Abstract Numerical simulation of ground‐water flow and transport is often impeded by a lack of information regarding the conceptual model and properties that best represent the water‐bearing formation. Inverse analysis assists in the estimation of the properties of the formation once a defensible form of the conceptual model is defined. In essence, inverse analysis reverses the direction of model application to determine the properties that best match data collected from the formation under investigation. This paper describes the development of an inverse analysis implementation of the well‐known and versatile SUTRA model of ground‐water flow and transport. The inverse analysis algorithm retains the extensive functionality of SUTRA in forward simulation and allows various forms of parameter constraints to be stipulated. Addition of inverse analysis functionality to an existing ground‐water model circumvents the development of redundant models, reduces development time, and ensures the consistent and concurrent development of predictive and interpretive capabilities. Two example analyses are presented to demonstrate a portion of the functionality of the novel inverse analysis algorithm.
The impacts of climate change on soil moisture in sub - Arctic watershed simulated by using the hydrologic model. A range of arbitrary changes in temperature and precipitation are applied to the runoff model to study the sensitivity of soil moisture due to potential changes in precipitation and temperature. The sensitivity analysis indicates that changes in precipitation are always amplified in soil moisture with the amplification factor for flow. The change in precipitation has effect on the soil moisture in the catchment. The percentage change in soil moisture levels can be greater than the percentage change in precipitation. Compared to precipitation, temperature increases or decreases alone have impacts on the soil moisture. These results show the potential for climate change to bring about soil moisture that may require a significant planning response. They are also indicative of the fact that hydrological impacts affecting water supply may be important in consider-ing the cost and benefits of potential climate change.
Numerical models of ground-water flow within the regional aquifer underlying Lambton County, Ontario, Canada, are constructed by the conjunctive application of methods of regression and inverse analyses. Regression analysis of physiographic and hydraulic head data reveals a distinct relation between ground-water levels and ground-surface topography that is used to condition the aquifer models that are subjected to inverse analysis. Inverse analysis determines the variation of hydraulic head along the perimeter of the region and the distribution of ground-water recharge and discharge within the region that optimally replicate the observed hydraulic head data. The use of physiographic data as a substitute for geologic data in the construction of the aquifer models is defended on the basis of the constraints that apply to the investigation and the opportunity to invoke hydrogeologic judgment in the evaluation of the results. Interpretation of the results of the analyses reveals important characteristics of the hydrogeology of Lambton County, including an area of elevated ground-water recharge and the partitioning of ground-water discharge to the Saint Clair River.
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