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1. Introduction

modifications of the Antecedent Rainfall Index (ARI) and theAntecedent Daily Rainfall Model have been used (e.g. Caine,

study here is unique in that the melt of the snow cover and the

landslides are considered. Although these relatively simple modelsof water balance are not substantiated physically, they are stillfeasible for initial approximation. The same is true for various otherindices describing landslide occurrence such as the Cumulative

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0081980; Glade et al., 2000; Godt et al., 2006). These usuallyconsider only liquid precipitation. However, the situation underShallow landslides in the Outer Western Carpathians arealmost always associated with extreme rainfall (e.g. Gil, 1997;Krej et al., 2002; Kudrna et al., 2003). In the spring of 2006,the thawing of the thick snow cover occurred together withmassive rainfall. This article attempts to uncover the causes ofthe resulting landslide disaster, and to establish the thresholdamount of water from snowmelt and rainfall that when soakedinto the soil, will trigger shallow landslides.

For evaluating the rainfall threshold for landsliding, various

liquid rainfall are combined. The snow cover can be regarded asa reservoir of water with a known content. As the depth of snowand its water equivalent are measured on a regular basis, thesedata can be used for calculating the total amount of waterdelivered into the soil. Gerstel et al. (1997) discussed extremelyfast snow thawing accompanied by rainfall, followed bylandslides in Washington State, USA.

In ascertaining the rainfall threshold for landsliding, most me-thods take the known dates of landslide occurrences as their inputparameter. Usually several episodes with a substantial number offorested areas. This region, geologically part of the Outer Western Carpathians, is prone to landslides because the bedrock is highly erodibleMesozoic and Tertiary flysch.

The available meteorological data (depth of snow, water equivalent of the snow, cumulative rainfall, air and soil temperatures) from five localweather stations were used to construct indices quantitatively describing the snow thaw. Among these, the Total Cumulative Precipitation (TCP)combines the amount of water from both thawing snow and rainfall. This concurrence of rain and runoff from snow melt was the decisive factor intriggering the landslides in the spring.

The TCP index was applied to data of snow thaw periods for the last 20 years, when no landslides were recorded. This was to establish the safethreshold of TCP without landslides. The calculated safe threshold value for the region is ca. 100 mm of water delivered to the soil during thespring thaw (corresponding to ca. 11 mm day1). In 2006, 10% of the landslides occurred under or at 100 mm of TCP. The upper value of 155 mmcovered all of the landslides. 2007 Elsevier B.V. All rights reserved.

Keywords: Shallow landslides; Antecedent rainfall; Snow thaw; Landslide threshold; Outer Western Carpathiansrainfall. Most watercourses suffered floods, and more than 90 shallow laAbstract

At the end of March 2006, the Czech Republic (CZ) witnessed a fast thawing of an unusually thick snow cover in conjunction with massivendslides occurred in the Moravian region of Eastern CZ, primarily in non-The origin of shallow landslidein the spri

Michal Bl

Faculty of Sciences, Palack University in Olomou

Received 5 July 2007; received in revised formAvailable online

Geomorphology 99 (2 Corresponding author. Tel.: +420 585 634 177; fax: +420 585 634 002.E-mail address: michal.bil@upol.cz (M. Bl).

0169-555X/$ - see front matter 2007 Elsevier B.V. All rights reserved.doi:10.1016/j.geomorph.2007.11.004in Moravia (Czech Republic)of 2006

Ivo Mller

. Svobody 26, Olomouc, 779 00, Czech Republic

November 2007; accepted 13 November 2007November 2007

) 246253www.elsevier.com/locate/geomorphEvent Rainfall (Corominas and Moya, 1999). Most of the work onrainfall threshold determination has been done in Italy (Govi andSorzana, 1980; Reichenbach et al., 1998; Calcaterra et al., 2000;

Aleotti, 2004; Giannecchini, 2005) and Spain (e.g. Corominas andMoya, 1999). The latest work on the rainfall threshold forlandsliding outside Europe includes the work of Gabet et al.(2004) and Claessens et al. (2006, 2007). Some studies in theTertiary AlpineCarpathianMountain Ranges also define a rainfallthreshold for landslides based on ARI (Moser and Hohensinn,1983; Cancelli and Nova, 1985; Pasuto and Silvano, 1998). For thePolish Flysch Carpathians, Gil (1997) states that if the rainfallamounts to 200300 mm within 2040 days, shallow landslidesare to be expected. However, these previous works did not considerprecipitation from snowmelt as a potential triggering factor. There-fore, we modified ARI into the more general index of the TotalCumulative Precipitation (TCP).

