Incorporation of groundwater pumping in a global Land Surface Model with the representation of human impacts
Year: 2014
Type: article
Abstract: Observations indicate that groundwater levels are declining in many regions around the world. Simulating such depletion of groundwater at the global scale still remains a challenge because most global Land Surface Models (LSMs) lack the physical representation of groundwater dynamics in general and well pumping in particular. Here we present an integrated hydrologic model, which explicitly simulates groundwater dynamics and pumping within a global LSM that also accounts for human activities such as irrigation and reservoir operation. The model is used to simulate global water fluxes and storages with a particular focus on groundwater withdrawal and depletion in the High Plains Aquifer (HPA) and Central Valley Aquifer (CVA). Simulated global groundwater withdrawal and depletion for the year 2000 are 570 and 330 km3 yr21, respectively; the depletion agrees better with observations than our previous model result without groundwater representation, but may still contain certain uncertainties and is on the higher side of other estimates. Groundwater withdrawals from the HPA and CVA are 22 and 9 km3 yr21, respectively, which are also consistent with the observations of 24 and 13 km3 yr21. The model simulates a significant decline in total terrestrial water storage in both regions as caused mainly by groundwater storage depletion. Groundwater table declined by 14 cm yr21 in the HPA during 2003–2010; the rate is even higher (71 cm yr21) in the CVA. These results demonstrate the potential of the developed model to study the dynamic relationship between human water use, groundwater storage, and the entire hydrologic cycle.
Source: Water Resources Research
DOI: 10.1002/2014wr015602
Institutions: Michigan State University, Max Planck Institute for Biogeochemistry, National University of Singapore, National Institute for Environmental Studies, Centre National de la Recherche Scientifique, Géosciences Rennes, Université de Rennes, Tokyo Institute of Technology, Institute of Industrial Science, The University of Tokyo, The University of Tokyo
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2012804429
