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  5. Soil erosion in the United States: Present and future (2020–2050)

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Article
English
2024

Soil erosion in the United States: Present and future (2020–2050)

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0 Files

English
2024
CATENA
Vol 242
DOI: 10.1016/j.catena.2024.108074

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Amir Gandomi
Amir Gandomi

University of Techology Sdyney

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Shahab Aldin Shojaeezadeh
Malik Al-Wardy
Mohammad Reza Nikoo
+6 more

Abstract

Brought on by anthropogenic actions, accelerated soil erosion inflicts extreme changes in terrestrial and aquatic ecosystems. These field-scale (30 m) changes have neither been fully surveyed in the present, nor predicted for a probable future. Water-driven soil erosion (i.e., sheet and rill erosion) rates across the contiguous United States were estimated for the present, and then predicted for the future using three alternative Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios (2.6, 4.5, and 8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6). The G2 erosion model which is integrated with Machine Learning (ML) and Remote Sensing (RS) techniques were used to estimate soil erosion based on gauge observations of long-term precipitation, and climate and land use land cover (LULC) scenarios. The baseline model (2020) estimated soil erosion rates of 2.32 Mg ha−1 yr−1 under current conservation agriculture practices (CPs). Maintaining current CPs, future scenarios predict an 8 % to 21 % increase in soil erosion under different combinations of SSP-RCP climate and LULC change scenarios. The findings of this study can help policy makers for future conservation planning on maintaining soil fertility, mitigating environmental impacts, and promoting food security.

How to cite this publication

Shahab Aldin Shojaeezadeh, Malik Al-Wardy, Mohammad Reza Nikoo, Mehrdad Ghorbani Mooselu, Mohammad Reza Alizadeh, Jan Adamowski, Hamid Moradkhani, Nasrin Alamdari, Amir Gandomi (2024). Soil erosion in the United States: Present and future (2020–2050). CATENA, 242, pp. 108074-108074, DOI: 10.1016/j.catena.2024.108074.

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Publication Details

Type

Article

Year

2024

Authors

9

Datasets

0

Total Files

0

Language

English

Journal

CATENA

DOI

10.1016/j.catena.2024.108074

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