Soil Erosion Assessment by RUSLE, Google Earth Engine, and Geospatial Techniques over Rel River Watershed, Gujarat, India

Abstract The assessment of soil erosion holds paramount significance in sustainable land management and environmental conservation. In this context, the integration of advanced technologies such as the Revised Universal Soil Loss Equation (RUSLE), Google Earth Engine (GEE), and geospatial techniques...
Ausführliche Beschreibung

Abstract The assessment of soil erosion holds paramount significance in sustainable land management and environmental conservation. In this context, the integration of advanced technologies such as the Revised Universal Soil Loss Equation (RUSLE), Google Earth Engine (GEE), and geospatial techniques presents a formidable approach for evaluating soil erosion dynamics. This integrated methodology proves particularly valuable when applied to the Rel River watershed, where factors such as terrain, land use, and precipitation patterns intricately influence erosion processes. The collective use of two methods, the quantitative method focused on RUSLE to assess soil under various circumstances of erosion and sediment yield, whereas the qualitative approach focused on spectral indices of soil erosion in GEE to generate degradation map. This study was aimed at evaluating soil erosion and land degradation across the Rel River watershed in the western region of Gujarat, India. Soil loss has been estimated using soil loss models, i.e., RUSLE and geoinformation datasets, which were extracted from GEE. The degraded area was prepared using GEE and mapped using geographical information system (GIS). The results demonstrate that estimated value for erosion due to rainfall is 37 to 40 MJ mm $ h^{−1} $ $ ha^{−1} $ $ year^{−1} $, soil erodibility is 0.01 to 0.05 ton h $ MJ^{−1} $ $ mm^{−1} $, topographic variables lies in a range from 0 to 20, and crop management factor is 0.001 to 1. The findings also demonstrate that the total annual soil loss for flood events in 2017 is 35.36 t/ha/year, which is categorized into the severe zone of degradation. According to the soil degradation map created using GEE, the majority of the study region falls into the low and medium degradation zones, while the northeastern part and river fall into the high degradation zone. The findings will be helpful in implementing soil management and conservation techniques to arrest soil erosion in the Rel River watershed. Ausführliche Beschreibung

Autor*in:	Jodhani, Keval H. [verfasserIn] Patel, Dhruvesh Madhavan, N. Singh, Sudhir Kumar

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Soil erosion Revised Universal Soil Loss Equation Google Earth Engine Remote sensing Geographical information system Rel River

Anmerkung:

© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: Water conservation science and engineering - [Singapore] : Springer Singapore, 2016, 8(2023), 1 vom: 26. Sept.
Übergeordnetes Werk:	volume:8 ; year:2023 ; number:1 ; day:26 ; month:09

Links:	Volltext

DOI / URN:	10.1007/s41101-023-00223-x

Katalog-ID:	SPR05321353X