Non-Point Source Nitrogen and Phosphorus Assessment and Management Plan with an Improved Method in Data-Poor Regions
AbstractTo enhance the quantitative simulation and integrated assessment of non-point source (NPS) pollution in plateau lakes in data-poor regions, a simple and practical NPS assessment method is developed by combining the improved export coefficient model (ECM) and the revised universal soil loss equation (RUSLE). This method is evaluated via application to the Chenghai Lake watershed (Yunnan Province, China), which contains a typical plateau lake. The estimated results reflect the actual situation within the watershed. The total nitrogen (TN) and total phosphorus (TP) loads in the study area in 2014 were 360.35 t/a (44.30% dissolved nitrogen (DN) and 55.70% adsorbed nitrogen (AN)) and 86.15 t/a (71.40% adsorbed phosphorus (AP)), respectively. The southern and eastern portions of the watershed are key regions for controlling dissolved and adsorbed pollutants, respectively. Soil erosion and livestock are the main TN and TP pollution sources in the study area and should be controlled first. Additionally, reasonable and practical suggestions are proposed to minimize water pollution according to a scenario analysis. The method in this study provides a foundation for scientific theories that can be used in water resources protection planning and the method can be applied to the NPS assessment of similar regions with scarce data. View Full-Text
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Chen, X.; Liu, X.; Peng, W.; Dong, F.; Huang, Z.; Wang, R. Non-Point Source Nitrogen and Phosphorus Assessment and Management Plan with an Improved Method in Data-Poor Regions. Water 2018, 10, 17.
Chen X, Liu X, Peng W, Dong F, Huang Z, Wang R. Non-Point Source Nitrogen and Phosphorus Assessment and Management Plan with an Improved Method in Data-Poor Regions. Water. 2018; 10(1):17.Chicago/Turabian Style
Chen, Xuekai; Liu, Xiaobo; Peng, Wenqi; Dong, Fei; Huang, Zhihua; Wang, Ruonan. 2018. "Non-Point Source Nitrogen and Phosphorus Assessment and Management Plan with an Improved Method in Data-Poor Regions." Water 10, no. 1: 17.
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