2. Regional setting

The Eastern part of the Czech Republic lies in the OuterWestern Carpathians where the bedrock is Tertiary flysch in thePaleocene and Miocene Magura nappe system dominated by theVsetn beds (vbenick et al., 1997). These rocks are a mixtureof claystone, siltstone, sandstone and conglomerate. With theexception of some sandstone layers that stand out as solitaryoutcrops, the rocks are weak and produce a relatively thick

altitudes occur in the west close to the floodplain of the MoravaRiver (200300 m). The relief between the ridges and the valleybottoms is largest in the east, up to 400 m. The area is moderatelysloped with the average slope being at 9 and with slopes of 4 to13making up 70%of the area. Themaximum slope is 42. Thesemorphological data were taken from a DEM with a cell size of2020 m. According to Tolasz (2007), the area had a meanannual temperature of 79 C and an annual precipitation of 600800mm during the 19612000 period. Rainfall inMarch to Aprilamounted to 4050mmwith a snow cover recorded for five to tendays in early March on average. A snow cover was usually notrecorded in April.

Shallow landslides are slope deformations that affect only acolluvial cover. The depth of a failure surface corresponds to theborder between the colluvium and the bedrock, and thus de-pends on the thickness of the colluvium. Landslides in the studyarea accessible for field measurement had a depth up to 4 m.The average depth was only 1.0 m. In the Outer WesternCarpathians deep-seated landslides with depths of 20 m or morecan also be found (Krej et al., 2002). Of all the landslides fromthe spring of 2006, only one can be classified as deep-seated. Atypical shallow landslide would be 35100 m long, 2070 mwide, with an average slope of 12, and located at a footslope.

247M. Bl, I. Mller / Geomorphology 99 (2008) 246253colluvium (Krej et al., 2002).Most of the landslides in the spring of 2006 occurred in an area

of about 1000 km2, within the cities of Zln, Uhersk Brod andValask Klobouky (Fig. 1). In this area, the maximum altitude is835 m, minimum is 200 m, and average is 407 m. Higher ele-vations occur in the south east at the border with Slovakia, withmountain ridges reaching 650800 m. Ridges in the central partare 550700 m, most of the area is 300550 m and the lowestFig. 1. Study area. Black dots landslides in the spring of 2006, flags weather stKlobouky, ST ttn.The winter of 2005/06 was exceptional in terms of a very thicksnow cover. The snow kept accumulating beginning in Decemberof 2005. As the air temperature stayed below zero until the end ofMarch, there was no partial thawing, and thus the water equivalentof the snow (SWE), particularly in themiddle elevations, reached itshighest level since 1961 (Sandev, 2006). The thick snow coverstayed until the end of March when higher air temperatures andheavy rainfall appeared due to changes in air mass circulation overations, LU Luhaovice, VI Vizovice, HL Horn Lhota, VK Valask

Europe. Until March 25, 2006, an anticyclone prevented warm airfrom spreading over the territory of theCZ. The first significant rain(N10mm) fell onMarch 26, which was followed onMarch 2829,by the passage of a strong frontal system over Central Europe. Ityielded up to 35 mm of rainfall. The consequence was majorflooding throughout theCZ andmore than 90 landslides inMoravia(Fig. 2).

The first landslides occurred at the end of the spring thaw.More slides followed in response to the rainfall. The dates of 28out of 90 landslides, with known dates of origin, are summa-rized in Table 1. The first landslide was recorded on March 27and the number of landslides peaked on March 29. The lastrecorded landslides occurred on April 4. This indicates that thethreshold conditions for landslides varied, reflecting the localvariability of snow cover and rainfall. The dates of origin of theother landslides are not known exactly but within a range ofseveral days. It is safe to say that the vast majority of landslideswith known dates of origin took place before the end of April.This was the period without snow and before the onset of rain at

of the study area, snow thaw occurs within several days. As thepoint of reference we took the last day when a continuous snowcover was recorded, since small patches of snow can survive inshaded locations for a long time.

We employed the following three indices.

