The determination of statistical and deterministic hydrological landslide-triggering thresholds

 Hydrological landslide-triggering thresholds separate combinations of daily and antecedent rainfall or of rainfall intensity and duration that triggered landslides from those that failed to trigger landslides. They are required for the development of landslide early warning systems. When a large data set on rainfall and landslide occurrence is available, hydrological triggering thresholds are determined in a statistical way. When the data on landslide occurrence is limited, deterministic models have to be used. For shallow landslides directly triggered by percolating rainfall, triggering thresholds can be established by means of one-dimensional hydrological models linked to the infinite slope model. In the case of relatively deep landslides located in topographic hollows and triggered by a slow accumulation of water at the soil-bedrock contact, simple correlations between landslide occurrence and rainfall can no longer be established. Therefore real-time failure probabilities have to be determined using hydrological catchment models in combination with the infinite slope model. Received: 15 October 1997 · Accepted: 25 June 1997     

降雨重现期及其用于滑坡概率分析的探讨

极端气候条件往往会诱发各种地质灾害,而降雨型滑坡的发生则与极值降雨关系密切。为了有效预防和控制汛期滑坡灾害的发生,定量评估滑坡灾害造成的人员与经济风险,讨论了汛期极值降雨条件下滑坡概率的分析方法。利用Gumbel极值分布理论,以三峡库区巴东县1990~2006年日降雨量为基础资料,采用统计分析方法,求取研究区在汛期(6月中旬至9月)最大一次连续降雨量、多日累积最大降雨量的极值及其分布曲线; 在此基础上,以研究区一个滑坡实例为对象,综合采用渗流模拟、稳定性分析和基于蒙特卡罗的滑坡概率分析方法,讨论了降雨极值及其重现期成果分别在降雨新生型滑坡和降雨复活型滑坡概率分析中的应用思路与方法。结果表明,随着重现期的增加,一次降雨过程的降雨量也增加; 随着降雨日数的增加,具有不同重现期降雨事件的累积降雨量均会增加,且重现期越长,累积降雨量值会越大; 降雨极值曲线分别应用于降雨新生型和降雨复活型滑坡概率分析的思路是可行并有效的。     

Frequency–volume relation and prediction of rainfall-induced landslides

Rainfall-induced landslides constitute a major public concern in Hong Kong. This paper investigates two aspects of critical importance to landslide hazard and risk assessment and management: magnitude–cumulative frequency relationship for landslides, and relationship between rainfall and the occurrence of landslides. The results indicated that landslides with a failure volume of not less than 4 m³ have a cumulative frequency–size distribution with a power-law dependence on volume of failure. Analysis of rainfall/landslides showed that the 12-hour rolling rainfall is most important in predicting the number of landslides. Failure volume dependency in the relationships between rainfall and the number of landslides is also presented. However, with an increase in failure volume of landslides, the most important rainfall variable may vary from rainfall of short duration (12-h rolling rainfall) to that of relatively long duration (24-h rolling rainfall).     

Identification of hazard conditions for mudflow occurrence by hydrological model: Application of FLaIR model to Sarno warning system

Mathematical models for forecasting landslides and mudflow movements triggered by heavy rainfalls are useful tools to develop warning systems and hazard mitigation strategy for loss reduction.

In the present paper, an application of Forecasting of Landslides Induced by Rainfalls (FLaIR) hydrological model, correlating the rainfall amount and landslide or mudflow movement occurrences, will be performed. Model application presented here refers to the mudflows of Sarno, Southern Italy, and is based on hourly precipitation data available from a real-time rain gauge installed immediately after the catastrophic event that occurred on May 1998.

The application is extended from October 1998 to May 2002. The main objective is to perform a backanalysis in order to verify the reliability of the proposed scheme for use in a warning system.

Among the most interesting results of the application, the relatively few false alarms for populations given by the model may be highlighted.

The FLaIR model is more useful when it is integrated with a probabilistic model for forecasting precipitation depths during a storm event at an hourly scale. By stochastic modelling of hourly precipitation, it is possible to estimate the probability of reaching the alarm threshold before allowing civil protection actions.     

