基于全子集回归的官厅水库WQImin构建与应用

Development and Application of WQImin for Guanting Reservoir Based on Full Subset Regression

  • 摘要: 针对官厅水库水质监测指标繁多、评价成本高昂及入库河流与库区水质异质性显著等问题,本研究基于2018~2022年逐月监测数据,构建了“分区差异化建模–协同对比分析”的入库河流–库区水环境协同评价体系,采用全子集回归方法分别构建了适用于库区和入库河流的最简水质指数(WQImin)评价模型,系统揭示了水质的时空演变规律及驱动机制.结果表明:库区WQImin模型包含氟、化学需氧量、氨氮、五日生化需氧量和总氮5项指标,调整R2达0.803;入库河流模型包含电导率、氨氮、溶解氧、五日生化需氧量和总氮5项指标,调整R2达0.841.多重共线性诊断与Bland-Altman一致性分析显示,WQImin与传统WQI具有良好的一致性(一致性比例>92%),模型统计结构稳健,但WQImin对水质变化响应更为敏感,可在保证评价精度的同时将监测指标数量减少58%.2018~2022年库区水质整体呈逐年改善趋势,年均WQImin处于中等至良好水平,春季(3月)水质最好,秋季(9月)相对较差;入库河流水质整体处于中等水平,汛期稀释效应可改善水质,但下花园桥(洋河)断面水质稳定性较差,汛期面源污染输入导致水质恶化风险较高.库区WQImin显著高于入库河流,表明水库对氮素等污染物具有一定的自净和稀释作用.本研究构建的协同评价体系和WQImin模型可为官厅水库及类似北方半湿润区大型水库的水质高效监测与精准管理提供方法支撑.

     

    Abstract: To address the issues of excessive monitoring indicators, high evaluation costs, and significant water quality heterogeneity between inflow rivers and reservoir zones in Guanting Reservoir, this study established a cooperative water environment evaluation system for inflow rivers and reservoir zones via “zoning differentiated modeling and cooperative comparative analysis”, and developed Water Quality Index-minimum (WQImin) evaluation models adapted to the reservoir zone and inflow rivers using full subset regression approach based on monthly monitoring data from 2018 to 2022, systematically revealing the temporal and spatial evolution patterns of water quality and their driving mechanisms. The results showed that: the optimal model for the reservoir zone included five variables (fluoride, chemical oxygen demand, ammonia nitrogen, five-day biochemical oxygen demand, and total nitrogen) with an adjusted R2 of 0.803; while the inflow rivers model incorporated five parameters (electrical conductivity, ammonia nitrogen, dissolved oxygen, five-day biochemical oxygen demand, and total nitrogen) achieving an adjusted R2 of 0.841. Multicollinearity diagnosis and Bland-Altman consistency analysis demonstrated good agreement between WQImin and conventional WQI (consistency ratio >92%) with robust statistical structure, with WQImin being more sensitive to water quality variations. The developed models could reduce monitoring indicators by 58% while maintaining evaluation accuracy. From 2018 to 2022, the reservoir zone water quality showed an overall improvement trend annually, with mean WQImin ranging from moderate to good levels. Water quality peaked in spring (March) and reached its lowest in autumn (September). Inflow rivers maintained moderate water quality levels, where flood season dilution effects improved water quality. However, the Xiahuayuanqiao (Yanghe River) section exhibited poor stability with higher risks of water quality degradation during flood seasons due to non-point source pollution. WQImin in the reservoir zone was significantly higher than that in inflow rivers, indicating the reservoir's self-purification and dilution capacity for nitrogen pollutants. The cooperative evaluation system and WQImin models constructed in this study can provide methodological support for efficient water quality monitoring and precise management of Guanting Reservoir and similar large reservoirs in semi-humid regions of northern China.

     

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