Hydrogeological Modeling and Water Resources Management: Improving the Link Between Data, Prediction, and Decision Making

Abstract

A risk-based decision-making mechanism capable of accounting for uncertainty regarding local conditions is crucial to water resources management, regulation, and policy making. Despite the great potential of hydrogeological models in supporting water resources decisions, challenges remain due to the many sources of uncertainty as well as making and communicating decisions mindful of this uncertainty. This paper presents a framework that utilizes statistical hypothesis testing and an integrated approach to the planning of site characterization, modeling prediction, and decision making. Benefits of this framework include aggregated uncertainty quantification and risk evaluation, simplified communication of risk between stakeholders, and improved defensibility of decisions. The framework acknowledges that obtaining absolute certainty in decision making is impossible; rather, the framework provides a systematic way to make decisions in light of uncertainty and determine the amount of information required. In this manner, quantitative evaluation of a field campaign design is possible before data are collected, beginning from any knowledge state, which can be updated as more information becomes available. We discuss the limitations of this approach by the types of uncertainty that can be recognized and make suggestions for addressing the rest. This paper presents the framework in general and then demonstrates its application in a synthetic case study. Results indicate that the effectiveness of field campaigns depends not only on the environmental performance metric being predicted but also on the threshold value in decision-making processes. The findings also demonstrate that improved parameter estimation does not necessarily lead to better decision making, thus reemphasizing the need for goal-oriented characterization. Environmental Performance Metrics and Water Resources ManagementSustainable groundwater management requires managers to make decisions based on answers to crucial questions regarding the quantity and quality of groundwater resources. For example, a water district manager needs to make decisions on when and where to divert water to storage facilities, so that the district has water that is suitably clean (i.e., that all contaminant concentrations are below the limit of the treatment system) and sufficiently ample (i.e., that there is an acceptable low risk of failure to supply the fluctuating domestic water demand). In these cases, the hydrological/hydrogeological variable(s) involved in these types of questions may be the arrival time of a contaminant plume at a water intake, the groundwater and contaminant flux passing through a specific area over a given period, or the contaminant concentration at a specific location or time. Such variables have been referred to as environmental performance metrics (EPMs; De Barros et al., 2012), the prediction of which helps water managers answer the aforementioned questions.

Sustainability Assessment of Water Resources in Beijing

“…The main objectives are to ensure that water resource systems are designed and managed to fully contribute to providing water of sufficient quantity and quality for agricultural, industrial, and municipal uses to meet the growing demands posed by social economic development, both now and in the future, while maintaining the ecological, environmental, and hydrological integrity [11]. The definition of water sustainability urges water resource managers to consider every impact of water-related programs and requires them to make difficult decisions regarding the selection, maintenance, and treatment of water sources in light of the increasing scarcity and prevalence of contamination in both surface water and groundwater [12]. Therefore, a comprehensive assessment that combines environmental, economic, and social criteria has become a high priority for sustainable water resource management to cope with complex and uncertain water-related issues [13,14].…”

Estimating Hydrothermal Properties and High-Frequency Fluxes From Geophysical Measurements in the Hyporheic Zone

“…Previous studies demonstrated how uncertain HZ properties result in incorrect discharge calculations (e.g., Shanafield et al, 2011), with the Bayesian framework presented in this study, uncertainties in HZ properties are accounted for on flux estimates in a way that is transparent and coherent. Another application of such framework is goal-oriented campaign design, where field campaigns are optimized so that they maximize the expected data worth (e.g., Nowak et al, 2012;Harken et al, 2019). For example, if the goal of a given campaign is to estimate hydraulic conductivity, one should favor field measurements collected in high-flow conditions (e.g., winter) over low-flow conditions.…”

Evaluating Domestic Well Vulnerability to Contamination From Unconventional Oil and Gas Development Sites

“…Groundwater models have been used for decades in physically based risk assessments and as decision support tools for various applications (Freeze et al, 1990; Harken et al, 2019; Rajabi et al, 2018). To date, the majority of the subsurface modeling studies within the UD context have focused on the vertical migration of fracking fluids and formation brines from the deep target shale units to shallow aquifers.…”