EKI has implemented a cutting-edge approach to improve model accessibility and value for its clients, including developing internal modeling toolkits to help streamline model input file generation, execution, and post-processing of results. EKI has also integrated these processes into customized, user-friendly decision support tool (DST) interfaces that allow clients to directly specify critical model inputs, run, extract, visualize, and compare model results to inform operational management decision-making. EKI’s approach to developing and deploying DSTs allows for streamlined data analytics and improved communication of outputs to support real-time operational and management decision-making.
The following is an example of a DST dashboard to support groundwater management for Arvin-Edison Water Storage District.
Consistent with Arvin-Edison Water Storage District’s mission to ensure sustainable, affordable and quality surface and groundwater supplies for the farmers and landowners within Arvin-Edison Water Storage District, EKI developed an operational Decision Support Tool (DST) that allows for the evaluation of District operational decisions, such as surface water delivery volumes and extent, groundwater pumping rates, and banking facility operations, within a projected 5-year groundwater flow simulation. Results can guide District decisions to avoid Undesirable Results defined by the Sustainable Groundwater Management Act (SGMA) under future hydrologic and water supply uncertainties.
The DST calculates how much water is projected to be available under a selected water year type, and allows the user to specify how to deliver water to meet demands, whether there is a groundwater allocation on private pumpers, how to distribute water between the Surface Water Service Area units and spreading basins, and where to recover banked water.
The DST is coupled to the Arvin-Edison Groundwater Flow Model to simulate projected groundwater conditions beneath the District. Model-projected groundwater levels are compared to Sustainable Management Criteria defined at individual SGMA Representative Monitoring Sites, and key quantitative metrics such as the projected water budget are graphically displayed to inform ongoing groundwater management policies and practices.
1. What is the DST
Leveraging new open-source tools, EKI developed an interactive decision support tool to assist in operational management decision-making and plan for future drought events in the SGMA era. The Tool is comprised of a dashboard built in R Shiny and run on a web browser. It is currently hosted on a virtual machine but can also be delivered on a web server. The DST has a user-friendly frontend interface that allows users to create model scenarios, run the Arvin-Edison Groundwater Flow Model (AEGFM), and evaluate and compare results with only a few clicks. The DST has a fully integrated backend that generates model input files, executes a 5-year Soil Moisture Balance model (SMB) and groundwater flow model simulation, post processes outputs, and creates key visualizations automatically.
2. Start Here
Upon initializing the DST through any web browser, the user is greeted by a home page outlining the background objectives and purpose of the tool. The front page also contains a simple “how-to” guide outlining the basic steps for operating the DST.
2. DST Inputs:
The user begins a model scenario by specifying assumptions regarding future hydrology and water supply availability, which can be generated automatically through stochastic sampling of historical data or manually assigned. The user can also assign variable boundary conditions and land use assumptions, including predictive land use changes based on historical trends. The user can also reload assumptions from a prior scenario.
The user can then specify a supply allocation framework for each year of the predicted simulation, including assigning pro-rated surface water deliveries, groundwater pumping allocations, and target groundwater recharge volumes. This allows the user to explore different conjunctive use strategies under variable hydrology. An interactive graph visualizes supply allocations relative to projected demands.
The user can then direct the model where to “put” imported supplies and “pull” banked supplies from. Specifically, the user assigns surface water deliveries to individual (existing and future) service units, and dictates where to store and/or recover banking supplies within individual spreading basins and recovery well networks. These are shown on an interactive map embedded within the dashboard.
3. Run Groundwater Model:
The user can then save the scenario and initialize the integrated soil moisture and groundwater ﬂow models with a single click. The DST will display status updates throughout each step of the simulation. The entire model set up, run, and postprocessing operation takes less than 5 minutes.
4. DST Outputs
After the model simulation is complete, the user can review critical timeseries outputs typically used to inform decision-making. These include hydrographs at SGMA representative monitoring sites relative to established Minimum Thresholds (MTs) and Measurable Objectives (MOs). The user can also examine maps of water level changes across the model domain to evaluate agency-wide groundwater conditions throughout the simulation period.
An accompanying groundwater management tab displays relevant graphical outputs that track groundwater recharge and recovery operations, water supply portfolios, water budget fluxes, and cumulative change in groundwater storage throughout the simulation period.
The user can also directly compare model outputs between two scenarios, including reviewing relative changes in water levels at SGMA wells, impacts on groundwater storage, and balances within the District’s groundwater banks between scenarios. This enables rapid evaluation of groundwater conditions and SGMA compliance under variable hydrologic conditions and/or operational management schema.
5. DST Scenario Manager
The scenario manager allows the user to quickly review all previous model runs, including the core assumptions associated with each scenario, check completion status, and delete unwanted scenarios. An accompanying “How does it work” tab provides a more detailed description of DST features and underlying assumptions used to generate model input ﬁles from the front-end interface.