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1.
This paper examines temporal correlations and temporal clustering of a proxy historical landslide time series, 2255 reported landslides 1951–2002, for an area in the Emilia‐Romagna Region, Italy. Landslide intensity is measured by the number of reported landslides in a day (DL) and in an ‘event’ (Sevent) of consecutive days with landsliding. The non‐zero values in both time series DL and Sevent are unequally spaced in time, and have heavy‐tailed frequency‐size distributions. To examine temporal correlations, we use power‐spectral analysis (Lomb periodogram) and surrogate data analysis, confronting our original DL and Sevent time series with 1000 shuffled (uncorrelated) versions. We conclude that the landslide intensity series DL has strong temporal correlations and Sevent has likely temporal correlations. To examine temporal clustering in DL and Sevent, we consider extremes over different landslide intensity thresholds. We first examine the statistical distribution of interextreme occurrence times, τ, and find Weibull distributions with parameter γ << 1·0 [DL] and γ < 1·0 [Sevent]; thus DL and Sevent each have temporal correlations, but Sevent to a lesser degree. We next examine correlations between successive interextreme occurrence times, τ. Using autocorrelation analysis applied to τ, combined with surrogate data analysis, we find for DL linear correlations in τ, but for Sevent inconclusive results. However, using Kendall's rank correlation analysis we find for both DL and Sevent the series of τ are strongly correlated. Finally, we apply Fano Factor analysis, finding for both DL and Sevent the timings of extremes over a given threshold exhibit a fractal structure and are clustered in time. In this paper, we provide a framework for examining time series where the non‐zero values are strongly unequally spaced and heavy‐tailed, particularly important in the Earth Sciences due to their common occurrence, and find that landslide intensity time series exhibit temporal correlations and clustering. Many landslide models currently are designed under the assumption that landslides are uncorrelated in time, which we show is false. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

2.
A model‐based method is proposed for improving upon existing threshold relationships which define the rainfall conditions for triggering shallow landslides but do not allow the magnitude of landsliding (i.e. the number of landslides) to be determined. The SHETRAN catchment‐scale shallow landslide model is used to quantify the magnitude of landsliding as a function of rainfall return period, for focus sites of 180 and 45 km2 in the Italian Southern Alps and the central Spanish Pyrenees. Rainfall events with intensities of different return period are generated for a range of durations (1‐day to 5‐day) and applied to the model to give the number of landslides triggered and the resulting sediment yield for each event. For a given event duration, simulated numbers of landslides become progressively less sensitive to return period as return period increases. Similarly, for an event of given return period, landslide magnitude becomes less sensitive to event duration as duration increases. The temporal distribution of rainfall within an event is shown to have a significant impact on the number of landslides and the timing of their occurrence. The contribution of shallow landsliding to catchment sediment yield is similarly quantified as a function of the rainfall characteristics. Rainfall intensity–duration curves are presented which define different levels of landsliding magnitude and which advance our predictive capability beyond, but are generally consistent with, published threshold curves. The magnitude curves are relevant to the development of guidelines for landslide hazard assessment and forecasting. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

3.
Rainfall characteristics for shallow landsliding in Seattle,Washington, USA   总被引：2，自引：0，他引：2  
Shallow landsliding in the Seattle, Washington, area, has caused the occasional loss of human life and millions of dollars in damage to property. The effective management of the hazard requires an understanding of the rainfall conditions that result in landslides. We present an empirical approach to quantify the antecedent moisture conditions and rainstorm intensity and duration that have triggered shallow landsliding using 25 years of hourly rainfall data and a complementary record of landslide occurrence. Our approach combines a simple water balance to estimate the antecedent moisture conditions of hillslope materials and a rainfall intensity–duration threshold to identify periods when shallow landsliding can be expected. The water balance is calibrated with field‐monitoring data and combined with the rainfall intensity–duration threshold using a decision tree. Results are cast in terms of a hypothetical landslide warning system. Two widespread landslide events are correctly identified by the warning scheme; however, it is less accurate for more isolated landsliding. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

