2011 Annual Report
1a.Objectives (from AD-416)
The objectives are to: (a) evaluate the utility of climate variations and forecasts for agriculture and resources conservation applications; (b) develop risk-based decision tools that take into consideration climate variations and forecasts for practical decision applications in agriculture and natural resource management; and (c) demonstrate climate-related decision and application opportunities for a livestock grazing enterprise and a reservoir water-level managment plan. The guiding principle underlying this project is the bridging of the gap between emerging climate knowledge and application of climate information to problem-solving by developing decision tools for real-life applications that meet the requirements of producers and resource managers.
1b.Approach (from AD-416)
Decadl-scale climate variations are identified by a trend analysis of historical climate data published by NOAA's national Climate Data Center, and the utility of seasonal climate forecasts by NOAA's Climate Prediction Center are evaluated in terms of forecasted and observed departure from average conditions. Statistical characteristics of climate variations and forecasts are quantified in terms of basic districution statistics and probability of exceedance cures (POE). Associated weather outcomes are developed using a weather generator, which will drive selected crop and hydrologic models that simulate climatic impacts on forage production and natural resources. Collaborating producers will capture their decision process using a journaling approach which will identify critical decision variables for which POE curves will be developed. The POE curves will reflect the risk and uncertainty of forecasted impacts and represent the basic decision information for decision makers. Two case studies, the management of a fall forage-grazing system in central Oklahoma and water-level regulation for Lake Texoma reservoir, will be used to demonstrate the management protential offered by climate variations and forecasts.
Mathematical techniques to compare precipitation statistics were explored and applied in a continuation of the previous year's work that compared digital precipitation estimates to actual precipitation measurements taken in Oklahoma. Success or failure in cool-season grass establishment is not readily explained by variations in management or monthly-averaged weather. A multi-day index of weather conditions relevant to cool-season grass establishment and productivity was designed. Data from Italian Rye Grass (IRG) field trials was gathered from across the southern US, and daily weather and soil temperature and moisture were acquired from stations near the field trials in OK. Data quality control was applied, and both 5-day and 7-day running averages of conditions through the IRG growing season were computed. A prototype weather-biomass index was developed. Irrigators in the delta region of Mississippi have been pumping groundwater at a rate sufficient to raise water supply concerns and to prompt regulatory efforts to curb water usage. In collaboration with others, a daily irrigation scheduling tool that would be accessible in-field via smart phones is in development. High-quality, baseline weather station data necessary to support the calculation and prediction of irrigation requirements are in very short supply in Mississippi, forcing consideration of the impacts of poor quality, intermittent data on the accuracy of the calculations. The decision support potential of climate statistics and initial soil moisture at seeding time was explored for a winter wheat-cattle grazing enterprise in OK. Historical weather record was prepared for the Enid, OK, region. A wheat-cattle performance model was applied for combinations of initial soil moisture and potential fall and winter weather realizations. For each weather-soil moisture combination, cattle weight gain and total weight at the end of the grazing season was calculated. An enterprise budget was developed to calculate profit/losses and risk due to inclement weather and/or low initial soil moisture at seeding time. The utility of the NOAAs seasonal climate forecasts for decision making was found to be of limited value for managing wheat-cattle production systems in OK. An alternative forecast method was explored for potential use with a newly developed wheat grazing model. The method is based on the assumption that similarities can be found between the statistics of a forecast year and a year in the historical record. The observed weather of a year with statistics similar to the forecast is taken as the forecast year. An experiment for initial exploration of the forecast potential was designed. Five stations in OK representing a range of precipitation conditions were selected for analysis. Daily and monthly precipitation data of about 90 years were first plotted graphically for visual identification of precipitation patterns. For selected potential patterns (if any), a similarity index was computed to find the best match. Preliminary results showed that there were no recognizable patterns at the window time-scales of 30, 60, 90, and 120 days for both daily and monthly precipitation.
Alternative weather/climate forecasting methodology does not live up to expectations. Agricultural systems models are useful tools for decision making and optimization of management practices. However, their usefulness would be greatly enhanced if future weather/climate with sufficient lead time could be forecasted. Researchers at the Grazinglands Research Laboratory have evaluated the utility of the NOAA's seasonal climate forecasts for decision making. NOAA's forecasts were found to have limited value for managing the wheat-cattle production systems in Oklahoma. An alternative forecast method, based on similarity between forecast and historical precipitation, was tested for potential use with a newly developed wheat grazing model. It was found that the methodology was an unlikely alternative to NOAA's seasonal climate forecast. This research alerts agricultural producers and managers in Oklahoma to use seasonal climate forecasts with great caution because investigations of new forecasts methodologies have reaffirmed the limitations of producing seasonal climate forecasts that contain actionable information for agronomic decision making in Oklahoma.
Garbrecht, J.D., Zhang, X.J., Schneider, J.M., Steiner, J.L. 2010. Utility of seasonal climate forecasts in management of winter-wheat grazing. Applied Engineering in Agriculture. 26(5):855-866.
Schneider, J.M., Ford Jr, D.L. 2011. Evaluating PRISM precipitation grid data as possible surrogates for station data at four sites in Oklahoma. Oklahoma Academy of Science Proceedings. 90:77-88.
Zhang, G., Luo, R., Cao, Y., Shen, R., Zhang, X.J. 2010. Impact of sediment load on manning coefficient in supercritical shallow flow on steep slopes. Hydrological Processes. 24:3909-3914.
Zhang, X.J. 2011. Grazing initiation timing affects net return to dual-purpose wheat systems. Transactions of the ASABE. 27(1):51-62.
Zhang, X.J., Liu, W.Z., Li, Z., Chen, J. 2011. Trend and uncertainty analysis of simulated climate change impacts with multiple GCMs and emission scenarios. Agricultural and Forest Meteorology. 151(10):1297-1304.