Watershed analysis of urban stormwater contaminant 6PPD-Quinone hotspots and stream concentrations using a process-based ecohydrological model.

Coho salmon () are highly sensitive to 6PPD-Quinone (6PPD-Q). Details of the hydrological and biogeochemical processes controlling spatial and temporal dynamics of 6PPD-Q fate and transport from points of deposition to receiving waters (e.g.

Improved urban runoff prediction using high-resolution land-use, imperviousness, and stormwater infrastructure data applied to a process-based ecohydrological model.

Modeling large-scale hydrological impacts brought about by site-level green and gray stormwater remediation actions is difficult because urbanized areas are extremely complex dynamic landscapes that include engineered features that, by design, expedite urban runoff to streams, creeks, and other water bodies to reduce urban flooding during storm events. Many urban communities use heavily engineered gray infrastructure to achieve that goal, along with more recent additions of green infrastructure such as rain gardens, bioswales, and riparian corridors. Therefore, successfully characterizing those design details and associated management practices, interactions, and impacts requires a detailed understanding of how fine and course-scale hydrologic processes and routing are altered and managed in urban watersheds.

Improved Soil Temperature Modeling Using Spatially Explicit Solar Energy Drivers.

Modeling the spatial and temporal dynamics of soil temperature is deterministically complex due to the wide variability of several influential environmental variables, including soil column composition, soil moisture, air temperature, and solar energy. Landscape incident solar radiation is a significant environmental driver that affects both air temperature and ground-level soil energy loading; therefore, inclusion of solar energy is important for generating accurate representations of soil temperature. We used the U.

Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: successes and challenges.

Decision-support tools (DSTs) are often produced from collaborations between technical experts and stakeholders to address environmental problems and inform decision making. Studies in the past two decades have provided key insights on the use of DSTs and the importance of bidirectional information flows among technical experts and stakeholders - a process that is variously referred to as co-production, participatory modeling, structured decision making, or simply stakeholder participation. Many of these studies have elicited foundational insights for the broad field of water resources management; however, questions remain on approaches for balancing co-production with uncertainty specifically for watershed modeling decision support tools.

Cumulative Effects of Low Impact Development on Watershed Hydrology in a Mixed Land-Cover System.

Low Impact Development (LID) is an alternative to conventional urban stormwater management practices, which aims at mitigating the impacts of urbanization on water quantity and quality. Plot and local scale studies provide evidence of LID effectiveness; however, little is known about the overall watershed scale influence of LID practices. This is particularly true in watersheds with a land cover that is more diverse than that of urban or suburban classifications alone.

MOESHA: A Genetic Algorithm for Automatic Calibration and Estimation of Parameter Uncertainty and Sensitivity of Hydrologic Models.

Characterization of the uncertainty and sensitivity of model parameters is an essential facet of hydrologic modeling. This article introduces the multi-objective evolutionary sensitivity handling algorithm (MOESHA) that combines input parameter uncertainty and sensitivity analyses with a genetic algorithm calibration routine to dynamically sample the parameter space. This novel algorithm serves as an alternative to traditional static space-sampling methods, such as stratified sampling or Latin hypercube sampling.

Cost of areal reduction of gulf hypoxia through agricultural practice.

A major share of the area of hypoxic growth in the Northern Gulf of Mexico has been attributed to nutrient run-off from agricultural fields, but no estimate is available for the cost of reducing Gulf hypoxic area using agricultural conservation practices. We apply the Soil and Water Assessment Tool using observed daily weather to simulate the reduction in nitrogen loading in the Upper Mississippi River Basin (UMRB) that would result from enrolling all row crop acreage in the Conservation Reserve Program (CRP). Nitrogen loadings at the outlet of the UMRB are used to predict Gulf hypoxic area, and net cash farm rent is used as the price for participation in the CRP.