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Landslide Area (landslide + area)
Selected AbstractsContribution of deep-seated bedrock landslides to erosion of a glaciated basin in southern AlaskaEARTH SURFACE PROCESSES AND LANDFORMS, Issue 9 2005Ann M. Arsenault Abstract Landslides represent a key component of catchment-scale denudation, though their relative contribution to the erosion of glaciated basins is not well known. Bedrock landslide contribution was investigated on the surface of one of eleven glaciers on a glaciated ridge in the Chugach-St Elias Range of southern Alaska, where the debris from four major landslides is easily distinguished from moraines and other supraglacial material. A series of aerial and satellite photos from 1972 to 2000 and field observations in 2001 and 2002 indicate that three of four landslides have fallen onto the surface of the glacier since about 1978. The landslides, which originated from the steeply dipping (60,70°) bedrock walls, were deposited onto the glacier in the ablation zone and are currently being transported downstream supraglacially. Individual glacial valleys with topographic relief of ,400 m are cut into high-grade metamorphic rock characterized by a steep north-dipping foliation and fractured by numerous large joints. Measurements of landslide area and average thickness obtained from high-resolution survey data indicate a total landslide volume of ,2·3 × 105 m3. This volume suggests a basin-averaged erosion rate from landslides of 0·48 mm a,1. An overall basin-scale erosion rate of 0·7 to 1·7 mm a,1 can be inferred, but depends on the percentage of the total-basin sediment yield contributed by supraglacial sources. A mean rockwall retreat rate of 6·7 mm a,1 is calculated and is considerably higher than published rates, which range from 0·04 to 4·0 mm a,1. Controls on landslide generation include seismicity, freeze,thaw processes, topography, rock strength, and debuttressing. It is likely all of these factors contribute to failure, although the primary controls for the landslides in this study are thought to be rock strength and topography. The absence of landslides on ten of the eleven glaciers on this ridge is attributed to landslide magnitude,frequency relationships and short temporal scale of this study. Large-volume bedrock landslides (>100 000 m3) may have low frequency, occurring less than once in a 55-year time frame. Copyright © 2005 John Wiley & Sons, Ltd. [source] Testing a model for predicting the timing and location of shallow landslide initiation in soil-mantled landscapesEARTH SURFACE PROCESSES AND LANDFORMS, Issue 9 2003M. Casadei Abstract 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. [source] Investigating the impact of the Chi-Chi earthquake on the occurrence of debris flows using artificial neural networksHYDROLOGICAL PROCESSES, Issue 19 2009Fi-John Chang Abstract Debris flows have caused enormous losses of property and human life in Taiwan during the last two decades. An efficient and reliable method for predicting the occurrence of debris flows is required. The major goal of this study is to explore the impact of the Chi-Chi earthquake on the occurrence of debris flows by applying the artificial neural network (ANN) that takes both hydrological and geomorphologic influences into account. The Chen-Yu-Lan River watershed, which is located in central Taiwan, is chosen for evaluating the critical rainfall triggering debris flows. A total of 1151 data sets were collected for calibrating model parameters with two training strategies. Significant differences before and after the earthquake have been found: (1) The size of landslide area is proportioned to the occurrence of debris flows; (2) the amount of critical rainfall required for triggering debris flows has reduced significantly, about half of the original critical rainfall in the study case; and (3) the frequency of the occurrence of debris flows is largely increased. The overall accuracy of model prediction in testing phase has reached 96·5%; moreover, the accuracy of occurrence prediction is largely increased from 24 to 80% as the network trained with data from before the Chi-Chi earthquake sets and with data from the lumped before and after the earthquake sets. The results demonstrated that the ANN is capable of learning the complex mechanism of debris flows and producing satisfactory predictions. Copyright © 2009 John Wiley & Sons, Ltd. [source] FLOW ANALYSIS OF LANDSLIDE DAMMED LAKE WATERSHEDS: A CASE STUDY1JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 6 2006Kwan Tun Lee Abstract: The Chi-Chi earthquake, which occurred on September 21, 1999, and had a magnitude of 7.3 on the Richter scale, resulted in an extensive landslide that blocked the Ching-Shui Creek in Taiwan, forming a large lake with a storage volume of 40 million m3. This paper describes an analytical procedure used to perform flow analysis of the Tsao-Ling watershed, which includes the new landslide dammed lake. In this study, a digital elevation model was applied to obtain the watershed geomorphic factors and stage-area storage function of the landslide dammed lake. Satellite images were used to identify the landslide area and the land cover change that occurred as a result of the earthquake. Two topography-based runoff models were applied for long term and short term streamflow analyses of the watershed because the watershed upstream of the landslide dam was ungauged. The simulated daily flow and storm runoff were verified using limited available measured data in the watershed, and good agreement was obtained. The proposed analytical procedure for flow analysis is considered promising for application to other landslide dammed lake watersheds. [source] Landslide inventories and their statistical propertiesEARTH SURFACE PROCESSES AND LANDFORMS, Issue 6 2004Bruce D. Malamud Abstract 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. [source] | ||||||||||