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Research article2019Peer reviewed

Identification of spatially distributed hotspots for soil loss and erosion potential in mining areas of Upper Damodar Basin - India

Karan, Shivesh Kishore; Ghosh, Somaparna; Samadder, Sukha Ranjan

Abstract

Limited measurements of soil erosion, sediment transport and deposition due to coal mining activities hamper the planning for soil and water management in large coalfields. Management of erosion in these areas requires the identification of vulnerable zones. In this study, a modified Universal Soil Loss Equation model coupled with Analytic Hierarchy Process has been used to develop an Erosion Potential Index (EPI) to identify probable zones of soil erosion in the Upper Damodar Basin (UDB). The Damodar river valley has been subjected to severe environmental contamination over the years due to large scale mining and industrial activities. The results revealed that north-western and the central part of the UDB lied in the high EPI zone. Revised Universal Soil Loss Equation (RUSLE) model was used to estimate the soil loss for the UDB. The results of the RUSLE model revealed that the soil loss in the study area varied from a minimum of 0 to a maximum of 91.34 t ha(-1) yr(-1) in some areas. The spatial distribution of soil loss in the UDB was classified into 5 categories (Very Slight, Slight, Moderate, Severe and Extremely Severe). From results it was observed that about 959.9 km(2) or 22% of the total study area lied in the severe soil loss zone i.e., soil losses in these areas ranged between 20 and 40 t ha(-1) yr(-1). Most of these areas were located in the vicinity of coal mining areas. Although, the lack of available data may impair the prediction accuracy of the proposed model at such a large watershed scale. However, the results of the proposed approach indicate usefulness in identifying erosion hotspots in large distributed watersheds with limited data.

Keywords

Analytic Hierarchy Process; Coal mining; GIS; Soil Erosion; USLE; Watershed

Published in

CATENA
2019, Volume: 182, article number: 104144Publisher: Elsevier {BV}

    UKÄ Subject classification

    Soil Science

    Publication identifier

    DOI: https://doi.org/10.1016/j.catena.2019.104144

    Permanent link to this page (URI)

    https://res.slu.se/id/publ/114843