An approach was presented to quantify the sensitivity of ground-water discharge by evapotranspiration (ET) to three categories of independent input variables. A basic ground-water discharge estimation model was adopted to estimate ground-water discharge by ET in Great Basin, USA. The volume of ground water lost to ET was computed as the product of the ground-water discharge rate and the associated area. The ground-water discharge rate was assumed to equal the ET rate minus local precipitation rate. The objective was to outline the procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground-water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation rates in sub-basins.  The specific goal was to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground-water discharge estimates. The influential independent variables to be included in the sensitivity analysis were first selected based on the physical characteristics and the ground-water discharge estimation model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables were calculated using the results from sampling-based Monte Carlo simulations. 

Results/Conclusions

Results illustrate that, while as many as 630 independent variables potentially contributed to the calculation of the total annual ground-water discharge for the area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground-water discharge eatimates. Results indicated that the variability of ET rate for moderately dense desert shrubland contributed to about 75% of the variance in the total ground-water discharge estimates. These results pointed to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground-water discharge. While the approach proposed here used a basic ground-water discharge model, the procedure of quantifying uncertainty and sensitivity could be generalized to handle other types of environmental and ecological models involving large numbers of independent variables.