Pairing top-down and bottom-up approaches to analyze catchment scale management of water quality and quantity

Watershed management requires information on the hydrologic impacts of local to regional land use, land cover and infrastructure conditions. Management of runoff volumes, storm flows, and water quality can benefit from large scale, "top-down" screening tools, using readily available information, as well as more detailed, "bottom-up" process-based models that explicitly track local runoff production and routing from sources to receiving water bodies. Regional scale data, available nationwide through the NHD+, and top-down models based on aggregated catchment information provide useful tools for estimating regional patterns of peak flows, volumes and nutrient loads at the catchment level. Management impacts can be estimated with these models, but have limited ability to resolve impacts beyond simple changes to land cover proportions. Alternatively, distributed process-based models provide more flexibility in modeling management impacts by resolving spatial patterns of nutrient source, runoff generation, and uptake. This bottom-up approach can incorporate explicit patterns of land cover, drainage connectivity, and vegetation extent, but are typically applied over smaller areas. Here, we first model peak flood flows and nitrogen loads across North Carolina's 70,000 NHD+ catchments using USGS regional streamflow regression equations and the SPARROW model. We also estimate management impact by altering aggregated sources in each of these models. To address the missing spatial implications of the top-down approach, we further explore the demand for riparian buffers as a management strategy, simulating the accumulation of nutrient sources along flow paths and the potential mitigation of these sources through forested buffers. We use the Regional Hydro-Ecological Simulation System (RHESSys) to model changes across several basins in North Carolina's Piedmont and Blue Ridge regions, ranging in size from 15 - 1,130 km2. The two approaches provide a complementary set of tools for large area screening, followed by smaller, more process based assessment and design tools.