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Computer simulation models are a useful tool in planning, enabling reliable yet affordable what-if scenario analysis. Many simulation models have been proposed and used for urban planning and management. Still, there are a few modeling options available for the purpose of evaluating the effects of various stormwater control measures (SCM), including LID (low-impact development) controls (green roof, rain garden, porous pavement, rainwater harvesting), upland off-line controls (sedimentation, filtration, retention–irrigation) and online controls (detention, wet pond). We explored the utility and potential of the Soil and Water Assessment Tool (SWAT) as a modeling tool for urban stormwater planning and management. This study demonstrates how the hydrologic modeling strategies of SWAT and recent enhancements could help to develop efficient measures for solving urban stormwater issues. The case studies presented in this paper focus on urban watersheds in the City of Austin (COA), TX, where rapid urbanization and population growth have put pressure on the urban stormwater system. Using the enhanced SWAT, COA developed a framework to assess the impacts on erosion, flooding, and aquatic life due to changes in runoff characteristics associated with land use changes. Five catchments in Austin were modeled to test the validity of the SWAT enhancements and the analytical framework. These case studies demonstrate the efficacy of using SWAT and the COA framework to evaluate the impacts of changes in hydrology and the effects of different regulatory schemes. 

Riparian buffer zones (RBZs) provide multiple benefits to watershed ecosystems. We aimed to conduct an extensive sensitivity analysis of the RBZ designs to climate change nutrient and sediment loadings to streams. We designed 135 simulation scenarios starting with the six baselines RBZs (grass, urban, two-zone forest, three-zone forest, wildlife, and naturalized) in three 12-digit Hydrologic Unit Code watersheds within the Albemarle-Pamlico river basin (USA). Using the hydrologic and water quality system (HAWQS), we assessed the sensitivity of the designs to five water quality indicator (WQI) parameters: dissolved oxygen (DO), total phosphorous (TP), total nitrogen (TN), sediment (SD), and biochemical oxygen demand (BD). To understand the climate mitigation potential of RBZs, we identified a subset of future climate change projection models of air temperature and precipitation using EPA’s Locating and Selecting Scenarios Online tool. Analyses revealed optimal RBZ designs for the three watersheds. In terms of watershed ecosystem services sustainability, the optimal Urban RBZ in contemporary climate (1983–2018) reduced SD from 61–96%, TN from 34–55%, TP from 9–48%, and BD from 53–99%, and raised DO from 4–10% with respect to No-RBZ in the three watersheds. The late century’s (2070–2099) extreme mean annual climate changes significantly increased the projected SD and BD; however, the addition of urban RBZs was projected to offset the climate change reducing SD from 28–94% and BD from 69–93% in the watersheds. All other types of RBZs are also projected to fully mitigate the climate change impacts on WQI parameters except three-zone RBZ. 

The quality of input data and the process of watershed delineation can affect the accuracy of runoff predictions in watershed modeling. The Upper Mississippi River Basin was selected to evaluate the effects of subbasin and/or hydrologic response unit (HRU) delineations and the density of climate dataset on the simulated streamflow and water balance components using the Hydrologic and Water Quality System (HAWQS) platform. Five scenarios were examined with the same parameter set, including 8- and 12-digit hydrologic unit codes, two levels of HRU thresholds and two climate data densities. Results showed that statistic evaluations of monthly streamflow from 1983 to 2005 were satisfactory at some gauge sites but were relatively worse at others when shifting from 8-digit to 12-digit subbasins, revealing that the hydrologic response to delineation schemes can vary across a large basin. Average channel slope and drainage density increased significantly from 8-digit to 12-digit subbasins. This resulted in higher lateral flow and groundwater flow estimates, especially for the lateral flow. Moreover, a finer HRU delineation tends to generate more runoff because it captures a refined level of watershed spatial variability. The analysis of climate datasets revealed that denser climate data produced higher predicted runoff, especially for summer months. 

Abstract Climate change and increasing demands are stressing water allocation. In many places, water reallocation and expensive water development actions are being undertaken with more likely to be stimulated by climate change. Here we examine reallocation and development actions between and within municipal, agricultural, and energy industry users in a water‐scarce region and examine how climate change stimulates further actions. We built a regional agricultural, water and electricity two‐stage stochastic model that simulates optimal strategies in South Central Texas. We find that climate change significantly expands water development, causes agricultural water use reduction and reallocation to municipal interests.