Effects of Spatiotemporal Constraints on Geostatistical Analysis of Groundwater Depth.

Geostatistical evaluation of the groundwater depth (GWD) in California's South Coast hydrologic region, and its sensitivity to different spatiotemporal assumptions, is presented in this paper. We obtain a pseudo-stationary representation of the groundwater depth, using the publicly available, online database from the GAMA GeoTracker project, while tracking the associated uncertainty throughout the process. We create nine different sub-datasets, using different temporal constraints, such as seasonal partitioning and different long-term variability filtering criteria. The geostatistical analysis and comparison between the different maps highlight the trade-off between spatial and temporal accuracy. For example, when moving to stricter filtering criteria, despite removing a large number of sites from the interpolation, the root mean squared error (RMSE) calculated in the analysis either decreased or only slightly increased. This suggests that the long-term variability filter is a good representation of the GWD accuracy and that the cross-validation RMSE captures both the stability effect as well as spatial density of the measurement points. We further find that the point-specific standard error is strongly correlated with the associated GWD prediction and that the mean relative error is approximately 60% of the prediction. Hence, it is highly recommended to account for such error in a forward-engineering application, by introducing a GWD distribution rather than a single value into the analysis. Finally, we analyze seasonal fluctuations in the study region and find that they are on average 2.5 m with a standard deviation of 8 m.

Groundwater Model Simulations of Stakeholder-Identified Scenarios in a High-Conflict Irrigated Area.

This study investigated collaborative groundwater-flow modeling and scenario analysis in the Little Plover River basin, Wisconsin, USA where an unconfined aquifer supplies groundwater for agricultural irrigation, industrial processing, municipal water supply, and stream baseflow. We recruited stakeholders with diverse interests to identify, prioritize, and evaluate scenarios defined as management changes to the landscape. Using a groundwater flow model, we simulated the top 10 stakeholder-ranked scenarios under historically informed dry, average, and wet weather conditions and evaluated the ability of scenarios to meet government-defined stream flow performance measures. Results show that multiple changes to the landscape are necessary to maintain optimum stream flow, particularly during dry years. Yet, when landscape changes from three scenarios-transferring water from the local waste water treatment plant to basin headwaters, moving municipal wells further from the river and downstream, and converting 240 acre (97 ha) of irrigated land to unirrigated land-were simulated in combination, the probability of meeting or exceeding optimum flows rose to 75, 65, and 34% at upper, mid, and lower stream gages, respectively, in dry climate conditions. Discussions with stakeholders reveal that the collaborative model and scenario analysis process resulted in social learning that built upon the existing complex and dynamic institutional landscape. The approach provided a forum for solution-based discussions, and the model served as an important mediation tool for the development and evaluation of community-defined scenarios in a high conflict environment. Today, stakeholders continue to work collaboratively to overcome challenges and implement voluntary solutions in the basin.

Depletion Mapping and Constrained Optimization to Support Managing Groundwater Extraction.

Groundwater models often serve as management tools to evaluate competing water uses including ecosystems, irrigated agriculture, industry, municipal supply, and others. Depletion potential mapping-showing the model-calculated potential impacts that wells have on stream baseflow-can form the basis for multiple potential management approaches in an oversubscribed basin. Specific management approaches can include scenarios proposed by stakeholders, systematic changes in well pumping based on depletion potential, and formal constrained optimization, which can be used to quantify the tradeoff between water use and stream baseflow. Variables such as the maximum amount of reduction allowed in each well and various groupings of wells using, for example, K-means clustering considering spatial proximity and depletion potential are considered. These approaches provide a potential starting point and guidance for resource managers and stakeholders to make decisions about groundwater management in a basin, spreading responsibility in different ways. We illustrate these approaches in the Little Plover River basin in central Wisconsin, United States-home to a rich agricultural tradition, with farmland and urban areas both in close proximity to a groundwater-dependent trout stream. Groundwater withdrawals have reduced baseflow supplying the Little Plover River below a legally established minimum. The techniques in this work were developed in response to engaged stakeholders with various interests and goals for the basin. They sought to develop a collaborative management plan at a watershed scale that restores the flow rate in the river in a manner that incorporates principles of shared governance and results in effective and minimally disruptive changes in groundwater extraction practices.