2008 Annual Report
1a.Objectives (from AD-416)
The mission of the Ogallala Aquifer Initiative is to ensure the sustainability of agricultural industries and rural communities, through innovative scientific research focused on irrigation and precipitation management and integrated crop/livestock systems, considering socioeconomic impacts and an assessment of all available water resources, providing scientifically sound information for public policy decisions. .
1) To investigate management of water, both irrigation and precipitation, within existing cropping systems and to conceptualize new cropping systems. A broad examination of the many issues in water management is needed to effectively provide options for producers and water managers..
2)To develop and evaluate integrated crop and livestock systems that reduce dependence on underground water resources while optimizing productivity, product quality, and profitability. A broad ranging, multidisciplinary attack is essential to developing new or improved management systems and must be tested across a range of ecosystems. .
3)To investigate designs, performance, and management of equipment and systems used for irrigation. This is an engineering focus to study the issues associated with irrigation equipment currently used and to reach beyond current concepts and identify future irrigation approaches. .
4)To provide estimates of economic impacts of various water management activities and strategies. This program supports and contributes to all other efforts in the overall program. The scope of economic studies must span the micro- or farm level, to the macro- or regional scale. .
5)To provide a common assessment of the groundwater resources in the Ogallala Aquifer and the interrelationships with climate. This includes understanding the status of the aquifer and potential rates of decline, as well as, investigating climatic variables specifically targeting prediction capacity. .
6) To enhance the knowledge base of producers, water professionals, and policy makers about soil water, crop water use, precipitation management, and irrigation principles; and to develop an information program for youth about the Ogallala Aquifer and its importance and use. .
7)To develop and evaluate water saving technologies for the confined animal feeding operations (CAFO) and industries that process agricultural commodities. This element contains evaluation of environmental and health risks of reusing water from other activities.
1b.Approach (from AD-416)
In partnership with the ARS Laboratories in Bushland and Lubbock, Texas, Kansas State University, Texas A&M University, Texas Tech University, and West Texas A&M University, a strategic plan has been developed to protect the economic integrity of West Texas and Western Kansas through new and enhanced water management strategies; enhanced integrated crop, forage, and livestock production systems; and enterprises for existing natural resources and associated agricultural products, while conserving water and natural resources. This partnership seeks solutions to these complex challenges through multidisciplinary team and partnerships with industry, producers, other institutions, and agencies.
This agreement was established for research conducted in crop years 2004, 2005, and 2006. The complete project accomplishment (by title) can be found in the report for the parent Project 6209-13000-013-00D.
1. Evaluating 'YieldTracker' Yield Forecasts for Dryland Wheat and Irrigated Corn in Western Kansas.
2. Comprehensive Examination of Preseason Irrigation for Corn in the Central Great Plains.
3. Grain and Forage Production with Limited Irrigated Cropping Systems.
4. Developing Spatio-Temporal Water Use Layers for the Ogallala Aquifer: A Modeling Approach.
5. Economic and Policy Implications of Underground Water Use in the Southern Ogallala Region.
6. Evaluating an Inverse Solution for Crop Stress Faxtors in Kansas Water Budget.
7. Comparison of LEPA and SDI for Corn, Sunflower, Soybean, and Grain Sorghum.
8. Relating Corn Genotypes' Ability to Maintain Grain Yield in Water-Stressed Environments & Distinguishable Plant Characteristics.
9. Hydrology/Climatology-Data Integration, Organization, Integrity, and Web Serving GIS Database Standardization and Hydrologic Modeling.
The ADODR and lead investigators are in regular contact via email, teleconferences, face-to-face meetings, and at an annual program progress conference.
