Enhanced System Models and Decision Support Tools to Optimize Water Limited Agriculture
Agricultural Systems Research Unit
Project Number: 3012-61660-007-00
Start Date: Oct 01, 2013
End Date: Dec 06, 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.
• Objective 4: Improve and extend the Wind Erosion Prediction System (WEPS) model.
RZWQM2 will be used in this study. Typical crop management systems will be selected at cooperating ARS locations: Fort Collins, CO, Akron, CO, and Bushland, TX, for cropping systems. Scientists at the selected locations will collect minimum datasets (e.g., weather, soil, and crop information) needed for RZWQM2 model, and then work with ASRU scientists to calibrate and evaluate the models. The model will then be validated by comparing the model predictions (e.g., crop production, evapo-transpiration, N uptake, and soil moisture) 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. 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. These results will be provided to the AgMIP economic modeling group for extrapolating the results to regional scale, and to other AgMIP groups.
WEPS will be: a) extended beyond the current homogenous simulation area approach to improve simulation of field-scale variability by: i) further modularizing the erosion science code, ii) adding sub-field capability,; b) provided improved model inputs and science through: i) updating weather and ii) adding crop competition and improved crop growth; c) extended to additional soil types (i.e., organic dominated soils); and d) modified for application to special problems (i.e., regional air quality modeling, add PM2.5 emission, batch mode for WEPS, develop a single-event model); and e) publish the WEPS technical document.