Quantitative assessment of landslide hazard along transportation lines using historical records

In this paper, a quantitative landslide hazard model is presented for transportation lines, with an example for a road and railroad alignment, in parts of Nilgiri hills in southern India. The data required for the hazard assessment were obtained from historical records available for a 21-year period from 1987 to 2007. A total of 901 landslides from cut slopes along the railroad and road alignment were included in the inventory. The landslides were grouped into three magnitude classes based on the landslide type, volume, scar depth, and run-out distance. To calculate landslide hazard, we estimated the total number of individual landslides per kilometer of the (rail) road for different return periods, based on the relationship between past landslides (recorded in our database) and triggering events. These were multiplied by the probability that the landslides belong to a given magnitude class. This gives the hazard for a given return period expressed as the number of landslides of a given magnitude class per kilometer of (rail) road. The relationship between the total number of landslides and the return period was established using a Gumbel distribution model, and the probability of landslide magnitude was obtained from frequency–volume statistics. The results of the analysis indicate that the total number of landslides, from 1- to 50-year return period, varies from 56 to 197 along the railroad and from 14 to 82 along the road. In total, 18 hazard scenarios were generated using the three magnitude classes and six return periods (1, 3, 5, 15, 25, and 50 years). The hazard scenarios derived from the model form the basis for future direct and indirect landslide risk analysis along the transportation lines. The model was validated with landslides that occurred in the year 2009.     

Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam

The main objective of this study is to assess regional landslide hazards in the Hoa Binh province of Vietnam. A landslide inventory map was constructed from various sources with data mainly for a period of 21 years from 1990 to 2010. The historic inventory of these failures shows that rainfall is the main triggering factor in this region. The probability of the occurrence of episodes of rainfall and the rainfall threshold were deduced from records of rainfall for the aforementioned period. The rainfall threshold model was generated based on daily and cumulative values of antecedent rainfall of the landslide events. The result shows that 15-day antecedent rainfall gives the best fit for the existing landslides in the inventory. The rainfall threshold model was validated using the rainfall and landslide events that occurred in 2010 that were not considered in building the threshold model. The result was used for estimating temporal probability of a landslide to occur using a Poisson probability model. Prior to this work, five landslide susceptibility maps were constructed for the study area using support vector machines, logistic regression, evidential belief functions, Bayesian-regularized neural networks, and neuro-fuzzy models. These susceptibility maps provide information on the spatial prediction probability of landslide occurrence in the area. Finally, landslide hazard maps were generated by integrating the spatial and the temporal probability of landslide. A total of 15 specific landslide hazard maps were generated considering three time periods of 1, 3, and 5 years.     

Hydrologic behavior and flood probability for selected arid basins in Makkah area, western Saudi Arabia

In arid regions, flash floods often occur as a consequence of excessive rainfall. Occasionally causing major loss of property and life, floods are large events of relatively short duration. Makkah area in western Saudi Arabia is characterized by high rainfall intensity that leads to flash floods. This study quantifies the hydrological characteristics and flood probability of some major wadis in western Saudi Arabia, including Na’man, Fatimah, and Usfan. Flood responses in these wadis vary due to the nature and rainfall distribution within these wadis. Rainfall frequency analysis was performed using selected annual maximums of 24-h rainfall from eight stations located in the area. Two of the most applied methods of statistical distribution, Gumbel’s extreme value distribution and log Pearson type III distribution, were applied to maximum daily rainfall data over 26 to 40 years. The Gumbel’s model was found to be the best fitting model for identifying and predicting future rainfall occurrence. Rainfall estimations from different return periods were identified. Probable maximum floods of the major wadis studied were also estimated for different return periods, which were extrapolated from the probable maximum precipitation.     

