Groundwater is not easily contaminated, but it is difficult to restore once contaminated. Therefore, groundwater management is important to prevent pollutants from reaching groundwater. A common step in developing groundwater management plans is assessment of aquifer risk using computational models. Groundwater modeling with a geographic information system (GIS) for efficient groundwater management can provide maps of regions where groundwater is contaminated or may be vulnerable and also can help select the optimal number of groundwater monitoring locations.
For efficient groundwater resources management, integrated aquifer vulnerability assessment is required. Integrated aquifer vulnerability assessment is incorporated into a groundwater characterization and pollutant transport analysis with tiered approaches for intrinsic aquifer vulnerability assessment (intrinsic aquifer properties) and aquifer hazard assessment (pollutant transport properties). Intrinsic aquifer vulnerability was conducted by using high resolution data to create high resolution results with DRASTIC. Aquifer hazard assessment was performed using a watershed scale hydrological model (SWAT) and a machine learning technique (Geo-ANN) developed in this study. For accurate estimation of aquifer hazard assessment, SWAT 2012 code was modified to simultaneously calibrate streamflow and baseflow using SUFI-2. With the DRASTIC, modified SWAT, and Geo-ANN, integrated aquifer assessment was performed in the Upper White River Watershed (UWRW) located in the East central IN.
The intrinsic aquifer vulnerability results from DRASTIC without calibration were validated with observed nitrate concentrations in wells. The results showed that approximately 35.3% of nitrate detections > 2 ppm are within “High” and “Very high” vulnerability areas (represent 3.2% of vulnerability area). The results from calibrated DRASTIC showed that approximately 42.2% of nitrate detections > 2 ppm are within DRASTIC “High” and “Very high” vulnerability areas which represent only 3.4% of the area. The calibrated DRASTIC better predicted vulnerability areas using based on observed well nitrate levels > 2 ppm.
An efficient flow calibration regime (EFCR) created by incorporating modified SWAT 2012 code and SUFI-2 was developed for accurate streamflow and baseflow estimation by calibrating streamflow and baseflow simultaneously. The results of the calibration and validation in the UWRW showed that the simulated streamflow and baseflow agreed well with the observed data. With the EFCR, for the calibration period (1990–2001), NSE / R2 / PBIAS for streamflow were 0.85 / 0.87 / 3.90 and NSE / R2 / PBIAS for baseflow were 0.63 / 0.73 / 16.7. For the validation period (2002–2010), NSE / R2 / PBIAS for streamflow and baseflow showed 0.88 / 0.92 / 1.50 (streamflow) and 0.65 / 0.70 / 13.8 (baseflow). These values indicate that the model is more than “Satisfactory” for all periods. For baseflow-related studies, such as analysis of nitrate leaching for aquifer hazard assessment, simultaneous streamflow and baseflow calibration would be a reasonable approach.
For integrated aquifer vulnerability assessment in the UWRW, an integrated aquifer vulnerability map was produced by combining the intrinsic aquifer vulnerability map from DRASTIC and the aquifer hazard map from SWAT and Geo-ANN. The results of integrated aquifer vulnerability assessment were validated with observed nitrate concentrations in wells. Approximately 81.0% of well nitrate detections > 2 ppm were within “High” and “Very high” vulnerability areas that represented only 5.8% of the area. Approximately 12% of the nitrate detections were within the “Moderate” vulnerability class (30.7% of area), and 6.9% of the nitrate detections were within the “Low” vulnerability class (50.7% of area). Well nitrate levels > 2 ppm were not detected within the “Very low” vulnerability class (12.8% of area). The results indicate that integrated aquifer vulnerability assessment performed well. The integrated aquifer vulnerability assessment considers both intrinsic aquifer properties and pollutant transport properties. Thus, the overall assessment of aquifer vulnerability can be performed using the integrated aquifer vulnerability assessment technique provided in this study. Moreover, this approach is expected to be an efficient guide for managing groundwater resources for policy makers and groundwater-related researchers.
|Advisor:||Engel, Bernard A.|
|Commitee:||Chaubey, Indrajeet, Harbor, Jon, Merwade, Venkatesh|
|Department:||Agricultural and Biological Engineering|
|School Location:||United States -- Indiana|
|Source:||DAI-B 79/05(E), Dissertation Abstracts International|
|Subjects:||Agricultural engineering, Water Resource Management|
|Keywords:||Aquifer vulnerability assessment, Drastic, Groundwater management, Machine learning, Optimization, SWAT|
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