Institute of International Rivers and Eco-security, Yunnan University, Kunming, Yunnan, 650500, China.
Institute of International Rivers and Eco-security, Yunnan University, Kunming, Yunnan, 650500, China; Yunnan Key Laboratory of International Rivers and Transboundary Eco-security, Kunming, Yunnan, 650500, China.
J Environ Manage. 2022 Dec 15;324:116339. doi: 10.1016/j.jenvman.2022.116339. Epub 2022 Sep 26.
Cross-border impact assessment of cascade reservoir operation on hydrological regimes is a vital prerequisite for the sustainable development and management of transboundary waters. However, assessment based on traditional hydrological modeling for transboundary rivers is limited by the availability of meteorological and hydrological data. In this study, a combined data-driven model (CV-LSTM) was built to simulate natural runoff without dam construction in the Upper Mekong River. Then, the simulated natural runoff was compared against the observation runoff influenced by dam operation to assess the impacts of reservoirs on flood and drought events. The research results are as follows: (1) CV-LSTM improved simulation performance by effectively utilizing spatial information from more extensive and diversified data, and it could overcome the limitation of classic data-driven models in that the spatial heterogeneity of input variables cannot be sufficiently considered. (2) Reservoir operation decreased the annual streamflow of the Upper Mekong River by 1.07% during the 2001-2016. In particular, with the operation of two mega reservoirs (Xiaowan and Nuozadu) after 2008, the annual streamflow decreased by 3.95%. (3) The upstream reservoirs exerted significant runoff regulative effects on the Lower Mekong during 2001-2016. Drought duration and severity significantly decreased at the Chiang Sean hydrological station, flood frequency decreased by 11%, and the mean day of flood occurrence decreased by 30%. This study developed an innovative approach, CV-LSTM, based on open-source spatial information, which could effectively analyze the cross-border impact of cascade reservoir operation. The results provide new insights into the quantitative assessment of the transboundary influence of upstream-downstream runoff change induced by cascade dams in international rivers.
跨境梯级水库运行对水文格局的影响评估是跨境水资源可持续开发和管理的重要前提。然而，基于传统水文模型对跨界河流进行的评估受到气象和水文数据的可用性限制。本研究构建了一个组合数据驱动模型（CV-LSTM），以模拟湄公河上游无大坝建设的自然径流量。然后，将模拟的自然径流量与受大坝运行影响的观测径流量进行比较，以评估水库对洪水和干旱事件的影响。研究结果如下：（1）CV-LSTM 通过有效利用来自更广泛和多样化数据的空间信息，改善了模拟性能，克服了经典数据驱动模型的局限性，即无法充分考虑输入变量的空间异质性。（2）水库运行导致 2001-2016 年湄公河上游年径流量减少了 1.07%。特别是 2008 年后两座大型水库（小湾和糯扎渡）的运行，使得年径流量减少了 3.95%。（3）上游水库对 2001-2016 年湄公河下游的径流具有显著的调节作用。Chiang Sean 水文站的干旱持续时间和严重程度显著降低，洪峰频率降低了 11%，洪峰出现的平均天数减少了 30%。本研究开发了一种基于开源空间信息的创新方法 CV-LSTM，可有效分析梯级水库运行的跨境影响。研究结果为定量评估国际河流上下游梯级大坝引起的径流变化对跨境影响提供了新的见解。