Snow thaw period, which begins when the average dailytemperature rises above 1 C and ends seven days after theloss of a continuous snow cover. The beginning is thuslocated within days when the day-time temperature is above0 C and freezing occurs overnight. The average daily tem-perature is calculated as the sum of temperatures at 7 a.m.,2 p.m. and twice the temperature at 9 p.m. divided by four.

Table 1Landslides with known dates of origin

Date 3/27 3/28 3/29 3/30 3/31 4/1 4/2 4/3 4/4 Sum

Frequency 1 4 6 3 4 4 1 1 4 28

248 M. Bl, I. Mller / Geomorphology 99 (2008) 246253the beginning of May (Fig. 3).Immediately after a larger number of landslides had been

reported, their documentation began, mostly by workers of theCzech Geological Survey. Within a month, more than 80 slideswere located, and the rest was reported later.

3. Data and methods

Fiveweather stations are located close to the landslides (Fig. 1)and their records were used to give account of the meteorologicalconditions of the landslide event.

The data are in the form of time series covering the period of17 days from March 20 to April 5, and capturing the wholelandslide event. From the available data we attempted to defineseveral indices that describe basically the same phenomenon asARI but include the effect of snow cover. In the natural settingFig. 2. Cumulative rainfall (mm) and snow depth (SD; cm) during the 20This is the standard procedure used by the Czech Hydro-meteorological Institute, CHMI. The end of the snow thawperiod is not defined as the last day of continuous snow coverbut extra seven days are added because snow can remain inisolated patches, and runoff water stays in pools on the soilsurface, gradually infiltrating into the ground.

Snow Thaw Rate (STR) is the average decrement (in mmday1) of the snow water equivalent (SWE) from the be-ginning of the snow thaw period until the last day of con-tinuous snow cover. Since the logs of SWE are available onlyonce a week, the exact value at the beginning of the snowthaw period may not be known, and STR suffers from thisuncertainty. In addition, an auxiliary index of the thawingrate was calculated from the snow depth (SD) (in cm day1).However, the latter index is not precise because of thesettling or compaction of snow with time.06 landslide episode at the station of Luhaovice, March 20April 5.

ve P

rpho Total Cumulative Precipitation (TCP) is the sum of SWE andthe measured rainfall during the snow that period (in mm).This is an estimate of the depth of water supplied to the soilsurface during the period. In 2006, the thaw period(approximately March 20April 4, depending on a weatherstation) covers all of the landslides with known dates (28slides). For better comparability (because of non-equidistantsnow thaw periods), the daily average TCP in mm day1

(defined as TCP divided by the number of days from therecord of SWE to the end of the snow thaw period) gives an

Fig. 3. Pentades of rainfall, snow depth (SD), Total Cumulati

M. Bl, I. Mller / Geomoaverage rate of water flux into the soil surface.

In order to determine the threshold TCP value for landslides,all the above-mentioned parameters were calculated for twoselected weather stations over the past 20 years, and the resultswere compared. Data from these two representative stationswere used in the following analyses, because all five stationsrecorded similar values.

4. Results

4.1. Effects of precipitation and snow melt in 2006

Since the end of the 2006 landslide episode, the question oftriggering factors has been attracting attention. One of our firsthypotheses was that the rapid thaw of a large amount of snowoccurred over frozen soil into which infiltration rates would below. Frozen water in soil forms particles of ice. After meltingthese ice particles increase the water content of soil and theinstability of the slopes. However, soil temperature data showthat the temperatures at all depths remained above 0 C, andthus that hypothesis was rejected.

The decisive factor for the occurrence of landslides in thespring 2006, was the combination of the effects of rainfall andhigh values of SWE. The precipitation chart at the station inVizovice (Fig. 3) over the months following the slides indicatesthat the heavy rainfall alone was not responsible for thelandslides. Although rainfall in late April and early May 2006 aswell as at the end of May was comparable to that during thespring thaw, no landslides were reported during that time.Adding SWE to the rainfall gives a value for the spring thawperiod that exceeds the rainfall of the later periods by more than70 mm.

4.2. Determination of the TCP threshold from 20-year data

recipitation (TCP) and change in SD at the Vizovice station.