4.
Landsliding induced by earthquakes and rainstorms in montane regions is not only a sculptor for shaping the landscape, but also a driver for delivering sediments and above‐ground biomass downstream. However, the terrain attributes of earthquake‐ and rainstorm‐induced landslides are less discussed comprehensively in Taiwan. As part of an island‐wide inventory, we here compare and contrast the landslide terrain attributes resulting from two catastrophic events: the Chi‐Chi earthquake (M w = 7.6, September 1999) and typhoon Morakot (rainfall >2500 mm, August 2009). Results show that the earthquake‐induced landslides are relatively small, round‐shaped and prone to occur primarily in middle and toe of slopes. In contrast, the rainstorm‐induced landslides are larger, horseshoe‐shaped and preferentially occurring in slope toes. Also, earthquake‐induced landslides, particularly large landslides, are usually found at steeper gradients, whereas rainstorm‐induced landslides aggregate at gradients between 25° and 40°. Lithologic control plays a secondary role in landsliding. From an island‐wide perspective, high landslide density locates in the region of earthquake intensity ≥ VI or one‐day rainfall ≥600 mm day?1. Through the landslide patterns and their terrain attributes, our retrospective approach sheds light on accessing the historical and remote events for close geophysical investigations. Finally, we should bear in mind that the landslide location, size, and terrain attributes varying with triggers may affect the landscape evaluation or biogeochemical processes in landslide‐dominated regions. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

5.
Landslide inventories and their statistical properties   总被引：1，自引：0，他引：1  
Landslides are generally associated with a trigger, such as an earthquake, a rapid snowmelt or a large storm. The landslide event can include a single landslide or many thousands. The frequency–area (or volume) distribution of a landslide event quanti?es the number of landslides that occur at different sizes. We examine three well‐documented landslide events, from Italy, Guatemala and the USA, each with a different triggering mechanism, and ?nd that the landslide areas for all three are well approximated by the same three‐parameter inverse‐gamma distribution. For small landslide areas this distribution has an exponential ‘roll‐over’ and for medium and large landslide areas decays as a power‐law with exponent ‐2·40. One implication of this landslide distribution is that the mean area of landslides in the distribution is independent of the size of the event. We also introduce a landslide‐event magnitude scale mL = log(NLT), with NLT the total number of landslides associated with a trigger. If a landslide‐event inventory is incomplete (i.e. smaller landslides are not included), the partial inventory can be compared with our landslide probability distribution, and the corresponding landslide‐event magnitude inferred. This technique can be applied to inventories of historical landslides, inferring the total number of landslides that occurred over geologic time, and how many of these have been erased by erosion, vegetation, and human activity. We have also considered three rockfall‐dominated inventories, and ?nd that the frequency–size distributions differ substantially from those associated with other landslide types. We suggest that our proposed frequency–size distribution for landslides (excluding rockfalls) will be useful in quantifying the severity of landslide events and the contribution of landslides to erosion. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

6.
In this work, a transient rainfall infiltration and grid‐based regional slope‐stability model (TRIGRS) was implemented in a case study of Yan'an City, Northwest China. In this area, widespread shallow landslides were triggered by the 12 July 2013 exceptional rainstorm event. A high‐resolution DEM, soil parameters from in‐situ and laboratory measurements, water table depths, the maximum depth of precipitation infiltration and rain‐gauge‐corrected precipitation of the event, were used as inputs in the TRIGRS model. Shallow landslides triggered on the same day were used to evaluate the modeling results. The summarized results are as follows: (i) The characteristics and distribution of thirty‐five shallow landslides triggered by the 12 July 2013 rainfall event were identified in the study area and all were classified as shallow landslides with the maximum depth, area and volume less than 3 m, 200 m2 and 1000 m3, respectively, (ii) Four intermediate factor of safety (FS) maps were generated using the TRIGRS model to represent the scenarios 6, 12, 18 and 24 hours after the storm event. The area with FS < 1 increased with the rainfall duration. The percentage of the area with FS < 1 was 0.2%, 3.3%, 3.8% and 5.1% for the four stages, respectively. Twenty‐four hours after the rainstorm, TRIGRS predicted that 1255 grid cells failed, which is consistent with the field data. (iii) TRIGRS generated more satisfactory results at a given precipitation threshold than SINMAP, which is ideal for landslide hazard zoning for land‐use planning at the regional scale. Comparison results showed that TRIGRS is more useful for landslide prediction for a certain precipitation threshold, also in the regional scale. (iv) Analysis of the responses of loess slope prone to slope failure after different precipitation scenarios revealed that loess slopes are particularly sensitive to extended periods of heavy precipitation. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

