−+−=

2

2

))ln()(ln(

))ln()(ln(1log

tt

tt

QQ

MQNSE ,

100

tQ=

where Qt are the observed flows (m3s-1), Mt are the modelled flows (m3s-1), ε is a small value (usually taken to be the observed mean flow divided by 100) and t is the time (month). A value of 1 indicates a perfect fit, whilst a negative value indicates that the fit is worse than the mean. For the performance assessment of the Thames at Kingston the naturalised monthly flow series is used, as the G2G essentially simulates natural flows. A monthly naturalised flow series is not available for the Severn at Deerhurst.

The performance scores for both the Thames at Kingston and the Severn at Deerhurst are very good (NSE~0.9; Table 3), indicating that the G2G model simulations at these

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locations can be used for drought analyses with some confidence. Note that the length of the observed flow record at Deerhurst is short (1995 – 2012) due to measurement issues at the site (http://nrfa.ceh.ac.uk/data/station/meanflow/54110). Missing data are excluded from the performance assessment.

Table 3: Model performance measures for the observation-driven simulation. Station number

Station name

Start date End date Number of obs

NSE NSEroot NSElog

39001 Thames at Kingston

01/01/1960 31/12/2015 672 0.93 0.92 0.91

54110 Severn at Deerhurst

01/12/1995 01/08/2012 192 0.91 0.93 0.93

Identification of droughts for the historical period

For the period 1960-2015 there were 15 droughts identified for the Thames at Kingston (Table 4) and 17 for the Severn at Deerhurst (Table 5). The tables list the start and end date of each drought, along with its duration, severity, maximum intensity (largest deficit in drought event), the date of occurrence of the maximum intensity, and the standardised severity.

Table 4: Table of moderate-threshold droughts for the Thames at Kingston (39001) from the observation-driven G2G simulation. Drought number Start End

Duration Severity

Maximum Intensity

Date of Max Int

Standardised Severity

1 01/08/1964 01/07/1965 11 496 84 01/02/1965 11

2 01/04/1972 01/12/1972 8 150 53 01/11/1972 4

3 01/01/1973 01/07/1973 6 284 86 01/01/1973 6

4 01/10/1975 01/10/1976 12 613 102 01/01/1976 17

5 01/10/1988 01/03/1989 5 296 96 01/01/1989 5

6 01/05/1989 01/12/1989 7 188 54 01/10/1989 7

7 01/03/1990 01/01/1991 10 388 81 01/12/1990 12

8 01/02/1991 01/07/1991 5 165 75 01/02/1991 4

9 01/08/1991 01/07/1992 11 494 99 01/01/1992 11

10 01/04/1995 01/09/1995 5 91 26 01/04/1995 4

11 01/01/1996 01/01/1998 24 747 111 01/01/1997 21

12 01/03/2003 01/01/2004 10 202 60 01/10/2003 7

13 01/11/2004 01/10/2006 23 779 82 01/01/2006 20

14 01/02/2011 01/05/2012 15 666 78 01/02/2012 16

15 01/02/2015 01/09/2015 7 138 39 01/04/2015 5

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Table 5: Table of moderate-threshold droughts for the Severn at Deerhurst (54110) from the observation-driven G2G simulation. Drought number Start End Duration Severity

Maximum Intensity

Date of Max Int

Standardised Severity

1 01/10/1962 01/04/1963 6 453 118 01/01/1963 6

2 01/12/1963 01/01/1965 13 759 157 01/01/1964 12

3 01/01/1973 01/05/1973 4 305 129 01/01/1973 4

4 01/03/1974 01/09/1974 6 177 69 01/04/1974 5

5 01/12/1974 01/09/1976 21 972 114 01/12/1975 20

6 01/03/1984 01/10/1984 7 196 57 01/04/1984 6

7 01/11/1988 01/03/1989 4 403 130 01/01/1989 5

8 01/05/1989 01/12/1989 7 215 70 01/10/1989 6

9 01/03/1990 01/01/1991 10 382 70 01/12/1990 9

10 01/12/1991 01/06/1992 6 401 123 01/02/1992 6

11 01/04/1995 01/05/1997 25 1111 166 01/01/1997 21

12 01/08/2003 01/01/2004 5 267 93 01/10/2003 4

13 01/11/2004 01/04/2005 5 367 97 01/12/2004 5

14 01/12/2005 01/04/2006 4 333 118 01/01/2006 4

15 01/10/2010 01/07/2011 9 459 131 01/12/2010 8

16 01/08/2011 01/05/2012 9 563 112 01/11/2011 9

17 01/12/2014 01/12/2015 12 290 75 01/10/2015 5

Calculate the duration and intensity of droughts

On average the droughts at Kingston were 2 months longer than those at Deerhurst (Table 6). The longest Deerhurst drought was 25 months (Apr 1995 – Apr 1997; Table 5) which is one month longer than the longest Kingston drought (Jan 1996 – Dec 1997; Table 4).

