Extending the Capture Map Concept to Estimate Discrete and Risk-Based Streamflow Depletion Potential

A popular and contemporary use of numerical groundwater models is to estimate the discrete relation between groundwater extraction and surface-water/groundwater exchange. Previously, the concept of a “capture map” has been put forward as a means to effectively summarize this relation for decision-making consumption. While capture maps have enjoyed success in the environmental simulation industry, they are deterministic, ignoring uncertainty in the underlying model. Furthermore, capture maps are not typically calculated in a manner that facilitates analysis of varying combinations of extraction locations and/or reaches. That is, they are typically constructed with focus on a single reach or group of reaches. The former of these limitations is important for conveying risk to decision makers and stakeholders, while the latter is important for decision-making support related to surface-water management, where future foci may include reaches that were not the focus of the original capture analysis. Herein, we use the concept of a response matrix to generalize the theory of the capture-map approach to estimate spatially discrete streamflow depletion potential. We also use first-order, second-moment uncertainty estimation techniques with the concept of “risk shifting” to place capture maps and streamflow depletion potential in a stochastic, risk-based framework. Our approach is demonstrated for an integrated groundwater/surface-water model of the lower San Antonio River, Texas, USA.     

Risk-Based Decision-Support Groundwater Modeling for the Lower San Antonio River Basin,Texas, USA

A numerical surface-water/groundwater model was developed for the lower San Antonio River Basin to evaluate the responses of low base flows and groundwater levels within the basin under conditions of reduced recharge and increased groundwater withdrawals. Batch data assimilation through history matching used a simulation of historical conditions (2006-2013); this process included history-matching to groundwater levels and base-flow estimates at several gages, and was completed in a high-dimensional (highly parameterized) framework. The model was developed in an uncertainty framework such that parameters, observations, and scenarios of interest are envisioned stochastically as distributions of potential values. Results indicate that groundwater contributions to surface water during periods of low flow may be reduced from 6% to 25% with a corresponding 25% reduction in recharge and a 25% increase in groundwater pumping over an 8-year planning period. Furthermore, results indicate groundwater-level reductions in some hydrostratigraphic units are more likely than in other hydrostratigraphic units over an 8-year period under drought conditions with the higher groundwater withdrawal scenario.     

Effect of hypersaline cooling canals on aquifer salinization

The combined effect of salinity and temperature on density-driven convection was evaluated in this study for a large (28 km²) cooling canal system (CCS) at a thermoelectric power plant in south Florida, USA. A two-dimensional cross-section model was used to evaluate the effects of hydraulic heterogeneities, cooling canal salinity, heat transport, and cooling canal geometry on aquifer salinization and movement of the freshwater/saltwater interface. Four different hydraulic conductivity configurations, with values ranging over several orders of magnitude, were evaluated with the model. For all of the conditions evaluated, aquifer salinization was initiated by the formation of dense, hypersaline fingers that descended downward to the bottom of the 30-m thick aquifer. Saline fingers reached the aquifer bottom in times ranging from a few days to approximately 5 years for the lowest hydraulic conductivity case. Aquifer salinization continued after saline fingers reached the aquifer bottom and coalesced by lateral movement away from the site. Model results showed that aquifer salinization was most sensitive to aquifer heterogeneity, but was also sensitive to CCS salinity, temperature, and configuration.