7.
Rainfall thresholds for shallow landslide initiation were determined for hillslopes with two types of bedrock, permeable sandstone and impermeable mudstone, in the Boso Peninsula, Japan. The pressure‐head response to rainfall was monitored above a slip scarp due to earlier landslides. Multiple regression analysis estimated the rainfall thresholds for landsliding from the relation between the magnitude of the rainfall event and slope instability caused by the increased pressure heads. The thresholds were expressed as critical combinations of rainfall intensity and duration, incorporating the geotechnical properties of the hillslope materials and also the slope hydrological processes. The permeable sandstone hillslope has a greater critical rainfall and hence a longer recurrence interval than the impermeable mudstone hillslope. This implies a lower potential for landsliding in sandstone hillslopes, corresponding to lower landslide activity. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

8.
Landslide erosion is a dominant hillslope process and the main source of stream sediment in tropical, tectonically active mountain belts. In this study, we quantified landslide erosion triggered by 24 rainfall events from 2001 to 2009 in three mountainous watersheds in Taiwan and investigated relationships between landslide erosion and rainfall variables. The results show positive power‐law relations between landslide erosion and rainfall intensity and cumulative rainfall, with scaling exponents ranging from 2·94 to 5·03. Additionally, landslide erosion caused by Typhoon Morakot is of comparable magnitude to landslide erosion caused by the Chi‐Chi Earthquake (MW = 7·6) or 22–24 years of basin‐averaged erosion. Comparison of the three watersheds indicates that deeper landslides that mobilize soil and bedrock are triggered by long‐duration rainfall, whereas shallow landslides are triggered by short‐duration rainfall. These results suggest that rainfall intensity and watershed characteristics are important controls on rainfall‐triggered landslide erosion and that severe typhoons, like high‐magnitude earthquakes, can generate high rates of landslide erosion in Taiwan. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

9.
Empirical prediction of coseismic landslide dam formation   总被引：1，自引：0，他引：1       下载免费PDF全文
In this study we develop an empirical method to estimate the volume threshold for predicting coseismic landslide dam formation using landscape parameters obtained from digital elevation models (DEMs). We hypothesize that the potential runout and volume of landslides, together with river features, determine the likelihood of the formation of a landslide dam. To develop this method, a database was created by randomly selecting 140 damming and 200 non‐damming landslides from 501 landslide dams and > 60 000 landslides induced by the Mw 7.9 2008 Wenchuan earthquake in China. We used this database to parameterize empirical runout models by stepwise multivariate regression. We find that factors controlling landslide runout are landslide initiation volume, landslide type, internal relief (H) and the H/L ratio (between H and landslide horizontal distance to river, L). In order to obtain a first volume threshold for a landslide to reach a river, the runout regression equations were converted into inverse volume equations by taking the runout to be the distance to river. A second volume threshold above which a landslide is predicted to block a river was determined by the correlation between river width and landslide volume of the known damming landslides. The larger of these two thresholds was taken as the final damming threshold. This method was applied to several landslide types over a fine geographic grid of assumed initiation points in a selected catchment. The overall prediction accuracy was 97.4% and 86.0% for non‐damming and damming landslides, respectively. The model was further tested by predicting the damming landslides over the whole region, with promising results. We conclude that our method is robust and reliable for the Wenchuan event. In combination with pre‐event landslide susceptibility and frequency–size assessments, it can be used to predict likely damming locations of future coseismic landslides, thereby helping to plan emergency response. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

