Response of Non-point Source Pollution Loads to Land Use Change under Different Precipitation Scenarios from a Future Pe
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Response of Non-point Source Pollution Loads to Land Use Change under Different Precipitation Scenarios from a Future Perspective Xiaoyan Bai 1 & Wen Shen 1 & Peng Wang 1,2 & Xiaohong Chen 3 & Yanhu He 4 Received: 5 November 2018 / Accepted: 16 July 2020/ # Springer Nature B.V. 2020
Abstract
To optimize the management of non-point source (NPS) pollution in a changing environment, the cellular automata (CA) and Hydrological Simulation Program-Fortran (HSPF) models were used to study the response mechanism of NPS pollution loads to land use change and different precipitation scenarios. Taking the Dongjiang River Basin as a case study, the land use situation and its spatial distribution patterns in 2020, 2030 and 2050 were predicted by the logistic regression-based CA model. The trends of the NPS pollution loads under different land use and precipitation scenarios were quantitatively evaluated. The results show that the total accuracy of the land use change simulated by the CA model was 81%. Both the HSPF model and the CA model were highly applicable to this basin. Precipitation is proven to be the main driving force of NPS pollution. From 2020 to 2050, the annual load, average monthly load, maximum and minimum monthly load of the BOD and TP show an upward trend. TN shows a slight downward trend, which is related to the reduction in cultivated land area and the use of nitrogen fertilizer. In view of the future trend of NPS pollution, the basin should continue to control TN pollution and focus on strengthening BOD and TP control to achieve high-quality management of the water environment. Keywords HSPF model . Cellular automata . Non-point source pollution load . Land use change . Dongjiang River basin
1 Introduction In recent years, with the improvement of point source pollution control capabilities, non-point source (NPS) pollution has become an important source of pollution in the water environment and has even
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11269-02002626-0) contains supplementary material, which is available to authorized users.
* Peng Wang [email protected] Extended author information available on the last page of the article
Bai X. et al.
become the primary source of pollution (Cai et al., 2018). It is currently estimated that approximately 30%–50% of the world’s surface water bodies are affected by NPS pollution (Corwin et al., 1998). For example, agricultural NPS pollution has become the primary source of pollution in rivers in the United States, with 73% of the biochemical oxygen demand (BOD), 92% of suspended matter and 83% of bacteria in the rivers coming from NPS pollution (U.S. EPA 2003). In China, 63.6% of the rivers and lakes are eutrophic due to NPS pollution, which is the main reason for the deterioration of water quality in lakes such as Chaohu Lake, Taihu Lake, and Dianchi Lake (Ongley et al., 2010). Therefore, the control of NPS pollution is urgent and essential. NPS pollution is affected by diverse factors, such as land use typ
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