State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing(LIESMARS), Wuhan University, Wuhan 430079, PR China; Stanford Woods Institute for the Environment, Stanford University, Stanford, CA 94305, USA; Natural Capital Project, Stanford University, Stanford, CA 94305, USA.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing(LIESMARS), Wuhan University, Wuhan 430079, PR China.
Sci Total Environ. 2021 Jun 20;774:145743. doi: 10.1016/j.scitotenv.2021.145743. Epub 2021 Feb 10.
Nearly half large dams of China have been built in the Yangtze River Basin (YRB) and the eco-environmental impacts of existing dams remain elusive. Here we present a spatio-temporal approach to measuring the eco-environmental impacts of dams and its long-term changes. We also develop a new metric, the dam eco-environmental effect index (DEEI), that quickly identifies the eco-environmental impacts on dams over 36 years. Underlying the analysis are the revised universal soil loss equation (RUSLE), the generalized boosted regression modeling (GBM), the generalized linear model (GLM), stepwise multiple regression, trend analysis, soil erosion and sediment yield balance equation, and sample entropy used to identify the eco-environmental impacts of dams on yearly timescales. We find that the accumulated negative environmental effects of constructed dams have increased significantly and has led to large-scale hydrophysical and human health risk affecting the Yangtze River Basins downstream (i.e. Jianghan-Lushui-Northeastern Hubei, Dongting Lake District, Yichang-Jianli, and Qingjiang) and reservoir areas (i.e. Wanxian-Miaohe, Miaohe-Huanglingmiao, and Huanglingmiao-Yichang). We also provide observational evidence that dam construction has reduced the complexity of short-term (1-12 months) in runoff and sediment loads. This spatial pattern seems to reflect a filtering effect of the dams on the temporal and spatial patterns of runoff and sediment. Three Gorges Dam (TGD) has a significant impact on the complexity of the runoff and sediment loads in the mainstream of the Yangtze River. This enhanced impact is attributed to the high trapping efficiency of the dam and its associated large reservoir. This assessment may underestimate the cumulative effect of the dam because it does not consider the future effects of the planned dam. Our study provides a quantitative methodology for finding the relative change rate of eco-environmental impact on dams, which is the first step towards addressing the extent, process, and magnitude of the dam-induced effects.
中国近一半的大型水坝都建在长江流域(YRB),现有水坝的生态环境影响仍难以捉摸。在这里,我们提出了一种时空方法来衡量大坝的生态环境影响及其长期变化。我们还开发了一种新的指标,即大坝生态环境效应指数(DEEI),该指标可以快速识别 36 年来大坝对生态环境的影响。该分析的基础是修正的通用土壤流失方程(RUSLE)、广义增强回归模型(GBM)、广义线性模型(GLM)、逐步多元回归、趋势分析、土壤侵蚀和泥沙平衡方程以及样本熵,用于识别大坝对每年时间尺度的生态环境影响。我们发现,已建成大坝的累积负面环境影响显著增加,导致大规模的水文物理和人类健康风险,影响长江流域下游(即江汉-陆水-鄂东北、洞庭湖地区、宜昌-监利和清江)和库区(即万州-庙河、庙河-黄陵庙和黄陵庙-宜昌)。我们还提供了观测证据,表明大坝建设减少了径流量和泥沙负荷的短期(1-12 个月)复杂性。这种空间格局似乎反映了大坝对径流量和泥沙时空格局的过滤效应。三峡大坝(TGD)对长江干流的径流量和泥沙负荷复杂性有显著影响。这种增强的影响归因于大坝的高捕获效率及其相关的大型水库。由于未考虑计划中的大坝的未来影响,因此本评估可能低估了大坝的累积效应。我们的研究提供了一种定量方法来寻找大坝对生态环境影响的相对变化率,这是解决大坝诱发效应的程度、过程和规模的第一步。