Toward calibration of regional groundwater models using GRACE data

被引:69
作者
Sun, Alexander Y. [1 ]
Green, Ronald [1 ]
Swenson, Sean [2 ]
Rodell, Matthew [3 ]
机构
[1] SW Res Inst, Geosci & Engn Div, San Antonio, TX USA
[2] Natl Ctr Atmospher Res, Boulder, CO 80307 USA
[3] NASA, Goddard Space Flight Ctr, Hydrol Sci Branch, Greenbelt, MD 20771 USA
关键词
Groundwater modeling; GRACE; Multiobjective optimization; Water budget analysis; GENETIC ALGORITHM; FLOW; METHODOLOGY; RECHARGE; SYSTEM;
D O I
10.1016/j.jhydrol.2011.10.025
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Regional groundwater models are increasingly used for short- and long-term water resources planning, in anticipation of greater climate variability and population growth. However, many of these models are subject to structural and parametric uncertainties because of the lack of field measurements. In recent years, the Gravity Recovery and Climate Experiment (GRACE) satellite mission has shown great potential for tracking total water storage changes over large regions. The pattern of groundwater storage changes inferred from GRACE may be incorporated as an additional regularization mechanism for calibrating regional groundwater models. Motivated by the demonstrated success of GRACE for monitoring groundwater storage changes, this study explores the combined use of in situ water level measurements and GRACE-derived groundwater storage changes for calibrating regional groundwater models. The resulting optimization problem is solved using an evolutionary optimization algorithm. We demonstrate the proposed calibration strategy for the hydraulically connected Edwards-Trinity Plateau and Pecos Valley aquifers (total area 115,000 km(2)) in west Texas. Monthly GRACE data from 2002 to 2007 were used to recalibrate a regional groundwater model developed for the area. Our results indicate that (i) calibration using in situ data alone may yield multiple plausible solutions, a phenomenon well known to hydrologists; and (ii) GRACE data helped further constrain model parameters over the study period and, thus, may be continuously assimilated, among other sources of data, for enhancing existing regional groundwater models. (C) 2011 Published by Elsevier B.V.
引用
收藏
页码:1 / 9
页数:9
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