Identifying critical source areas of non-point source pollution to enhance water quality: Integrated SWAT modeling and multi-variable statistical analysis to reveal key variables and thresholds.
Autor: | Fang S; Soil, Water, and Ecosystem Sciences Department, University of Florida/IFAS/West Florida Research and Education Center, Milton, FL 32583, USA. Electronic address: sfang1@ufl.edu., Deitch MJ; Soil, Water, and Ecosystem Sciences Department, University of Florida/IFAS/West Florida Research and Education Center, Milton, FL 32583, USA., Gebremicael TG; Soil, Water, and Ecosystem Sciences Department, University of Florida/IFAS/West Florida Research and Education Center, Milton, FL 32583, USA., Angelini C; Department of Environmental Engineering Sciences, Environmental School for Sustainable Infrastructure and the Environment (ESSIE), University of Florida, Gainesville, FL 32611, USA., Ortals CJ; Department of Environmental Engineering Sciences, Environmental School for Sustainable Infrastructure and the Environment (ESSIE), University of Florida, Gainesville, FL 32611, USA. |
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Jazyk: | angličtina |
Zdroj: | Water research [Water Res] 2024 Apr 01; Vol. 253, pp. 121286. Date of Electronic Publication: 2024 Feb 06. |
DOI: | 10.1016/j.watres.2024.121286 |
Abstrakt: | By integrating soil and water assessment tool (SWAT) modeling and land use and land cover (LULC) based multi-variable statistical analysis, this study aimed to identify driving factors, potential thresholds, and critical source areas (CSAs) to enhance water quality in southern Alabama and northwest Florida's Choctawhatchee Watershed. The results revealed the significance of forest cover and of the lumped developed areas and cultivated crops ("Source Areas") in influencing water quality. The stepwise linear regression analysis based on self-organizing maps (SOMs) showed that a negative correlation between forest percent cover and total nitrogen (TN), organic nitrogen (ORGN), and organic phosphorus (ORGP), highlighting the importance of forests in reducing nutrient loads. Conversely, Source Area percentage was positively correlated with total phosphorus (TP) loads, indicating the influence of human activities on TP levels. The receiver operating characteristic (ROC) curve analysis determined thresholds for forest percentage and Source Area percentage as 37.47 % and 20.26 %, respectively. These thresholds serve as important reference points for identifying CSAs. The CSAs identified based on these thresholds covered a relatively small portion (28 %) but contributed 47 % of TN and 50 % of TP of the whole watershed. The study underscores the importance of considering both physical process-based modeling and multi-variable statistical analysis for a comprehensive understanding of watershed management, i.e., the identification of CSAs and the associated variables and their tipping points to maintain water quality. Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2024 Elsevier Ltd. All rights reserved.) |
Databáze: | MEDLINE |
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