Department of Water Environment, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China.
College of Hydrology and Water Resources, Hohai University, Nanjing, 210098, China.
Environ Monit Assess. 2020 Feb 4;192(3):160. doi: 10.1007/s10661-020-8122-8.
Heavy background pollutant loads pose a difficult problem for the assessment and management of regional water quality, especially in areas where surface water quality is less affected by anthropogenic pollution. Deducting background values from those derived from water quality monitoring is a new method for evaluating surface water environments in areas with heavy background loads. In this study, river source reserves in Heilongjiang province were evaluated with an export coefficient model (ECM) that considers the rainfall influence factor, has an improved timescale, and is based on synchronous rainfall monitoring data and concentrations. Moreover, the ECM was combined with a mechanism model. The chemical oxygen demand, ammonia nitrogen, and other water quality indices are affected by background environment, and therefore, suitable export coefficients for the study area were determined and a regression equation between the rainfall influence factor and precipitation was established. By combining the ECM and mechanism model, the concentrations entering the river during eight rainfall events in 2018 were predicted, and the background value was calculated to evaluate surface water quality. The predicted values were found to approximate the monitored values. Therefore, this study is of great significance for water quality assessment and management in areas with heavy background pollutant loads.
重背景污染物负荷给区域水质评估和管理带来了难题,特别是在地表水较少受到人为污染影响的地区。从水质监测中扣除背景值是评估重背景负荷地区地表水环境的一种新方法。本研究采用考虑降雨影响因子、改进时间尺度、基于同步降雨监测数据和浓度的导出系数模型(ECM)评估了黑龙江省河川源保护区。此外,将 ECM 与机制模型相结合。化学需氧量、氨氮等水质指标受背景环境影响,因此,确定了适合研究区的导出系数,并建立了降雨影响因子与降雨量之间的回归方程。通过结合 ECM 和机制模型,预测了 2018 年 8 次降雨事件中进入河流的浓度,并计算了背景值以评估地表水水质。预测值与监测值接近。因此,本研究对重背景污染物负荷地区的水质评估和管理具有重要意义。