Location: Water Management Research
2023 Annual Report
Objectives
U.S. dairy industry’s economic value is estimated at $51.4 billion. About 30% of the total U.S. milk production comes from the Western states with 20% of it from California. Alfalfa production in California is heavily dependent on irrigation. Competition for declining water resources for domestic, industrial, and agricultural uses, combined with frequent droughts, have resulted in reduced alfalfa acreage. With high milk producing dairy cows requiring high-quality forage, sustainable management strategies are needed for alfalfa production in the West with maximized water productivity and forage quality. The overall goal of this multidisciplinary project is to develop new tools and strategies for alfalfa production in the Western U.S. that conserve scarce water resources and lead to high yield and quality dairy forage.
Objective 1: Develop new tools and strategies for management of alfalfa production in the Western U.S. that conserves scarce water resources, maintains water quality, and leads to high-quality dairy forage and the delivery of environmental services.
Sub-objective 1A: Determine the effects of irrigation and cutting schedules management on forage yield, quality, water use efficiency and water extraction patterns of non-dormant reduced-lignin and conventional alfalfa varieties under semi-arid growing conditions.
Sub-objective 1B: Utilize remotely sensed data products to quantify differences in consumptive water use and water productivity for commercial alfalfa produced with different irrigation techniques, on different soil types, and considering inter-annual variability of growing conditions.
Objective 2: Develop agronomic management strategies for production of alfalfa forage with improved yield, quality, nutritional and economic value.
Sub-objective 2A: Optimize yield and quality of reduced-lignin alfalfa varieties by altering cutting schedules.
Sub-objective 2B: Determine effects of specific traits on growth, yield, quality and plant stand persistence of new and conventional varieties.
Approach
Objective 1, Sub-objective 1A: The research goal for this study is to develop a sustainable irrigation strategy for alfalfa that can ensure optimum forage yield, stand persistence, and nutritional and economic values. Field experiments with frequent and infrequent irrigation are planned for alfalfa varieties with reduced- and non-reduced lignin traits. Yield, quality, and plant biophysical parameters of alfalfa will be determined and analyzed to evaluate the interactive effect of irrigation frequency and varietal traits. If the pre-selected irrigation level is too low in the first year, adjustments will be made to avoid the loss of alfalfa stands and the experimental treatments.
Sub-objective 1B: The research goal for this study is to utilize remote sensing data to evaluate sub-surface drip irrigation for increasing alfalfa water use efficiency and water productivity compared to flood irrigation on dairy farms in the San Joaquin Valley of California. We will assess methodological accuracy and uncertainty of model estimation of crop evapotranspiration using satellite imagery and evaluate the hypothesis that sub-surface drip irrigation increases water use efficiency in actual production settings. Remote-sensing data products will be combined with USDA crop statistics to evaluate soil type, irrigation water source, and irrigation technology associated with optimal water use for alfalfa production. If the daily evapotranspiration estimates provided by commercial systems are not adequate for evaluating time-dependent variability, short-term targeted field experiments will be conducted using eddy-covariance and supporting sensor systems.
Objective 2, Sub-objective 2A: The research goal of this study is to develop a sustainable cutting schedule management strategy for reduced-lignin alfalfa varieties that can ensure optimum yield, dairy quality forage, stand persistence, and nutritional and economic values. The field experiment treatments include 3 cutting schedules (28-day, 35-day, and staggered/alternating between 21- and 35-day) and 8 varieties. Treatment effects on alfalfa yield, quality, stand persistence, and nutritional and economic values will be determined annually. This study will be located at a University of California field facility, and we rely on farm labor support from the university. If the farm support becomes unavailable, we will provide labor support from ARS project employees and work with the university collaborator to continue the project as planned.
Sub-objective 2B: The research goal of this study is to evaluate 20 diverse alfalfa varieties for growth, biomass, and quality dynamics, yield forming traits, and plant biophysical characteristics to improve variety development and to develop a growth model using a regression analysis approach for predicting growth dynamics, forage yield and quality. Plant samples will be collected at each harvest for forage quality analysis. For model development, plant height, biomass, leaf area index, photosynthetic rate, and stomatal conductance will be measured. Planting is in the spring and if some varieties do not establish well, they will be classified as poor performers.
Progress Report
In support of Sub-objective 1A, data collection was continued to assess interactions between alfalfa variety, irrigation frequency, and cutting schedule. Ten alfalfa varieties were irrigated under two scenarios: one irrigation between each harvest after 28-day growth, and weekly irrigation harvested at 28- or 35-day intervals. First year plant samples were processed, and forage quality analyses were completed. One day before each harvest, drone images were collected to estimate differences in plant biomass between varieties and irrigation treatments. Preliminary research findings were presented at the 2022 World Alfalfa Congress.
Under Sub-objective 1B, models in the OpenET ensemble were compared for accuracy in estimating evapotranspiration (ET) in alfalfa. The cropland data layer from National Agricultural Statistical Service or NASS was imported into OpenET to obtain spatial data for alfalfa within the study region. For alfalfa, temporal data showed decreases in ET after each harvest. Average alfalfa ET was the lowest from November to February with a mean value of about 25 mm per month, and highest in July ranging from 25 mm per month after each harvest to 200 mm per month before each harvest. Predicted ET from the five models in OpenET were also comparable.
Under Sub-objective 2A, research continued to evaluate the effect of three cutting schedule strategies on alfalfa yield, quality, stand persistence, and nutritional values. Eight alfalfa varieties, including reduced-lignin and conventional types, were used in the field study. Following alfalfa’s termination, a winter wheat and a summer corn crop were planted to access the nitrogen carryover benefits after the alfalfa crop. Yield and forage quality for the winter wheat and summer corn crop were measured. Data analysis for publication is underway.
Under Sub-objective 2B, research continued to determine yield and forage quality of 20 alfalfa varieties harvested at 35-day intervals. Hand samplings of alfalfa leaves and stems from four varieties were conducted during early-, mid- and late-cropping season. Leaf area index and stomatal conductance values were measured three times during the early-, mid- and late-cropping season. Forage quality analysis is ongoing. The first two years of yield data were published in the December 2022 Issue of the University of California Agronomy Progress Report Extension Publication. Data will be used for plant growth dynamics modeling.
Accomplishments
1. Model simulation of agricultural managed aquifer recharge in alfalfa. Agricultural managed aquifer recharge is a potential practice for recharging depleted groundwater aquifers. However, there is little information on the amount of water that can actually move below the rootzone, especially for deep-rooted crops such as alfalfa. ARS researchers at Parlier, California, in collaboration with University of California researchers, determined that from 76 to 89 percent of the applied water was available for groundwater recharge during the winter alfalfa dormancy. This finding is valuable to alfalfa growers, water managers, and policymakers for making informed decisions regarding groundwater recharge using alfalfa.
