SWAT-WASP coupled modeling of ammonia nitrogen in rare earth mining watersheds

High concentrations of ammonia nitrogen (NH<sub>4</sub><sup>+</sup>-N) are a dominant water pollutant in ionic rare earth mining basins, threatening aquatic ecosystems and drinking-water safety. To quantify these dynamics, this study developed a coupled SWAT-WASP model for the upper Dongjiang River Basin (UDRB), integrating remote sensing and long-term monitoring data; the model was calibrated and validated with 2016-2018 monthly observations, and quantitative evaluation via Nash-Sutcliffe Efficiency (NSE) and Percent Bias (PBIAS) showed good performance (runoff: NSE = 0.77-0.80; NH<sub>4</sub><sup>+</sup>-N: SWAT NSE = 0.56-0.61, SWAT-WASP NSE = 0.65-0.87), confirming its reliability. 2022 simulations revealed strong NH<sub>4</sub><sup>+</sup>-N spatial heterogeneity, with concentrations >1.8 mg L<sup>-1</sup> near mining zones versus <0.5 mg L<sup>-1</sup> in upstream natural areas; geodetector analysis identified population density combined with industrial-agricultural activity as the top driver of spatial differentiation (<i>q</i> > 0.40), while interactions between precipitation, temperature, and land use further amplified variability. Overall, the SWAT-WASP framework provides a robust tool for evaluating NH<sub>4</sub><sup>+</sup>-N dynamics and supports targeted pollution control and ecological restoration in rare earth mining watersheds.

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Publication Details

Journal
Water Science & Technology
Published
2026-01-19
DOI
https://doi.org/10.2166/wst.2025.190
Primary Topic
Geochemistry and Elemental Analysis
Type
article
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article

SWAT-WASP coupled modeling of ammonia nitrogen in rare earth mining watersheds

Fei Meng, Jinfeng Zeng, Youcun Liu, Mingyong Zhu et al.
Water Science & Technology
Geochemistry and Elemental Analysis
article

SWAT-WASP coupled modeling of ammonia nitrogen in rare earth mining watersheds

Fei Meng, Jinfeng Zeng, Youcun Liu, Mingyong Zhu, David Labat, Zidan Wu
article en

Abstract

High concentrations of ammonia nitrogen (NH<sub>4</sub><sup>+</sup>-N) are a dominant water pollutant in ionic rare earth mining basins, threatening aquatic ecosystems and drinking-water safety. To quantify these dynamics, this study developed a coupled SWAT-WASP model for the upper Dongjiang River Basin (UDRB), integrating remote sensing and long-term monitoring data; the model was calibrated and validated with 2016-2018 monthly observations, and quantitative evaluation via Nash-Sutcliffe Efficiency (NSE) and Percent Bias (PBIAS) showed good performance (runoff: NSE = 0.77-0.80; NH<sub>4</sub><sup>+</sup>-N: SWAT NSE = 0.56-0.61, SWAT-WASP NSE = 0.65-0.87), confirming its reliability. 2022 simulations revealed strong NH<sub>4</sub><sup>+</sup>-N spatial heterogeneity, with concentrations >1.8 mg L<sup>-1</sup> near mining zones versus <0.5 mg L<sup>-1</sup> in upstream natural areas; geodetector analysis identified population density combined with industrial-agricultural activity as the top driver of spatial differentiation (<i>q</i> > 0.40), while interactions between precipitation, temperature, and land use further amplified variability. Overall, the SWAT-WASP framework provides a robust tool for evaluating NH<sub>4</sub><sup>+</sup>-N dynamics and supports targeted pollution control and ecological restoration in rare earth mining watersheds.

Water Science & TechnologyVol. 93(3)
South China Agricultural University (CN), Jiaying University (CN), State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (CN), Géosciences Environnement Toulouse (FR), Shandong Jianzhu University (CN)
Life in Land
Openalex Percentile: Top 63%
Geochemistry and Elemental Analysis
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