Following the implementation of the strictest water resource management system in China, it has become increasingly important to understand and improve the surface water quality and the rate at which water function zones reach the water quality standard. Based on the monthly monitoring data from 450 monitoring sites at the provincial borders of 27 provinces in China in 2019, the overall surface water quality at provincial boundaries in China was evaluated. The Canadian Council of Ministers of the Environment-water quality index (CCME-WQI) showed that the provincial boundary water quality exceeded the fair level, and F1 was the most influential factor. Then, 27 factors that directly or indirectly affect the surface water quality were identified, and the indirect influencing factors were integrated into the ecological environmental quality index and human activities quantitative index. Finally, the 27 factors were integrated into six factors, and the relationship between these indicators and CCME-WQI as well as the concentration of influencing elements with respect to regulatory standard limits were analyzed. The proportion of building land was the most significant factor affecting the quality of the aquatic environment in provincial boundaries. In addition, the economic development level, proportion of farmland, and degree of social development were identified as significant influencing factors. The six factors have different degrees of impact on the concentrations of major elements with respect to standard limits. This study basically explores water resource management and offers significant reference and guidelines for the improvement of the quality of surface water at provincial boundaries in China.
Various uncertain influencing factors and incomprehensible mechanisms have posed daunting challenges to the management and treatment of regional surface water environment quality. The unified measures and the “one-size-fits-all” management approach limit the treatment effectiveness. Therefore, considering natural and human activities which are major factors affecting the surface water environment quality, the present study proposed a set of zoning management and control schemes for nitrogen and phosphorus concentrations in surface water based on its natural attributes. Selecting DEM, rainfall, vegetation type, soil type, and land use, and employing “grid transformation”, “data extraction”, “attribute superposition” of GIS software and “correlation analysis”, “cluster analysis”, and “principal component analysis” of SPSS software, the Haihe River Basin was divided into the prevention zone, the control zone, and the non-control zone with different natural attribute sets by the correlation coefficient R2 and the nitrogen and phosphorus pollution therein. Based on the nitrogen and phosphorus data of 276 surface water quality monitoring sites, the multiple nonlinear stepwise regression analysis was conducted to construct the relationship between a single water quality indicator and its natural attributes in the three zones. The results are of essential practical significance to surface water environment quality zoning management and survey in the Haihe River Basin. Meanwhile, it provides innovative insights into environmental zoning management in other regions.
Following the implementation of the strictest water resource management system in China, it has become increasingly important to understand and improve the surface water quality and the rate at which water function zones reach the water quality standard. Based on the monthly monitoring data from 450 monitoring sites at the provincial borders of 27 provinces in China in 2019, the overall surface water quality at provincial boundaries in China was as follows: 61.7% of the water was classified under Class I–III; and 5%, 8.6%, and 12.2% of the water was classified under Class IV, V, and inferior V, respectively. The main standard items are DO, CODMn, COD, BOD5, NH3-N, and TP. The Canadian Council of Ministers of the Environment-water quality index (CCME-WQI) showed that the provincial boundary water quality exceeded the fair level, and F1 was the most influential factor. Then, 27 factors that directly or indirectly affect the water quality of surface water at the provincial boundaries of 27 provinces were identified, and the indirect influencing factors were integrated into the ecological environmental quality index and human activities quantitative index. Finally, the 27 factors were integrated into six factors, and the relationship between these indicators and CCME-WQI as well as the concentration of influencing elements with respect to regulatory standard limits were analyzed. The proportion of building land was the most significant factor affecting the quality of the aquatic environment in provincial boundaries. In addition, the economic development level, proportion of farmland, and degree of social development were identified as significant influencing factors. The six factors have different degrees of impact on the concentrations of major elements with respect to standard limits. This study basically explores water resource management and offers significant reference and guidelines for the improvement of the quality of surface water at provincial boundaries in China
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