Page Banner

United States Department of Agriculture

Agricultural Research Service



2009 Annual Report

1a. Objectives (from AD-416)
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 with respect to biomass production (including selected bio-energy crops), soil water usage, soil carbon and nitrogen status, and yield in crop and rangeland systems. • 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 range-livestock systems from selected locations in the arid western United States for the purpose of evaluating existing and alternative crop and range-livestock management systems. • 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 alternative crop sequences/rotations, improving irrigation scheduling, using reduced tillage practices, crop residue management, and range-livestock drought management tools. Assess the DSS tools under real-world situations by analyzing their economic feasibility and uncertainty/risk under drought and limited-water conditions. Objective 2: Use RZWQM2 and GPFARM-Range models to evaluate the effects of projected climate change on current and alternative production systems. • 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. • 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.

1b. Approach (from AD-416)
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 in the arid western U.S.: 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. The work will be done with cooperating scientists at each location. 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. Calibrated model parameters should be transferable from location to location, except for site-specific inputs (e.g., soil, weather, crop variety). 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. Failure of satisfactory validation will require more accurate measurement of the input data for site-specific parameters or enhancement of a model component’s science code for the 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. Biomass production, soil water usage, soil C/N status, and yield in different crop sequences or rangeland plant species over both the long and short term periods will be analyzed and interpreted. 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. Synthesizing all simulation results across locations will give confidence in applying the model outside the test locations and will result in a comprehensive set of guidelines for management and policy in areas around the locations. 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, carbon and nitrogen allocations in plants. Simulated and experimental results will be used to populate a database with querying ability, which will provide information for crop selection, plant species composition, and management effects on crop production, forage-livestock production, water use efficiency, soil C sequestration, and soil water and N losses in different environments, under current and projected climate conditions. Simple regression-based decision tools will be developed for guiding planning and management.

3. Progress Report
Meeting and training of collaborators occurred in January 2009 for cropping systems and in March 2009 for range systems. Scientists from Sidney, MT, Pullman, WA, Pendleton, OR, Akron, CO, and Bushland, TX were trained for RZWQM2 use. Follow-up contacts have been made to help them organize the experimental data and data for model inputs, including soil, weather and management practices, in preparation for model simulations to begin as soon as the collaborators are ready. Representatives from two of the locations, Cheyenne, WY, and Woodward, OK, received training using versions of GPFARM-Range specifically modified and tested for their locations. Initial soil moisture effects on crop growth were evaluated using RZWQM2 at Akron, CO. See Accomplishments. The GPFARM-Range model was used to evaluate grazing effects at Mile City, MT, Woodward, OK, and Cheyenne, WY. The simulation showed that long term heavy grazing significantly reduced rangeland productivity. At Woodward, the effect of heavy grazing on forage growth was the result of grazing pressure as well as soil compaction effects. The C/N code has been added to the model. Data from the Rangeland Resources Research Unit in Cheyenne, WY, will be used to calibrate and validate the model for C/N cycling in the next FY. The SQL database design with a rudimentary interface is in place. Over 50 years of climate and range research data from Cheyenne, WY have been added to the database. Crop production files from Akron, CO are being added and should be completed this FY. The files include production and management data for winter wheat, corn, triticale, canola, proso millet, and foxtail millet. CO2 effects have been incorporated in RZWQM2. FACE (Free Air CO2 Enrichment) experiments conducted in Maricopa, Arizona, from 1992-1997 were simulated with RZWQM2 for CO2 enrichment effects under two N and two water levels. The model correctly simulated high water and N use efficiency under high CO2 conditions as observed experimentally. Results of this study provide confidence in using simulation models to project climate change effects on wheat growth in the region. The code for simulating CO2 effects on forage has been incorporated in the model. Data from the Rangeland Resources Research Unit in Cheyenne, WY. will be used to calibrate and validate the model for CO2 effects in the next FY. We had a good meeting with NOAA and they promised to provide us the daily climate change data. Until now, we have used the Colorado Climate Change report based on the latest IPCC projections for the State, to develop scenario data for our models. The data include the projected increases in CO2 and temperatures, and seasonal shifts in precipitation, separately for six months during fall and winter months and six months of spring and summer. Instrumentation for measuring energy components, e.g., the net radiation, and latent, sensible and soil heat fluxes from the system, was installed at the Water Management Unit farm at Greely, CO, under two irrigation levels for corn. These results will be incorporated into RZWQM2 to improve plant response to water.