Table 6: Statistics of duration and maximum intensity at the Thames at Kingston (39001) and the Severn at Deerhurst (54110) for the observation-driven G2G simulation (1960-2015).

gauge mean

standard deviation

maximum

Duration 39001 11 6 24

54110 9 6 25

maximum intensity 39001 75 24 111

54110 108 32 166

Investigate how often flows at the Thames gauge are in drought but flows at the Severn gauge are not

Figure 3 shows the number of times when the flows at the Thames at Kingston were in drought, but the flows at the Severn at Deerhurst were not, for each month of the year for the period 1960-2015. The graph shows that this occurred a total of 9 times in June (over the 56-year period) but only once in December and January.

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Figure 3: Count of the number of times when the flows at the Thames at Kingston (39001) are in drought and the flows at the Severn at Deerhurst (54110) are not (1960-2015), for each month.

The mean number of consecutive months when flows for the Thames at Kingston are in drought but flows for the Severn at Deerhurst are not is 4.3, with a standard deviation of 2.7. The maximum number of consecutive months is 8.

3.2.2 Climate ensemble-driven G2G runs

The climate ensemble-driven G2G simulation cannot be directly compared to observed flows because the baseline river flow time series will not directly resemble reality (e.g. the climate ensemble-driven river flows for 1976 for ensemble member 2 will not directly resemble observed reality in 1976); only statistics over long (multi-decadal) periods should be compared. Comparison of climate ensemble-driven G2G simulations to the observation-driven G2G simulation will indicate how biases in the climate ensemble affect the results for the baseline periods; comparison to observed flow will be additionally affected by the accuracy of G2G model simulations.

Comparison of the long-term monthly mean flow (1975-2004) for the climate ensemble-driven simulation (100 ensemble members) and the observation-driven G2G simulation shows that they are comparable for both the Severn at Deerhurst and the Thames at Kingston (Figure 4). Naturalised flows are also available for this period for the Thames at Kingston, and a comparison indicates that these show a similar monthly pattern to that from simulated flows, although the simulations have a tendency to overestimate in the autumn (Figure 4).

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Figure 4: Comparison of the long-term monthly mean flow: climate ensemble-driven and observation-driven G2G simulation and naturalised flows (39001 only), 1975-2004.

Drought incidence in the baseline and projected-future periods

At both gauges the number of droughts in each time-slice is projected to increase into the future (Figure 5). For the Thames at Kingston the mean number of droughts for the baseline period is 8.9, increasing to 12.5 for the near-future and 17.1 for the far-future. Similarly, for the Severn at Deerhurst the mean number of droughts is 9.0 for the baseline period, 12.5 for the near-future, and 17.1 for the far-future.

Figure 5: Distribution of the number of droughts in each ensemble member, for each time-slice. The y-axis is the count (number of ensemble members, out of 100).

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Figure 6 shows the ensemble mean number of times each month is in drought (out of a possible maximum of 28 times). Here a drought is defined as being of moderate severity or greater. On average, month by month, there are more occasions when the Thames at Kingston experiences a drought than the Severn at Deerhurst. The number of months when the Thames at Kingston is in drought is projected to increase, as is the number of months when the Severn at Deerhurst is in drought (Figure 6); there is an increase in the likelihood of drought in each catchment. This is not surprising given that the number of droughts is projected to increase (Figure 5).

Figure 6: Ensemble mean number of times each month is in a drought; the Thames at Kingston (39001; solid lines) and the Severn at Deerhurst (54110; dot-dashed lines).

Calculate the duration and intensity of droughts

For the 100-member climate ensemble-driven simulations, the variation in drought duration and intensity is plotted as frequency distributions for each time-slice (Figure 7 and Figure 8). At both gauges the range of the mean, standard deviation and maximum of drought duration decreases slightly over time, i.e. the variability in the ensemble decreases. However, the range is much narrower for the Severn at Deerhurst than for the Thames at Kingston, for all time-slices.

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a) Thames at Kingston (39001)

b) Severn at Deerhurst (54110)

Figure 7: Ensemble distribution of the statistics (mean, maximum and standard deviation) of the duration (months) of droughts in the climate ensemble-driven G2G simulation.

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a) Thames at Kingston (39001)

b) Severn at Deerhurst (54110)

Figure 8: Ensemble distribution of the statistics (mean, standard deviation and maximum) of the maximum intensity of droughts in the climate ensemble-driven G2G simulation. Note that the x-axis scales are different for the Thames and Severn.

