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Development of a Simple Irrigation Scheduling Calendar for Mesilla Valley Pecan Growers

2008; American Society for Horticultural Science; Volume: 18; Issue: 4 Linguagem: Inglês

10.21273/horttech.18.4.714

1943-7714

Jeffery C. Kallestad, John G. Mexal, Theodore W. Sammis, Richard J. Heerema,

Archaeology and Natural History

For farmers to accurately schedule future water delivery for irrigations, a prediction method based on time-series measurements of soil moisture depletion and climate-based indicators of evaporative demand is needed. Yet, numerous reports indicate that field instruments requiring high in-season labor input are not likely to be used by farmers. In New Mexico, pecan ( Carya illinoensis ) farmers in the Mesilla Valley have been reluctant to adopt new soil-based or climate-based irrigation scheduling technologies. In response to low adoption rates, we have developed a simple, practical irrigation scheduling tool specifically for flood-irrigated pecan production. The information presented in the tool was derived using 14 years of archived climate data and model-simulated consumptive water use. Using this device, farmers can estimate the time interval between their previous and the next irrigation for any date in the growing season, in a range of representative soil types. An accompanying metric for extending irrigation intervals based on field-scale rainfall accumulation was also developed. In modeled simulations, irrigations scheduled with the tool while using the rainfall rule were within 3 days of the model-predicted irrigation dates in silty clay loam and loam soil, and less than 2 days in sandy loam and sand soil. The simulations also indicated that irrigations scheduled with the tool resulted in less than 1% reduction in maximum annual consumptive water use, and the overall averaged soil moisture depletion was 45.14% with an 18.1% cv , relative to a target management allowable depletion of 45%. Our long-term objective is that farmers using this tool will better understand the relationships between seasonal climate variation and irrigation scheduling, and will seek real-time evapotranspiration information currently available from local internet resources.