College of Water Sciences, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China; Engineering Research Center of Groundwater Pollution Control and Remediation of Ministry of Education, Beijing 100875, China.
College of Water Sciences, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China; Engineering Research Center of Groundwater Pollution Control and Remediation of Ministry of Education, Beijing 100875, China.
Sci Total Environ. 2021 May 10;768:145489. doi: 10.1016/j.scitotenv.2021.145489. Epub 2021 Jan 30.
The ecological water replenishment (EWR) of Yongding River has been an important project implemented in response to the Development of an Ecological Civilization policy in China since 2016. A reasonable amount of EWR requires a systematic understanding of the relationship among the surface water, groundwater, ecology and economy. However, studying surface water-groundwater interactions still remains an important issue. Thus, a coupled model integrating a Muskingum method-based open channel flow model and machine learning-based groundwater model is developed to describe the dynamic changes in streamflow and groundwater level in response to the EWR of Yongding River. The model is calibrated using observed streamflow data as well as groundwater level data on a daily scale for the spring EWR in 2020. The simulated results match well with the observed data and suggest that significant groundwater level increases occur only around the main channel of Yongding River. Fifteen scenarios under different EWR schemes are set to obtain reasonable streamflow during EWR, and then the responses of streamflow and groundwater level changes are simulated. Reasonable streamflow at the Guanting Reservoir need to be above 65 m/s to ensure the streamflow can pass through Beijing and significant groundwater level recoveries of 170 million m through EWR. The developed models can improve the understanding of the interaction between surface water and groundwater and provide a quick assessment of the factors influencing the different EWR schemes and thus aid in effective EWR project management.
永定河生态补水工程是中国自 2016 年以来实施的生态文明建设政策的重要项目。合理的生态补水需要系统地了解地表水、地下水、生态和经济之间的关系。然而，研究地表水-地下水相互作用仍然是一个重要问题。因此，开发了一个集成 Muskingum 方法的明渠流模型和基于机器学习的地下水模型的耦合模型，以描述永定河生态补水对河川流量和地下水位的动态变化。该模型使用 2020 年春季生态补水的实测河川流量数据和每日尺度的地下水位数据进行校准。模拟结果与观测数据吻合较好，表明地下水位仅在永定河主河道附近显著升高。设置了 15 种不同生态补水方案的情景，以获得生态补水期间的合理河川流量，然后模拟河川流量和地下水位变化的响应。为了确保河川流量能够通过北京，官厅水库的合理流量需要超过 65 m/s，并且需要通过生态补水恢复 1.7 亿立方米的地下水位。所开发的模型可以提高对地表水和地下水相互作用的理解，并快速评估影响不同生态补水方案的因素，从而有助于有效管理生态补水项目。
