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Assessing rainfall erosivity and erosivity density over a western Himalayan catchment, India
Journal of Earth System Science ( IF 1.9 ) Pub Date : 2020-03-16 , DOI: 10.1007/s12040-020-1362-8
Jagdeep Singh , Omvir Singh

The present study aims to assess rainfall erosivity and erosivty density both in space and time over the Suketi River catchment of western Himalayan region in India during 1971–2015. The data used comprises of daily rainfall measurements at three rain gauge stations, which are sparsely distributed over the catchment. Rainfall erosivity was assessed by employing Wischmeier and Smith algorithms, whereas erosivity density was estimated by applying Kinnell’s algorithm. The spatial distribution of both algorithms was analyzed through Kriging method based on geographical information system. The obtained results indicate remarkable year-to-year, seasonal and monthly variations in average annual rainfall erosivity and erosivity density. Apart from this, individual cases of high and very high rainfall erosivity and erosivity density were noticed. The long-term average annual rainfall erosivity and erosivity density revealed a general decreasing trend. This decreasing trend in rainfall erosivity was found to be statistically significant at 0.05 significance level, whereas it was found to be non-significant for erosivity density. The highest values of both indices were observed in the month of July followed by August and June particularly in northern parts. These results indicate that July month followed by August and June are the most susceptible months for soil erosion over the Suketi River catchment with lower reaches (northern) being the most vulnerable one. Finally, results of this study will be valuable for farmers, agronomists and regional planners in chalking out best management practices for reducing water erosion in vulnerable areas of the catchment.



中文翻译:

评估印度喜马拉雅西部流域的降雨侵蚀力和侵蚀力密度

本研究旨在评估1971-2015年印度喜马拉雅西部地区苏克提河流域的降雨侵蚀力和侵蚀力密度的时空分布。所使用的数据包括三个雨量计站的每日降雨测量值,这些测量值稀疏分布在流域上。通过使用Wischmeier和Smith算法评估降雨侵蚀力,而通过应用Kinnell算法估算侵蚀力密度。通过基于地理信息系统的克里格方法分析了两种算法的空间分布。获得的结果表明年平均降雨侵蚀力和侵蚀力密度的逐年,季节性和每月变化显着。除此之外,还注意到个别情况下降雨侵蚀力和侵蚀力密度很高和很高。长期平均年降雨侵蚀力和侵蚀力密度显示总体下降趋势。发现降雨侵蚀力的这种下降趋势在0.05显着性水平上具有统计显着性,而对于侵蚀力密度则无统计学意义。这两个指数的最高值出现在7月,随后是8月和6月,特别是在北部地区。这些结果表明,7月之后是8月和6月,是苏克提河流域水土流失最敏感的月份,下游(北部)是最脆弱的月份。最后,这项研究的结果对于制定有关减少流域脆弱地区水土流失的最佳管理方法的农民,农艺师和区域规划师将是有价值的。

更新日期:2020-04-16
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