10.
The growing availability of digital topographic data and the increased reliability of precipitation forecasts invite modelling efforts to predict the timing and location of shallow landslides in hilly and mountainous areas in order to reduce risk to an ever‐expanding human population. Here, we exploit a rare data set to develop and test such a model. In a 1·7 km2 catchment a near‐annual aerial photographic coverage records just three single storm events over a 45 year period that produced multiple landslides. Such data enable us to test model performance by running the entire rainfall time series and determine whether just those three storms are correctly detected. To do this, we link a dynamic and spatially distributed shallow subsurface runoff model (similar to TOPMODEL) to an in?nite slope model to predict the spatial distribution of shallow landsliding. The spatial distribution of soil depth, a strong control on local landsliding, is predicted from a process‐based model. Because of its common availability, daily rainfall data were used to drive the model. Topographic data were derived from digitized 1 : 24 000 US Geological Survey contour maps. Analysis of the landslides shows that 97 occurred in 1955, 37 in 1982 and ?ve in 1998, although the heaviest rainfall was in 1982. Furthermore, intensity–duration analysis of available daily and hourly rainfall from the closest raingauges does not discriminate those three storms from others that did not generate failures. We explore the question of whether a mechanistic modelling approach is better able to identify landslide‐producing storms. Landslide and soil production parameters were ?xed from studies elsewhere. Four hydrologic parameters characterizing the saturated hydraulic conductivity of the soil and underlying bedrock and its decline with depth were ?rst calibrated on the 1955 landslide record. Success was characterized as the most number of actual landslides predicted with the least amount of total area predicted to be unstable. Because landslide area was consistently overpredicted, a threshold catchment area of predicted slope instability was used to de?ne whether a rainstorm was a signi?cant landslide producer. Many combinations of the four hydrological parameters performed equally well for the 1955 event, but only one combination successfully identi?ed the 1982 storm as the only landslide‐producing storm during the period 1980–86. Application of this parameter combination to the entire 45 year record successfully identi?ed the three events, but also predicted that two other landslide‐producing events should have occurred. This performance is signi?cantly better than the empirical intensity–duration threshold approach, but requires considerable calibration effort. Overprediction of instability, both for storms that produced landslides and for non‐producing storms, appears to arise from at least four causes: (1) coarse rainfall data time scale and inability to document short rainfall bursts and predict pressure wave response; (2) absence of local rainfall data; (3) legacy effect of previous landslides; and (4) inaccurate topographic and soil property data. Greater resolution of spatial and rainfall data, as well as topographic data, coupled with systematic documentation of landslides to create time series to test models, should lead to signi?cant improvements in shallow landslides forecasting. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

11.
Many investigators have attempted to define the threshold of landslide failure, that is, the level of the selected climatic variable above which a rainfall-induced landslide occurs. Intensity–duration (I–d) relationships are the most common type of empirical thresholds proposed in the literature for predicting landslide occurrence induced by rainfall. Recent studies propose the use of the kinetic power per unit volume of rainfall (J m−2 mm−1) to quantify the threshold of landslides induced by rainfall. In this paper, the relationship between rainfall duration and kinetic power corresponding to landslides triggered by rain was used to propose a new approach to define the threshold for predicting landslide occurrence. In particular, for the first time, a kinetic power per unit volume of rainfall–duration relationship is proposed for defining the minimum threshold needed for landslide failure. This new method can be applied using commonly used relationship for estimating the kinetic power per unit volume of rainfall and a new equation based on the measured raindrop size distribution. The applicability of this last method was tested using the data of rainfall intensity, duration and median volume diameter for 51 landslides in Taiwan. For the 51 landslides, the comparison between the measured pairs' kinetic power–duration and all selected relationships demonstrated that the equation based on the measured raindrop size distribution is the best method to define the landslide occurrence threshold, as it is both a process-oriented approach and is characterized by the best statistical performance. This last method has also the advantage to allow the forecasting of landslide hazard before the end of the rainfall event, since the rainfall kinetic power threshold value can be exceeded for a time interval less than the event duration.  相似文献   

12.
—Rainfall-triggered landslides constitute a serious hazard and an important geomorphic process in many parts of the world. Attempts have been made at various scales in a number of countries to investigate triggering conditions in order to identify patterns in behaviour and, ultimately, to define or calculate landslide-triggering rainfall thresholds. This study was carried out in three landslide-prone regions in the North Island of New Zealand. Regional landslide-triggering rainfall thresholds were calculated using an empirical “Antecedent Daily Rainfall Model.” In this model, first introduced by, triggering rainfall conditions are represented by a combination of rainfall occurring in a period before the event (antecedent rainfall) and rainfall on the day of the event. A physically-based decay coefficient is derived for each region from the recessional behaviour of storm hydrographs and is used to produce an index for antecedent rainfall. Statistical techniques are employed to obtain the thresholds which best separate the rainfall conditions associated with landslide occurrence from those of non-occurrence or a given probability of occurrence.The resultant regional models are able to represent the probability of occurrence of landsliding events on the basis of rainfall conditions. The calculated thresholds show regional differences in susceptibility of a given landscape to landslide-triggering rainfall. These differences relate to both the landslide database and the difference of existing physical conditions between the regions.  相似文献   

