Location: Grassland Soil and Water Research Laboratory
Project Number: 3098-13610-009-000-D
Project Type: In-House Appropriated
Start Date: Jan 12, 2022
End Date: Jan 11, 2027
Objective:
Objective 1: In support of LTAR and CEAP, develop management strategies to maintain agronomic resilience through climate extremes that support natural resource conservation and agroecosystem sustainability in the Texas Gulf Coast region.
Sub-objective 1.A: Identify, develop, and evaluate strategies to improve precision agronomic management of croplands to incorporate precision conservation that will optimize agronomic, environmental and economic outcomes.
Sub-objective 1.B: Evaluate the role of landscape scale spatiotemporal soil, water and genetic variability within representative plant species to determine production potential through extreme climatic events in the Texas Gulf Coast region.
Sub-objective 1.C: Catalog, archive and synthesize observational research data across the LTAR network to facilitate collaborate research using advanced database and visualization technologies.
Objective 2. Enhance process-based model algorithms and structure using modern programming paradigms and new research findings from LTAR and CEAP.
Sub-objective 2.A: Improve the SWAT+ model using streamlined code, data structures and upgraded algorithms to better address U.S. and global environmental challenges.
Sub-objective 2.B: Improve ALMANAC predictive capacity using enhanced phenology algorithms and updated plant parameters derived from LTAR-Phenocam observational data on fraction leaf cover.
Objective 3: Develop tools using enhanced models and other new technologies to support improved agroecosystems management and policy formulation from the field to national scales.
Subobjective 3.A: Develop a trans-scale unified national modeling framework to support CEAP and LTAR.
Subobjective 3.B: Develop decision support tools to address unmet agricultural and environmental problems by synthesizing observational data and model predictions using emerging technologies (ML, AI, Drones).
Approach:
The overall goal of this research is to improve agricultural and environmental sustainability by providing producers and policymakers with scientifically credible information to make good decisions. There is a strong need for improved data driven decision support tools which can predict the effects of both human activity and climate variability on agricultural production systems and the environment. These tools are needed and requested by producers, conservation/watershed planners, USDA leadership, State Agencies, Federal Agencies (NRCS, FPAC, EPA, NOAA, USGS), Non-Governmental Organizations (The Nature Conservancy, Environmental Defense Fund, Field to Market), and local stakeholder groups. The Grassland, Soil and Water Research Laboratory (GSWRL) is well positioned to address this need using complementary programs in field/ monitoring and hydrologic/water quality modeling.
There are three interlinked principal components of this project: 1) collection and synthesis of field data to aid in the evaluation of environmental and agro-economic impacts to support the development of more sustainable production strategies; 2) enhancement and testing of the Soil and Water Assessment Tool (SWAT) and Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model algorithms that represent field-, farm-, and watershed-scale processes using up-to-date scientific knowledge from Conservation Effects Assessment Program (CEAP), Long-Term Agro-ecosystem Research (LTAR), and other applied research programs; and 3) development of decision support tools using emerging technologies for conservation management, planning, and policy development at local, regional, and national scales.
Model enhancement is a foundational component of this project, models developed at GSWRL are critical components of local/regional, USDA, and legislative decision-making. These models are being used to assess USDA conservation policy in the second generation of the Office of Management and Budget (OMB) and congressionally mandated CEAP program. These models are widely used in Europe, Asia, Africa, and South America, and their enhancement has significant global impact.
