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<p>Flooding and soil erosion are critical environmental challenges affecting the SRB in western India, disrupting agriculture, ecology, and infrastructure. This study integrates GEE with the to evaluate soil erosion and flood vulnerability using high-resolution geospatial datasets from USGS and ESA. The RUSLE model estimated annual soil loss ranging from 0 to 1,232.34 t ha⁻¹ yr⁻¹, with the most severe erosion concentrated in the northern and northeastern SRB, primarily due to steep slopes and sparse vegetation. The rainfall erosivity (R-factor) ranged from 11,202.65 to 29,410.22&#xa0;MJ mm ha⁻¹ h⁻¹ yr⁻¹, and the slope length-steepness (LS-factor) peaked at 0.499 in upland zones. Flood-frequency mapping using Sentinel-1 SAR and JRC Global Surface Water datasets (2017–2023) identified low-lying plains that experienced 4–6 flood events per year, spatially overlapping with erosion hotspots. The combined analysis revealed a strong positive correlation (<i>r</i> = 0.97) between slope gradient and soil loss, confirming terrain control on erosion intensity. These findings highlight dual risk zones that threaten agricultural productivity and rural settlements. The study demonstrates GEE’s capability for rapid, large-scale environmental monitoring and supports integrated watershed management strategies aligned with Sustainable Development Goals 13 (Climate Action) and 15 (Life on Land).</p>

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Flood and erosion assessment of the sabarmati river basin: integrating big data in RUSLE and Google Earth engine

  • 期刊论文

  • 发表日期：

    2025年11月6日

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  • Keval H. Jodhani,
  • Nensi A. Sachapara,
  • Manan Patel,
  • Nitesh Gupta,
  • Dhruvesh P. Patel,
  • Sudhir Kumar Singh,
  • Upaka Rathnayake

摘要

Flooding and soil erosion are critical environmental challenges affecting the SRB in western India, disrupting agriculture, ecology, and infrastructure. This study integrates GEE with the to evaluate soil erosion and flood vulnerability using high-resolution geospatial datasets from USGS and ESA. The RUSLE model estimated annual soil loss ranging from 0 to 1,232.34 t ha⁻¹ yr⁻¹, with the most severe erosion concentrated in the northern and northeastern SRB, primarily due to steep slopes and sparse vegetation. The rainfall erosivity (R-factor) ranged from 11,202.65 to 29,410.22 MJ mm ha⁻¹ h⁻¹ yr⁻¹, and the slope length-steepness (LS-factor) peaked at 0.499 in upland zones. Flood-frequency mapping using Sentinel-1 SAR and JRC Global Surface Water datasets (2017–2023) identified low-lying plains that experienced 4–6 flood events per year, spatially overlapping with erosion hotspots. The combined analysis revealed a strong positive correlation (r = 0.97) between slope gradient and soil loss, confirming terrain control on erosion intensity. These findings highlight dual risk zones that threaten agricultural productivity and rural settlements. The study demonstrates GEE’s capability for rapid, large-scale environmental monitoring and supports integrated watershed management strategies aligned with Sustainable Development Goals 13 (Climate Action) and 15 (Life on Land).