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Probabilistic analysis of the effects of climate change on groundwater recharge
Author(s) -
Ng GeneHua Crystal,
McLaughlin Dennis,
Entekhabi Dara,
Scanlon Bridget R.
Publication year - 2010
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2009wr007904
Subject(s) - groundwater recharge , environmental science , precipitation , climate change , hydrology (agriculture) , depression focused recharge , groundwater , climatology , aquifer , geology , meteorology , geography , oceanography , geotechnical engineering
Groundwater recharge is likely to be affected by climate change. In semiarid regions where groundwater resources are often critical, annual recharge rates are typically small and most recharge occurs episodically. Such episodic recharge is uncertain and difficult to predict. This paper analyzes the impacts of different climate predictions on diffuse episodic recharge at a low‐relief semiarid rain‐fed agricultural area. The analysis relies on a probabilistic approach that explicitly accounts for uncertainties in meteorological forcing and in soil and vegetation properties. An ensemble of recharge forecasts is generated from Monte Carlo simulations of a study site in the southern High Plains, United States. Soil and vegetation parameter realizations are conditioned on soil moisture and soil water chloride observations (Ng et al., 2009). A stochastic weather generator provides realizations of meteorological time series for climate alternatives from different general circulation models. For most climate alternatives, predicted changes in average recharge (spanning −75% to +35%) are larger than the corresponding changes in average precipitation (spanning −25% to +20%). This suggests that amplification of climate change impacts may occur in groundwater systems. Predictions also include varying changes in the frequency and magnitude of recharge events. The temporal distribution of precipitation change (over seasons and rain events) explains most of the variability in predictions of recharge totals and episodic occurrence. The ensemble recharge analysis presented in this study offers a systematic approach to investigating interactions between uncertainty and nonlinearities in episodic recharge.