Towards hydrological triggering mechanisms of large deep-seated landslides

It is a widely accepted idea that hydrologically triggered deep-seated landslides are initiated by an increase in pore-water pressure on potential slip surface induced by rising groundwater level after prolonged period of intense rainfall although the process is not fully understood. In order to contribute to better understanding, the rainfall–groundwater relationships, hydrogeological monitoring and repeated geoelectrical imaging were carried out from March 2007 to April 2011 in large deep-seated landslide near ?ubietová (Western Carpathians) catastrophically reactivated at the end of February 1977. Based on our observations, groundwater level (GWL) response to precipitation differs considerably with respect to both overall hydrological conditions and GWL mean depth. While the rate of GWL increase up to 25 cm/day were measured after some rainfall events during wet periods, noticeably lower recharge rate (up to 1–2 cm/day) and delayed GWL response to rainfall (usually from 2 weeks to 2–4 months) were observed at the beginning of the wet season after considerable depression of GWLs due to previous effective rainfall deficit. Likewise, slow GWL fluctuations without short-term oscillations are typical for deeper GWLs. Thus, long-term (several seasons to several years) hydrological conditions affect markedly groundwater response to rainfall events in the studied landslide and can be crucial for its behaviour. Comparison of hydrological conditions characterising the analysed period with those that accompanied the landslide reactivation in 1977 allow us to assume that slightly above-average rainy season following the prolonged wet period can be far more responsible for movement acceleration (and possibly failure initiation) in deep landslides than the isolated season of extreme precipitation following a longer dry period. This is true especially for landslides in regions with significant seasonal temperature changes where potential effective precipitation (PEP), calculated as excess of precipitation (P) over potential evapotranspiration (PET), may be efficiently used for estimation of slope saturation condition.     

基于位移比模型的三峡库区云阳县域内蠕变型滑坡降雨预警

建立高效合理的区域滑坡灾害降雨预警模型对滑坡防治具有重要意义.然而以往的研究多侧重于临滑预警,对蠕变型滑坡在强降雨工况下的短暂加速变形的预警研究还有待深入.以三峡库区云阳县域内滑坡为例,首先根据滑坡地表位移监测数据的特点对统计样本进行合理筛选.再通过降雨因子与滑坡发生的相关性分析以及对滑坡在降雨条件下位移变化情况的数值模拟,确定了适用于不同时间阶段的降雨统计变量.然后将考虑了滑坡规模特征的滑坡位移比（累计位移与滑坡纵长之比）作为变形指标,分时段统计滑坡地表位移监测数据与历史降雨信息,建立了日降雨数据与月位移数据的对应关系,得到了可用于确定降雨量阈值的位移比模型,并获得了云阳县蠕变型滑坡的五级预警分区.最后分别选用研究区滑坡险情实例、长年位移监测数据及极端降雨事件对模型预警效果进行检验.结果显示基于专业监测数据的位移比模型的滑坡降雨预警结果与实际情况相符,可为蠕变型滑坡的预警预报提供依据.      

降雨诱发深层老滑坡复活变形的动态作用机制

强降雨易引发大型深层老滑坡的复活变形,研究其作用机制对建立滑坡变形破坏的降雨阈值,实现滑坡灾害的预警预报具有重要意义.以三峡库区秭归县谭家湾大型深层老滑坡为例,在地表宏观裂缝时空分布规律的精细描述基础上,结合15年的人工监测和2年的实时监测数据,分析了老滑坡的复活变形特征和发展过程.通过滑坡阶跃阶段的位移与降雨（当前降雨和前期降雨）的相关性分析,提出了降雨对深层滑坡复活变形演化过程的动态作用机制.谭家湾滑坡的7次“阶跃”变形与强降雨相关,但累积位移增量与累积降雨量无明显正相关关系,水平位移增量基本相同时,累积降雨量明显不同.引起第一次阶跃变形的累积降雨量和最大日降雨量均明显大于后续阶段,可能受控于强降雨的作用机制由“孔隙渗流”为主,逐渐转变为“渗透性增加的孔隙渗流+裂隙优势流”的综合渗流模式.这对进一步深入研究强降雨诱发深层老滑坡阶跃变形的内在机理与灾害预警具有一定的理论意义和参考价值.     

DEM-based deterministic landslide hazard analysis in the Lesser Himalaya of Nepal

In Nepal, people live in widely spread settlements in the fragile Himalayan terrains, and suffer more from landslides than from any other type of natural disaster. The small-scale rainfall-triggered landslides in the Lesser Himalaya of Nepal are generally shallow (about 0.5 to 2.5 m) and are triggered by changes in the physical property of soil layers during rainfall. The relation between landslides and slope hydrology has received little attention in Himalayan landslide research. Thus, this paper deals with the probability of slope failure during extreme rainfall events by considering a digital elevation model (DEM)-based hydrological model for soil saturation depth and an infinite slope stability model. Deterministic distributed analysis in a geographic information system (GIS) was carried out to calculate the probability of slope failure. A simple method of error propagation was used to calculate the variance of the safety factors and the probability of failure. When normally distributed failure probability values were checked against existing landslides, it was found that more than 50% of the pixels of existing landslides coincided with a high calculated probability of failure. Although the deterministic distributed analysis has certain drawbacks, as described by previous researchers, this study concluded that the calculated failure probability can be utilised to predict the probability of slope failure in Himalayan terrain during extreme rainfall events.     

