Irrigation Management Improvements for San Joaquin Valley Pima Cotton Systems PDF Download

Author: Daniel S. Munk
Publisher:
ISBN:
Category : Irrigation
Languages : en
Pages : 26

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Author: San Joaquin Valley Interagency Drainage Program
Publisher:
ISBN:
Category : Agriculture
Languages : en
Pages : 232

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Author:
Publisher:
ISBN:
Category : Water
Languages : en
Pages : 204

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Author: Anonymous
Publisher: Legare Street Press
ISBN: 9781022218093
Category :
Languages : en
Pages : 0

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This report presents the findings of a study on the adoption of improved irrigation and drainage reduction technologies in the Westside of the San Joaquin Valley. Drawing on extensive data collected from farmers and other stakeholders, the report analyzes the factors that influence the adoption of these technologies and provides recommendations for increasing their uptake. This report is an essential resource for policymakers, researchers, and agricultural professionals. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Author: Ariel Dinar
Publisher:
ISBN:
Category : Drainage
Languages : en
Pages : 252

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Author: Steven Russell Raine
Publisher:
ISBN:
Category : Cotton
Languages : en
Pages :

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Author: Alison Christine McCarthy
Publisher:
ISBN:
Category : Cotton
Languages : en
Pages : 504

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Improving the efficiency of water use in agriculture is increasingly essential to maintain the profitability and sustainability of farms. This involves applying only the minimum necessary irrigation water to maintain or improve the yield of individual plants. Improving cotton yield involves management of flower/fruit production in relation to vegetative growth. The cotton industry represents a signicant proportion of agricultural production and water use in Australia. Irrigation control strategies can be used to improve site-specific irrigation. These control strategies generally require weather, plant and/or soil data to determine irrigation volumes and/or timing that improve crop water use efficiency while maintaining or improving crop yield. In this dissertation the difficulties in applying standard control theory to irrigation control are reviewed, in particular that the system, the growing crop, varies with time and does not have fully-defined dynamics. Hence, as the plant response and environmental conditions fluctuate throughout the season, control strategies which accommodate temporal and spatial variability in the field and which locally modify the control actions (irrigation amounts) need to be `adaptive'. Such irrigation control systems may then be implemented on large mobile irrigation machines, both `lateral move' and `centre pivot' configurations, to provide automatic machine operation. This dissertation presents the specification and creation of a simulation framework `VARIwise' to aid the development, evaluation and management of spatially and temporally varied site-specific irrigation control strategies. The cotton model OZCOT has been integrated into VARIwise to provide feedback data in the control strategy simulations. VARIwise can accommodate sub-field scale variations in all input parameters using a 1 m2 cell size, and permits application of differing control strategies within the field, as well as differing irrigation amounts down to this scale. An automatic model calibration procedure was developed for VARIwise to enable realtime input of field data into the framework. The model calibration procedure was accurately implemented with measured field data and the calibrated model was then used to evaluate the effect of using different types of data in an irrigation control system. With the field data collected, the model was most effectively calibrated using the full set of plant, soil and weather data, while either weather-and-plant or soil-and-plant input provided adequate inputs to the control system if only two inputs were available. A literature review of control systems identified three adaptive control strategies that are applicable to irrigation, namely: (i) Iterative Learning Control (ILC) which involves applying irrigation volumes to cells in the field calculated by comparing the desired and measured value of the input variable for control (e.g. soil moisture deficit); (ii) iterative hill climbing control which involves applying test irrigation volumes to test cells in the field to determine the application that produced the best crop response and applying that volume to the remainder of the field; and (iii) Model Predictive Control (MPC) which involves using a calibrated crop model to evaluate various irrigation applications and timings to determine which irrigation decision to implement. The three control strategies were implemented and simulated in VARIwise to evaluate their respective robustness to limitations in data availability and system constraints. These strategies effectively adapted to temporal changes in weather conditions and spatially variable soil properties. For the set of field conditions simulated in VARIwise, the ILC, iterative hill climbing and MPC controllers produced their highest yield and water use efficiency with soil data, weather-and-plant data, and the full data input, respectively. MPC was most sensitive to spatially sparse input data but performed well with spatially variable rainfall and limited machine capacity. ILC was least sensitive to spatially sparse input data and variable rainfall, whilst iterative hill climbing control was most sensitive to spatially sparse input data and variable rainfall. Hence, in situations of high data input MPC should be implemented, whilst in situations of low data input ILC should be implemented. Iterative hill climbing control was most sensitive to limited irrigation machine capacity. It is further concluded that cotton yield and irrigation water use efficiency may be significantly improved using adaptive control systems; and that adaptive control systems can adjust the irrigation application and improve the irrigation performance despite various data availability limitations and irrigation hardware constraints.

Author: United States. Congress. Senate. Committee on Appropriations. Subcommittee on Agriculture, Rural Development, and Related Agencies
Publisher:
ISBN:
Category : Government publications
Languages : en
Pages : 1452

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Author: Fawzi Karajeh
Publisher:
ISBN:
Category : Agricultural pollution
Languages : en
Pages : 76

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Author: Frank Adams
Publisher:
ISBN:
Category : Cotton growing
Languages : en
Pages : 1008

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