Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region
In humid regions with dense stream networks, surface water exerts a fundamental control on the water levels and flow directions of shallow groundwater. Understanding interactions between groundwater and surface water is critical for managing groundwater resources and groundwater-dependent ecosystems. Representing streams in groundwater models has historically been arduous and error prone. In recent years, however, all the information needed to numerically describe stream boundary conditions for a model area has become readily available online, as have robust open-source software tools for translating that information to a model grid. The SFRmaker Python package leverages geospatial capabilities in the scientific Python ecosystem to robustly automate the production of input to the Streamflow-Routing (SFR) Package of MODFLOW from the National Hydrography Dataset Plus or other hydrography data. This report documents an application of SFRmaker to automate production of SFR Package input for groundwater models within the Mississippi Embayment Regional Aquifer Study area. SFR Package input was developed in three steps: (1) preprocessing to develop a single set of grid-independent flowlines from National Hydrography Dataset Plus version 2 data; (2) setting up the SFR package from the preprocessed flowlines, and (3) correcting streambed top elevations after an initial model run. Separating the hydrography preprocessing from the construction of SFR Package input was advantageous in that it minimized the need to repeat computationally expensive geoprocessing (thereby speeding model construction) and also allowed for the curation of a single set of grid-independent SFR input data that can be used for any MODFLOW model within the study area.
Citation Information
Publication Year | 2023 |
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Title | Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region |
DOI | 10.3133/sir20235051 |
Authors | Andrew T. Leaf |
Publication Type | Report |
Publication Subtype | USGS Numbered Series |
Series Title | Scientific Investigations Report |
Series Number | 2023-5051 |
Index ID | sir20235051 |
Record Source | USGS Publications Warehouse |
USGS Organization | Upper Midwest Water Science Center |