Department of Management Science and Engineering, School of Business, Hohai University, Nanjing, China.
Department of Finance, School of Business, Hohai University, Focheng West Road 8, Jiangning District, Nanjing, 211100, Jiangsu Province, China.
Environ Monit Assess. 2023 Feb 9;195(3):371. doi: 10.1007/s10661-023-11001-6.
Dynamic assessment of the water environment reflects variations in water resources in a basin under the combined influence of nature and humans and is a prerequisite for rational water management. This study provides an integrated assessment of the water environment in a water quantity-quality-soil model. Using the long-term monthly data from hydrological monitoring stations, the water environment of the Yellow River basin is assessed from the year 2006 to 2019. The kernel density estimation and the Dagum Gini coefficient are used to analyze the spatial and temporal imbalances of the water environment. Geographic detectors are used to extract external driving factors of the unbalanced evolution. The study results reveal that (1) the water environment in the basin shows a fluctuating downward trend, which mainly depends on the organic pollution control indicators, with a contribution of 22.85%. Scores of the water environment in the midstream are lower than those in the upstream and downstream due to the heavy pollutant discharges. (2) The spatial imbalance shows a fluctuating downward trend. Inter-regional variation is the primary source of regional variation in the water environment, with an average contribution of 56.02%. (3) The temporal imbalance of the water environment is on the rise, with a degree of multipolarity. The significant left trailing feature of the kernel density curve suggests that there are areas within the basin where the water environment is extremely poor. (4) For the overall basin and upstream, economic development and technological innovation are the main external driving factors influencing the spatial and temporal imbalances of the water environment. For the midstream and downstream, population density and environmental regulations are the main drivers. The interaction of any two factors has a greater impact than the single one.
水环境动态评价反映了在自然和人为因素共同影响下流域水资源的变化,是进行合理水资源管理的前提。本研究在水量-水质-土壤模型中对水环境进行了综合评价。利用长期逐月水文监测站数据,对 2006 年至 2019 年黄河流域的水环境进行了评估。采用核密度估计和达古基尼系数分析了水环境的时空不平衡,并利用地理探测器提取了不平衡演化的外部驱动因素。研究结果表明:(1)流域水环境呈波动下降趋势,主要取决于有机污染控制指标,贡献度为 22.85%。中游的水环境评分低于上游和下游,这是由于污染物排放量大造成的。(2)水环境的空间不平衡呈波动下降趋势,区域间变化是水环境区域变化的主要来源,平均贡献度为 56.02%。(3)水环境的时间不平衡呈上升趋势,具有多极性特征。核密度曲线的显著左拖尾特征表明,流域内存在水环境极差的区域。(4)对于整个流域和上游地区,经济发展和技术创新是影响水环境时空不平衡的主要外部驱动因素。对于中游和下游地区,人口密度和环境法规是主要驱动力。任何两个因素的相互作用比单一因素的影响更大。