1a. Objectives (from AD-416)
1. Develop new tools and a knowledge base that will enable decision makers to more effectively manage and conserve water resources. 1.a Design and test sensors that will quantify the level of plant water stress in growing crops and can be used to make irrigation decisions. 1.b Determine the relationship between crop productivity and applied water as a function of environmental factors so that irrigation can be managed for optimal use of all available water. 2. Develop and evaluate techniques and methodologies that maintain efficient agricultural production under deficit irrigation and dryland production. 2.a Design and evaluate water management strategies that optimize water use and crop production with limited well capacity. 2.b Define and evaluate crop management systems to facilitate the transition from irrigated to dryland cropping, considering crop species and varieties, cultural practices, and that incorporate long range weather prediction. 3. Identify changes in soil microbial, chemical, and physical properties affecting soil water availability and develop management practices that impact soil properties to sustain and improve crop production where water supply is in transition from limited irrigation to rainfed production. 4. Develop Best Management Practices based on a growing region's climate variability. 4.a Develop optimal planting strategies that integrate seasonal climate forecast information into agricultural managment. 4.b Develop software tools that provide detailed knowledge of precipitation, temperature stress, and evapotranspiration and demand to producers and plant breeders.
1b. Approach (from AD-416)
Develop and evaluate techniques and methodologies that utilize limited water resources efficiently to maintain economically viable deficit irrigated and dryland agricultural production systems. Develop new approaches, including acoustic detection of xylem cavitation and portable chamber technologies, to quantify the degree of crop drought stress and evaluate new and existing deficit irrigation strategies. Examine irrigation quantity and application rate effects on water use efficiency using the BIOTIC protocol for irrigation scheduling. Explore the efficiency of subsurface drip irrigation for storing water from low capacity wells in the soil during the fallow season. Determine the feasibility of enhancing water infiltration with adapted grasses and use water stored in playa lakes for forage production. Evaluate new crop species and cultural practices for facilitating the transition from irrigated to dryland cropping systems. Determine the effects of crop rotations and residue management systems on soil microbial, chemical, and physical properties including effects on soil water availability, infiltration, and rainfall capture efficiency. Assess the influence of row spacing and planting patterns on water use efficiency of different cropping systems. Use seasonal climate forecasts to develop optimal planting strategies and software tools to provide detailed predictions of precipitation, temperature stress, and evapotranspiration demand for producers and plant breeders. This multifaceted research program will provide the knowledge base for optimizing the use of scarce water resources especially in arid and semi-arid regions where ground water resources are being depleted.
3. Progress Report
The value of El Nino–Southern Oscillation (ENSO) forecast information to combined winter wheat and cattle grazing production systems over the U.S. Southern High Plains was estimated via computer simulation. These simulations had two goals: 1) estimate the profit and risk effects of a simple forecast method based on equatorial Pacific sea-surface temperatures (SST) in the months before planting, i.e., May-July, and, 2) identify management practices that maximize the value of seasonal forecast information in dual-purpose wheat management. Profit outcomes were derived from the simulations based on four production scenarios that assumed wheat prices varying about either historical ($3.22 bu-1) or elevated ($7.00 bu-1) means, and returns on live weight gain consistent with the grain producer leasing pasturage ($0.75 kg-1) or owning cattle ($2.42 kg-1). Under each production scenario the most profitable management strategy for specified forecast conditions was identified among 125 management practices defined by planting date, nitrogen application, and cattle stocking rate. The simple forecast system's value was compared with that of an ideal forecast method that exactly predicted whether regional November-March precipitation would fall in the driest, middle, or wettest 33rd percentile of historical values. Forecast value was calculated as the difference between profits resulting from the most profitable management practices for specific forecast conditions, and those derived from a most profitable baseline practice that assumed no forecast information. In the $3.22 bu-1 simulations the best practices for specific forecast conditions varied under different cattle ownership conditions. However, the simple forecast system's value distributions were comparable to that of the perfect forecast system, which suggests that more accurate regional precipitation forecasts may not lead to increases in forecast value. In the $7.00 bu-1 simulations, even perfect categorical forecasts produced minor profit effects. The best management practices for most forecast conditions planted on a date best for grain production, applied the maximum nitrogen level, and avoided cattle stocking rates that might decrease grain yields. Because these practices were identical to the baseline practices best when no forecast information is available, forecast value as defined here was $0.0 ha-1 under all but dry forecast conditions. The profit effect of dry forecasts from both the perfect and ENSO methods were negligible. This lack of a profit effect under $7.00 bu-1 wheat price conditions is attributed here to increased profit margins rather than an increased commodity value. When production costs increase and profit margins narrow under $7.00 bu-1 conditions, forecast value effects reappear. However, under both elevated and historical wheat price conditions the best no-forecast baseline practices are also shown to have value relative to a sub-optimal management practice. This suggests that when forecast information is not available; which is the case in most growing regions, producers might profit from following management practices that are best for growing region's climatology.
1. Effects of Dryland Cropping Systems on Soil Microbial Communities and Functionality in a Semiarid Region: This study evaluated the microbial communities and functionality as affected by dryland cropping systems in a representative low organic matter content soil of a semi-arid climate in Lubbock, TX. The cropping systems evaluated range from low to maximum cropping intensity, including: sorghum-cotton (Sr-Ct), cotton-winter rye-sorghum (Ct-Rye-Sr), and haygrazer(another variety of sorghum)-winter rye rotation (Hay-Rye). After 3 yrs, the rotations with a winter cover crop (Ct-Rye-Sr and Hay-Rye) demonstrated enhanced soil microbial biomass, and soil carbon and phosphorus cycling enzyme activities (up to 2 times) compared to Sr-Ct. After 5 yrs, Sr-Ct and Ct-Rye-Sr showed similar levels of microbial biomass carbon and nitrogen, and phosphorus and carbon cycling enzyme activities. Soil total carbon was higher under Hay-Rye compared to Ct-Rye-Sr and Sr-Ct rotations after 5 yrs. Microbial properties were not affected by tillage treatments. Changes in the microbial properties indicated trends in soil organic matter that could lead to other soil changes, such as decreased soil compaction, and higher water, aggregation, and water infiltration. This study demonstrated improvements in soil properties as affected by dryland cropping systems that are of ecological significance as the growing season, and desired crop sequence, were not always possible due to lack of precipitation in certain years.
2. The Value of ENSO Forecasts in ENSO Winter Wheat Management: In semi-arid regions forecasts of growing season precipitation before planting might allow producers to make management decisions that exploit wet growing seasons, or limit the producer's risk during dry conditions. A simulation approach was used here to determine optimal management strategies and estimate the profit effects of El Nino–Southern Oscillation (ENSO) forecast information to combined winter wheat and cattle grazing production systems over the U.S. Southern High Plains. Visual Basic risk management applications might be developed based on this simulation approach that are capable of testing a wider range of production scenarios and cost conditions. Thus for a given set of either climatological or ENSO phase conditions, and current or projected market conditions defined by the user, such applications might propose a best management practice for a particular forecast condition and present distributions of possible profit outcomes.
Baker, J.T., Van Pelt, R.S., Gitz, D.C., Payton, P.R., Lascano, R.J., McMichael, B.L. 2009. Canopy gas exchange measurements of cotton in an open system. Agronomy Journal. 101(1):52-59.