浅层滑坡诱发沟谷泥石流的地形和降雨条件

2011年贵州省望谟县打易镇的大范围浅层滑坡诱发的沟谷泥石流提供了研究这类泥石流地形和降雨条件的机会。在地质条件一致和小区域内的降雨条件基本一致的情况下,地形条件就是这些泥石流暴发与否的唯一决定因素。对比一些重要的地形因素与泥石流暴发的关系,得出了由流域面积、沟床纵比降和25°~45°山坡坡度面积比组成的泥石流综合地形因子T。在地形因子T的基础上,研究获得了由前期降雨量、1 h降雨强度、年平均降雨量等组成的降雨因子R。由地形因子T和降雨因子R获得的临界条件P可以判断该区域的泥石流暴发。由于研究工作部分基于泥石流的形成机理,研究成果还可用于其他区域的泥石流形成预测,为泥石流的预测预报提供了一个较好的方法。     

Rainfall induced debris flows in pyroclastic deposits, Campania (southern Italy)

A combination of empirical and physically based hydrological models has been used to analyze historical data on rainfall and debris-flow occurrence in western Campania, to examine the correlation between rainfall and debris-flow events.

Rainfall data from major storms recorded in recent decades in western Campania were compiled, including daily series from several rain gauges located inside landslide areas, supplemented by hourly rainfall data from some of the principal storms.

A two-phase approach is proposed. During phase 1, soil moisture levels have been modelled as the hydrological balance between precipitation and evapotranspiration, on a daily scale, using the method of Thornthwaite [Geograph. Rev. 38 (1948) 55].

Phase 2 is related to the accumulation of surplus moisture from intense rainfall, leading to the development of positive pore pressures. These interactions take place on an hourly time scale by the “leaky barrel” (LB) model described by Wilson and Wiezoreck [Env. Eng. Geoscience, 1 (1995) 11]. In combination with hourly rainfall records, the LB model has been used to compare hydrological effects of different storms. The critical level of retained rain water has been fixed by the timing of debris-flow activity, related to recorded storm events.

New rainfall intensity–duration thresholds for debris-flow initiation in western Campania are proposed. These thresholds are related to individual rain gauge and assume a previously satisfied field capacity condition. The new thresholds are somewhat higher than those plotted by previous authors, but are thought to be more accurate and thus need less conservatism.     

Landslide-hazard mapping through multi-technique activity assessment: an example from the Betic Cordillera (southern Spain)

Landslide hazard in a region limited to data from a regional scale about triggering factors is assessed via cross tabulation between determining factors and landslides with recent activity. Firstly, landslide susceptibility was evaluated and validated through a bivariate statistical method between the previously identified stability conditioning factors and the mapped landslides. In this way, the most susceptible areas for assessing landslide hazards were selected. The main problem to solve in this type of research is the landslide activity. For this purpose, several techniques were applied: news reports, differential interferometric synthetic aperture radar, digital photogrammetry, light detection and ranging, photointerpretation, and dendrochronology. Both the strong and weak points of these techniques are also mentioned. The landslide return period was computed via the association between landslide activity and triggering factors, in this case annual rainfall. Finally, landslide hazard was mapped solely based on landslides with recent activity and their computed return period. The relationship between landslide occurrence and triggering factors shows that, according to both the considered assumptions and the observations made, deep-seated landslides are triggered or reactivated together with superficial landslides once every 18 years, while superficial landslides as flows or falls occur once every 5 years. The results show that there is generally a low landslide hazard in the study zone, especially when compared to landslide susceptibility. This means that landslides are mainly dormant from a natural evolution point of view, but could be reactivated as a result of geomorphological, climate, or human changes. In any case, the landslide hazard is successfully assessed, with a prediction of a 6% annual probability of a high hazard in 5% of the area, intersecting with the main infrastructures of the region; thus, control strategies are justified in order to avoid damage in extraordinary rainfall periods.     

Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy)

Mountainous areas surrounding the Campanian Plain and the Somma-Vesuvius volcano (southern Italy) are among the most risky areas of Italy due to the repeated occurrence of rainfall-induced debris flows along ash-fall pyroclastic soil-mantled slopes. In this geomorphological framework, rainfall patterns, hydrological processes taking place within multi-layered ash-fall pyroclastic deposits and soil antecedent moisture status are the principal factors to be taken into account to assess triggering rainfall conditions and the related hazard. This paper presents the outcomes of an experimental study based on integrated analyses consisting of the reconstruction of physical models of landslides, in situ hydrological monitoring, and hydrological and slope stability modeling, carried out on four representative source areas of debris flows that occurred in May 1998 in the Sarno Mountain Range. The hydrological monitoring was carried out during 2011 using nests of tensiometers and Watermark pressure head sensors and also through a rainfall and air temperature recording station. Time series of measured pressure head were used to calibrate a hydrological numerical model of the pyroclastic soil mantle for 2011, which was re-run for a 12-year period beginning in 2000, given the availability of rainfall and air temperature monitoring data. Such an approach allowed us to reconstruct the regime of pressure head at a daily time scale for a long period, which is representative of about 11 hydrologic years with different meteorological conditions. Based on this simulated time series, average winter and summer hydrological conditions were chosen to carry out hydrological and stability modeling of sample slopes and to identify Intensity-Duration rainfall thresholds by a deterministic approach. Among principal results, the opposing winter and summer antecedent pressure head (soil moisture) conditions were found to exert a significant control on intensity and duration of rainfall triggering events. Going from winter to summer conditions requires a strong increase of intensity and/or duration to induce landslides. The results identify an approach to account for different hazard conditions related to seasonality of hydrological processes inside the ash-fall pyroclastic soil mantle. Moreover, they highlight another important factor of uncertainty that potentially affects rainfall thresholds triggering shallow landslides reconstructed by empirical approaches.     

A distributed hydrological–geotechnical model using satellite-derived rainfall estimates for shallow landslide prediction system at a catchment scale

This paper describes the potential applicability of a hydrological–geotechnical modeling system using satellite-based rainfall estimates for a shallow landslide prediction system. The physically based distributed model has been developed by integrating a grid-based distributed kinematic wave rainfall-runoff model with an infinite slope stability approach. The model was forced by the satellite-based near real-time half-hourly CMORPH global rainfall product prepared by NOAA-CPC. The method combines the following two model outputs necessary for identifying where and when shallow landslides may potentially occur in the catchment: (1) the time-invariant spatial distribution of areas susceptible to slope instability map, for which the river catchment is divided into stability classes according to the critical relative soil saturation; this output is designed to portray the effect of quasi-static land surface variables and soil strength properties on slope instability and (2) a produced map linked with spatiotemporally varying hydrologic properties to provide a time-varying estimate of susceptibility to slope movement in response to rainfall. The proposed hydrological model predicts the dynamic of soil saturation in each grid element. The stored water in each grid element is then used for updating the relative soil saturation and analyzing the slope stability. A grid of slope is defined to be unstable when the relative soil saturation becomes higher than the critical level and is the basis for issuing a shallow landslide warning. The method was applied to past landslides in the upper Citarum River catchment (2,310 km²), Indonesia; the resulting time-invariant landslide susceptibility map shows good agreement with the spatial patterns of documented historical landslides (1985–2008). Application of the model to two recent shallow landslides shows that the model can successfully predict the effect of rainfall movement and intensity on the spatiotemporal dynamic of hydrological variables that trigger shallow landslides. Several hours before the landslides, the model predicted unstable conditions in some grids over and near the grids at which the actual shallow landslides occurred. Overall, the results demonstrate the potential applicability of the modeling system for shallow landslide disaster predictions and warnings.     

Flood frequency analysis based on simulated peak discharges

Flood frequency approaches vary from statistical methods, directly applied on the observed annual maximum flood series, to adopting rainfall–runoff simulation models that transform design rainfalls to flood discharges. Reliance on statistical flood frequency analysis depends on several factors such as the selected probability distribution function, estimation of the function parameters, possible outliers, and length of the observed flood series. Through adopting the simulation approach in this paper, watershed-average rainfalls of various occurrence probabilities were transformed into the corresponding peak discharges using a calibrated hydrological model. A Monte Carlo scheme was employed to consider the uncertainties involved in rainfall spatial patterns and antecedent soil moisture condition (AMC). For any given rainfall depth, realizations of rainfall spatial distribution and AMC conditions were entered as inputs to the model. Then, floods of different return periods were simulated by transforming rainfall to runoff. The approach was applied to Tangrah watershed in northeastern Iran. It was deduced that the spatial rainfall distribution and the AMCs exerted a varying influence on the peak discharge of different return periods. Comparing the results of the simulation approach with those of the statistical frequency analysis revealed that, for a given return period, flood quantiles based on the observed series were greater than the corresponding simulated discharges. It is also worthy to note that existence of outliers and the selection of the statistical distribution function has a major effect in increasing the differences between the results of the two approaches.     

