基于形态计量分析和主成分分析法的侵蚀易感流域优先排序——以印度旁遮普萨特莱吉河下游流域为例

Navneet Sharma , Arun Kaushal , Abrar Yousuf , Samanpreet Kaur , Rakesh Sharda , Som Pal Singh , OP Gupta , Anil Sood
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引用次数: 0

摘要

形态计量学有助于了解排水特性在各种水文过程中的表现,包括渗透、径流、侵蚀和沉积物输送。流域形态计量分析是研究流域对拓扑特征响应的重要技术。河流流域的形态计量分析是一项重要的技术,可以优先考虑流域,以实施水土管理战略。在本研究中,已使用地理空间技术确定了Sutlej河下游的形态计量特征。流域面积8577km2,在GIS环境中划分为14个子流域(WS-1至WS-14)。利用ALOS PALSAR DEM和ArcGIS对划定流域的形态参数进行了评价。计算的形态计量参数用于根据土壤侵蚀潜力对流域进行排名。流域的优先等级是根据复合参数分配的,该参数是通过对每个形态测量参数指定的等级取平均值来计算的。具有最低复合参数值的流域被给予最高优先级,反之亦然。根据结果,WS-7被分配了第一个等级,而WS-13被分配了第13个等级。进行主成分分析以确定高度相关的形态计量学参数。在18个参数中,有13个被发现高度相关。基于这些高度相关的参数获得的复合参数也将WS-7列为最脆弱的分水岭。因此,水土保持战略的实施应选择WS-7。可以得出的结论是,形态计量分析以及主成分分析与地理信息系统相结合,有助于从土壤侵蚀脆弱性和水资源管理的角度对流域进行优先排序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prioritization of erosion susceptible watersheds using morphometric analysis and PCA approach: A case study of lower Sutlej River basin of Indian Punjab

Morphometry helps in understanding the behaviour of drainage characteristics with respect to various hydrological processes including infiltration, runoff, erosion and sediment transport. Morphometric analysis of river basins is an essential technique to the study the response of drainage basin in response to topological characteristics. The river basins' morphometric analysis is an important technique to prioritize the watersheds for implementation of soil and water management strategies. In this study, the morphometric characteristics of the lower Sutlej River have been determined using the geo-spatial techniques. The river basin, having area of 8577 km2, was delineated into the fourteen sub-watersheds (WS-1 to WS-14) in the GIS environment. The ALOS PALSAR DEM and ArcGIS were utilized to evaluate the morphometric parameters of the delineated watersheds. The calculated morphometric parameters were used to rank the watersheds in terms of soil erosion potential. The priority ranks to the watersheds were assigned as per compound parameter, which was calculated by averaging the ranks designated to each morphometric parameter. Watersheds with the lowest compound parameter values were given the highest priority rating, and vice versa. Based on the results WS-7 was assigned the first rank whereas WS-13 was assigned the 13th rank. The principal component analysis was performed to determine the highly correlated morphometric parameters. Out of the 18 parameters, 13 were found be highly correlated. The compound parameter obtained based on these highly correlated parameters also prioritized WS-7 as the most vulnerable watershed. Therefore, WS-7 should be selected for the implementation of soil and water conservation strategies. It can be concluded that morphometric analysis along with PCA in combination with GIS can be helpful in prioritizing the watersheds in terms of soil erosion vulnerability and water management.

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