Mass movement in Sri Lanka is mainly triggered by heavy rainfall. International literature is rich of works defining rainfall intensity-duration models to identify the rainfall threshold for various types of Mass movement. However, studies have not focused to establish a relationship between intensity and duration of rainfall in Sri Lanka. Therefore, this study focused to establish rainfall intensity-duration models to identify the rainfall threshold for mass movements in Badulla district in Sri Lanka, where forty four (44) rainfall events that resulted in same number of landslides during the last three decades were considered. Results indicate the rainfall threshold relationship fits to the log linear model of the exponential function, I = α · D -β. The constructed I-D curve revealed that short duration (<2 h) and high-intensity (>54 mm/h) in rainfall events can potentially trigger the landslide. However, long-duration (>8 h) and low-intensity (<25 mm/h) in rainfall events may also trigger mass movements in Badulla. As per the results, most mass movements occur during northeast monsoons and inter-monsoons. In general, higher mean rainfall intensities trigger the debris flows, while long-duration rainfall events can trigger both landslides and debris flow. When compared to Sri Lankan mass movements triggering threshold intensities are fairly higher than the global threshold values. It confirms that within Badulla, mass movements are triggered by very high intense and/or long duration rainfalls events only. Further, time series analysis of the rainfall events shows an upward trend of extreme rainfall events, which increased landslide occurring frequency in last six (6) years.
Landslide (mass movements) acts on natural and engineered slopes in steep topography [
Various methods have been proposed in the literature to predict rainfall conditions that are expected to trigger mass movements [
Badulla district in Sri Lanka is one of the major districts where large-scale landslides are observed during heavy rainfall (
The rainfall intensity and duration analyses are important to study the sliding trends during the past, and such analyses can help to forecast future events under
heavy rainfall. Therefore, the major aim of this study is to investigate the rainfall variation in the last few decades and to study the temporal pattern of landslides. Further, the study expects to analyze rainfall events that have caused landslides in Badulla, to define the threshold for possible occurrence of landslides.
Badulla is about 230 km away from Colombo towards the eastern slopes of the central hills of Sri Lanka (
The population of Badulla district is approximately 886,000, with 1:1 male to female ratio. Although 47% of residents are employed, the high rate of dependency reaches 54% of the population [
Badulla district is located in the southeastern mountainous terrain in Sri Lanka and represents an area of 2870 km2 (
Rainfall over Sri Lanka is characterized by its tropical location and by the monsoonal regime, and thus has a significant seasonal variation in the rainfall pattern. There are four climatologic seasons in Sri Lanka, namely, the northeast monsoon from December to February, the southwest monsoon from May to September, the first inter-monsoon from March to April, and the second inter-monsoon from October to November. The north-east monsoon provides a high rainfall to the eastern slopes, but the south-west monsoon and inter-monsoon is relatively dry (500 - 750 mm). The average annual rainfall of Badulla is around 2000 mm and has a clear variation along the terrain. Northern and southern-most extremities have 900 mm annual average and Uva Basing has 1700 mm. However, over 2500 mm is in the eastern Namunukula and Lunugala ridges [
The rainfall regimes differ with the region’s geography. The northern-most tips of the Lunugala ridges received 40% - 50% of the annual rainfall by north-east monsoons, 30% - 40% during the inter-monsoons, and 12% - 20% in south-west monsoons [
Precambrian high-grade metamorphic rocks in Sri Lanka belong to three major geological units known as the Highland, Wanni, and Vijayan Complexes. Badulla district is located in the eastern section of the Highland Complex, which is composed of meta-igneous rocks and meta-sedimentary rocks [
With respect to spatial distribution, most landslides appear to occur in the Uva, Central, and Southern, provinces. Especially, Badulla, Nuwara Eliya, Kegalle, Rathnapura, Galle, Matara, and Kalutara are the most landslide prone districts. In general, higher incidences are reported within the Badulla district. In addition, approximately 66.9% of the land area in Badulla district is prone to landslides [
Land use of Badulla district is mostly covered by scrubs (≈790 km2), home gardens (≈582 km2), and forests (≈335 km2). Main plantations around hilly regions are tea cultivations (≈890 km2) while flat terrain in the northern region is predominant by paddy lands (≈270 km2 [
The methodology used in this study mainly consisted of two components: 1) collection of landslide and rainfall records in Badulla district from 1986 to 2014 and evaluate the trend and patterns of the landslide occurrences and rainfall variability; and 2) analysis of the relationship between rainfall and landslide occurrence using empirical models. Data was collected from NBRO and Metrological Department of Sri Lanka. The parameters and analysis model were obtained from the referred from previous international studies.
