Soil erosion in future scenario using CMIP5 models and earth observation datasets

JOURNAL OF HYDROLOGY

卷:594

Article

Maurya, Swati¹  Srivastava, Prashant K.^1,2  Yaduvanshi, Aradhana³  Anand, Akash¹  Petropoulos, George P.⁴  Zhuo, Lu^5,6,7  Mall, R. K.² 

[1] Banaras Hindu Univ, Inst Environm & Sustainable Dev, Remote Sensing Lab, Varanasi 221005, Uttar Pradesh, India

[2] Banaras Hindu Univ, DST Mahamana Ctr Excellence Climate Change Res, Inst Environm & Sustainable Dev, Varanasi 221005, Uttar Pradesh, India

[3] Indian Inst Technol, Dept Civil Engn, Powai 400076, India

[4] Harokopio Univ Athens, Dept Geog, Athens, Greece

[5] Univ Sheffield, Dept Civil & Struct Engn, Sheffield, S Yorkshire, England

[6] Lab Target Microwave Properties, Deqing 313200, Peoples R China

[7] Deqing Acad Satellite Applicat, Deqing 313200, Peoples R China

关键词: Soil erosion;    CMIP5 model;    CA-Markov;    Mahi River Basin;    GIS;    Remote sensing;   

DOI  :  10.1016/j.jhydrol.2020.125851

来源: Elsevier

【 摘 要 】

Rainfall and land use/land cover changes are significant factors that impact the soil erosion processes. Therefore, the present study aims to investigate the impact of rainfall and land use/land cover changes in the current and future scenarios to deduce the soil erosion losses using the state-of-the-art Revised Universal Soil Loss Equation (RUSLE). In this study, we evaluated the long-term changes (period 1981-2040) in the land use/land cover and rainfall through the statistical measures and used subsequently in the soil erosion loss prediction. The future land use/land cover changes are produced using the Cellular Automata Markov Chain model (CA-Markov) simulation using multi-temporal Landsat datasets, while long term rainfall data was obtained from the Coupled Model Intercomparison Project v5 (CMIP5) and Indian Meteorological Department. In total seven CMIP5 model projections viz Ensemble mean, MRI-CGCM3, INMCM4, canESM2, MPI-ESM-LR, GFDL-ESM2M and GFDL-CM3 of rainfall were used. The future projections (2011-2040) of soil erosion losses were then made after calibrating the soil erosion model on the historic datasets. The applicability of the proposed method has been tested over the Mahi River Basin (MRB), a region of key environmental significance in India. The finding showed that the rainfall-runoff erosivity gradually decreases from 475.18 MJ mm/h/y (1981-1990) to 425.72 MJ mm/h/y (1991-2000). A value of 428.53 MJ mm/h/y was obtained in 2001-2010, while a significantly high values 661.47 MJ mm/h/y has been reported for the 2011-2040 in the ensemble model mean output of CMIP5. The combined results of rainfall and land use/land cover changes reveal that the soil erosion loss occurred during 1981-1990 was 55.23 t/ha/y (1981-1990), which is gradually increased to 56.78 t/ha/y in 1991-2000 and 57.35 t/ha/y in 2000-2010. The projected results showed that it would increase to 71.46 t/h/y in 2011-2040. The outcome of this study can be used to provide reasonable assistance in identifying suitable conservation practices in the MRB.

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