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| Estimation of total phosphorus flux in river based on the change-point of concentration and flow |
| Received:August 22, 2023 |
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| KeyWord:change-point analysis;concentration-flow relationship;total phosphorus;LOADEST model;Chaohe River |
| Author Name | Affiliation | E-mail | | HUANG Jieyu | College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China | | | PANG Shujiang | College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China | | | WANG Xiaoyan | College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China | wangxy@cnu.edu.cn |
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| Abstract: |
| It is necessary to gain more insights into the characteristics of flow and water-quality concentration change points and explore the role of concentration and flow change points in flux simulation. Mann-Kendall trend analysis and a Bayesian-based change point recognition model were used to evaluate the material flux of rivers with the LOADEST model. The Chaohe River Basin was selected as the research area, and the long-term(1992-2014) variation and change points of flow, TP concentration, and the relationship between the two were explored. The results indicated that the overall flow trend and TP concentration were decreasing. The flow changed in 1998, with an average flow rate of 7.92 m3·s-1 and 2.86 m3·s-1 before and after it happened. The changes in TP concentration occurred in 1993 and 1996, with average concentrations of 0.08, 0.06 mg·L-1, and 0.03 mg·L-1 from 1992 to 1993, 1994 to 1996, and 1997 to 2014, respectively.Around December 2004, there was a change point in the relationship between the TP concentration and flow. Before and after the relationship change-point, the flow thresholds were 2.36 m3·s-1 and 9.08 m3·s-1, respectively. The TP concentration-flow relationship was typical of flow-driven regimes before the change point but changed to dilution-dominant regimes under high flow conditions. The simulation performance of the LOADEST model could be enhanced by segmental modeling with change points, and different types of change points had their advantages. The segmented model based on the TP concentration change-point showed the best overall simulation results, which increased the Nash-Sutcliffe efficiency coefficient(NSE) from 0.50 to 0.96. The model based on concentration-flow relationship change-points performed best after the relationship change-point, increasing the NSE of that period from -0.31 to 0.89. In addition, the possible impacts of precipitation and watershed management measures were discussed. In summary, when simulating water quality and flux, analyzing the change points in water quality concentration, flow, and their relationship may improve the model's applicability to a certain extent. Furthermore, the potential effects of precipitation and watershed management measures were discussed. To sum up, when simulating water quality and flux, evaluating the change points in water quality concentration, flow, and their relationship may enhance the model's applicability to a specific extent. |
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