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Surface Depression and Wetland Water Storage Improves Major River Basin Hydrologic Predictions
Citation:
Rajib, A., H. Golden, C. Lane, AND Q. Wu. Surface Depression and Wetland Water Storage Improves Major River Basin Hydrologic Predictions. WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, 56(7):e2019WR026561, (2020). https://doi.org/10.1029/2019WR026561
Impact/Purpose:
Surface depressions, including wetlands, ponds, and other similar small waterbodies, perform important hydrologic functions affecting downstream waters. While the hydro-geoscience community has recently started including these abundant landscape features in process-based hydrologic modeling across small- to meso-scale watersheds, disregarding depressions and their effects remains a persistent issue in conventional continental-scale modeling of flood, drought, and water availability in response to climate and land use changes. In this study, we hypothesized that including surface depression storage in process-based hydrologic models will substantially enhance our understanding of hydrologic dynamics across the world’s major river basins.
Description:
Surface water storage in small yet abundant landscape depressions—including wetlands and other small waterbodies—is largely disregarded in conventional hydrologic modeling practices. No quantitative evidence exists of how their exclusion may lead to potentially inaccurate model projections and understanding of hydrologic dynamics across the world's major river basins. To fill this knowledge gap, we developed the first‐ever major river basin‐scale modeling approach integrating surface depressions and focusing on the 450,000‐km2 Upper Mississippi River Basin (UMRB) in the United States. We applied a novel topography‐based algorithm to estimate areas and volumes of ~455,000 surface depressions (>1 ha) across the UMRB (in addition to lakes and reservoirs) and subsequently aggregated their effects per subbasin. Compared to a “no depression” conventional model, our depression‐integrated model (a) improved streamflow simulation accuracy with increasing upstream abundance of depression storage, (b) significantly altered the spatial patterns and magnitudes of water yields across 315,000 km2 (70%) of the basin area, and (c) provided realistic spatial distributions of rootzone wetness conditions corresponding to satellite‐based data. Results further suggest that storage capacity (i.e., volume) alone does not fully explain depressions' cumulative effects on landscape hydrologic responses. Local (i.e., subbasin level) climatic and geophysical drivers and downstream flowpath‐regulating structures (e.g., reservoirs and dams) influence the extent to which depression storage volume in a subbasin causes hydrologic effects. With these new insights, our study supports the integration of surface depression storage and thereby catalyzes a reassessment of current hydrological modeling and management practices for basin‐scale studies.
URLs/Downloads:
DOI: Surface Depression and Wetland Water Storage Improves Major River Basin Hydrologic Predictions