Addressing Data Resolution in Precision Agriculture Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/st74ct270

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  • Irrigated agriculture constitutes the greatest consumptive water use globally, so that irrigation efficiency measures are an important part of global efforts to best utilize this limited resource. However, greater irrigation efficiency must be achieved while simultaneously maintaining or increasing crop yields and farming profitability. Incremental water use decisions are made at the local level by farmers under many real world constraints; consequently they face significant risks in operating large and complex irrigation systems. These decisions should be supported by reliable information upon which to base operational plans and irrigation scheduling. Implementing precision irrigation effectively depends upon highly resolved estimates of crop water demand so that application rates match demand precisely both in location and timing. A fundamental challenge in mapping the irrigation requirement is addressing the heterogeneity of soil, biophysical, and atmospheric processes which mediate water demand. However, existing methods to determine the irrigation requirement assume that field conditions are homogeneous. Precision irrigation systems may enable more specific water distribution than traditional irrigation equipment, but allocating the correct amount of water requires crop water estimates that accurately reflect the variability of the irrigation requirement and consider the scale and timing at which irrigation can be delivered. This dissertation synthesizes the results from field studies which analyzed spatial patterns of irrigation performance and crop water demand under real field conditions. The first experiment quantified the performance of a precision irrigation system and determined the data resolution required for effective utilization of the system’s capability (Chapter 2). Field trials were conducted with a variable rate center pivot sprinkler (VRI) under normal farming conditions to determine this spatial resolution. The result was the definition of a performance coefficient and characteristic length scale associated with the irrigation system. The characteristic length scale describes the highest resolution prescription possible with VRI. Following on these findings, a second study compares an electromagnetic (EM) soil mapping method using extensive laboratory soil characterization as a basis for comparison (Chapter 3). The motivation of the study was to validate the EM method’s capability to detect small scale variations in soil water holding capacity, and to determine under which conditions the EM method can obtain reliable and robust soil maps. The findings reinforce earlier work on the importance of instrument calibration, and also show that specific soil characteristics may preclude using EM methods to map soil in some regions. Following the soil mapping study, further studies investigated methods to measure crop evapotranspiration (ET). A literature review was conducted to establish a catalog of contemporary methods to monitor ET, focusing on those commonly used in agriculture (Chapter 4). From this review, the surface renewal method (SR) emerged as potentially able to map ET feasibly and cost-effectively. Four field experiments were conducted over two years under a range of field conditions to establish a robust protocol for the determination of surface fluxes with SR (Chapter 5). Three of these experiments specifically investigated the potential for SR to be implemented from a moving sensor platform, such as an unmanned aerial vehicle. Experiments showed SR could estimate sensible heat flux as accurately as eddy covariance during moving trials. However, analysis of the minimum flux averaging period demonstrated that SR cannot resolve fluxes at the requisite spatial scales for precision irrigation. Nonetheless, SR remains promising for other practical applications in measuring surface fluxes. Future research questions and potential applications are explored in Chapters 5 and 6. The methods described here are directly relevant to water managers at the levels of farms and irrigation districts. Efficient irrigation planning depends on timely, reliable, and site-specific information in order to anticipate crop water demand, irrigate adequately to prevent drought stress, and maximize yield from the available resource. Growers and irrigation specialists currently have many resources at their disposal, including regional and satellite based ET estimates, state and local soil mapping, and scientific irrigation planning software. However, these methods do not provide site-specific and real time measurements of actual crop water demand, and farmers do not have any reliable means by which to validate the accuracy and precision of these estimates. For this information to be directly useful in irrigation planning, it should be validated by on site measurements. Reliable, local, and real time information is required to realize the full potential of precision agriculture.
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