13.
Sediments produced by landslides are crucial in the sediment yield of a catchment, debris flow forecasting, and related hazard assessment. On a regional scale, however, it is difficult and time consuming to measure the volumes of such sediment. This paper uses a LiDAR‐derived digital terrain model (DTM) taken in 2005 and 2010 (at 2 m resolution) to accurately obtain landslide‐induced sediment volumes that resulted from a single catastrophic typhoon event in a heavily forested mountainous area of Taiwan. The landslides induced by Typhoon Morakot are mapped by comparison of 25 cm resolution aerial photographs taken before and after the typhoon in an 83.6 km2 study area. Each landslide volume is calculated by subtraction of the 2005 DTM from the 2010 DTM, and the scaling relationship between landslide area and its volume are further regressed. The relationship between volume and area are also determined for all the disturbed areas (VL = 0.452AL1.242) and for the crown areas of the landslides (VL = 2.510AL1.206). The uncertainty in estimated volume caused by use of the LiDAR DTMs is discussed, and the error in absolute volume estimation for landslides with an area >105 m2 is within 20%. The volume–area relationship obtained in this study is also validated in 11 small to medium‐sized catchments located outside the study area, and there is good agreement between the calculation from DTMs and the regression formula. By comparison of debris volumes estimated in this study with previous work, it is found that a wider volume variation exists that is directly proportional to the landslide area, especially under a higher scaling exponent. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

14.
The first application of the SHETRAN basin‐scale, landslide erosion and sediment yield model is carried out for a major landsliding event in the upper 505 km2 of the Llobregat basin, in the eastern Spanish Pyrenees, in November 1982. The model simulates the spatial distribution of shallow landslides and their sediment yield. Acknowledging uncertainty in the model parameter evaluation, the aim of the application was not to reproduce the observed occurrence of landslides as accurately as possible with one simulation, but to bracket the observed pattern with several simulations representing uncertainty in the key input conditions. Bounds on the landslide simulations were thus determined as a function of uncertainty in the vegetation root cohesion (used in the model factor of safety calculations). The resulting upper bound considerably overestimates the observed pattern (17 000 landslides compared with an observation of around 700), but it reproduces several of the principal clusters in the observed pattern. The lower bound contains around 500 landslides. The sediment yield estimates (2670–14 630 t km?2) are comparable to measurements elsewhere in the Pyrenees for extreme events. The results demonstrate an ability to simulate the basin‐scale landslide response to a rainfall event and the resulting sediment yield. They also highlight the need for further research in setting the uncertainty bounds and in avoiding large overestimates of landslide occurrence arising in part from a current inability to model small‐scale controls for a basin of the given size. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

15.
Improving empirical prediction of plot soil erosion at the event temporal scale has both scientific and practical importance. In this investigation, 492 runoff and soil loss data from plots of different lengths, λ (11 ≤ λ ≤ 44 m), and steepness, s (14.9 ≤ s ≤ 26.0%), established at the Sparacia experimental station, in Sicily, South Italy, were used to derive a new version of Universal Soil Loss Equation (USLE)‐MM model, by only assuming a value of one for the topographic length, L, and steepness, S, factors for λ = 22 m and s = 9%, respectively. An erosivity index equal to (QREI30)b1, QR and EI30 being the runoff coefficient and the event rainfall erosivity index, respectively, with b1 > 1 was found to be an appropriate choice for the Sparacia area. The specifically developed functions for L and S did not differ appreciably from other, more widely accepted relationships (maximum differences by a factor of 1.22 for L and 1.09 for S). The new version of the USLE‐MM performed particularly well for highly erosive events, because predicted soil loss differed by not more than a factor of 1.19 from the measured soil loss for measured values of more than 100 Mg ha?1. The choice of the relationships to predict topographic effects on plot soil loss should not represent a point of particular concern in the application of the USLE‐MM in other environments. However, tests of the empirical approach should be carried out in other experimental areas in an attempt to develop analytical tools, usable at the event temporal scale, reasonably simple and of wide validity. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

