Evidence map›Paper›PMID 41254107›Full record

ArticleScientific reports2025

Impact of soil erosion on agricultural sustainability based on crop water productivity in semi-arid Iran.

Elham Rafiei-Sardooi, Fahimeh Mirchooli, Ali Azareh, John J Clague

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Elham Rafiei-SardooiDepartment of Ecological Engineering, Faculty of Natural Resources, University of Jiroft, Kerman, 7867161167, Iran. ellrafiei@ujiroft.ac.ir.
Fahimeh MirchooliSari Agricultural Sciences and Natural Resources University, Sari, Iran.
Ali AzarehDepartment of Geography, University of Jiroft, Kerman, 7867161167, Iran.
John J ClagueDepartment of Earth Sciences, Institute for Quaternary Research, Simon Fraser University, British Columbia, Burnaby, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soil erosion is a significant threat to global food production, reducing the productivity of natural ecosystems and agricultural lands. In this study, we examine the loss of crop water productivity in the Halil River agricultural watershed, Iran. Areas within this watershed that are prone to soil erosion were delineated using two machine learning algorithms viz. Support Vector Machines (SVM) and Multivariate Discriminant Analysis (MDA), and 11 geo-environmental factors including elevation, lithology, land use, hydrologic soil group, soil depth, drainage density, soil available water capacity (SAWC), population density, slope (degrees), R factor, and distance to road. Finally, the loss of blue, green, and total crop water productivity of some main cultivated crops (wheat, dates, citrus, and tomatoes) in the study watershed was assessed under pessimistic (20%), optimistic (10%), and normal (15%) scenarios of crop water productivity loss. The results indicate that hydrologic soil group, elevation, and land use are the most important factors for soil erosion susceptibility. In addition, validation results of machine learning algorithms showed that the SVM model (AUC = 94%, TSS = 0.85) outperformed MDA (AUC = 92.3%, TSS = 0.81), and was therefore selected for further analysis. According to the SVM model, 14.3% of the watershed falls within the very high erosion susceptibility class. Agricultural lands are mostly located in areas of moderate to very high erosion risk. Production of wheat, citrus, dates, and tomatoes in moderate, high, and very high areas of erosion susceptibility map are estimated to be 2.4, 5.3, 13.3, and 10.7 million tons, respectively. In the optimistic scenario, total productivity losses per unit of water consumed water by wheat, dates, citrus, and tomatoes are 0.22, 1.24, 2.15, and 2.35 kg m

Indexed as

ErosionFood securityHalil river watershedIranMachine learning

Identifiers

PMID41254107
PMCPMC12627513

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