A total of 44 mass movements caused by rainfall events were analyzed during the 28 years from 1986 to 2014. Mass movement data were compiled from NBRO Sri Lanka. NBRO has been classified Mass movement events based on material type and type of movement in such a way that, Debris flow, Rock fall, Cutting failure, Earth slip, and Landslide. Temporal variability of different types of landslide events and corresponding annual average rainfall illustrated in
Further secondary data was collected including the type of the landslide, location, and approximate time which mass movement taken place (to the closest hour) of each event and summarized in a table.
Rainfall records were obtained from 54 rain-gauge stations located within the district established by Metrological Department and National Building Research Organization (NBRO) of Sri Lanka. This data series provided records of rainfall
data of 28 years including occurrences of mass movements. Mass movements, for selected rainfall was verified by using archival newspapers and remote sensing data. According to NBRO, 44 mass movements had been occurred during the considered period from 1986 to 2014. Because of that, hourly cumulative rainfall 72 hrs prior to the taken place each and every mass movements, and the duration (hrs) of that rainfall were obtained from the located rain-gauge stations belongs to Metrological Department and NBRO of Sri Lanka.
Throughout the preliminary field survey and satellite image observation, it is observed that rain gauges stations are not always exactly located close to mass movement sites however, to threshold analysis, the cumulative rainfall and duration of rainfall for triggering each mass movement is essential [
A threshold is defined as the level or the value that must be exceeded to produce a given effect or result [
In this study the causative amount of mean rainfall (mm) and consequent duration (hr) were obtained from the beginning of each of 44 rainfall events to the time of mass movement occurrence. The mean rainfall intensity per hour (I, mm/hr) was calculated for each mass movement (
International literature revealed that various methods have been used to establish the relationship between rainfall intensity and duration [
I = α ⋅ D − β (1)
i.e., a simple exponential function, where α is a scaling constant (intercept), and β is the shape parameter (slope). The Equation (1) is commonly used for model the Intensity and Duration in many studies.
Exponential equations can be written as logarithmic equations and vice versa. In this study exponential rainfall intensity and duration relationship ( I = α ⋅ D − β ) were converted into linear form, because linear model can overcome the problems associated with the fitting of data into exponential form. For that exponential function transformed into logarithmic form as given below
ln ( I ) = ln ( α ) − β ln ( D ) (2)
Equation (2) is the liner form of the Equation (1). Rainfall intensity (I) and duration (D) was log transformed and then a plotted ln(I) against ln(D) for 44 rainfall events from 1986 to 2014 in same graph. This liner function (I-D) has been empirically proved for a wide range of time durations [
Rainfall conditions, ln(I) vs. ln(D), that have resulted in landslides is fitted (least square method) with a linear equation of the type log(I) = log(α) − βlog(D) which is entirely equivalent to the exponential function in linear coordinates. Then log-linier regression model was established for most common mass movement types in Badull district.
The Independent Samples t Test was conducted compares the means of rainfall intensity of landslides and means of rainfall intensity of Mud/debris flow in order to determine whether there is statistical evidence that the associated population means are significantly different.
Annual average daily rainfall and landslide data were analyzed for the period from 1986 to 2014 in Badulla district. Trend analysis examined the variation in rainfall and landslide patterns using Minitab 20 (Minitab Inc). Nonparametric Chi-Square goodness of fit test was employed to study the association between month (season) and occurrence of landslides using SPSS 19 (p < 0.05).
Temporal variation of landslide events is therefore vital to determine the significance of the landslide trend, and nonparametric Mann-Kendall test was conducted using SPSS 19 (p < 0.05). The calculations are described below:
S = ∑ i = 2 n ∑ j = 1 i − 1 s i n g n ( x i − x j ) (3)
where, S is the sum of signs of differences between any two observations for a series xn. Also, where sign (z) is 0 when z is zero, and 1 when z > and −1 when z < 1.
In the considered period, i.e. from 1986 to 2014, the rainfall pattern in Badulla depicted a noticeable change; analogous to the rainfall change, landslide occurrences also showed an increasing trend having two events per year. A threshold was fitted to the liner form of I-D curve, expressed as ln(I) = 3.9882 − 0.1570 ln(D).
The I-D threshold for mass movements is identified on an I-D plot as the minimum rainfall for which a landslide could occur (Chen, 2015).
