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United States Department of Agriculture

Agricultural Research Service

Research Project: Enhanced System Models and Decision Support Tools to Optimize Water Limited Agriculture

Location: Agricultural Systems Research Unit

Project Number: 3012-61660-007-00
Project Type: Appropriated

Start Date: Oct 01, 2013
End Date: Dec 31, 2015

The long-term research objective of this project is to help evaluate current and proposed alternative practices for limited-water and projected global change conditions in the arid western United States. This modeling research will support a broad USDA-ARS effort of integrating and extending temporal and spatial experimental research across environments, and the transfer of recommendation to producers and decision-makers via decision support tools. • Objective 1: Extend RZWQM2 and GPFARM-Range model applications to limited-water agricultural systems in the arid western U.S. by evaluating current experimental results for long-term weather and different soil conditions, and derive alternative optimal management strategies for limited-water agriculture. o Sub-objective 1A. Assess and improve the utility of RZWQM2 and GPFARM-Range applications and their components using existing and new datasets of crop and rangelivestock systems from selected locations. o Sub-objective 1B. Develop relational databases and simple Decision Support System (DSS) tools using the above modeling and experimental results to help agricultural decision makers better cope with drought and water-limited conditions by selecting appropriate management practices. • Objective 2: Use RZWQM2 and GPFARM-Range models to evaluate the effects of projected climate change on current and alternative production systems. o Sub-objective 2A. Evaluate and improve RZWQM2/GPFARM-Range models for response to higher CO2 and temperature and extreme rainfall patterns on crop and range growth, water use, and productivity. o Sub-objective 2B. Under the projected climatic conditions, re-evaluate management systems for crop rotation, plant species, irrigation, tillage, and crop residue management, and propose alternative management practices for typical crop and rangeland systems at the selected locations in the arid western U.S. • Objective 3: Intercompare crop and economic models and foster improvements in these models to increase their capability to utilize data from climate scenarios as part of AgMIP.

RZWQM2 (a RZWQM-DSSAT4.0 hybrid) and GPFARM-Range process-level models will be used in this study. Typical crop and range livestock management systems will be selected at cooperating ARS locations: Fort Collins, CO, Akron, CO, Bushland, TX, Sidney, MT, Pendleton, OR and Pullman, WA for cropping systems, and Cheyenne-WY, Miles City-MT, and Woodward-OK for range-livestock systems. Scientists at the selected locations will collect minimum datasets (e.g., weather, soil, and crop information) needed for RZWQM2 or GPFARM-Range models, and then work with ASRU scientists to calibrate and evaluate the models. The models will then be validated by comparing the model predictions (e.g., crop production, evapo-transpiration, N uptake, soil moisture, and etc.) against measured data not used in the calibration or in another location. Once the model has been satisfactorily validated for available experimental data at a location, it will be used to extend results for a longer duration using historical and projected climate-change weather conditions (down-scaled from climate change model) and for other important soil types in the surrounding area of the location. The model will then be applied to propose alternative crop and grazing management scenarios. Promising alternative management scenarios derived from the models will be the subject of future field testing. The effects of high CO2 and high temperature on plant growth under possible global change conditions will also be examined for interactions and indirect effects on water and nitrogen uptake. We will compare our RZWQM2 model with DSSAT, Hybrid Maize (university of Nebraska), and MAIZESIM (ARS-Beltsville) models for response to water stress levels, using the 6-years’ experimental data for different water levels at Greeley, CO, as well for response to climate change scenarios for two locations in Colorado (Greeley and Akron) provided by the AgMIP climate group and by the NCAR group. Based on the results, we will improve our model for responses to water, temperature, and their interactions. We will make the results of climate scenario simulations for Colorado available to the AgMIP economic modeling group for extrapolating the results to regional scale, and to other AgMIP groups.

Last Modified: 7/31/2015
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