Recipient Organization
TEXAS A&M UNIVERSITY
750 AGRONOMY RD STE 2701
COLLEGE STATION,TX 77843-0001
Performing Department
Dallas-TAMU Agr Res Cntr
Non Technical Summary
Monitoring Best Management Practices (BMPs) for water quality has lagged due to high costs and better evaluation of BMPs is needed. With new types of urban BMPs being implemented worlswide in Urban areas such a green stormwater infrastructure (GSI), it is imperative to evaluate the short and long term performance of such BMPs. the first objective of this study is to increae the monitoring of existing and new BMPs in urban areas and use the data for increasing the knowledge of water quality professionalss as well as encourage adoption of the BMPs.The Results of the above objective will also be used in modeling BMPs at watershed scale to improve watershed management and protection projects as well as understand the potential benefits of such benefits at larger scale accounting for current conditions as well as the imapact of a changing climate.
Animal Health Component
50%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
(N/A)
Goals / Objectives
Develop tools that utilize both monitoring and modeling to better inform targeted BMP implementation
Advance water quantity and quality models for mixed-use watersheds
Project Methods
Objective 1: Develop tools that utilize both monitoring and modeling to better inform targeted BMP implementation.Water quality improvements at the watershed-scale due to BMP implementations have been slow and often not as extensive as expected The lack of progress in addressing water quantity and water quality issues could be due to the overly high expectation of long-term effectiveness of BMPs, the possible degradation of BMP effectiveness over time, and possibly BMPs themselves becoming sources of pollutants. While the need for assessing effectiveness of past and current BMPs have been widely acknowledged, implementation of novel BMPs that are targeted and precision-based is needed. Insights into the processes that determine pollutant fluxes, their fate and transport and the part that each BMP plays in pollutant reduction are needed. In addition to the process of pollutant transport and removal over time and space, it is essential to more fully understand the role that BMP targeting may have in NPS reduction, and at what scale that targeting may be most effective. In order to make this assessment, detailed information about forcing-functions, BMPs specific data, at various temporal and spatial scales are needed.The major task for Objective 1 is to collect data at the BMP, field- and watershed-scale and various time scales as budget allows. Data will include water quantity, water quality (e.g. sediment, nutrients, and pathogens), pollutant removal kinetics, various climatic variables, etc. The targeted BMPs for this research include urban BMPs such as riparian buffer zones/filter strips, constructed wetlands, stream-side fencing, sediment detention practices, nutrient management, integrated pest management, denitrifying bioreactors, conservation tillage, infiltration practices, porous pavement, green roofs, grass waterways/vegetated swales, rain garden, soil carbon enhancement, etc.Objective 2: Advance water quantity and quality models for mixed-use watersheds.With monitoring data from Objective 1 and previous studies we can use physically and statistically-based predictive modeling to improve the understanding of linkages between driving variables and water-quality outcomes. The driving variables can include land uses, land-use management (e.g., cropping systems, stormwater management systems, waste disposal systems), and climatic factors such as the probability distributions of air temperatures and precipitation amounts. The water quality outcomes can be probability distributions of concentrations or fluxes of water-quality variables in surface water bodies, streams, and reservoirs. The improvement in understanding and planning of watershed management strategies is accomplished through analysis and methods that use the observed weather, hydrology, land use, and water quality data to estimate the parameters of geospatially referenced modelling tools that statistically relate the inputs to relevant water-quality outputs. Novel theoretical approaches to address watershed issues associated with emerging contaminants will need to be better integrated with present models or developed anew. Interdisciplinary cooperation with researchers, watershed specialists, agricultural producers, local stakeholders, agency personnel, etc., will need to be incorporated during the development of novel watershed modeling approaches. The purpose of such models is to better predict water quality responses to the combination of changes in climate, land use, land-use management, and conservation practice implementation that anticipate to occur short or long-term in the future. The models need to be improved to be capable of prioritizing management action plans and investments to help ensure that the highest quality of water is available for use. As the result of achieving this objective, model evaluation, model development, and data collection responsibilities for the participating states/partners will be established. The results will be shared among stakeholders as research progresses. Therefore the major tasks of this objective are to develop, improve and evaluate process-based models and other approaches for planning and management of mixed land use watersheds.