Recipient Organization
TEXAS A&M UNIVERSITY
750 AGRONOMY RD STE 2701
COLLEGE STATION,TX 77843-0001
Performing Department
Agri Economics
Non Technical Summary
In arid regions such as southwest United States, the rveer systems had faced low flows and poor water qualitty, such as high salinity, which had reulted in reduciton of agriucltural prodcution and deterioation of ecosystem health. Therefore BMP and tools for evaluaitng BMP are needed to achive maximum production and minimize risk. The goal of this proejc is to develop new tools and BMPs for regioal stakehodlers to make timely decisions in managing natural resources and proctecting environemnt. TAMU proejct team will work on following topics to addree issues: 1. Develop an Early Warning System / Decision Making (EWS/DM) tool based on science-based, field derived threshold values of drought indicators for specific crops. The EWS/DM tool will have three integrated components; 1) a drought forecast program, 2) a hydrologic forecast model, and 3) in-field crop stress monitoring program. The EWS/DM tool will give agricultural producers hydrologic forecasts for impending droughts and allow them to make appropriate responses to maximize production and minimize risk. 2. Develop tools and new modules needed for BMP evaluation. Wih new modeuldes impacts of BMP can be better evaluated. A better guidelines can be developed for stakeholders to folow through during implementaiton. 3. Develop methodology to asess salinity by integrating hydrological aseesment and geophysical survey. With assessment resutls, stakeholders can identify sources of salinity and develop BMPs and strategies for salinity control and management. 4. Develop a general frame work for decision making including the selection, placement and cost of BMPs, whcih provides guidance on the integration of LID for various development types (e.g. high density, low density or village designs), and develop tools for evaluating the effect of the use of LID practices on stream health, stream erosion and flooding. Results from the project will be shared with city officials to get feedback and to encourage implementation as the final product is developed. Overall goal of this proejc is to help stakeholders better understand natural resources, streses that natural system such as land, water and ecosytem are facing and develop BMPs to sustain water development, agriculrual production and ecosytem health through implementation of BMPs and reudction of risks of drought, floods, salinity and other adverse factors.
Animal Health Component
50%
Research Effort Categories
Basic
25%
Applied
50%
Developmental
25%
Goals / Objectives
Engage collaborators from the needed broad range of disciplines, institutions, and stakeholder groups to catalyze conceptual and quantitative synthesis, collaboration, and data sharing
Facilitate organization, synthesis, and integration of component-based research findings and supporting data and
Discover (or reveal), substantiate, and interpret the broader impacts of component-level modifications to animal-production systems.
Project Methods
Meteorological Forecasts An important step in the forecasting process is to convert forecasts into the detailed information needed by the hydrologic model. Many meteorological forecasts generated by computers only simulate the large-scale aspects of the weather. Seasonal outlooks produced by the Climate Prediction Center only include broad predictions of average values of temperature and rainfall. To solve this problem, a technique called the "analog method" will be used. Time periods in the past whose weather closely matches the predicted weather will be identified. Then, the highly detailed analyses of past weather will be fed into the hydrologic model. Improvements will be made on this basic method during the first two weeks of the forecast by finding time periods whose model forecast closely matches the current model forecast. This eliminates forecast model biases. The longer, seasonal forecasts are in the form of probabilities based on what actually happened during the period 1981-2010. This allows the direct use the 1981-2010 weather as a source of analogs. By providing the hydrologic model with analyses from that time period, it is possible to actually compute the future probability of streamflow rates, reservoir/lake levels and soil moisture values. Hydrologic Forecasts The goal of the hydrologic forecast model is to provide agricultural producers with two weeks' notice about water availability during drought conditions. Soil moisture, stream flows, reservoir/lake levels, and biomass production will be forecast based on meteorological forecasts coupled with a hydrologic model named the Soil and Water Assessment Tool (SWAT). The first watershed to be simulated is the Upper The model is now being calibrated to accurately simulate historic streamflows and cotton yields. After the model has been successfully calibrated, forecasted weather data for the extreme drought of 2011 will be used. The accuracy of the combined weather forecasting-hydrology model to predict streamflows and cotton yields will be assessed. After all adjustments to the combined model have been made, it will be used to predict hydrologic conditions in 2012 and 2013 as drought conditions continue in the Upper desktop" hydrogeological assessment of subsurface flow conditions utilizing only existing data and assessment of collected geophysical data. Salinity Assessment This project combines ground-based hydrogeological data assessment and geophysical survey. Electrical resistivity of the subsurface soil layers and water they contain, along the selected reaches of the Pecos River will be collected and interpreted to highlight saline intrusion areas. These data will be collected providing a detailed assessment of electrical resistivity, which can be translated into salinity. This will aid in identifying salt sources influencing salt loads and salinity levels in the Pecos River. This approach will provide high-resolution, 3-D visualization of salinity levels in the soil and water profile from the surface to depths thus providing exceptional detail of the area's hydrogeology. Combining this rapid assessment method with ground based hydrogeological assessments will verify the results and provide a timely and cost effective hydrogeological assessment of the evaluated river reaches. This project will focus on conducting a "desktop" hydrogeological assessment of subsurface flow conditions utilizing only existing data and assessment of collected geopysical data. Low Impact Development Water quality management in urbanizing watersheds presents new challenges rarely encountered in agricultural regions. These relate mainly to the increased runoff due to imperviousness and the introduction of new pollutants. Low impact development (LID) is one approach that is becoming increasingly common to address these challenges. Modeling LID at watershed scale presents its own challenges. Namely, there is a lack of performance data for the various BMPs, especially at local scale. In order to provide decision makers with information that will help in implementing LID at regional scale, filed studies have been constructed to provide data on BMP performance. Models are being developed and evaluated to integrate this data and provide answers to decision makers.