Date of Award
Master of Science
Tim Grundl, Weon Shik Han
Emission Scenario, Gcm, Growing Season, Recharge, Swb, Wisconsin
A watershed, the Prairie River in north-central Wisconsin was used to analyze why the same annual precipitation generates variable annual recharge rates. Global Climate Models (GCMs) with three greenhouse gas emission scenarios (B1, A1B and A2) for two time series 2047-2065 and 2082-2100 were used to examine the annual and monthly differences between the Prairie River watershed future projections and the Prairie River watershed historical record, 1954-2009. The USGS soil water balance (SWB) model was used to calculate recharge.
In the Prairie River watershed, there is a strong correlation (R²=0.84) between growing season recharge and growing season precipitation, and there is a strong correlation (R²=0.74) between non-growing season recharge and non-growing season precipitation. Using the linear regression equations from the two correlation plots, recharge for the watershed was calculated that shows that higher non-growing season precipitation and lower growing season precipitation generate higher annual recharge rates. Simulations of annual precipitation were generated using SDSM, a statistical downscaling model. Using SWB, recharge rates were generated for the simulations. The correlations were similar to the non-simulated data with a correlation (R²=0.75) between growing season recharge and growing season precipitation and a correlation (R²=0.83) between non-growing season recharge and non-growing season precipitation. The linear regression equations for growing season recharge and precipitation and non-growing season recharge and precipitation showed similar equations to the non-simulated data.
For the future climate data, the student's t-test was applied to compare the annual and monthly means of precipitation, temperature, recharge and ET of the Prairie River watershed time series, 1954-2009 to the time series, 2047-2065 and 2082-2100 for the Global Climate Models using three greenhouse gas emission scenarios B1, A1B and A2. For all scenarios for both time series, the t-values predict significant increases in recharge in December and January although annual recharge is not predicted to change, significant increases in temperature in all months with the highest increases occurring in July, August, and September and significant annual increases in ET.
Egan, Alice, "Simulating Recharge in a Wisconsin Watershed: the Effect of Sub Annual Precipitation Patterns" (2014). Theses and Dissertations. 401.