Watershed prioritization of Kailali district through morphometric parameters and landuse/landcover datasets using GIS

利用地理信息系统,通过形态参数和土地利用/土地覆盖数据集对凯拉利县流域进行优先排序。

阅读:2

Abstract

Watershed prioritization is considered an important tool for soil and watershed management. This study focuses on the watershed prioritization of the Kailali district in terms of soil erosion, considering morphometric parameters and land use/landcover (LULC) datasets using GIS. ALOS DEM of 30 m resolution was used to delineate sub-watersheds and calculate linear, areal, and relief morphometric parameters. Similarly, Esri LULC 2021 (Sentinel-2 imagery at 10 m resolution) was used to calculate LULC parameters. An integrated approach of Principal Component Analysis (PCA) and Weighted Sum Analysis (WSA) was used for prioritization. PCA was used to reduce selected parameters, calculate the correlation matrix, and define the significant parameters. WSA was used to define weightage value, and Compound Value (CV) was calculated for the ranking of sub-watersheds. 22 sub-watersheds with at least 3rd order stream and 15 parameters were selected for prioritization. PCA integrated with WSA was found to be effective for prioritization. The findings showed that about 61.58% of the watershed area is in the high-priority category, suggesting those areas are at a higher risk of erosion. Therefore, different land rehabilitation programs and bioengineering techniques should be focused on the sub-watershed of high-priority categories followed by medium and low-priority categories to control further soil erosion. The adopted methodology of prioritization can also be performed for multi-hazard mapping.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。