Watershed Modeling of Surface Water-Groundwater Interaction under Projected Climate Change and Water Management in the Haihe River Basin, China
Zhonggen Wang, Yuzhou Luo, Xinjun Zhu, Rui Wang, Wei Li, Minghua Zhang
International Journal of Environment and Climate Change · pp. 421–443 · Published 15 Sep 2013
10.9734/BJECC/2013/2673Abstract
The Haihe River Basin (HRB), located in northern China with a drainage area of 318,200 km2, is one of the most developed regions in China. With rapid population growth and economic development, the combined problems of water shortage and groundwater over-pumping significantly constrain the sustainable development in this area. In order to strengthen the unified management of groundwater and surface water, we developed hydrologic modeling of surface water and groundwater interaction by coupling SWAT (for surface water simulation) and MODFLOW (for groundwater simulation). The newly developed modeling framework reasonably captured the spatiotemporal variability of the hydrological processes of the surface water and groundwater in the study area. The modeling results showed a good agreement with the measurements of surface water and groundwater during 1996-2006. Results of model evaluation indicated that the developed model could be a promising tool in watershed management planning under the context of global climate change and the “South-North Water Transfer Project”. In the HRB, climate change has significant effects on surface hydrology as indicated by the predicted increases on actual evapotranspiration and precipitation during 2041-2050 relative to those during 1991-2000. Changes of groundwater storage were mainly contributed by water diversion which would reduce the requirement of water pumping from groundwater especially for domestic and industrial uses. By the middle of the 21st century, increased water supply by projected precipitation and water diversion would result in annual increases of 3.9~9.9 billion m3 for river discharge and 1.7~2.9 billion m3 for groundwater storage as annual averages.
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