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Estimation of Soil Erosion and Identification of Critical Areas for Soil Conservation Measures using RS and GIS-based Universal Soil Loss Equation

机译:基于RS和GIS的通用土壤流失方程估算土壤侵蚀并确定水土保持措施的关键区域

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Present study aimed at estimating soil erosion potential and identification of critical areas for soil conservation measures in an ungauged catchment situated in Aravalli hills of Udaipur district, Rajasthan (India). Also, impact of rainfall on soil erosion is evaluated. The soil erosion is estimated for 10 year period (2001-2010) by Universal Soil Loss Equation (USLE) model using Geographical information system (GIS) and remote sensing techniques for every 12 m x 12 m area. Thematic maps of six USLEmodel parameters, i.e., rainfall erosivity (^-factor), soil erodibility (A'-factor), slope length (L-factor), slope steepness (^-factor), crop and management (C-factor), and support practice (P-factor), were prepared in GIS platform. The ^-factor rangedfrom 1,522.93 to 10,225.88 MJ mm ha"1 h_1 year"1 in the years 2006 and 2008, respectively, when the annual rainfall was 984.3 and 572.2 mm, and number of rainy days were 58 and 47, respectively. The ^-factor was highest for fine loam soil covering 56 %area, while the lowest value was for coarse loamy sand in 22 % area. The lowest value of the L-factor (0.736) was in accordance with the high slopes nearby catchment boundary; whereas the highest value (0.832) was for almost zero slopes in 34 % area nearby waterbodies. Opposite to the L-factor, the 5-factor values were high (>4) for the higher slopes nearby catchment boundary and the lowest values for the zero slopes. The C-factor value in 170.36 km2 or 48.91 % of the area is 0.1 while the value is zerofor waterbodies and builtup lands. The P-factor value in 250.36 km2 or 71.87 % of the area is 0.8. The mean annual soil erosion in the major portion of the catchment (231.13 km2 or 66.38 %) exceeds 10 t ha-1 year-1 indicating high to very severe soil erosion conditions prevailing in the catchment. It is apparent that vast quantities of the soil are getting eroded from the catchment, and the annual rainfall amount and rainfall intensity have the profound effect on the soil erosion potential. This studyemphasizes that USLE model coupled with GIS and remote sensing techniques are promising and cost-effective tools for mapping critical areas of soil erosion in ungauged catchments especially in developing countries.
机译:目前的研究旨在估算位于印度拉贾斯坦邦乌代浦地区Aravalli丘陵的无污染流域的水土流失潜力并确定水土保持措施的关键区域。此外,还评估了降雨对土壤侵蚀的影响。根据通用土壤流失方程(USLE)模型,使用地理信息系统(GIS)和遥感技术对每12 m x 12 m区域进行10年(2001-2010年)土壤侵蚀估算。六个USLE模型参数的专题图,即降雨侵蚀力(^因子),土壤侵蚀性(A'因子),坡长(L因子),坡度(^因子),作物和管理(C因子) ,并在GIS平台中准备了支持实践(P因子)。在2006年和2008年,当年降水量为984.3和572.2 mm,雨天数分别为58和47时,^因子分别为1,522.93至10,225.88 MJ mm ha“ 1 h_1年” 1。对于覆盖56%的细壤土,^因子最高,而对于覆盖22%的粗壤土沙,最低。 L因子的最小值(0.736)与集水区边界附近的高坡度一致。而最高值(0.832)是水体附近34%区域几乎为零的坡度。与L因子相反,集水区边界附近的较高坡度的5因子值较高(> 4),零坡度的5因子值较低。在170.36 km2或面积的48.91%中,C因子值为0.1,而对于水体和人为土地,C因子值为零。 250.36 km2或面积的71.87%中的P系数值为0.8。流域大部分地区(231.13 km2或66.38%)的平均年土壤侵蚀量超过10 t ha-1 year-1,表明该流域普遍存在着严重的土壤侵蚀状况。显然,大量的土壤被流域侵蚀了,年降水量和降雨强度对土壤侵蚀潜力产生了深远的影响。这项研究强调,USLE模型与GIS和遥感技术相结合是用于绘制未受污染流域特别是发展中国家的水土流失关键区域的地图的有前途且具有成本效益的工具。

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