Martin August, Gunter James T, Regens James L
CDM, Inc., Austin, TX 78727, USA.
Environ Sci Pollut Res Int. 2003;10(4):245-50. doi: 10.1065/espr2003.05.153.
GOAL, SCOPE, BACKGROUND: Sheet erosion from agricultural, forest and urban lands may increase stream sediment loads as well as transport other pollutants that adversely affect water quality, reduce agricultural and forest production, and increase infrastructure maintenance costs. This study uses spatial analysis techniques and a numerical modeling approach to predict areas with the greatest sheet erosion potential given different soils disturbance scenarios.
A Geographic Information System (GIS) and the Universal Soil Loss Equation (USLE) were used to estimate sheet erosion from 0.64 ha parcels of land within the watershed. The Soil Survey of St. Tammany Parish, Louisiana was digitized, required soil attributes entered into the GIS database, and slope factors determined for each 80 x 80 meter parcel in the watershed. The GIS/USLE model used series-specific erosion K factors, a rainfall factor of 89, and a GIS database of scenario-driven cropping and erosion control practice factors to estimate potential soil loss due to sheet erosion.
A general trend of increased potential sheet erosion occurred for all land use categories (urban, agriculture/grasslands, forests) as soil disturbance increases from cropping, logging and construction activities. Modeling indicated that rapidly growing urban areas have the greatest potential for sheet erosion. Evergreen and mixed forests (production forest) had lower sheet erosion potentials; with deciduous forests (mostly riparian) having the least sheet erosion potential. Erosion estimates from construction activities may be overestimated because of the value chosen for the erosion control practice factor.
This study illustrates the ease with which GIS can be integrated with the Universal Soil Loss Equation to identify areas with high sheet erosion potential for large scale management and policy decision making.
The GIS/USLE modeling approach used in this study offers a quick and inexpensive tool for estimating sheet erosion within watersheds using publicly available information. This method can quickly identify discrete locations with relatively precise spatial boundaries (approximately 80 meter resolution) that have a high sheet erosion potential as well as areas where management interventions might be appropriate to prevent or ameliorate erosion.
目标、范围、背景：农业、森林和城市土地的片蚀可能会增加河流泥沙负荷，还会输送其他对水质产生不利影响的污染物，降低农业和森林产量，并增加基础设施维护成本。本研究采用空间分析技术和数值建模方法，预测在不同土壤扰动情景下片蚀潜力最大的区域。
利用地理信息系统（GIS）和通用土壤流失方程（USLE）估算流域内0.64公顷地块的片蚀情况。对路易斯安那州圣塔曼尼教区的土壤调查进行了数字化处理，将所需土壤属性输入GIS数据库，并确定了流域内每个80×80米地块的坡度因子。GIS/USLE模型使用特定系列的侵蚀K因子、降雨因子89以及情景驱动的种植和侵蚀控制实践因子的GIS数据库，来估算片蚀造成的潜在土壤流失。
随着种植、伐木和建设活动导致的土壤扰动增加，所有土地利用类别（城市、农业/草地、森林）的潜在片蚀均呈现增加的总体趋势。建模表明，快速发展的城市地区片蚀潜力最大。常绿和混交林（生产林）的片蚀潜力较低；落叶林（主要是河岸林）的片蚀潜力最小。由于侵蚀控制实践因子所选用的值，建设活动的侵蚀估算可能被高估。
本研究表明，GIS可轻松与通用土壤流失方程相结合，以识别具有高片蚀潜力的区域，用于大规模管理和政策决策。
本研究中使用的GIS/USLE建模方法提供了一种快速且廉价的工具，可利用公开可用信息估算流域内的片蚀情况。该方法可快速识别具有相对精确空间边界（约80米分辨率）且片蚀潜力高的离散位置，以及可能适合进行管理干预以预防或减轻侵蚀的区域。
