Forecasting Climate Induced Ground Water Recharge Variability Across Subbasins in the Mid Western US

Optimal groundwater resource management under changing climate requires knowledge of the rates and spatial distribution of recharge to aquifers. The SOM technique was used to estimate groundwater recharge from available and uncertain hydrologic, land use, and topographic information without long-term monitoring [10].

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□ Observed 1997 O Cherkauer 1997 * SOM 1997 ® SOM Dry Year a SOM Wet Year -regression

Fig. 3.2 Comparison of observed and forecasted annual recharge as a function of short-term ENSO climatic events

□ Observed 1997 O Cherkauer 1997 * SOM 1997 ® SOM Dry Year a SOM Wet Year -regression

Fig. 3.2 Comparison of observed and forecasted annual recharge as a function of short-term ENSO climatic events

The technique was applied to twelve basins in southeastern Wisconsin where recharge observations were determined using a recession-curve-displacement technique and normalized by annual precipitation. Uncertainty was introduced and nonlinear correlation preserved among these explanatory and response variables using a Monte Carlo (MC) technique. Common patterns among the MC realizations were identified and mapped onto a two-dimensional torroid. Fitted data vectors in the SOM were then used to impute normalized recharge ratios that compared well with the observations and published results (Fig. 3.2). The effects of climate change on spatial groundwater recharge were evaluated using the model and precipitation extremes associated with the ENSO.

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