Search

In urbanized areas, incorporating residents' concerns and priorities into the stormwater management debate has focused on adults rather than youth. This study used Photovoice, a tool that includes photographs taken by youth, to uncover youth concerns and perceptions about their local watersheds. This study consisted of a comparative study of two watersheds. Twenty students produced 468 photographs. Although both groups of students shared common themes regarding stormwater and pollution, these themes differed in level of concerns over local environmental issues, sentiments with particular features in their local watersheds, and concerns about local watersheds. From a methodological perspective, Photovoice provided a way of capturing youth perspectives and to identify important features and issues in their respective local watersheds.

Nonpoint source (NPS) pollution is a severe problem in the U.S. and worldwide. Best management practices (BMPs) have been widely used to control stormwater and reduce NPS pollution. Previous research has shown that socio-economic factors affect households' adoption of BMPs, but few studies have quantitatively analyzed the spatio-temporal dynamics of household BMP adoption under different socio-economic conditions. In this paper, diverse regression approaches (linear, LASSO, support vector, random forest) were used on the ten-year data of household BMP adoption in socio-economically diverse areas of Washington, D.C., to model BMP adoption behaviors. The model with the best performance (random forest regression, R2 = 0.67, PBIAS = 7.2) was used to simulate spatio-temporal patterns of household BMP adoption in two nearby watersheds (Watts Branch watershed between Washington, D.C., and Maryland; Watershed 263 in Baltimore), each of which are characterized by different socio-economic (population density, median household income, renter rate, average area per household, etc.) and physical attributes (total area, percentage of canopy in residential area, average distance to nearest BMPs, etc.). The BMP adoption rate was considerably higher at the Watts Branch watershed (14 BMPs per 1000 housing units) than at Watershed 263 (4 BMPs per 1000 housing units) due to distinct differences in the watershed characteristics (lower renter rate and poverty rate; higher median household income, education level, and canopy rate in residential areas). This research shows that adoption behavior tends to cluster in urban areas across socio-economic boundaries and that targeted, community-specific social interventions are needed to reach the NPS control goal. [ABSTRACT FROM AUTHOR]

Understanding water flow and its relative quantities through different pathways is vital for watershed management. Like many problems in hydrology, numbers of methods have been proposed for streamflow partitioning. Five methods were identified as being the most relevant and least input intensive. This study tested performance of these methods against separately measured surface and subsurface flow data from the coastal plain physiographic region of the southeastern United States. Separately measured surface and subsurface flow were collected for 12 years (1970-1981) in a field scale watershed by the Southeast Watershed Research Laboratory of the USDA-Agricultural Research Service. Results of comparative analysis indicated that Method IV performed the best. Results also indicated that accuracy of this method is highly dependent upon the proper estimation of the 'fraction coefficient' that is based on many physical and hydrologic characteristics of the watershed. This study concluded that deterministic/empirical methods such as Boughton's Method IV, require proper parameter value for increased accuracy. DOI: 10.1061/(ASCE)IR.1943-4774.0000093 CE Database subject headings: Subsurface flow; Overland flow; Base flow; Streamflow; Case studies.

Abstract Background Biological mass transport processes determine the behavior and function of cells, regulate interactions between synthetic agents and recipient targets, and are key elements in the design and use of biosensors. Accurately predicting the outcomes of such processes is crucial to both enhancing our understanding of how these systems function, enabling the design of effective strategies to control their function, and verifying that engineered solutions perform according to plan. Methods A Galerkin-based finite element model was developed and implemented to solve a system of two coupled partial differential equations governing biomolecule transport and reaction in live cells. The simulator was coupled, in the framework of an inverse modeling strategy, with an optimization algorithm and an experimental time series, obtained by the Fluorescence Recovery after Photobleaching (FRAP) technique, to estimate biomolecule mass transport and reaction rate parameters. In the inverse algorithm, an adaptive method was implemented to calculate sensitivity matrix. A multi-criteria termination rule was developed to stop the inverse code at the solution. The applicability of the model was illustrated by simulating the mobility and binding of GFP-tagged glucocorticoid receptor in the nucleoplasm of mouse adenocarcinoma. Results The numerical simulator shows excellent agreement with the analytic solutions and experimental FRAP data. Detailed residual analysis indicates that residuals have zero mean and constant variance and are normally distributed and uncorrelated. Therefore, the necessary and sufficient criteria for least square parameter optimization, which was used in this study, were met. Conclusion The developed strategy is an efficient approach to extract as much physiochemical information from the FRAP protocol as possible. Well-posedness analysis of the inverse problem, however, indicates that the FRAP protocol provides insufficient information for unique simultaneous estimation of diffusion coefficient and binding rate parameters. Care should be exercised in drawing inferences, from FRAP data, regarding concentrations of free and bound proteins, average binding and diffusion times, and protein mobility unless they are confirmed by long-range Markov Chain-Monte Carlo (MCMC) methods and experimental observations.

The soil and water assessment tool (SWAT) was used to investigate the effects of hydrologic response unit (HRU) thresholds (0–20%) on predictions of multiple variables by calibrated and uncalibrated models in a 10.4-km2 urban watershed in the U.S. Mid-Atlantic region. Surface runoff, discharge, sediment yield, and nutrient yield were simulated in stream and on land, and used to spatially identify hotspots for each constituent. SWAT2012 was able to produce accurate discharge and nitrogen estimates that were not sensitive to HRU thresholds. HRU thresholds significantly affected sediment and phosphorus predictions in calibrated and uncalibrated models. Constituent hotspots identified by an uncalibrated model with a 0% HRU threshold were found to be acceptable for the urban watershed under study, except for sediment. Hotspots identified with calibrated models, with HRU thresholds of 5% or less, fit with the identification of on-land sediment and nutrient hotspots. These findings suggest that researchers should carefully consider HRU thresholds when predicting on-land variables of small urban watersheds similar to the watershed in this study when using SWAT. [ABSTRACT FROM AUTHOR]

This study describes application of a catchment scale model, SWAT (Solid Water Assessment Tool), to a small scale agriculture watershed in northern Maryland. It covers the steps involved in model application and associated model uncertainty as affected by variability in input parameters using Latin Hyper Cube Sampling (LHS) with Constrained Monte Carlo Simulation (MCS). SWAT model predictions of the impact of environmentally friendly practices are discussed within the context of input variability. Results indicate that SWAT is a reasonable monthly predictor of hydrology, but does not provide strong association between measured and simulated nitrate loss at that time scale. SWAT was found to perform very well when used for annual nitrate loss predictions. Results also show that using average input parameter values without considering their variability due to media heterogeneity produces simulation outputs that can be misleading and should not be given 100% confidence. It was concluded that in developing TMDL (Total Maximum Daily Load) plans for a given watershed one has to assert associated uncertainty levels in model's inputs and simulation results for proper resource management. [ABSTRACT FROM AUTHOR]