Interpretation of probability of landsliding triggered by rainfall

This paper is a contribution to an important aspect of the systematic and quantitative assessment of landslide hazard and risk. The focus is on site-specific and detailed assessment for rainfall-triggered landslides and, in particular, on the estimation and interpretation of the temporal probability of landsliding. Historical rainfall data over a 109-year period were analysed with particular reference to a site along the Unanderra and Moss Vale Railway Line in the State of New South Wales, Australia. It is shown that the recurrence interval of landsliding and hence annual probability of occurrence is subject to significant uncertainty and that it cannot be regarded as a constant. Accordingly landslide hazard varies spatially as well as being a function of time. For the example case study considered in this paper the annual probability of landslide occurrence was estimated to be in the range 0.026–0.172. However, the mean annual probability of landslide reactivation was estimated to be in the range 0.037–0.078. Utilisation of methods for probability assessment proposed in this paper will contribute to more realistic assessment of hazard and risk and, therefore, to more efficient risk management.     

Comparison of statistical methods and multi-time validation for the determination of the shallow landslide rainfall thresholds

Shallow landslides are unforeseeable phenomena often resulting in critical conditions in terms of people’s safety and damage. The main purpose of this paper is the comparison of different statistical methods used to determine the rainfall thresholds for the shallow landslide occurrence. Rainfall data over a 46-year period were collected for one rain gauge located in a test area of northwest Italy (Riviera Spezzina; RS). In the RS, intense rainfalls often induce shallow landslides causing damage and sometimes casualties. The rainfall events occurred in the 1967–2006 period were classified as events inducing shallow landslides (SLEs_1967–2006) and events that did not trigger shallow landslides (NSLEs_1967–2006). Thresholds for various percentiles of SLEs_1967–2006 were computed by identifying the lower limit above which shallow landslides occurred. Another set of thresholds, corresponding to different probabilities of occurrence, was determined using SLEs_1967–2006 and NSLEs_1967–2006. The least-squares linear fit (LSF) and the quantile regression (QR) techniques were employed in the former approach, while the logistic regression (LR) was applied in the latter. The thresholds were validated with the same data used for their definition and with the data recorded in the 2008–2014 period. Contingency tables were created and contingencies and skill scores were computed. The 10% probability threshold obtained using the LR method is characterized by the best values of at least two skill scores for both periods considered; therefore, it may be considered the “best” threshold for the RS. The results of this work can help the choice of the best statistical method to determine the shallow landslide rainfall thresholds.     

Rainfall patterns for shallow landsliding in perialpine Slovenia

This paper presents two types of analysis: an antecedent rainfall analysis based on daily rainfall and an intensity-duration analysis of rainfall events based on hourly data in perialpine Slovenia in the ?kofjelo?ko Cerkljansko hills. For this purpose, eight rainfall events that are known to have caused landslides in the period from 1990 to 2010 were studied. Over the observed period, approximately 400 records of landslides were collected. Rainfall data were obtained from three rain gauges. The daily rainfall from the 30 days before landslide events was investigated based on the type of landslides and their geo-environmental setting, the dates of confirmed landslide activity and different consecutive rainfall periods. The analysis revealed that the rainfall events triggering slope failure can be divided into two groups according to the different antecedent periods. The first group of landslides typically occurred after short-duration rainstorms with high intensity, when the daily rainfall exceeded the antecedent rainfall. The second group comprises the rainfall events with a longer antecedent period of at least 7 days. A comparison of the plotted peak and mean intensities indicates that the rainfall patterns that govern slope failure are similar but do not necessarily reflect the rainfall intensity at the time of shallow landslides in the Dav?a or Poljane areas, where the majority of the landslides occurred. Because of several limitations, the suggested threshold cannot be compared and evaluated with other thresholds.