No abstract

In 2006, bacterial pathogens were the leading cause of water quality concerns in the U.S. With more than 300 water bodies in the state of Texas failing to meet water quality standards because of bacteria, managing bacteria pollution commanded the attention of regulatory agencies, researchers, and stakeholders across Texas. In order to assess, monitor, and manage water quality, it was necessary to characterize the sources of pathogens within the watershed. The objective of this study was to develop a spatially explicit method to estimate potential E. coli loads in Plum Creek watershed in east central Texas. Locations of contributing non-point and point sources in the watershed were defined using Geographic Information Systems (GIS). By distributing livestock, wildlife, wastewater treatment plants, septic systems, and pet sources, the bacterial load in the watershed was spatially characterized. Contributions from each source were quantified by applying source specific bacterial production rates, and ranking of each contributing source was assessed for the entire watershed. Cluster and discriminant analyses were used to identify similar regions within the watershed for selecting appropriate best management practices. Based on the statistical analysis and the spatially explicit method, four clusters of subwatersheds were found and characterized. The analysis provided a basis for development of spatially explicit identification of best management practices (BMPs) to be applied within the Watershed Protection Plan (WPP).

This paper investigates the development of flood hazard and flood risk delineations that account for uncertainty as improvements to standard floodplain maps for coastal watersheds. Current regulatory floodplain maps for the Gulf Coastal United States present 1% flood hazards as polygon features developed using deterministic, steady‐state models that do not consider data uncertainty or natural variability of input parameters. Using the techniques presented here, a standard binary deterministic floodplain delineation is replaced with a flood inundation map showing the underlying flood hazard structure. Additionally, the hazard uncertainty is further transformed to show flood risk as a spatially distributed probable flood depth using concepts familiar to practicing engineers and software tools accepted and understood by regulators. A case study of the proposed hazard and risk assessment methodology is presented for a Gulf Coast watershed, which suggests that storm duration and stage boundary conditions are important variable parameters, whereas rainfall distribution, storm movement, and roughness coefficients contribute less variability. The floodplain with uncertainty for this coastal watershed showed the highest variability in the tidally influenced reaches and showed little variability in the inland riverine reaches. Additionally, comparison of flood hazard maps to flood risk maps shows that they are not directly correlated, as areas of high hazard do not always represent high risk. Copyright © 2012 John Wiley & Sons, Ltd.

Teague, Aarin, Philip B. Bedient, and Birnur Guven, 2011. Targeted Application of Seasonal Load Duration Curves Using Multivariate Analysis in Two Watersheds Flowing Into Lake Houston. Journal of the American Water Resources Association (JAWRA) 47(3):620‐634. DOI: 10.1111/j.1752‐1688.2011.00529.x Abstract:  Water quality is a problem in Lake Houston, the primary source of drinking water for the City of Houston, Texas, due to pollutant loads coming from the influent watersheds, including Spring Creek and Cypress Creek. Statistical analysis of the historic water quality data was developed to understand the source characterization and seasonality of the watershed. Multivariate analysis including principal component, cluster, and discriminant analysis provided a custom seasonal assessment of the watersheds so that loading curves may be targeted for season specific pollutant source characterization. The load duration curves have been analyzed using data collected by the U.S. Geologic Survey with corresponding City of Houston water quality data at the sites to characterize the behavior of the pollutant sources and watersheds. Custom seasons were determined for Spring Creek and Cypress Creek watersheds and pollutant source characterization compared between the seasons and watersheds.

A multi-level coastal wetland assessment strategy was applied to wetlands in the northern Gulf of Mexico (GOM) to evaluate the feasibility of this approach for a broad national scale wetland condition assessment (US Environmental Protection Agency's National Wetlands Condition Assessment). Landscape-scale assessment indicators (tier 1) were developed and applied at the sub-watershed (12-digit hydrologic unit code (HUC)) level within the GOM coastal wetland sample frame with scores calculated using land-use maps and geographic information system. Rapid assessment protocols (tier 2), using a combination of data analysis and field work, evaluated metrics associated with landscape context, hydrology, physical structure, and biological structure. Intensive site monitoring (tier 3) included measures of soil chemistry and composition, water column and pore-water chemistry, and dominant macrophyte community composition and tissue chemistry. Relationships within and among assessment levels were evaluated using multivariate analyses with few significant correlations found. More detailed measures of hydrology, soils, and macrophyte species composition from sites across a known condition gradient, in conjunction with validation of standardized rapid assessment method, may be necessary to fully characterize coastal wetlands across the region.