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首页> 外文期刊>Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution >Simulation of field-measured soil loss in Mediterranean hilly areas (Chianti, Italy) with RUSLE
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Simulation of field-measured soil loss in Mediterranean hilly areas (Chianti, Italy) with RUSLE

机译：用RUSLE模拟地中海丘陵地区（意大利基安蒂）的水土流失

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The issue of soil erosion is considered highly important by local administrators of the Chianti region. Thus, a methodology for predicting the long-term average annual soil loss, by using the Revised Universal Soil Loss Equation (RUSLE) in a Geographical Information System framework was developed and assessed. The rainfall and runoff erosivity factor was calculated using 35 raingauges with an acquisition interval of 15 min in the period from 1996 to 2010. The soil erodibility factor was estimated using a soil map at a scale of 1:50,000. The topographic factor was calculated from a 10 m digital elevation model. Moreover, a methodology was proposed that took into account the vineyard row direction and slope. Soil loss field data (566 field sites) were measured over 6 years using a topographical approach, and used to validate the model results. The statistical indices for the evaluation of the model were, respectively, the mean percent error (M%E), -0.1%, the ratio of the RMSE to the standard deviation of the observations (RSR), 23.7%; and the Nash-Sutcliffe coefficient (NCS), 0.9. Statistics indicated good predictions of long-term average annual soil losses at a field scale. The average annual soil loss for the study area was predicted up to 6.4 t.ha(-1).y(-1). Approximately 13% of the study area was classified as high erosion (>= 22 t.ha(-1).y(-1)). The identification of areas with the greatest erosion risk supports the possibility of using the model for land-use and land-management planning purposes. Moreover, this assists in the identification of those areas towards which conservation measures can be directed. (C) 2016 Elsevier B.V. All rights reserved.
机译：基安蒂地区的地方行政人员认为水土流失问题非常重要。因此，开发并评估了一种通过在地理信息系统框架中使用修订的通用土壤流失方程（RUSLE）来预测长期年均土壤流失的方法。在1996年至2010年期间，使用35个雨量计以15分钟的采集间隔来计算降雨和径流侵蚀力因子。使用1：50,000比例尺的土壤图估算土壤易蚀性因子。地形因子由10 m数字高程模型计算得出。此外，提出了一种方法，该方法考虑了葡萄园行的方向和坡度。使用地形学方法在6年中测量了土壤流失现场数据（566个现场），并用于验证模型结果。用于模型评估的统计指标分别为平均误差百分比（M％E）-0.1％，RMSE与观测值标准偏差的比率（RSR）23.7％; Nash-Sutcliffe系数（NCS）为0.9。统计数据表明，对田间规模的长期平均年土壤流失有很好的预测。预计研究区域的年平均土壤流失量可达6.4 t.ha（-1）.y（-1）。大约13％的研究区域被归类为高侵蚀（> = 22 t.ha（-1）.y（-1））。确定侵蚀风险最大的区域，支持将模型用于土地利用和土地管理规划的可能性。此外，这有助于确定可以采取保护措施的区域。 （C）2016 Elsevier B.V.保留所有权利。

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