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The pore water pressure head that builds in the soil during storms is a critical factor for the prediction of potential slope instability. We report findings from a 3-year study of pressure head in 83 piezometers distributed within a 13-ha forested catchment on the northern coast of California. The study's primary objective was to observe the seasonal and storm-based dynamics of pressure head at a catchment scale in relation to observed rainfall characteristics and in situ topography to better understand landscape patterns of pressure head. An additional goal was to determine the influence of the interaction between rainfall and forest canopy in altering delivery of water and pressure head during the large storms necessary to induce landsliding. We found that pressure head was highly variable in space and time at the catchment scale. Pore pressures peaked close to maximum rainfall intensity during the largest storms measured. The difference between rainfall and throughfall delivered through the canopy was negligible during the critical landslide-producing peak rainfall periods. Pore pressure was spatially variable within the catchment and did not strongly correlate with surficial topographic features. Only 23% of the piezometers located in a variety of slope positions were found to be highly responsive to rainfall. Topographic index statistically explained peak pressure head at responsive locations during common storms, but not during the larger storms with potential to produce landslides. Drainage efficiency throughout the catchment increased significantly in storms exceeding 2 to 7 months peak pressure head return period indicated by slowing or cessation of the rate of increase of pressure head with increasing storm magnitude. This asymptotic piezometric pattern persisted through the largest storm measured during the study. Faster soil drainage suppressed pressure head response in larger storms with important process implications for pore pressure development and landslide hazard modelling. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The potential of multitemporal Landsat Thematic Mapper (TM) data was examined for its use in detecting areas affected by flood and erosion from a heavy rainfall. The study area is the Kulekhani watershed (124 kin²) located in the central region of Nepal. Four change-detection techniques were compared for their effectiveness including (1) Spectral Image Differencing (SID), (2) Tasseled Cap Brightness Image Differencing (TCBID), (3) Principal Component Analysis (PCA), and (4) Spectral Change Vector Analysis (SCVA). SID was performed on four raw bands (bands 1, 2, 3, and 7), and altogether seven new images (change images) were produced. Visible bands were effective in detecting affected areas. SCVA (using bands 1, 2, and 3) was found to be most accurate for detecting areas affected by flood and erosion followed by SID (band 2), PCA (using bands 1, 2, and 3), SID (band 1), and SID (band 3). The change image produced from SCVA showed overall and Khat accuracies of 88.3 percent and 75.4 percent, respectively. The analysis of spatial agreement conducted among the seven change images, produced from different techniques, varied from 89 percent to 98 percent. The change image produced from SCVA showed high spatial agreements with change images produced from PCA, SID (band 3), and SID (band 2). SCVA and SID (band 3) showed the spatial agreement of 88.1 percent and 98.7 percent in the change and no-change categories, respectively. [ABSTRACT FROM AUTHOR]

An application of GIS for landslide hazard assessment using multivariate statistical analysis, mapping, and the evaluation of the hazard maps is presented. The study area is the Kulekhani watershed (124 km2) located in the central region of Nepal. A distribution map of landslides was produced from aerial photo interpretation and field checking. To determine the factors and classes influencing landsliding, layers of topographic factors derived from a digital elevationmodel, geology, and land use/land cover were analyzed by quantification scaling type II (discriminant) analysis, and the results were used for hazard mapping. The effects of different samples of landslide and non-landslide groups on the critical factors and classes and subsequently on hazard maps were evaluated. Simple random sampling was used to obtain samples of the landslide group, and either an unaligned stratified random sampling or an aligned systematic sampling method generated the non-landslide group. For the analysis, one set of the landslide group was combined with each of five different sets of the non-landslide groups. Combinations of different samples yielded some minor differences in the critical factors and classes. The geology was found to be the most important factor for landslide hazard. The scoresof the classes of the factors quantified by the five analyses were used for the hazard mapping in the GIS, with four levels of relative hazard classes: high, moderate, less, and least. The evaluation of five hazard maps indicated higher accuracy for the combinations in whichthe non-landslide group was generated by the unaligned stratified random sampling method. The agreements in the hazard maps, produced from different sample combinations using unaligned stratified random sampling for selecting non-landslide group, were within the acceptable range for the practical use of a hazard map. [ABSTRACT FROM AUTHOR]