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

Swati Maurya; Prashant K Srivastava; Aradhana Yaduvanshi; Akash  Anand; George Petropoulos; Lu Zhuo; R. K. Mall

doi:10.1016/j.jhydrol.2020.125851

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

Swati Maurya, Prashant K Srivastava^*, Aradhana Yaduvanshi, Akash Anand, George Petropoulos, Lu Zhuo, R. K. Mall^*

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

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Abstract

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.

Original language	English
Article number	125851
Number of pages	17
Journal	Journal of Hydrology
Volume	594
Early online date	13 Dec 2020
DOIs	https://doi.org/10.1016/j.jhydrol.2020.125851
Publication status	Published - 1 Mar 2021

Bibliographical note

Funding Information:
The first author is highly thankful to the Department of Science and Technology, Government of India for funding the research work. The authors would like to thank the Banaras Hindu University for supporting this PhD research work and for providing necessary funds.

Publisher Copyright:
© 2020

Research Groups and Themes

Water and Environmental Engineering

Keywords

Soil erosion
CMIP5 model
CA-Markov
Mahi River Basin
GIS
Remote sensing

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@article{25ccb75c5a7b4f3392e640ed5c004a08,

title = "Soil erosion in future scenario using CMIP5 models and earth observation datasets",

abstract = "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. ",

keywords = "Soil erosion, CMIP5 model, CA-Markov, Mahi River Basin, GIS, Remote sensing",

author = "Swati Maurya and Srivastava, {Prashant K} and Aradhana Yaduvanshi and Akash Anand and George Petropoulos and Lu Zhuo and Mall, {R. K.}",

note = "Funding Information: The first author is highly thankful to the Department of Science and Technology, Government of India for funding the research work. The authors would like to thank the Banaras Hindu University for supporting this PhD research work and for providing necessary funds. Publisher Copyright: {\textcopyright} 2020",

year = "2021",

month = mar,

day = "1",

doi = "10.1016/j.jhydrol.2020.125851",

language = "English",

volume = "594",

journal = "Journal of Hydrology",

issn = "0022-1694",

publisher = "Elsevier",

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TY - JOUR

T1 - Soil erosion in future scenario using CMIP5 models and earth observation datasets

AU - Maurya, Swati

AU - Srivastava, Prashant K

AU - Yaduvanshi, Aradhana

AU - Anand, Akash

AU - Petropoulos, George

AU - Zhuo, Lu

AU - Mall, R. K.

N1 - Funding Information: The first author is highly thankful to the Department of Science and Technology, Government of India for funding the research work. The authors would like to thank the Banaras Hindu University for supporting this PhD research work and for providing necessary funds. Publisher Copyright: © 2020

PY - 2021/3/1

Y1 - 2021/3/1

N2 - 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.

AB - 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.

KW - Soil erosion

KW - CMIP5 model

KW - CA-Markov

KW - Mahi River Basin

KW - GIS

KW - Remote sensing

U2 - 10.1016/j.jhydrol.2020.125851

DO - 10.1016/j.jhydrol.2020.125851

M3 - Article (Academic Journal)

SN - 0022-1694

VL - 594

JO - Journal of Hydrology

JF - Journal of Hydrology

M1 - 125851

ER -

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

Abstract

Bibliographical note

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Keywords

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