AGRICULTURAL LAND MANAGEMENT TO OPTIMIZE PRODUCTIVITY AND NATURAL RESOURCE CONSERVATION AT FARM AND WATERSHED SCALES
Great Plains Agroclimate and Natural Resources Research Unit
Project Number: 6218-13000-011-00
Start Date: Feb 26, 2012
End Date: Feb 15, 2017
The long-term objective is to bridge the gap between farm management goals and landscape or watershed goals that are shared across farms and communities, using research watersheds as the primary outdoor laboratories to address these issues of global relevance. The project is structured around three inter-related objectives that enhance hydrologic simulation tools, develop new understanding and technologies to characterize climate and landscapes, elucidate landscape and hydrologic function, and build toward an optimization framework for assessment of conservation targeting, land management, and climate scenarios. More specifically, the research objectives are:
Obj 1: Improve watershed management and ecosystem services in mixed use agricultural watersheds by developing remote sensing and modeling tools and techniques for the selection and placement or application of conservation practices on the landscape for maximum effectiveness.
1A: Assess potential impacts of conservation practice targeting strategies to meet desired environmental endpoints.
1B: Develop and evaluate a sequentially linked evapotranspiration, surface, and groundwater hydrology model system to help identify alternative agricultural management practices to mitigate water quality problems and enhance water use efficiency through better surface/groundwater management.
1C: Develop, evaluate, and refine new subsurface tile drainage and water table depth algorithms in SWAT to improve water budget predictions for increasing accuracy of water quality simulations.
1D: Develop remote sensing-based techniques to quantify phytologic, geomorphic, and other landscape variables to inform the selection or application of conservation practices in grazing lands and watersheds.
Obj 2: Quantify impacts of land management, land cover, and climate on the generation, movement, and fate of sediments and nutrients in watersheds.
2A: Quantify interactive effects of land cover, land management, and climate on reservoir sedimentation.
2B: Quantify impacts of changing land use on hydrologic model simulations.
2C: Quantify impacts of juniper removal on surface and groundwater resources in central Oklahoma.
Obj 3: Develop climate-informed decision support tools for crop and forage management, for natural resource conservation, and to support assessments of policy options.
3A: Develop and maintain a fundamental climate database and statistical analyses covering the Fort Cobb Reservoir Experimental Watershed and Little Washita River Experimental Watershed to support CEAP-related analyses and modeling.
3B: Generate daily grids of synthetic weather that are both spatially and temporally coherent and replicate recent climate statistics for use in hydrologic and agronomic models.
3C: Develop decision support tools for cool season forages based on sub-monthly weather statistics that accurately predict the direction of variations in productivity.
3D: Develop multi-scale, multiple-objective optimization framework for agricultural production, conservation, and policy assessment.
The Soil and Water Assessment Tool (SWAT) will be the primary hydrologic model used to address watershed scale studies. SWAT will be linked to the USGS groundwater model, MODFLOW, and will be coupled to an energy balance/evapotranspiration (EB_ET) model to fully address the project’s conservation targeting research objectives. Field studies will be conducted to provide relevant data to SWAT and to verify SWAT performance and accuracy, and to assess the impacts of climate variability and land cover/land use on reservoir sedimentation. New remotely sensed products will be evaluated for their ability to better characterize landscape variables needed for watershed-scale hydrologic simulations. Mathematical and statistical analysis of climate data will be conducted to generate more realistic climatologies (e.g., non-stationary conditions, extreme conditions) and to produce spatiotemporally coherent daily weather grids required by SWAT. Farm to watershed scale process modeling will be conducted in the context of the project’s research watersheds and will focus on identifying practices or policies that optimize economic enterprise and environmental goals across farm to landscape scales.