Thresholds for the possible initiation of rainfall-induced landslides in the Badulla district were identified from the log-linier model of the I-D exponential function. Mean rainfall intensity for all mass movements ranged from 25 mm/h to 54 mm/h with an average of 42 mm/h, and rainfall duration ranged between 3 - 8 h with an average of 5 h (
Average rainfall intensity, duration, and cumulative rainfall for debris flow/mud flow were 49 mm/h, 7 h, and 260 mm respectively, and those for landslides were 41 mm/h, 5 h, and 210 mm respectively (
This study established an empirical linear regression line I-D plot, considering all 44 mass-movement events summarized in
Ln(I) = 3.9882 - 0.1570 ln(D) (3 < D < 8 h; all mass movements, R2 = 59%) (4)
Ln(I) = 3.8892 - 0.1614 ln(D) (5 < D < 8 h; landslides only, R2 = 54%) (5)
Ln(I) = 5.8892 - 0.8475 ln(D) (5 < D < 8 h; debris & mud flow only R2 = 47%) (6)
This threshold are fitted to the mean values of the data point reflects the approximate average rainfall conditions necessary to trigger any mass movement in Badulla district. The equation for all mass movements (Equation (4)) indicates that short duration (<2 h) and high-intensity (>53.75 mm/h) rainfall events can potentially trigger any mass movement in Badulla district. However, long-duration (>8 h) and low-intensity (<24.6 mm/h) rainfall events may also trigger mass movements in Badulla district.
Independent sample t-test and resultant p-values (<0.05) indicate that mean
Year | Month | Date | Landslide information | |||
---|---|---|---|---|---|---|
Avg. Accumulation mm | Duration hr | Avg. Intensity mm/hr | Type | |||
1986 | January | 6 | 316 | 7 | 45 | Landslide |
1986 | January | 7 | 259 | 7 | 37 | Landslide |
1986 | January | 9 | 119 | 4 | 30 | Landslide |
1986 | January | 9 | 244 | 5 | 49 | Landslide |
1986 | January | 10 | 237 | 6 | 40 | Landslide |
1986 | January | 10 | 197 | 5 | 39 | Landslide |
1986 | January | 10 | 205 | 5 | 41 | Landslide |
1988 | December | 21 | 165 | 4 | 41 | Landslide |
1992 | November | 16 | 319 | 7 | 46 | Debris flow |
1992 | November | 16 | 305 | 7 | 44 | Debris flow |
1993 | December | 16 | 310 | 6 | 52 | Debris flow |
1993 | December | 17 | 179 | 4 | 45 | Rockfall |
1993 | December | 26 | 198 | 8 | 25 | Cutting failure |
1995 | April | 17 | 212 | 4 | 53 | Landslide |
1995 | July | 24 | 228 | 5 | 46 | Landslide |
1997 | November | 17 | 257 | 6 | 43 | Earth slip |
1997 | November | 19 | 268 | 5 | 53 | Landslide |
1997 | November | 19 | 289 | 6 | 48 | Landslide |
1997 | November | 19 | 215 | 4 | 54 | Landslide |
1998 | November | 16 | 149 | 3 | 50 | Landslide |
1998 | November | 17 | 180 | 4 | 45 | Landslide |
1999 | October | 5 | 147 | 5 | 29 | Landslide |
2002 | April | 23 | 198 | 6 | 33 | Landslide |
2002 | April | 24 | 206 | 5 | 41 | Landslide |
2004 | December | 21 | 198 | 6 | 33 | Cutting failures |
2004 | December | 22 | 182 | 5 | 36 | Cutting failures |
2004 | December | 23 | 211 | 5 | 42 | Landslide |
2004 | December | 23 | 320 | 6 | 53 | Mudflow |
2006 | November | 22 | 307 | 7 | 44 | Landslide |
2006 | December | 20 | 338 | 8 | 42 | Creep on old lS |
2006 | December | 20 | 316 | 7 | 45 | Debris flow |
2009 | January | 20 | 199 | 5 | 40 | Rock fall |
2009 | January | 20 | 189 | 4 | 47 | Rock fall landslide |
2010 | January | 26 | 160 | 3 | 53 | Instability of cut slope |
2011 | November | 23 | 221 | 6 | 37 | Cutting failures |
2012 | December | 21 | 160 | 3 | 53 | Rock fall |
2014 | October | 29 | 306 | 6 | 51 | Landslide-Mud flow |
2014 | October | 30 | 197 | 8 | 25 | Landslide |
2014 | October | 30 | 174 | 4 | 44 | Landslide |
2014 | October | 30 | 149 | 4 | 37 | Earth slip |
2014 | October | 30 | 189 | 5 | 38 | Landslide |
2014 | October | 30 | 107 | 3 | 36 | Landslide potential |
2014 | October | 30 | 149 | 4 | 37 | Instability of cut slope |
2014 | October | 30 | 135 | 4 | 34 | Landslide potential |
Max | 338 | 8 | 54 | |||
min | 107 | 3 | 25 | |||
Avg. | 218 | 5.3 | 42.2 | |||
Std | 62 | 1 | 8 |
rainfall intensity of landslides and mean rainfall intensity of debris/mud flows are significantly different at 95% confidence level.