COMPREHENSIVE EXAMINATION OF PRESEASON IRRIGATION FOR CORN IN THE CENTRAL GREAT PLAINS:
A field study was conducted to evaluate the impact of preseason irrigation at different well capacities on irrigated corn. With declining well capacities, preseason irrigation may be necessary for optimum corn growth. Irrigated corn was grown with and without preseason irrigation at three different well capacities. Preseason irrigation increased grain yields an average of 0.8 Mg ha**-1; although not significant, the effect was greater at lower well capacities. Preseason irrigation is a viable practice when in-season well capacity cannot fully meet crop needs. Plant populations should be adjusted for well capacity and preseason irrigation. (NP211, Problem Area 2)
GRAIN AND FORAGE PRODUCTION WITH LIMITED IRRIGATED CROPPING SYSTEMS:
When irrigation was reduced in corn and sorghum production, there was less impact on grain and forage yield from the same proportional decrease in irrigation. For example, a 50% reduction in full irrigation caused a 20% reduction in corn grain yields. Sorghum grain yields were reduced by 8% with a 72% reduction in irrigation. However, net economic return from corn production increased at the same rate with additional irrigation. Additional irrigation decreased annual net returns from sorghum production. Irrigators, responding to economic returns form their irrigation practices, would tend to fully irrigate corn and reduce irrigation for sorghum. (NP 211, Problem Area 2)
DEVELOPING SPATIO-TEMPORAL WATER USE LAYERS FOR THE OGALLALA AQUIFER: A MODELING APPROACH:
A vast amount of daily temperature and precipitation data are available from the Ogallala Aquifer region. These data were aggregated to a county level database and are now available for evaluating crop water use and productivity levels. Cotton yield potentials were estimated using heat unit data from this database. Crop water use for the region was also estimated and used to create spatial layers. Historic weather data can be used to predict crop yields and water use for the Ogallala Aquifer region. (NP 211, Problem Area 2)
ECONOMIC AND POLICY IMPLICATIONS OF UNDERGROUND WATER USE IN THE SOUTHERN OGALLALA REGION:
Researchers at Kansas State University projected the economic and hydrological impacts of a Conservation Reserve Enhancement Program (CREP) for select sub-basins in western Kansas. The CREP proved to be a costly method of conserving water. While producers are compensated, based on a fair market value of land rent, this payment may not fully compensate the average producer for current losses in gross profit or the value-added contribution of crop production to the regional economy. The CREP scenario has a large impact to the input supply sectors. The magnitude of these losses is the result of the program's requirement that enrolled irrigated acreage be idled, and also the assumption that additional non-irrigated acreage will be enrolled and idled. The CREP program may be the easiest water conservation policy to implement. The program has wide spread support of environmental groups and will generate additional recreational benefits. Importantly, the majority of monies necessary to fund this program will come from the federal government as opposed to Kansas taxpayers.
Consistent with the ongoing objective of applying the previously developed economic, hydrological, and refining the socio-economic models; an extensive policy analysis was conducted in northwest Kansas. The purpose of this research was to provide input into the water planning process for six relatively small sub-basins. The study considered three water conservation policies aimed at achieving a 30% reduction in current groundwater consumption levels. Stakeholder input suggests that a reduction in water-use is desirable in order to preserve the Ogallala aquifer and extend its economic contribution to both the producer and the regional economy. Results suggest that promoting the adoption of a deficit irrigation strategy may be the least costly method of conserving groundwater. (NP 211, Problem Area 2)
EVALUATING AN INVERSE SOLUTION FOR CROP STRESS FACTORS IN KANSAS WATER BUDGET:
Weighting factors (which quantify yield impacts of water deficits) of the Kansas Water Budget (KWB) were evaluated with respect to wheat and grain sorghum productivity. Simple and accurate models of crop water use and productivity, with sparse input requirements, can support simulation of hydrologic, yield formation, and soil conservation processes at regional scales. An inverse solution for weighting factors minimized predictive error from the KWB for water deficit effects on wheat and grain sorghum yields observed in over 40 site-years at two western Kansas locations. Soil water balance calculations of Kansas Water Budget provided adequate predictions of end-of-season soil water profile for wheat and grain sorghum in the Kansas High Plains when crop coefficient was scaled to leaf area index observed at flowering for sparse canopies. Optimized crop stress factors improved predictive accuracy of wheat yields; default crop stress factors provided acceptable predictive accuracy for grain sorghum yields. (NP 211, Problem Area 2)
COMPARISON OF LEPA AND SDI FOR CORN, SUNFLOWER, SOYBEAN AND GRAIN SORGHUM:
