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101.
The dynamics of vegetation‐driven spatial heterogeneity (VDSH) and its function in structuring runoff and sediment fluxes have received increased attention from both geomorphological and ecological perspectives, particularly in arid regions with sparse vegetation cover. This paper reviews the recent findings in this area obtained from field evidence and numerical simulation experiments, and outlines their implications for soil erosion assessment. VDSH is often observed at two scales, individual plant clumps and stands of clumps. At the patch scale, the local outcomes of vegetated patches on soil erodibility and hydraulic soil properties are well established. They involve greater water storage capacity as well as increased organic carbon and nutrient inputs. These effects operate together with an enhanced capacity for the interception of water and windborne resources, and an increased biological activity that accelerates breakdown of plant litter and nutrient turnover rates. This suite of relationships, which often involve positive feedback mechanisms, creates vegetated patches that are increasingly different from nearby bare ground areas. By this way a mosaic builds up with bare ground and vegetated patches coupled together, respectively, as sources and sinks of water, sediments and nutrients. At the stand scale within‐storm temporal variability of rainfall intensity controls reinfiltration of overland flow and its decay with slope length. At moderate rainfall intensity, this factor interacts with the spatial structure of VDSH and the mechanism of overland flow generation. Reinfiltration is greater in small‐grained VDSH and topsoil saturation excess overland flow. Available information shows that VDSH structures of sources and sinks of water and sediments evolve dynamically with hillslope fluxes and tune their spatial configurations to them. Rainfall simulation experiments in large plots show that coarsening VDSH leads to significantly greater erosion rates even under heavy rainfall intensity because of the flow concentration and its velocity increase. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   
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Active tectonics in a basin plays an important role in controlling a fluvial system through the change in channel slope. The Baghmati, an anabranching, foothills-fed river system, draining the plains of north Bihar in eastern India has responded to ongoing tectonic deformation in the basin. The relatively flat alluvial plains are traversed by several active subsurface faults, which divide the area in four tectonic blocks. Each tectonic block is characterized by association of fluvial anomalies viz. compressed meanders, knick point in longitudinal profiles, channel incision, anomalous sinuosity variations, sudden change in river flow direction, river flow against the local gradient and distribution of overbank flooding, lakes, and waterlogged area. Such fluvial anomalies have been identified on the repetitive satellite images and maps and interpreted through DEM and field observations to understand the nature of vertical movements in the area. The sub-surface faults in the Baghmati plains cut across the river channel and also run parallel which have allowed us to observe the effects of longitudinal and lateral tilting manifested in avulsions and morphological changes.  相似文献   
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On Shikoku Island, which is one of the four main islands of Japan, a large number of large-scale crystalline schist landslides have been revealed and are being monitored by an observation system. Seasonal heavy rainfall is the most active meteorological factor that can threaten the stability of this kind of site-specific landslide. In this paper, on the basis of the study of the rainfall-related behavior of a typical crystalline schist landslide, the Zentoku landslide, by analyzing the precisely and continuously observed piezometric and movement data, a method was developed to quantitatively assess the effect of heavy rainfall on a large-scale landslide. The results indicated that heavy rainfall-induced landslide displacement shows good correlation with the variation of groundwater levels. Variations of groundwater level have been simulated with the use of a tank model. The simulation using this model permits the change in water levels for future rainfall events to be predicted. By combining the predicted results with the empirical relation between displacements and water levels, rainfall-induced landslide movement during extreme rainfall events can be estimated in advance. The effect of heavy rainfall on sliding behavior can be quantified in terms of the change in displacement. Thus warning information or advisories for the local residents can be provided.  相似文献   
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Regional models of extreme rainfall must address the spatial variability induced by orographic obstacles. However, the proper detection of orographic effects often depends on the availability of a well‐designed rain gauge network. The aim of this study is to investigate a new method for identifying and characterizing the effects of orography on the spatial structure of extreme rainfall at the regional scale, including where rainfall data are lacking or fail to describe rainfall features thoroughly. We analyse the annual maxima of daily rainfall data in the Campania region, an orographically complex region in Southern Italy, and introduce a statistical procedure to identify spatial outliers in a low order statistic (namely the mean). The locations of these outliers are then compared with a pattern of orographic objects that has been a priori identified through the application of an automatic geomorphological procedure. The results show a direct and clear link between a particular set of orographic objects and a local increase in the spatial variability of extreme rainfall. This analysis allowed us to objectively identify areas where orography produces enhanced variability in extreme rainfall. It has direct implications for rain gauge network design criteria and has led to promising developments in the regional analysis of extreme rainfall. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   
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Recent advances have been made to modernize estimates of probable precipitation scenarios; however, researchers and engineers often continue to assume that rainfall events can be described by a small set of event statistics, typically average intensity and event duration. Given the easy availability of precipitation data and advances in desk‐top computational tools, we suggest that it is time to rethink the ‘design storm’ concept. Design storms should include more holistic characteristics of flood‐inducing rain events, which, in addition to describing specific hydrologic responses, may also be watershed or regionally specific. We present a sensitivity analysis of nine precipitation event statistics from observed precipitation events within a 60‐year record for Tompkins County, NY, USA. We perform a two‐sample Kolmogorov–Smirnov (KS) test to objectively identify precipitation event statistics of importance for two related hydrologic responses: (1) peak outflow from the Six Mile Creek watershed and (2) peak depth within the reservoir behind the Six Mile Creek Dam. We identify the total precipitation depth, peak hourly intensity, average intensity, event duration, interevent duration, and several statistics defining the temporal distribution of precipitation events to be important rainfall statistics to consider for predicting the watershed flood responses. We found that the two hydrologic responses had different sets of statistically significant parameters. We demonstrate through a stochastic precipitation generation analysis the effects of starting from a constrained parameter set (intensity and duration) when predicting hydrologic responses as opposed to utilizing an expanded suite of rainfall statistics. In particular, we note that the reduced precipitation parameter set may underestimate the probability of high stream flows and therefore underestimate flood hazard. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   
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The regional frequency analysis of extreme annual rainfall data is a useful methodology in hydrology to obtain certain quantile values when no long data series are available. The most crucial step in the analysis is the grouping of sites into homogeneous regions. This work presents a new grouping criterion based on some multifractal properties of rainfall data. For this purpose, a regional frequency analysis of extreme annual rainfall data from the Maule Region (Chile) has been performed. Daily rainfall data series of 53 available stations have been studied, and their empirical moments scaling exponent functions K(q) have been obtained. Two characteristics parameters of the K(q) functions (γmax and K(0)) have been used to group the stations into three homogeneous regions. Only five sites have not been possible to include into any homogenous regions, being the local frequency analysis of extreme daily rainfall the most appropriate method to be used at these locations. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   
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