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ARS Home » Midwest Area » West Lafayette, Indiana » National Soil Erosion Research Laboratory » Research » Research Project #445338

Research Project: Improving Understanding of Soil Processes for Making More Informed Agricultural Management Decisions that Increase Agricultural Sustainability in the Central U.S.

Location: National Soil Erosion Research Laboratory

Project Number: 5020-21600-001-000-D
Project Type: In-House Appropriated

Start Date: Oct 9, 2023
End Date: Oct 8, 2028

Objective:
Objective 1: Enhance and develop best management practices that optimize crop nutrition and ecosystem services related to soil health, water quality, and crop production efficiency for Central U.S. cropping systems. Subobjective 1.A: Develop relationships that describe how soil properties partly control soil P dynamics and kinetics in the context of crop uptake. Subobjective 1.B: Assess the impact of combined conservation practices on soil health indicators, including soil organic C dynamics (SOC) and physical properties. Subobjective 1.C: Quantify phosphorus uptake efficiency and timing in corn towards formulating more efficient nutrient application strategies. Subobjective 1.D: Evaluate the effect of soil phosphorus drawdown on crop yield and water quality in tile-drained fields among three different regions of Indiana (Northeast, Central, and Eastern). Objective 2: Enhance, develop, integrate, and support soil erosion prediction tools to enable and inform policy-maker decisions on soil conservation practices and improve communication on the impact of erosion on sediment, nutrient, and carbon budgets. Subobjective 2.A: Improve USDA-ARS soil erosion model functionality and performance. Sub-objective 2.B: Enhance prediction of Soil erosion and redistribution in agricultural landscapes under climate and land use change. Objective 3: Improve functionality and resilience of agricultural systems in the Central U.S. to drought and extreme weather through the expansion, development, integration, and deployment of hydrological modeling across coordinated Long-Term Agroecosystem Research (LTAR) network sites. Subobjective 3.A: Evaluate the impact of management on resilience of soil health to extreme weather of depression watersheds. Subobjective 3.B: Assess the propagation of drought through the hydrological system in the Western Lake Erie Basin. Subobjective 3.C: Systems/community resilience and natural resource sustainability at the agriculture-environment-society nexus.

Approach:
Approach Objective 1: Laboratory and field crop growth experiments will be used to study nutrient uptake at several scales for improving fertility recommendations as well as assessing how various management practices impact soil organic matter stability and water quality. Approach Objective 2: This research will expand and improve sediment transport knowledge, equations, and logic used within process-based soil erosion prediction technologies. Paired no-till vs. tilled soils will be subjected to simulated rainfall in the laboratory, as well as inflow water to measure interrill and rill detachment rates and determine baseline erodibility parameters. Existing public web services from NRCS (https://data.nal.usda.gov/dataset/soil-data-access-web-service), U.S. Geological Service (USGS) (https://www.mrlc.gov/data-services-page), National Oceanic and Atmospheric Administration (NOAA) and NASA (https://daymet.ornl.gov/) and National Agricultural Statistical Service (NASS) (https://www.nass.usda.gov/Research_and_Science/Cropland/sarsfaqs2.php) will be used with data transformation algorithms developed to integrate these datasets of different scales in dynamic mapping applications related to soil erosion at a specific scale (e.g. pixel size, field size and shapes). Approach Objective 3: Historic and additional soil samples within depression watersheds will be analyzed to better understand long- and short-term soil redistribution dynamics of spatial and temporal pattern within depression watersheds. Long-term datasets of precipitation, soil moisture, and discharge across spatial scales ranging from individual fields to large watersheds will be leveraged to quantify how anomalous meteorological conditions transition into hydrological drought.