Studies were initiated to compare low energy precision application (LEPA) sprinkler irrigation and subsurface drip irrigation (SDI) for corn, sunflower, soybean, and grain sorghum production. SDI is a water-efficient irrigation technology but is much more expensive than another efficient irrigation technology, LEPA sprinkler irrigation. There were no significant differences in sunflower yield, water use, or water use efficiency as affected by irrigation system type or irrigation level. There was also no significant differences in soybean yields and water use efficiency, but there was a difference in water use between irrigation treatments. As was the case with the sunflower, there was a trend towards higher SDI yield at lower irrigation levels and higher LEPA yields at the higher irrigation level. There were no significant differences in grain sorghum yield, water use, or water use efficiency as affected by irrigation system type or irrigation level. There was a trend towards higher LEPA yields, particularly at lower irrigation levels. This was counter to most results for sunflower, soybean and corn. Water use was significantly higher for LEPA, which may explain the grain trends. (NP 211, Problem Area 2)
RELATING CORN GENOTYPES' ABILITY TO MAINTAIN GRAIN YIELD IN WATER-STRESSED ENVIRONMENTS AND DISTINGUISHABLE PLANT CHARACTERISTICS:
Plant and soil conditions were measured in both dryland and irrigated corn research plots over three years. The data collected were analyzed to examine how corn genotypes produced (responded) with adequate water and how they produced (responded) under water-limited conditions. The number of days to the initiation of silking was the variable most strongly correlated with variation in grain yield in the dryland environment. The number of days to the initiation of silking in the irrigated environment did not have a significant correlation with variation in grain yield. Other measurements, including canopy temperature, PAR (photosynthetically active radiation), color, leaf angle, number of internodes, number of leaves, and leaf nitrogen, had no significant correlation with variation in grain yield for both the dryland and irrigated environments. (NP 211, Problem Area 2)
HYDROLOGY/CLIMATOLOGY-DATA INTEGRATION, ORGANIZATION, INTEGRITY AND WEB SERVING GIS DATABASE STANDARDIZATION AND HYDROLOGIC MODELING:
The enterprise geodatabase storing national and state data resources essential to understanding agricultural systems in the Ogallala Aquifer and Central Plains Regions has been furthered in development to incorporate additional resources required for crop, hydrologic, and economic models. Static data resources are complemented with web service connections to spatial temporal dynamic data resources on climate and stream flow. All data resources are made available to the public via an internet mapping site available at www.gis.ksu.edu/ogallala. To facilitate data discovery, a GIS metadata portal catalogs information about stored and web-service-provided resources (www.gis.ksu.edu/portal). The geodatabase assembled both uses and extends national standard data models to support integration with multiple types of hydrologic models (MODFLOW and AEM), as well as economic and crop models. Together, the geodatabase and web interfaces for data discovery provide critical cyber-infrastructure required for the development of coupled groundwater economic models aimed at evaluating the impact of policy change on the Ogallala Aquifer. Additionally, these resources have been tested for use in a coupled hydrologic-economic modeling framework, and as inputs to the EPIC model running on a HPCC for parameter estimation of variables in both the hydrologic and economic models. Specific accomplishments related to modeling include calibrating hydrologic and crop (EPIC) models to existing data observations. Activities include exercising these models, implementing on a grid computing platform, and implementing an optimization technique to relate irrigation to crop yields. These accomplishments and activities are important for understanding the relationships between groundwater availability and crops, and to plan for the future. (NP 211, Problem Area 2)
EVALUATING 'YIELDTRACKER' YIELD FORECASTS FOR DRYLAND WHEAT AND IRRIGATED CORN IN WESTERN KANSAS:
YieldTracker--a mathematical model that simulates growth and yield of crops using weather and plant canopy observations--was tested for accuracy using corn data from Colby, Kansas. Hyperspectral reflectance data were collected seasonally above corn canopies differing in water status. Three years of yield data for three treatments (rainfed, SDI at 38 mm d**-1, 76 mm d**-1) and four replications (36 model runs) were compared to simulated yields. Results indicated corn yields forecast by YieldTracker were slightly under-predicted for well-watered plants, and significantly over-predicted for plants experiencing water deficits. Hyperspectral reflectance data supported vegetation indices with increased accuracy for dense canopies and water deficit effects. YieldTracker has potential as a decision support tool for irrigated corn, but has insufficient mechanistic complexity to handle water-stressed corn. (NP 211, Problem Area 2)
|Number of Non-Peer Reviewed Presentations and Proceedings||10|
|Number of Newspaper Articles and Other Presentations for Non-Science Audiences||2|