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United States Department of Agriculture

Agricultural Research Service



Project Number: 5402-13660-007-00-D
Project Type: Appropriated

Start Date: Feb 9, 2007
End Date: Feb 8, 2012

Objective 1.Develop, implement, enhance, and maintain an object modeling system (OMS) and a library of modules for building agricultural system models at field to watershed scales for a variety of applications. [Contributes to Problem Area #1, Effectiveness of Conservation Practices, Product #5 of the new National Program (NP) 201 Action Plan (FY 2006 - 2010)] Objective 2.Develop, verify, and evaluate field to watershed modeling tools and techniques that quantify environmental outcomes of conservation practices in major agricultural regions, including modeling and decision aids for drainage water management systems. [Contributes to Problem Area #1, Effectiveness of Conservation Practices, Product #5 and Problem Area #3, Drainage Water Management Systems, Product #4 of the new NP 201 Action Plan (FY 2006 - 2010)] Objective 3.Develop improved space-time scaling and model parameterization approaches for landscape processes in new agricultural system models from field to watershed scales. [Contributes to Problem Area #1, Effectiveness of Conservation Practices, Product #5 of the new NP 201 Action Plan (FY 2006 - 2010), and to Goal 1.7.2 of NP 201 to develop methods to determine input model parameters, values, and state variables for multiple scales to account for the effect of management practices].

Objective 1. Hypothesis: The OMS framework can be used to develop customized, modular field to watershed ag system models with interchangeable components for assessing the effects of conservation practices. Experimental Design: OMS represents an ARS-led effort in partnership with the NRCS, USGS, and university collaborators (e.g. CO State University). Enhancing OMS functionality includes the development of improved capabilities for: 1) model building 2) code testing, data connectivity, and database integration; 3) geospatial output visualization and model parallelization; and 4) uncertainty, sensitivity analysis and parameter estimation. Objective 2 Hypothesis 2-1: A new prototype regionalized model can provide improved estimates of the effects of conservation practices on environmental responses at the field to watershed scales. Experimental Design: The overall goal is to develop an OMS-based modular simulation model with interchangeable components that can address regional soil and water conservation and water quality need from field to watershed scales. Specific task areas for Objective 2 are: 1) Identify regions and define process modules for a selected regional area; 2) Obtain needed scientific model components; 3) Develop a prototype regionalized watershed model and perform a preliminary evaluation; 4) Modify existing modules or identify and develop additional modules; 5) Evaluate the prototype watershed model with various conservation practices; and 6) Transfer the prototype model to NRCS. Hypothesis 2-2: An agricultural systems model, RZWQM2, can simulate and quantify the effects of BMPs under tile drainage for different Midwest climate and soil conditions. Experimental Design: In a collaborative research effort with the National Soil Tilth Laboratory (Ames, IA). Field experiments will be conducted in Iowa. RZWQM2 will be used to quantify controlled drainage and cover crop effects on drainage volumes, nitrate losses in drainage flow, and crop growth. Objective 3 Hypothesis: Soil, water and plant properties can be scaled over space and time to identify scale-appropriate behaviors and model parameters across agricultural landscapes. The resulting perameters can be used to improve the modeling of spatial interactions between land areas containing differential management and conservation practices. Experimental Design: The prototype regionalized watershed model will be used to assess the propogation of uncertainty in model structure, parameter values, and inputs to water quantity and quality effects up to watershed scales. Scale-dependence and uncertainty of model parameters will be evaluated as follows: 1) Characterize the spatial and temporal variability of measured system variables in the prototype watershed model; 2) Relate key model parameters to spatial surrogates; 3) Generate high resolution inputs to detailed process modules and upscale the results; determine effective parameter values over the range of scales of interest; and 4) Quantify parameter uncertainty and its impacts on model output uncertainty using a suite of object-based tools developed for parameter estimation.

Last Modified: 2/23/2016
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