Deep Aquifer Modeling within an Operations and Planning Decision Support Tool on the Rio Grande River, New Mexico

In the Rio Grande basin in New Mexico, water managers must balance irrigation and water supply demands, environmental flow targets, flood control targets, and other operating objectives. Several agencies share a suite of models used for planning, forecasting, operations and water accounting called the Upper Rio Grande Water Operations Model (URGWOM), implemented in RiverWare. While the basin is highly dependent on shallow groundwater and, at longer time scales, the underlying deep aquifer, only the shallow groundwater system is included directly in URGWOM. The shallow groundwater is represented by a gridded network that solves for flow between groundwater nodes and the surface river reaches using an explicit head-based approach. External MODFLOW simulations provide boundary conditions to this shallow groundwater network that represent the deep aquifer. The MODFLOW simulations are computationally intensive, which has limited the number and type of operating scenarios that could be explored with URGWOM. We introduced a set of “aquifer objects” beneath the shallow groundwater network to directly represent the deep groundwater system. This new approach reduces the computational burden by eliminating the MODFLOW simulations, allowing efficient testing of operating policies that are impacted by the response of the deep aquifer, such as increased or decreased pumping and different hydrologic and climate change scenarios. We describe the head-based solution approach for these aquifer objects and show how the MODFLOW model cells are aggregated into larger aquifer objects to represent the entire basin. This new simplified approach produces results that are consistent with the previous approach.