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Figure 8 shows that at both locations the range of the mean, standard deviation, and maximum of drought intensity narrows into the future, i.e. less variability in the ensemble. The maximum values of the maximum intensity are projected to increase into the future, i.e. more ensemble members give rise to droughts of greater intensity.

Investigate how often flows at the Thames gauge are in drought but flows at the Severn gauge are not

For droughts that affect the Thames at Kingston but not the Severn at Deerhurst, water could potentially be transferred from the Severn to supplement flows in the Thames. However, this study found that the period of time when the Thames at Kingston is affected by drought, but the Severn at Deerhurst is not, is projected to decrease into the future, especially so for summer (JJA) months (Figure 9).

For example, in JJA the mean period of time Deerhurst is not in drought but Kingston is, is 39% in the baseline period (the period of time is expressed as a percentage of the time Kingston is in drought), but this is projected to decrease to 30% in the near-future and 22% in the far-future.

For winter (DJF) droughts projections indicate that there is little change in the mean period of time when Kingston is in drought but Deerhurst is unaffected (~40%).

These results are further emphasised by Figure 10, which shows the ensemble mean period for each month separately (expressed as a percentage of the time Kingston is in drought). Generally, in the future there are projected to be fewer occasions when the Severn would be able to supply water to a drought-affected Thames at Kingston via a transfer scheme.

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Figure 9: Ensemble distribution of the period of time (expressed as a percentage of time Thames is in drought) when the Thames at Kingston is in drought, but the Severn at Deerhurst is not, for flows in each time-slice and season.

Figure 10: Ensemble mean period of time (expressed as a percentage of time Thames is in drought) when the Thames at Kingston is in drought, but the Severn at Deerhurst is not, for flows in each month and for each time-slice.

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Figure 11 shows the length of time (number of consecutive months) for which the Thames at Kingston is in drought but the Severn at Deerhurst is not. The mean length is 5.2 months in the baseline period, which is projected to decrease to a mean of 4.7 months in the near-future and 4 months in the far-future. Although the ensemble means (Figure 11) do not change dramatically over time, the ranges narrow considerably (Table 7). This indicates that the variation across the ensemble, and within the ensemble members, is reducing into the future.

Figure 11: Ensemble distribution of the length of time (number of consecutive months) when the Thames at Kingston is in drought and the Severn at Deerhurst is not (mean, standard deviation and maximum).

Table 7: Ensemble means and range (in brackets) of the length of time the Thames at Kingston is in drought but the Severn at Deerhurst is not (consecutive months).

Mean Standard deviation Maximum

Baseline 5.2 (1.3-10.7) 3.3 (0.5-7.0) 10.7 (2-22) Near-future 4.7 (2.0-8.0) 3.2 (0.8-5.6) 10.8 (3-22) Far-future 4.0 (2.3-6.9) 3.2 (1.6-6.0) 10.8 (6-21)

4 Conclusions In the first work package the regional approach used by Rudd et al. (2018) to identify major droughts in the Thames and Severn UKCP09 regions was adapted to consider such droughts in the Thames to Kingston and the Severn to Deerhurst catchments.

Work package two involved identifying and analysing river flow drought characteristics for moderate or greater severity droughts at two locations: the Thames at Kingston

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and the Severn at Deerhurst. The analysis used G2G hydrological model flow simulations from observation-driven and climate ensemble-driven runs.

Both work packages applied the drought threshold method of Rudd et al (2017). Further work could investigate the use of a different threshold, such as flow quantiles.

When interpreting the results it is important to remember that

• The G2G hydrological model simulates natural flows, i.e. it does not take into account abstractions and artificial influences. Work is underway to include such flow modifications as options in the G2G.

• The droughts identified in this study are done so relative to conditions over a recent baseline period, and changes from that, rather than in an absolute way.

• No “pooling” of consecutive droughts (e.g. 2 droughts with a short recovery in between) has been included in the drought identification method.

• Water transfers, and the subsequent effect on the likelihood of available water, are not included in the analysis.

• Due to a very short observational flow record and missing data for the Severn at Deerhurst, a comparable analysis using the observed/naturalised flows could not be carried out.

The results using future projections presented here are from a single climate model, results using other climate models could be different.

The key results of both work packages are highlighted below.

WP1: catchment-based analysis

• The number of ensemble members for which the largest major drought in the Thames to Kingston also affected the Severn to Deerhurst is projected to increase into the future (considering the largest major drought in the Thames in each ensemble member).

