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A Decision Support System for Matching Irrigation Demand and Supply in the Near Real Time Environment

机译:近实时环境下灌溉供需匹配的决策支持系统

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This study deals with the application of a novel decision support system (DSS)for precise matching of irrigation demand and supply in a the near real time environment for the Coleambally Irrigation area (CIA),located in the southwest of New South Wales(NSW),Australia.Forecasting of irrigation demand in the real time environment entails a complete understanding of the spatio-temporal variability of meteorological parameters and evapotranspiration (ET).For improved irrigation system management and operation,a holistic approach of integrating remote sensing derived ET from the SEBAL method with forecasted meteorological data and water use efficiency was used to forecast net irrigation demand.In order to capture the spatial variability,the CIA has been divided into 22 nodes based on direction of flow and connectivity.All hydrological data of inflow and outflow was estimated at all nodes of the CIA for the estimation of water use efficiencies.10 Landsat 5 TM satellite images were used for mapping irrigated crops and estimation of actual ET for the summer cropping season of 2008 ~2009.This estimated actual ET and forecasted meteorological data was used for demand forecasting for 7 d.The results were compared with the data obtained for irrigation supplies.The methodology is very robust and cost effective for demand driven irrigation systems that have a good database,and daily demand can be forecast and updated by using remote sensing image analysis with minimum time input.The outcome of irrigation demand forecasting on a daily basis for three summer months (December 2009-February 2010) has been applied within the DSS by linking crop water demand with irrigation system management in the near real time environment.The developed model has been coupled with CICL' s water ordering system and has been tested and refined for implementation across all spatial scales ranging from farm to irrigation system in the CIA.The developed DSS,featuring a web-based interface for near real time inquiry into the irrigation status from farm to system level,will enable irrigators to more closely match water application to crop water consumption within daily operational constraints in the CIA.This user friendly decision support model provides water managers with a deeper and more useful understanding about the irrigation demand and supply in the CIA.
机译:这项研究涉及一种新颖的决策支持系统(DSS)的应用,该系统可在新南威尔士州(NSW)西南部的Coleambally灌溉区(CIA)的近实时环境中精确匹配灌溉需求和供给。实时环境中的灌溉需求预测需要完全了解气象参数和蒸散量(ET)的时空变化。为改善灌溉系统的管理和运行,一种综合的方法是将基于遥感的ET集成到系统中使用SEBAL方法结合气象数据和水资源利用效率进行预测,以预测净灌溉需求。为了捕获空间变异性,根据流量和连通性的方向将CIA分为22个节点。在CIA的所有节点上进行估算,以估算用水效率.10 Landsat 5 TM卫星图像用于监测对2008〜2009年夏季作物进行灌溉套种和实际ET的估算。该估算的实际ET和预测的气象数据用于7天的需求预测。对于具有良好数据库的按需灌溉系统而言,该系统非常强大且具有成本效益,并且可以使用最少的时间输入就可以通过使用遥感图像分析来预测和更新每日需求。每天三个夏季的灌溉需求预测结果在2009年12月至2010年2月期间)通过将作物需水量与灌溉系统管理在近乎实时的环境中联系起来而在DSS中得到了应用。中央情报局从农场到灌溉系统的所有空间尺度。发达的DSS,具有基于网络的界面,可用于近乎真实的ti从农场到系统水平的灌溉状态查询,使灌溉人员能够在CIA的日常运行限制范围内使灌溉用水与作物耗水更加紧密地匹配。这种用户友好的决策支持模型为水管理人员提供了更深入,更有用的了解中情局的灌溉需求和供应。

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