Managing Uncertainty in Runoff Estimation with the U.S. Environmental Protection Agency National Stormwater Calculator.

The U.S. Environmental Protection Agency National Stormwater Calculator (NSWC) simplifies the task of estimating runoff through a straightforward simulation process based on the EPA Stormwater Management Model. The NSWC accesses localized climate and soil hydrology data, and options to experiment with low-impact development (LID) features for parcels up to 5 ha in size. We discuss how the NSWC treats the urban hydrologic cycle and focus on the estimation uncertainty in soil hydrology and its impact on runoff simulation by comparing field-measured soil hydrologic data from 12 cities to corresponding NSWC estimates in three case studies. The default NSWC hydraulic conductivity is 10.1 mm/h, which underestimates conductivity measurements for New Orleans, Louisiana (95 ± 27 mm/h) and overestimates that for Omaha, Nebraska (3.0 ± 1.0 mm/h). Across all cities, the NSWC prediction, on average, underestimated hydraulic conductivity by 10.5 mm/h compared to corresponding measured values. In evaluating how LID interact with soil hydrology and runoff response, we found direct hydrologic interaction with pre-existing soil shows high sensitivity in runoff prediction, whereas LID isolated from soils show less impact. Simulations with LID on higher permeability soils indicate that nearly all of pre-LID runoff is treated; while features interacting with less-permeable soils treat only 50%. We highlight the NSWC as a screening-level tool for site runoff dynamics and its suitability in stormwater management.

Comparison of Measured and Simulated Urban Soil Hydrologic Properties.

Urban communities use hydrologic models to plan for and assess the effectiveness of stormwater control measures. Although emphasis is placed on soils as permeable surfaces that regulate the rainfall-runoff process, representative soil hydrologic parameters for urban areas are rare. The extent to which measured and commonly simulated hydrologic data may differ is also largely uncharacterized. As part of the US EPA urban soil assessment, infiltration and drainage rates were measured in 12 cities, and the authors compared these measured data to estimates generated from the EPA National Stormwater Calculator (NSWC), United States Department of Agriculture (USDA) Soil Survey Geographic Database (SSURGO), and USDA Rosetta. The analysis highlights the overall lack of soil hydrologic data for many cities in the NSWC and SSURGO and show that common prediction algorithms for infiltration and drainage poorly represent urban soil hydraulics. Paired comparison of field-measured values and model-estimated values resulted in root-mean-square errors ranging from 23 to 173 mm=h. These findings are presented in the context of planning for effective stormwater and wastewater management practices, and the need for confirming simulation results with site-specific field data.

Realizing the opportunities of black carbon in urban soils: Implications for water quality management with green infrastructure.

Soils and associated microbial processes regulate the carbon cycle and provide a sink for atmospheric black carbon (BC). Particularly in urban areas, present and accumulated soil BC may act as an effective sorbent of anthropogenic contaminants in green spaces. We characterized carbon concentrations that have accumulated in urban soils (organic carbon, BC, and inorganic C) and determined soil physical attributes (soil texture, hydraulic conductivity) from urban soil assessments (surface and sub-surface horizons) carried out in eleven cities in the United States. We used both ordinary least squares and non-parametric classification and regression tree (CART) methods to discern trends in soil BC concentrations with regard to soil, landscape, and emission characteristics. We found that for all cities, regional traffic density and vegetation were good predictors of soil BC concentration. Additionally, the thickness of the top soil horizon explained additional variation in sub-surface BC concentrations. Sites with coincident BC stocks and favorable infiltration rate were discussed as per their potential for improving water quality in multifunctional green infrastructure installations. In the broader sense, the high sorption capacity of existing, accumulated soil BC can contribute to regulation of contaminant cycling in urban areas and may enhance the overall value of urban soils in terms of ecosystem services.

Situating Green Infrastructure in Context: A Framework for Adaptive Socio-Hydrology in Cities.

Management of urban hydrologic processes using green infrastructure (GI) has largely focused on stormwater management. Thus, design and implementation of GI usually rely on physical site characteristics and local rainfall patterns, and do not typically account for human or social dimensions. This traditional approach leads to highly centralized stormwater management in a disconnected urban landscape, and can deemphasize additional benefits that GI offers, such as increased property value, greenspace aesthetics, heat island amelioration, carbon sequestration, and habitat for biodiversity. We propose a Framework for Adaptive Socio-Hydrology (FrASH) in which GI planning and implementation moves from a purely hydrology-driven perspective to an integrated socio-hydrological approach. This allows for an iterative, multifaceted decision-making process that would enable a network of stakeholders to collaboratively set a dynamic, context-guided project plan for the installation of GI, rather than a 'one-size-fits-all' installation. We explain how different sectors (e.g., governance, non-governmental organizations, academia, and industry) can create a connected network of organizations that work towards a common goal. Through a graphical Chambered Nautilus model, FrASH is experimentally applied to contrasting GI case studies and shows that this multi-stakeholder, connected, de-centralized network with a co-evolving decision-making project plan results in enhanced multi-functionality, potentially allowing for the management of resilience in urban systems at multiple scales.