A new method for mapping groundwater recharge areas and for zoning recharge for an inverse model

This thesis presents a new methodology for delineating groundwater recharge and discharge areas. Estimates of recharge rates and locations of recharge areas are important components in strategies for managing groundwater resources. The main contribution of this thesis is a method for zoning recharge for parameter-estimation (inverse) models. The importance of the zoning method presented here is that it is objective, whereas inverse models usually have been zoned subjectively. Moreover, zoning can be adjusted iteratively.; A second contribution of this thesis is comparison of recharge maps to maps of soil association, soil drainage, surficial geology, and depth to water, to test the possibility of inferring recharge from other easily mapped parameters. The thesis relates the various parameters to mechanisms controlling recharge. The comparison of maps is important because it addresses the question whether or not there is a relatively easy way to map recharge apart from the method presented here which uses primarily the water-table elevation. The comparison of maps indicates that no parameter by itself can be used to infer the entire recharge distribution.; Finally, the thesis provides maps of recharge and optimized recharge rates and hydraulic conductivities for a test area in central Wisconsin. These maps and rates are important for refining conceptual and numerical models of the region, and may be of direct use in groundwater management planning.; The methodology uses a finite-element statistical parameter-estimation model to simulate two-dimensional, steady-state groundwater flow. Water-level, hydraulic conductivity, streamflow, and bedrock elevation data are used with a mass-balance technique to zone and estimate recharge means. Transmissivity and aquifer thickness data are used to zone and estimate mean hydraulic conductivity.; The "best" model for the test area was selected by refining zones and assessing the significance of extra parameters using a statistical model discrimination procedure. The best model extractable from the data includes four recharge and two hydraulic conductivity parameters, including strong discharge ({dollar}-{dollar}75 cm/yr), interflow (3 cm/yr), two recharge parameters (26 and 43 cm/yr), and two hydraulic conductivity parameters (0.072 and 0.096 cm/s). The standard error of the head estimates is 1.3 m. The model is most sensitive to zonation and to discharge parameters.