Soil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS

被引:18
作者
Kashiwar, Sumedh R. [1 ]
Kundu, Manik Chandra [1 ]
Dongarwar, Usha R. [2 ]
机构
[1] Visva Bharati Univ, Inst Agr Palli Siksha Bhavana, Dept Soil Sci & Agr Chem, Sriniketan 731236, W Bengal, India
[2] Zonal Agr Res Stn Dr PDKV, Sindewahi 441222, Maharashtra, India
关键词
RUSLE; Remote sensing; GIS; Soil erosion; Bhandara region; Godavari basin; LOSS EQUATION RUSLE; SEDIMENT YIELD; RIVER-BASIN; LAND-USE; MODEL; RISK; SUSCEPTIBILITY; VULNERABILITY; DEGRADATION; DEPOSITION;
D O I
10.1007/s11069-021-04974-5
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The agricultural land of the whole world is deteriorating due to the loss of top fertile soil reducing agricultural productivity and groundwater availability. Mainly, natural conditions and human manipulations have made soils extremely prone to soil erosion. Therefore, information on soil erosion status is of paramount importance to the policymakers for land conservation planning in a limited time. Spatial information systems like GIS and RS are known for their efficiencies. With that prospect, the GIS-based RUSLE model is used in this study to assess the soil erosion losses from Bhandara regions of Maharashtra, India. The study area comes under Wainganga sub-river basin, a portion of the Godavari River basin. We have prepared the required five potential parameters (R*K*LS*C*P) of RUSLE model on pixel-to-pixel basis. We have prepared the R factor map from monthly rainfall data of Indian Meteorological Department (IMD) and K factor map by digital the soil series map of NBSS & LUP, Govt. of India. We have used the digital elevation model data (DEM) of Cartosat-1 for LS-factor map, Landsat 8 and Sentinel-2A satellite dataset to generate LULC and NDVI map to obtain C and P factors. The results and satellite data were validated using Google Earth Pro and field observations. The results showed significant soil erosion from the river banks and wastelands near water bodies, with the soil loss values ranging between 20 and 40 t ha(-1) yr(-1). The land under reserved forest was very slight erosion-prone soil with soil loss of < 5 t ha(-1) yr(-1), but few water bodies in forest land have resulted in more than 40 t ha(-1) yr(-1). Some steep sloppy land near the riverbank showed soil erosion loss ranging from 44.37 to 241.03 t ha(-1) yr(-1) due to higher water forces, most minor vegetation, high steep slopes, and sandy loam soils. The spatial techniques used for assessing soil erosion in the study area will be helpful for decision-makers and planners to take appropriate land management measures to counter the soil loss and protect the natural environment. Thus, the GIS-based RUSLE model is a convenient, time-efficient, and cost-effective tool to evaluate and map soil erosion on a pixel-to-pixel basis.
引用
收藏
页码:937 / 959
页数:23
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