• The number of ensemble members projecting a major drought in both catchments that affects at least 70% of the rivers in each, is projected to increase by 56% in the near-future (2022-2049), and by 135% in the far-future (2072-2099). Thus analysis of future climate projections indicate that the largest major droughts in each ensemble member are more likely to affect both catchments.

WP2: site-based analysis

• G2G model performance for historical periods for both the Thames at Kingston and the Severn at Deerhurst are very good (NSE~0.9; Table 3), indicating that the G2G model simulations at these locations can be used for drought analyses with some confidence.

• At both the Thames at Kingston and the Severn at Deerhurst the number of droughts of moderate severity or greater is projected to increase into the future.

• The ensemble range of the mean, standard deviation and maximum duration at both gauges decreases slightly into the future and is much narrower for the Severn at Deerhurst than the Thames at Kingston.

• There is projected to be less variability in the maximum drought intensity for future ensembles, this is shown by the decrease in the range of the mean and standard deviation.

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• On average, month by month, there are more occasions when the Thames at Kingston experiences a drought than the Severn at Deerhurst. The number of months when the Thames at Kingston is in drought is projected to increase, as is the number of months when the Severn at Deerhurst is in drought

• The period of time when the Thames at Kingston is affected by drought, but the Severn at Deerhurst is not, is projected to decrease into the future, especially so for summer months. Generally, in the future there are projected to be fewer occasions when the Severn would be able to supply water to a drought-affected Thames at Kingston via a transfer scheme.

• For winter droughts projections indicate that there is little change in the mean period of time when Kingston is in drought but Deerhurst is unaffected, thus potential water transfers in winter months would remain as viable in the future as they are for the baseline period.

• On average the length of time (number of consecutive months) for which the Thames at Kingston is in drought but the Severn at Deerhurst is not (and so a water transfer would be possible) is projected to decrease into the future (from a mean of 5.2 months in the baseline period to 4 months in the Far-Future).

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Bell VA, RUDD AC, Kay AL and Davies HN (2018b): Grid-to-Grid model estimates of monthly mean flow and soil moisture for Great Britain: weather@home2 (climate model) driving data [MaRIUS-G2G-WAH2-monthly], NERC-EIDC. doi:10.5285/3b90962e-6fc8-4251-853e-b9683e37f790

Bell VA, Kay AL, Davies HN and Jones RG (2016). An assessment of the possible impacts of climate change on snow and peak river flows across Britain. Clim. Chang., 136(3), 539–553.

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Appendix 1: Work package schematics

Figure A1. WP1: Illustration of how the coincidence of major droughts with the largest spatial extent are compared in two catchments for a single ensemble member.

Figure A2. WP2: droughts with moderate severity or greater are compared at the Severn at Deerhurst and the Thames at Kingston. In each ensemble member, the total period of time (months) when a water transfer is possible (grey area) is expressed as a percentage of the total time in drought at Kingston.

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Appendix 2: Work plan

Work package 1: Adapt approach used in Rudd et al. (2018) for specific catchments Task 1.1: Sub-catchment selection

Select mutually-agreed sub-catchments from each river catchment, one from the Severn and one from the Thames (e.g. Deerhurst and Kingston) that will be used in the drought extent analysis.

Task 1.2: Drought identification

Modify and run the drought identification algorithm from Rudd et al. (2018) for all ensemble members (100) of the MaRIUS weather@home2 ensemble and for three time slices (baseline; 1975-2004, near-future; 2020-2049; far-future, 2070-2099).

Task 1.3: Analyse the coincidence of droughts

Calculate the proportion of ensemble members projecting a major drought affecting the Thames and the Severn at the same time, for each time slice.

Work package 2: Drought duration and intensity at specific gauged locations Task 2.1: Identity droughts for a flow record in the Thames and in the Severn

Identify droughts using the monthly mean flow for the two sub-catchments using the weather@home2 climate model simulations (1975-2004, 2020-2049 and 2070-2099), an observation-driven G2G run (1960-2015) and observed flows2. This involves adapting the existing gridded drought identification code from Rudd et al. (2017 and 2018). Alternative drought thresholds, other than the long-term mean, could be considered.

Task 2.2: Calculate the duration and intensity of river flow droughts at the gauging station location

Post-process the droughts identified in Task 2.1 and investigate drought duration and intensity for each ensemble member, for each time slice. Analyse how drought duration and intensity might change in the future, and provide a comparable historical analysis using observation-driven G2G simulations and observed flows.

Task 2.3: Investigate how often flows at the Thames gauge are in drought but flows at the Severn gauge are not

Analyse how often, and at what time of year, flows at the Thames gauge are in drought but flows at the Severn gauge are not, and for how long, for the observation-driven, baseline and projected future G2G simulations and observed flows.

2 The flow record for Deerhurst (54110) started in 1995.