4. Accomplishments
1. RZWQM2 Model Provides Synthesis of Dryland Cropping Systems Data for Central Great Plains: Extending and extrapolating the results of site-specific crop rotation experiments to other locations with differing climate and soils would increase the value and benefit of data collected. System simulation models are potential tools to address this challenge, but these models require calibration and validation if they are to provide useful results. RZWQM2 model was used to simulate long-term (1992 to 2008) dryland crop rotations data at Akron, Colorado, for: conventional tilled winter wheat-fallow, no-till wheat-fallow, no-till wheat-corn-fallow, and no-till wheat-corn-proso millet. Average long-term yields of the three crops in different rotations were simulated well, as were the range of yields and differential yield responses due to rotational sequence. The simulation results confirm the potential for using RZWQM2 to simulate dryland crop rotation yields under varying weather and soil conditions, and to provide results that will aid in the creation of decision support tools for dryland crop rotation selection.

2. Effects of initial soil moisture on plant growth: Dryland farming strategies in the High Plains must make efficient use of limited and variable precipitation and stored water in the soil profile for stable and sustainable farm productivity. Current research efforts focus on replacing summer fallow in the region with more profitable and environmentally sustainable spring and summer crops. In the absence of reliable precipitation forecasts for the crop growing season, farmers rely mainly upon knowledge of plant available water (PAW) in the soil profile at planting for making crop choice decisions. To develop a decision support strategy for crop selection based on initial PAW, The Root Zone Water Quality Model (RZWQM2) was successfully used to simulate the growth of spring triticale, proso millet, and foxtail millet under artificially controlled Low, Medium, and High initial PAW levels during 2004 and 2005 at Akron,Colorado, and Sidney, Nebraska. The validated model consequently can aid in the development of decision support tools for the season-to-season management of these summer fallow replacement crops under dryland conditions in semi-arid environments.

3. GPFARM-Range Model Complements Grazing System Research and Extends Results: A quantitative systems approach provided by the system models is needed to adequately understand the multifactor complexity in the field research data and extend the results beyond the limited weather and soil conditions of the studies. The GPFARM-Range model was parameterized and validated for experimental data from three locations, Woodward, OK, Cheyenne, WY, and Miles City, MT, and then used to extend results for multiple years of weather. These new site-specific versions of the model have been delivered to scientists from these locations, who can now use the models to test their hypotheses on many issues that impact ranchers and range managers including issues of grazing effects, global climate change, and changes in forage composition. This benefits society at large by assisting range scientists to develop grazing schemes that do not cause deterioration of the nation’s rangelands.

Review Publications
Ahuja, L.R., Reddy, V., Saseendran, S.A., Yu, Q. 2009. Responses of Crops to Limited Water: Understanding and Modeling Water Stress Effects on Plant Growth Processes. Complete Book. Madison, Wisconsin. American Society of Agronomy, Inc., Crop Soil Science Society of America, Inc., Soil Science Society of America, Inc. 436 p.

Ahuja, L.R., Reddy, V., Saseendran, S.A., Yu, Q. 2009. Synthesis of Papers and Actions and Further Research to Improve Response of Crop System Models to Water Stress in Ahuja, R., Reddy, V., Saseendran, S.A., Yu, Q, editors. Response of Crops to Limited Water: Understanding and Modeling Water Stress Effects on Plant Growth Processes. Madison, Wisconsin: American Society of Agronomy, Inc, Crop Soil Science Society of America, Inc., Soil Science Society of America, Inc. p 411-421.

Last Modified: 06/23/2017
Footer Content Back to Top of Page