Rainfall-induced erosion involves the detachment of soil particles by raindrop impact and their transport by the combined action of the shallow surface runoff and raindrop impact. Although temporal variation in rainfall intensity (pattern) during natural rainstorms is a common phenomenon, the available information is inadequate to understand its effects on runoff and rainfall-induced erosion processes. To address this issue, four simulated rainfall patterns (constant, increasing, decreasing, and increasing - decreasing) with the same total kinetic energy were designed. Two soil types (sandy and sandy loam) were subjected to simulated rainfall using 15?cm × 30?cm long detachment trays under infiltration conditions. For each simulation, runoff and sediment concentration were sampled at regular intervals. No obvious difference was observed in runoff across the two soil types, but there were significant differences in soil losses among the different rainfall patterns and stages. For varying-intensity rainfall patterns, the dominant sediment transport mechanism was not only influenced by raindrop detachment but also was affected by raindrop-induced shallow flow transport. Moreover, the efficiency of equations that predict the interrill erosion rate increased when the integrated raindrop impact and surface runoff rate were applied. Although the processes of interrill erosion are complex, the findings in this study may provide useful insight for developing models that predict the effects of rainfall pattern on runoff and erosion. 相似文献
In many arid ecosystems, vegetation frequently occurs in high-cover patches interspersed in a matrix of low plant cover. However, theoretical explanations for shrub patch pattern dynamics along climate gradients remain unclear on a large scale. This context aimed to assess the variance of the Reaumuria soongorica patch structure along the precipitation gradient and the factors that affect patch structure formation in the middle and lower Heihe River Basin (HRB). Field investigations on vegetation patterns and heterogeneity in soil properties were conducted during 2014 and 2015. The results showed that patch height, size and plant-to-patch distance were smaller in high precipitation habitats than in low precipitation sites. Climate, soil and vegetation explained 82.5% of the variance in patch structure. Spatially, R. soongorica shifted from a clumped to a random pattern on the landscape towards the MAP gradient, and heterogeneity in the surface soil properties (the ratio of biological soil crust (BSC) to bare gravels (BG)) determined the R. soongorica population distribution pattern in the middle and lower HRB. A conceptual model, which integrated water availability and plant facilitation and competition effects, was revealed that R. soongorica changed from a flexible water use strategy in high precipitation regions to a consistent water use strategy in low precipitation areas. Our study provides a comprehensive quantification of the variance in shrub patch structure along a precipitation gradient and may improve our understanding of vegetation pattern dynamics in the Gobi Desert under future climate change.
Smart card-automated fare collection systems now routinely record large volumes of data comprising the origins and destinations of travelers. Processing and analyzing these data open new opportunities in urban modeling and travel behavior research. This study seeks to develop an accurate framework for the study of urban mobility from smart card data by developing a heuristic primary location model to identify the home and work locations. The model uses journey counts as an indicator of usage regularity, visit-frequency to identify activity locations for regular commuters, and stay-time for the classification of work and home locations and activities. London is taken as a case study, and the model results were validated against survey data from the London Travel Demand Survey and volunteer survey. Results demonstrate that the proposed model is able to detect meaningful home and work places with high precision. This study offers a new and cost-effective approach to travel behavior and demand research. 相似文献