249logy 99 (2008) 246253In order to determine the threshold value of TCP forlandsliding, it was necessary to compare the landslide event of2006 to the snow thaw periods in the preceding years. Theweather stations in Luhaovice (years 19882005) andVizovice (years 19862005) were selected, as they are locatedin the central part of the region. For each year and each station,the dates of the snow thaw period were determined based on thecriteria previously established.

As no similar landslide episode was recorded in the landslideinventory, the data from previous years serve as a reference fordefining a safe limit of TCP, under which landslides arerelatively rare. Over the past 20 years, the snow that period atthe stations in Luhaovice and Vizovice lasted 1020 days andoccurred sometime between December and April.

Tables 2 and 3 show that the year of 2006 was extreme atboth stations in terms of rainfall, SD and SWE. The value ofTCP reached 143.5 mm (STR=9.0 mm day1) in Luhaoviceand 163.1 mm (STR=10.2 mm day1) in Vizovice. At the sametime SWE in Luhaovice was 78.4 mm and 114 mm inVizovice. The snow thaw period of 2005 was also rich in snowwhen SD, SWE and STR at both stations were comparable totheir 2006 values. STR appears to be slightly higher for 2006,but as SWE is recorded only once a week, this index is not veryaccurate. However, this comparison suggests that a large value

of SD, at the level of 2005 or 2006 alone, is insufficient to rejection for the data until 2006. This conclusionwas also validated

Table 2Station Luhaovice weather conditions during Snow Thaw Periods 19882006

Year 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06

Spring Thaw Period (STP) [days] 12 15 10 10 20 14 11 13 12 15 13 14 20 12 17 12 15 20 16Rainfall [mm] 16.9 8.2 21.3 0.3 21.2 26.0 21.2 25.2 8.9 20.7 6.1 39.0 38.5 25.4 19.0 0.3 6.8 6.7 65.1Snow Depth (SD) [cm] 8 11 5 11 12 17 22 13 5 16 6 20 22 13 23 6 15 36 33Snow Water Equivalent (SWE) [mm] 17.0 14.0 10.5 22.4 44.1 23.0 31.2 26.2 12.1 27.7 9.0 33.3 44.9 16.0 45.4 13.5 33.1 93.1 78.4Snow Thaw Rate (STR) [mm day1] 4.3 2.3 10.5 5.0 4.0 11.5 7.8 6.6 1.7 6.9 3.0 11.1 4.5 3.2 5.7 1.9 5.5 7.8 9.8Total Cumulative Precipitation (TCP) [mm] 32.7 17.5 31.8 22.7 62.4 48.1 52.1 37.1 21.4 48.4 15.1 65.4 64.7 41.4 55.4 13.8 37.2 99.8 143.5Daily average TCP [mm day1] 2.7 1.2 3.2 1.9 3.1 3.4 4.3 2.9 1.4 3.2 1.2 4.7 3.2 3.2 3.3 0.9 2.5 5.0 9.0

Daily average TCP is defined as TCP divided by number of days since the record of SWE to the end of STP.

250 M. Bl, I. Mller / Geomorphology 99 (2008) 246253provoke landslides. As noted in the previous section, rainfallalone is not a sufficient cause of landslides either. Therefore, thecause of landsides was the combination of the thick snow andheavy rainfall during the spring thaw. Through a comparison ofTCP in 2006 and that in the previous years, we can reach atentative conclusion that the safe threshold of TCP for land-slides in this region is approximately 85 mm or an average dailyvalue of 59 mm day1.

A statistical analysis of the 20-year record (Table 4) shows howexceptional the year 2006was. The extreme value of TCP in 2006causes a substantial increase in both the arithmetic mean and thestandard deviation of TCP, SWE and rainfall. We estimatedwhether this outlier fits to the series of previous records using aGaussian model. For this analysis we used the TCP records fromthe Luhaovice station because the Vizovice station gave verysimilar data and would yield identical conclusions.

