Improving accuracy for sugar beet and developing an iOS app to increase functionality of a Colorado irrigation scheduler - Bartlett, Andrew Charles, author; Andales, Allan A., advisor; Bauder, Troy, committee member; Arabi, Mazdak, committee member (Colorado State University. Libraries, 2014)
Modeling actual crop water usage allows for improved information-based decision making and ultimately more effective use of water allocations within irrigated agriculture. Evapotranspiration (ET), a dynamic process of water loss through the soil surface (evaporation) and plant stomata (transpiration), is the main component of consumptive water use. Scheduling agricultural irrigation events is an effective tactic to minimize crop stress while avoiding unnecessary irrigation. A cloud based irrigation scheduling tool (WISE - Water Irrigation Scheduling for Efficient Application) which applies the soil water balance (SWB) approach, has been developed on the eRAMS (Environmental Risk Assessment Management System) platform. Actual crop water usage (ETc) is the main cause of the depletion of soil moisture, thus ETc is one of the most important variables within the SWB. Multiple ET equations have been developed as a function of a handful of meteorological measurements including the equation used in this thesis, the 2005 American Society of Civil Engineers (ASCE-EWRI) Standardized Reference equation. The alfalfa based reference evapotranspiration (ETr) models the water loss via ET for a 0.5 m tall, well watered alfalfa stand. In order to model sugar beet water use, an empirically derived crop coefficient (Kcr) curve is applied to the alfalfa reference (ETc = ETr x Kcr). Region specific sugar beet crop coefficient values are available; however, these values have not yet been adjusted for the semi-arid climate of Northeastern Colorado. The first objective of this thesis was to modify the sugar beet Kcr curve for the semi-arid climate of Northeastern Colorado to increase the accuracy of sugar beet scheduling within WISE. By using the soil water balance and observing plant growth and water uptake rates, it was discovered that the original coefficient was drastically overestimating ETc. Shortening the full canopy stage by delaying the initial point (cutoff 2) from 33% to 43% maturity and reducing the length until senescence from 83% to 69% maturity reduced predicted water use to an acceptable value. After comparing actual soil water deficits (D) with modeled values for both the original and adjusted Kcr over two growing seasons, it was found that the relative error (RE) of daily D over all fields was decreased from RE values ranging from 11% - 300% down to RE values ranging from 0% - 265%. Large errors were caused by uncertainties in soil properties, effects of hail damage on actual leaf area and ETc, spatial variability in precipitation or irrigation, and differences in field micro-climate and measured weather station data. The second objective of this thesis was to describe the development and purpose of an iPhone and iPad application that was created to add mobile functionality to the WISE tool. This app allows users to view their field's current soil moisture profile, previous day's weather, upload irrigation and precipitation amounts, and calculate gross irrigation amounts as a function of flow rate, length of application, and acreage. The new sugar beet Kcr curve and the iOS app can lead to more effective irrigation scheduling in agriculture within Colorado.
Keywords: sugar beet; crop coefficient; evapotranspiration; iPhone; irrigation; scheduling