Surface Depression and Wetland Water Storage Improves Major River Basin Hydrologic Predictions.

摘要: Surface water storage in small yet abundant landscape depressions-including wetlands and other waterbodies-is largely disregarded conventional hydrologic modeling practices. No quantitative evidence exists of how their exclusion may lead to potentially inaccurate model projections understanding dynamics across the world's major river basins. To fill this knowledge gap, we developed first-ever basin-scale approach integrating surface depressions focusing on 450,000-km2 Upper Mississippi River Basin (UMRB) United States. We applied a novel topography-based algorithm estimate areas volumes ~455,000 (>1 ha) UMRB (in addition lakes reservoirs) subsequently aggregated effects per subbasin. Compared "no depression" model, our depression-integrated (a) improved streamflow simulation accuracy with increasing upstream abundance depression storage, (b) significantly altered spatial patterns magnitudes yields 315,000 km2 (70%) basin area, (c) provided realistic distributions rootzone wetness conditions corresponding satellite-based data. Results further suggest that capacity (i.e., volume) alone does not fully explain depressions' cumulative responses. Local subbasin level) climatic geophysical drivers downstream flowpath-regulating structures (e.g., reservoirs dams) influence extent which volume causes effects. With these new insights, study supports integration thereby catalyzes reassessment current hydrological management practices for studies.