statemodify: a Python framework to facilitate accessible exploratory modeling for water systems planning and management in Colorado
The Colorado River Basin (CRB) is experiencing an unprecedented water shortage crisis brought upon by large hydroclimatic changes and over-allocation of the Colorado River. The complexity of balancing the demands of agriculture and growing cities in the basin combined with a diminishing water supply makes water systems planning and management a growing challenge. Future conditions in the basin are uncertain, so tools that facilitate exploratory modeling are needed to uncover vulnerabilities in the CRB under many plausible future scenarios. One such tool is StateMod, a highly resolved, open source, regional water allocation model that is currently used by the State of Colorado to support water use assessments. It can also be used to develop and simulate hypothetical scenarios to assess how changes in hydrology, water rights, or infrastructure impact regional water shortages, streamflow, or reservoir levels.
Using StateMod with exploratory modeling requires familiarity with Fortran and poses nontrivial challenges in sampling model inputs and managing the size and complexity of outputs of interest, especially for large ensembles. These challenges limit its use among researchers and users who have valuable insight that can lead to more sustainable management of the CRB. Thus, we develop statemodify, a Python-based package and framework that allows users to easily interact with StateMod in a Jupyter Notebook environment. We provide functions to manipulate StateMod’s input files to develop alternative demand, hydrology, infrastructure, and institutional scenarios for Colorado’s West Slope. We also create methods to compress and extract model output into easily readable data frames. Overall, the statemodify framework will not only broaden the user base that can interact with StateMod, but also can serve as a guide on how to make exploratory modeling accessible to diverse groups whose inclusion can lead to more robust basin management.