16.
地震应急是减轻地震灾害的重要途径之一。地震应急工作具有时间紧迫、事关重大的特点。2017年8月8日四川九寨沟MS7.0级地震发生后,为快速、准确地提供地震引发的滑坡灾害分布,本研究基于震后第一天获取到的高分辨率遥感影像（高分二号卫星影像、北京二号卫星影像）,通过人工目视解译的方法初步建立了四川九寨沟地震滑坡编目。结果表明,该地震至少触发了622处同震滑坡,分布在沿使用影像边界框定的面积为3919km2的区域内。本研究还利用这个地震滑坡编目,统计了九寨沟地震滑坡数量和滑坡点密度（LND）与地形（坡度、坡向）、地震（地震烈度、震中距）等因素的关系。结果表明九寨沟地震滑坡多发生在坡度为20°—50°的区域内,滑坡的易发性随着坡度的增加而增加。受地震波传播方向的影响,E、SE向是地震滑坡较易发生的坡向。滑坡的易发程度和地震烈度呈正相关,即随着烈度的增大,滑坡易发性增大。滑坡易发性还随着震中距增加而降低,这是由于地震波能量随震中距的增加而衰减导致的。  相似文献   

17.
Probabilistic thresholds for triggering shallow landslides by rainfall are developed using two approaches: a logistic regression model and Iverson's physically based model. Both approaches are applied to a 180 km2 area in northern Italy. For the physically based model a Monte Carlo approach is used to obtain probabilities of slope failure associated with differing combinations of rainfall intensity and duration as well as differing topographic settings. For the logistic regression model hourly and daily rainfall data and split‐sample testing are used to explore the effect of antecedent rainfall on triggering thresholds. It is demonstrated that both the statistical and physically based models provide stochastic thresholds that express the probability of landslide triggering. The resulting thresholds are comparable, even though the two approaches are conceptually different. The physically based model also provides an estimate of the percentage of potentially unstable areas in which failure can be triggered with a certain probability. The return period of rainfall responsible for landslide triggering is studied by using a Gumbel scaling model of rainfall intensity–duration–frequency curves. It is demonstrated that antecedent rainfall must be taken into account in landslide forecasting, and a method is proposed to correct the rainfall return period by filtering the rainfall maxima with a fixed threshold of antecedent rainfall. This correction produces an increase of the return periods, especially for rainstorms of short duration. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

18.
Summary statistics derived from the frequency–area distribution (FAD) of inventories of triggered landslides allows for direct comparison of landslides triggered by one event (e.g. earthquake, rainstorm) with another. Such comparisons are vital to understand links between the landslide‐event and the environmental characteristics of the area affected. This could lead to methods for rapid estimation of landslide‐event magnitude, which in turn could lead to estimates of the total triggered landslide area. Previous studies proposed that the FAD of landslides follows an inverse power‐law, which provides the basis to model the size distribution of landslides and to estimate landslide‐event magnitude (mLS), which quantifies the severity of the event. In this study, we use a much larger collection of earthquake‐induced landslide (EQIL) inventories (n=45) than previous studies to show that size distributions are much more variable than previously assumed. We present an updated model and propose a method for estimating mLS and its uncertainty that better fits the observations and is more reproducible, robust, and consistent than existing methods. We validate our model by computing mLS for all of the inventories in our dataset and comparing that with the total landslide areas of the inventories. We show that our method is able to estimate the total landslide area of the events in this larger inventory dataset more successfully than the existing methods. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.  相似文献   

19.
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20.
Many landslides are triggered by rainfall. Previous studies of the relationship between landslides and rainfall have concentrated on deriving minimum rainfall thresholds that are likely to trigger landslides. Though useful, these minimum thresholds derived from a log–log plot do not offer any measure of confidence in a landslide monitoring or warning system. This study presents a new and innovative method for incorporating rainfall into landslide modelling and prediction. The method involves three steps: compiling radar reflectivity data in a QPESUMS (quantitative precipitation estimation and segregation using multiple sensors) system during a typhoon (tropical hurricane) event, estimating rainfall from radar data and using rainfall intensity and rainfall duration as explanatory variables to develop a landslide logit model. Given the logit model, this paper discusses ways in which the model can be used for computing probabilities of landslide occurrence for a real‐time monitoring system or a warning system, and for delineating and mapping landslides. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

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