Since the sample size (N=20) is rather small, several tests ofnormality were performed. The first of these was based on em-pirical moments. For all records up to 2006, skewness 3 is 1.589and kurtosis 4 is 5.610. After appropriate standardizing, the teststatistics in both cases exceed the critical value u(.05)=1.96 forstandard normal distribution. However, for data up to 2005, we get3=0.782 and4=3.489,which does not reject the null hypothesisfor normal distribution. D'Agostino (1970) and D'Agostino et al.(1990) suggested a modification of the test of normality based onstatistical moments, which can be used with quite small samplesizes: nN8 for skewness and n20 for kurtosis. The modified testconfirmed non-rejection of normality for the data until 2005 butTable 3Station Vizovice weather conditions during Snow Thaw Periods 19862006

Year 86 87 88 89 90 91 92 93 94

Snow Thaw Period(STP) [days]

12 14 11 10 10 10 13 14 16

Rainfall [mm] 7.6 7.9 10.5 5.2 30.4 0.3 7.6 29.0 37.8Snow Depth (SD) [cm] 17 32 10 6 4 6 12 18 24Snow Water Equivalent(SWE) [mm]

25.5 66.4 19.7 11.4 8.6 9.3 17.4 23 30.5

Snow Thaw Rate (STR)[mm day1] 4.3 11.1 6.6 5.7 8.6 1.9 4.4 11.5 7.6Total CumulativePrecipitation(TCP) [mm]

33.1 74.3 30.0 16.6 39.0 9.6 19.2 49.7 50.6

Daily average TCP[mm day1]

2.4 5.3 2.7 1.7 3.9 0.7 1.5 3.6 3.2by the so-called omnibus test (D'Agostino et al., 1990) that usesboth empirical moments simultaneously.

Second, the Kolmogorov goodness-of-fit test was performed.It takes better account of tails of a frequency distribution and isalso recommended for use with small sample sizes (Lehmann,1999, p.341). The maximum difference between the empiricaland theoretical (Gaussian) distribution functions (with theparameters and 2 estimated from the data) for records in-cluding 2006 is 0.185, leading to non-rejection of normality on0.05-level (the non-rejection being by a narrowmargin, though).The results of all the above-performed tests do not contradict theinterpretation that TCP fits the normal model and the value of2006 deviates from the model in the sense that it constitutes arare observation originating from the tail of the distribution.

The TCP values up to 2005 show no linear increasing orlinear decreasing time trend (t=1.63 in a straight-line fit) andthus only a constant value of the average may be used to expressa trend. The sign test on residuals from the average did not detectany systematic error (the test statistic 0.04). Therefore theresiduals can be considered random and the model of constanttrend is applicable. The 95-percent confidence interval for themean value, calculated from data until 2006 under normalmodel, is [32.69; 63.15].

Assuming a normal distribution N(, 2), we can estimatethe probability of the occurrence of the extreme TCP value in2006. Estimating the mean as 47.92 and the standard de-viation 2 as 998.31, we get P(X143.5)=0.0012, that is, thechance of observing an equal or higher TCP value is 0.12%.95 96 97 98 99 00 01 02 03 04 05 06

13 15 15 10 12 13 1 15 11 12 18 16

33.2 14.4 28.0 6.1 42.4 31.5 18.0 20.1 1.8 4.1 10.0 49.113 16 13 7 13 24 discont. 30 5 21 49 3230.4 31.8 26 8.6 20 48 10 58 8 31 87 114

7.6 15.9 6.5 1.2 20.0 16.0 2.0 9.7 1.3 5.2 10.9 14.350.0 45.8 54.0 16.0 57.0 59.8 28.0 67.8 9.8 37.0 93.8 163.1

4.2 3.1 3.6 1.1 4.8 4.6 2.2 4.5 0.7 2.6 5.2 10.2

assumption that SWE in 2006, although rather high, was notextreme in terms of the previous history.

The agreement in the time-course of the TCP data at thestations in Vizovice and Luhaovice can be seen both from thehigh correlation coefficient .91, and from the two-sample t-teston equality of mean values. Assuming normality and havingemployed Bartlett's test to check the equality of variances at thetwo stations (these are the assumptions for the t-test), we get thetest statistic 0.0095. This number is highly insignificant, andso the mean values of both stations can be considered equal.Both stations give the same meteorological picture of the areaunder investigation.

