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Integrated GIS-based RUSLE approach for quantification of potential soil erosion under future climate change scenarios

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Abstract

Human-induced agricultural and developmental activities cause substantial alteration to the natural geography of a landscape; thereby accelerates the geologic soil erosion process. This necessitates quantification of catchment-scale soil erosion under both retrospective and future scenarios for efficient conservation of soil resources. Here, we present a revised universal soil loss equation (RUSLE) based soil erosion estimation framework at an unprecedentedly high spatial resolution (30 × 30 m) to quantify the average annual soil loss and sediment yield from an agriculture-dominated river basin. The input parameters were derived by using the observed rainfall data, soil characteristics (soil texture, hydraulic conductivity, organic matter content), and topographic characteristics (slope length and percent slope) derived from digital elevation model (DEM) and satellite imageries. The developed approach was evaluated in the Brahmani River basin (BRB) of eastern India, wherein the different RUSLE inputs, viz., rainfall erosivity (R factor), soil erodibility (K factor), topographic (LS factor), crop cover (C factor), and management practice (P factor) factors have the magnitude of 1937 to 4867 MJ mm ha−1 h−1 year−1, 0.023 to 0.039 t h ha MJ−1 ha−1 mm−1, 0.03 to 74, 0.16 to 1, and 0 to 1, respectively. The estimated average annual soil loss over the BRB ranged from 0 to 319.55 t ha−1 year−1, and subsequent erosion categorization revealed that 54.2% of basin area comes under extreme soil erosion zones in the baseline period. Similarly, the sediment yield estimates varied in the range of 0.96 to 133.31 t ha−1 year−1, and 35.81% area were identified as high soil erosion potential zones. The extent of erosion under climate change scenario was assessed using the outputs of HadGEM2-ES climate model for the future time scales of 2030, 2050, 2070, and 2080 under the four representative concentration pathways (RCPs) 2.6, 4.5, 6.0, and 8.5. The severity of soil erosion under climate change is expected to have a mixed impact in the range of −25 to 25% than the baseline scenario. The outcomes of this study will serve as a valuable tool for decision-makers while implementing management policies over the BRB, and can be well extended to any global catchment-scale applications.

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Abbreviations

ArcGIS:

Aeronautical Reconnaissance Coverage Geographic Information System

ASTER:

Advanced spaceborne thermal emission and reflection radiometer

BMPs:

Best management practices

BRB:

Brahmani River basin

C-factor:

Crop cover factor

DEM:

Digital elevation model

e.g.:

Exempli gratia

et al.:

And others

GCM:

General circulation model

GIS:

Geographical information system

HadGEM2-ES:

Hadley Center Global Environmental Model, version 2 (Earth System)

i.e.:

that is

ICAR:

Indian Council of Agricultural Research

IDW:

Inverse distance weighting

IISWC:

Indian Institute of Soil and Water Conservation

IMD:

India Meteorological Department

IPCC:

Intergovernmental panel on climate change

K-factor:

Soil erodibility factor

LS-factor:

Topographic factor

LULC:

Land use land cover

MSL:

Mean sea level

MUSLE:

Modified universal soil loss equation

NBSS&LUP:

National Bureau of Soil Survey and Land Use Planning

NDVI:

Normalized difference vegetation index

NICRA:

National innovations on climate resilient agriculture

NRSC:

National remote sensing Centre

OLI:

Operational land imager

P factor:

Management practice factor

RCM:

Regional climate model

RCPs:

Representative concentration pathways

R factor:

Rainfall erosivity factor

RUSLE:

Revised universal soil loss equation

SCS:

Soil conservation service

SDR:

Sediment delivery ratio

TM:

Thematic mapper

USA:

United States of America

USDA:

United States Department of Agriculture

USGS:

United States Geological Survey

USLE:

Universal soil loss equation

viz:

Namely

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Acknowledgments

The authors are thankful to the NICRA project at ICAR-IISWC Dehradun for partially funding the present research. Thanks are extended to Ms. Monika Rawat for assisting in the future climate data preparation. The fellowship received by the first author from the TEQIP program is duly acknowledged.

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Authors and Affiliations

  1. Odisha, India

    Madhusmita Behera

  2. Hydrology and Engineering Division, ICAR-Indian Institute of Soil and Water Conservation, Dehradun, 248195, India

    Dipaka R. Sena & Uday Mandal

  3. Department of Soil and Water Conservation Engineering, G. B. Pant University of Agriculture and Technology, PantNagar, Uttarakhand, 263145, India

    Pradeep S. Kashyap

  4. School of Water Resources, IIT Kharagpur, Kharagpur, West Bengal, 721302, India

    Sonam S. Dash

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  1. Madhusmita Behera
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  2. Dipaka R. Sena
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  3. Uday Mandal
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  4. Pradeep S. Kashyap
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  5. Sonam S. Dash
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Correspondence to Uday Mandal or Sonam S. Dash.

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Behera, M., Sena, D.R., Mandal, U. et al. Integrated GIS-based RUSLE approach for quantification of potential soil erosion under future climate change scenarios. Environ Monit Assess 192, 733 (2020). https://doi.org/10.1007/s10661-020-08688-2

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