Established empirical I-D thresholds for mass movements in Badulla from all type of mass movements, landslide and debris/ mud flow were compared with those for other areas of the world is essential.
Worldwide threshold for debris flows developed by Caine (1980), log liner form that worldwide threshold given by ln(I) = 2.6959 − 0.92 ln(D). This worldwide threshold falls below the Badulla it indicates much rainfall required to trigger any mass movement in Badulla with compared to the global scenario.
[
Such unusual rainfall patterns resulted in heavy rainfall events and dry spells throughout the last 28 years, and this uncertainty trend of rainfall was rapidly amplified after year 2000 (
However, the data displays a sudden positive mean deviation of average rainfall during the period of 2000 to 2014 (
During the period of 1986-2014, 44 large scale mass movement events were clearly identified and recorded in table (
According to the Mann-Kendall test, landslide trend is significant at 95% confidence level. If this rainfall trend and mass movement pattern will continue to the future, it can be conclude that landslides hazards in Badulla may be higher than the past decades. Sri Lankan government also prophesied that rise of landslides in Badulla due to the extreme rainfall events from year 2000 to future.
Generally, mass movements are more common during rainy sessions in Sri Lanka, and thus seasonal distribution of mass movements demonstrate a clear link with the seasonal variation of rainfall (
The records of landslides are high in the months of April, May, and July, and once again from November to January, indicating a clear relationship with first inter-monsoon and northeast monsoon seasons respectively (
In Sri Lanka, landslide process begins with rainfall but is affected by many other factors; therefore it is impossible to determine the possible rainfall level to initiate landslides. This study revealed that landslides are a result of heavy precipitation and when average monthly rainfall exceeds 168 mm/month, the occurrence of landslides becomes more dominant in the district. Worldwide studies have shown that this value may vary from 150 mm/month to 200 mm/month in the global context [
This may be due to the role played by predisposing factors such as proper land management practices and stable geological settings. However, no recorded landslide below 168 mm/month level is available during the last 28 years.
Developed log-linear model can determine the amount of precipitation needed to trigger landslide in Badulla district. However, limitations exist. In study, log-liner model developed by studying individual rainfall events and corresponding landslides however, other landslide initiation control factors such as morphological, lithological differences, soil characteristics, human activities have not been considered. But these data are difficult to collect and model precisely over large areas. Developed log-linear model can be calibrated using rainfall events for which precipitation measurements and the location and the time of slope failures are known.
Regional and local ID thresholds are the fact that thresholds defined for a specific administrative region in this study it was Badulla district. If ID thresholds based on specific administrative region then it would not be possible to export it for surrounding regions. Therefore it is recommended to consider climatological boundaries rather than the administrative boundaries in further studies.
This study confirmed that most landslides occur in Badulla district during northeast monsoons and inter-monsoon seasons and indicated that a strong correlation exists between frequency of landslides and rainfall seasons of the district. The rainfall shows increasing trends in Badulla district within last three decades. This could indicate the amount of rainfall per day may have increased. In particular, the number of landslides occurred per year increased over the period of 28 years. However, the sudden upsurge on landslide occurrences from 2002 to 2014 can be due to the increase of rainfall intensity during that period. This study could conclude a direct proportional relationship between the amount of rainfall per day and the frequency of landslide events in Badulla district. This will lead to the potential landslide hazards having an increasing trend.
The established I-D threshold reveled that short-duration rainfall events and higher mean rainfall intensities were required to trigger debris/mud flow, while long-duration rainfall events can trigger both landslide and debris flow with almost the low rainfall intensity. This study also demonstrated the importance of peak rainfall intensity to trigger any type of mass movement in Badulla. Generally, most mass movements (83%) occurred within 5 - 6 h of peak rainfall.
Comparing our I-D thresholds with those from other areas of the world shows that the I-D threshold for Badulla is relatively high, particularly for long-duration rainfall events. As Taiwan is characterized by high-relief topography and complex geology (
Badulla district is more vulnerable to deforestation and forest degradation as results of human activities. Reduction of forest cover may cause to change the rainfall threshold value for mass movement in the region that will increase landslide hazard within the district.
We thank Mr. A.L.K. Wijemannage from Department of Meteorology, Sri Lanka, for access to rainfall data. We also acknowledge the Director General of National Building Research Organization for the great support by providing land slide information. This study was supported by Faculty of Graduate Studies, University of Sri Jayewardenepura, for Ph.D. candidate Mr. E. N. C. Perera.
Perera, E.N.C., Jayawardana, D.T. and Jayasinghe, P. (2017) A Rainfall Intensity-Duration Threshold for Mass Movement in Badulla, Sri Lanka. Journal of Geoscience and Environment Protection, 5, 135-152. https://doi.org/10.4236/gep.2017.512010