4.3. TCP threshold in the spring 2006

Table 4Basic characteristics of stations Luhaovice and Vizovice from 20-year data

Averageuntil2005

Averageuntil2006

Medianuntil2005

Medianuntil2006

Std.deviationuntil 2005

Std.deviationuntil 2006

LuhaoviceTCP[mm]

42.61 47.92 39.3 41.4 22.13 31.60

VizoviceTCP[mm]

42.06 47.82 42.4 45.8 22.56 34.37

LuhaoviceSWE[mm]

28.69 31.31 24.6 26.2 19.99 22.53

LuhaoviceRainfall

17.32 19.83 19.85 20.7 11.54 15.58

251M. Bl, I. Mller / Geomorphology 99 (2008) 246253Next, let us examine the chance of exceeding the past meanlevel by calculating the probability that a future observation Xexceeds a k-multiple of the average of the past n observations X

n:

P Xzk PXn P X k PX nz0 1 U k 1 A= r2 1 k2=n ;

where k is a given constant (N0), is the standard normaldistribution function and all the observations are assumedindependent. After substituting the estimated values for and 2

and assuming k=3.4 (in 2006 the value of TCP was 3.4 timeshigher than the antecedent average), we get a probability of 0.0024for exceeding the k-multiple of the past mean value of TCP.Similarly, for k=3.9 this probability in Vizovice is 0.0012. Thus,both stations are on the order of magnitude 103.

Let us now examine SWE and rainfall in 2006 in Luhaovice.The probability of observing a rainfall of 56.1 mm or higher is0.0020, and the probability of exceeding the 3.8-multiple of theantecedent rainfall average is 0.0045. Both numbers were thesame order of magnitude as those for TCP. The respective

[mm]probabilities for SWE are 0.018 and 0.022 (for 2.7-multiple ofthe previous mean). Here the numbers are one order of mag-nitude larger than those for TCP. These results support the

Table 5Weather conditions during Snow Thaw Period 2006 for selected stations

Weather station LU

Elevation [m] 254Snow Depth (SD) on March 20 [cm] 33Snow Water Equivalent (SWE) on March 20/27[mm] 78.4/28.5Discontinuous snow cover/Snow thawed completely [day] Mar 28/30Snow Thaw Rate (STR) from SWE [mm day1] 9.8Snow Thaw Rate (STR) from SD [cm day1] 4.1Snow Thaw Period (STP) Mar 20Apr 4Rainfall in STP [mm] 65.1Rainfall March 2629 [mm] 50.6Mean daily temperature in STP [C] NATotal Cumulative Precipitation (TCP) [mm] 143.5Daily average TCP [mm day1] 9.0

LU Luhaovice, VI Vizovice, ST ttn, HL Horn Lhota, VK ValaAlthough the climatic data from previous years of otherstations are not available, comparisons among rainfall, snowand temperature in 2006 indicate that the area under study iswell characterized by records from the stations in Luhaoviceand Vizovice as well as ttn, Horn Lhota and ValaskKlobouky. Table 5 shows the values of the indices for individualstations. It is evident that differences among stations are notlarge. The largest variability is due to SWE, which is measuredonly once a week and is usually underestimated (Sandev, 2006).

For the year 2006 we analyzed data from the five stations.The TCP values at these stations ranged between 120.4 and176.5 mm (7.5 to 12.6 mm day1). To obtain a clearer picture ofthe relationship between the total amount of available waterduring the spring thaw period and landslides, we used theaveraged values of TCP of five stations since March 20. Thiswas calculated cumulatively from March 27 to April 4 duringwhich time 28 slides occurred. Fig. 4 illustrates the relationshipbetween landslides and TCP for the whole study area. From thedistributional curve, the TCP percentiles can be read. Forexample, up to the point of 85 mm of TCP (11 mm day1) only5% of all slides occurred. ATCP value of 100 mm correspondsto 10% of slides and 140 mm to 40%. All the landslides fell ifTCP reaches 155 mm.

To predict a future landslide calamity would require theprediction of TCP, which is beyond the scope of this article.

VI ST HL VK

315 315 340 43032 40 30 36114.0/66.0 137.0/55.0 119.7/0 57.6/33. 2Mar 28/29 Mar 29/30 Mar 26/Apr 5 Mar 30/3114.3 15.2 20.0 5.84.0 4.4 5.0 3.6Mar 20Apr 4 Mar 22Apr 5 Mar 20Apr 2 Mar 20Apr 649.1 61.8 57.3 62.841.9 42.4 50.0 47.45.0 4.9 NA NA

163.1 164.6 176.5 120.410.2 11.0 12.6 7.5

sk Klobouky; NA = not available.

rphHowever, we might formulate the following tentative statement,using the TCP percentiles x. Under the assumption that TCPreaches the level of 2006 or higher during the snow thaw period,no more than percent of slides will occur at a TCP of x mmTCP, or beyond x more than (100) percent of slides arepossible. That is to say that if y landslides were observed whenTCP reached x, more than (100 /1)y slides could beexpected. For a given , observed x can serve as an indicatorof the landslide risk, when rain and snowmelt continueunabated. We suggest using =10.

