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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Comparison of Tensiometer and Climatological Methods for Estimating Soil Moisture Depletion and Scheduling Irrigation for Potatoes

Wiser, Thayne B. 01 May 1972 (has links)
The purpose of this thesis was to compare the tensiometer and climatic methods of scheduling irrigation of potatoes under field conditions. Tensiometers were placed in a 160 acre field to maintain the crop within the optimum moisture range and schedule irrigations. An automatic solid set system was used to apply water to the potato crop. Instrumentation was used to determine daily input for the climatological method. Daily evapotranspiration (Et) was computed and Et (tensiometer) was comPared with Et (climatic). The results showed total variation of the climatic method from the tensiometer method of .62 inches or less than 5 per cent. The study indicated that the climatological method would have under irrigated the potato crop by . 62 inches during the 48 day study. Variations are also shown for each irrigation interval. Results indicated that a combination of both methods would allow the most feasible approach to scheduling irrigation of potatoes.
2

Characterizing the Spatial Variation of Crop Water Productivity for Variable-Rate Irrigation Management

Svedin, Jeffrey David 01 June 2018 (has links)
Irrigated agriculture is the primary consumer of limited worldwide freshwater resources. Drought, growing world populations, and environmental demands compete with irrigation for freshwater resources"”threatening sustainable global food, fuel, and fiber production. This escalating global crisis demands that agriculture produce more food using less water. Traditional irrigation management has used technology to apply uniform irrigation rates across landscapes"”ignoring natural environmental variation. This provides inherent inefficiencies of over- or under- irrigation within individual fields. Variable-rate irrigation (VRI) is modern technology that employs global positioning systems and geographic information systems to match irrigation to spatially variable crop water demands within a field. Although commercially available, VRI lacks scientifically validated decision support systems to determine spatially and temporally variable crop water demand. The purpose of this research is to explore spatial and temporal variations in crop water demand to inform growers utilizing VRI. This research consists of four seasons of winter wheat (Triticum aestivum L.) production on a commercial farm in Idaho that employs a VRI system. In Chapter 1, the spatial variation of crop water productivity (CWP, the grain produced per unit of water consumed), is characterized for two seasons (2016-2017) and we propose a unique conceptual strategy for VRI management targeted at CWP. Observed CWP ranged from 4.1-21 kg ha-1 mm-1 with distinct spatial variation that, when considered together with grain yield, were shown to be useful for VRI management. During the 2017 growing season, VRI zones conserved 25% of irrigation compared to traditional uniform irrigation management. In the second chapter the spatial variation of soil water holding capacity (SWHC) was measured at 90 sampling points throughout the field. Then, during the 2016-2017 growing seasons, the spatial and temporal variation of soil moisture were modelled to characterize crop stress and its influence on grain yield. Soil within the field showed large spatial variation of SWHC, ranging from 147-369 mm. Under uniform irrigation in 2016, the natural variation of TAW created 21 day variation in the onset of crop stress throughout the field and under VRI in 2017 the onset of crop stress spanned 56 d. Surprisingly the variations in TAW did not statistically influence yield in 2016, and in 2017 the rate of irrigation predicted yield and TAW again did not statistically predict yield. This suggests that other environmental variables should be included when delineating irrigation zones and rates for VRI.

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