The overall conclusion from both the 20-year records and the2006 data is that the threshold value of TCP, at which extensivelandslides are imminent, is about 100 mm (with the dailyaverage of approximately 11 mm day1). In 2006, this thresholdcorresponds to the 10th percentile of the observed landslides.

5. Discussion

The above results represent an attempt to establish a thresholdamount of water that has to be delivered into the soil during

Fig. 4. Relationship between landslide frequency (%) and the Total CumulativePrecipitation (TCP; mm).

252 M. Bl, I. Mller / Geomosnowmelt for landslides to occur, primarily in non-forested areas.Because only five of the 90 landslides were identified in thewoods, it seems likely that the threshold for landslides in forestedterrain was not exceeded. A slower release of water from thesnow, as is the case in the woods, may play a role here. A forestusually has its own local climate with smaller fluctuations andlimited sun insolation. Thus the warming of the air and groundnecessary for the snow thaw is not abrupt. Of course, the thresholdis subject to other influencing factors such as geology, relief, soiltypes and vegetation. However, we consider these influences ofsecondary importance compared to the total amount of water inthe soil during the spring runoff.

With the input data of a small size, due to the limited number oflandslides with known dates of origin, the construction of alandslide prediction map is impossible. Therefore, the thresholdTCP was given as an average for the five neighboring stations andnot as a specific value for each landslide.Other potential sources ofuncertainty are that rainfall at eachweather station does not alwayscorrespond to precipitation in a broader area, that the value ofSWE is difficult to measure and model and that data processingtechniques can influence the rainfall records. The standard practiceof the CHMI is to register daily rainfall at 7 a.m. and record it as avalue for the previous day. Data from automatic probes that workwith a differently defined day-span have to be adjusted to makethem comparable to manual readings. Glade et al. (2000) pointedout the difficulty with this correction.

Our threshold value for shallow landslides (100 mm) is two tothree times lower than that given by Gil (1997) for the PolishCarpathians where landslides occur with a rainfall of 200300 mmwithin 2040 days. In our case, however, an extraordinary eventtook place when snow thaw was combined with rainfall during ashorter period (about 15 days). The threshold value was reached inabout nine days in the study area. Both results are consistent interms of the daily average value of TCP (circa 10 mm day1).

6. Conclusions

This article presents the results from analysis of the landslideepisode in March and April of 2006 that affected the eastern partof the Czech Republic. After the snow thaw and followingrainfall, more than 90 shallow landslides occurred. The causefor this episode appears to be the concurrence of the thawing ofan extraordinarily thick snow cover and heavy rain, which canbe encompassed in a general index, TCP. For all the landslideswith a known date of origin to occur, it was necessary for TCPto reach 155 mm within ten days. The lower threshold repre-senting 10% of observed landslides is about 100 mm. Thesevalues are averages for the whole affected area.

Acknowledgements

Our thanks extend to: The Grant Agency of AS CR (GAAV),project No. KJB301370601, for the financial support; OldichKrej and coworkers from the Czech Geological Survey andJan Klime from the Academy of Sciences of the CzechRepublic for data on landslides; Vt Voenlek for assistance incollecting data; Petr tpnek from the Czech Hydrometeor-ological Institute for assistance in pre-processing the climaticdata; to Luk Macur and Frantiek Kuda for their help withfield work; Nel Caine, Adam Kotarba and Takashi Oguchi fortheir comments that helped to improve the quality of the text.

Appendix A. Supplementary data

Supplementary data associated with this article can be found,in the online version, at doi:10.1016/j.geomorph.2007.11.004.

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The origin of shallow landslides in Moravia (Czech Republic) in the spring of 2006IntroductionRegional settingData and methodsResultsEffects of precipitation and snow melt in 2006Determination of the TCP threshold from 20-year dataTCP threshold in the spring 2006

DiscussionConclusionsAcknowledgementsSupplementary dataReferences