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Estimating water demand at irrigation scheme scales using various levels of knowledge: applications in Northern Tunisia.

机译:使用各种知识水平来估计灌溉计划规模的需水量:在突尼斯北部的应用。

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The precise estimation of water demand at large-scale irrigation perimeters is a key requirement for water management. Most methods for estimating water demand use biophysical models and cropping patterns but do not account for the wide range of actual farming practices. As a result, these methods only allow estimation of theoretical water demand. The objective of this study was to analyze different methods for evaluating irrigation water demands using several levels of knowledge about irrigation perimeters such as crop water requirements, cropping pattern, irrigation techniques, and water application depths (WAD). Most of this knowledge was related to farming practices, which can vary. Farm typology is an appropriate way to account for the variability in farming practices. These methods were applied in an irrigation scheme in northern Tunisia. The perimeter was subdivided into two sectors: the first sector was designed for surface irrigation and the second for sprinkler irrigation. The first method estimated water demand at the scheme scale based on actual cropping patterns and assuming that farmers used the planned irrigation techniques and satisfied plant water requirements (L1). However, the farmers did not use the planned irrigation techniques. Instead, they combined surface, sprinkler, and drip irrigation techniques depending on the crops they were growing. The second method examined current irrigation techniques using the results of farm typology that provided the areas under each crop irrigation system (L2). The two methods provided a theoretical water demand model at the scheme scale. However, water demand also needed to account for actual WADs (L3). Field surveys were performed to evaluate the WAD of each crop irrigation technique. Methods L1 and L2 showed similar estimations of water demand at the scale of the perimeter, and the savings in water obtained by converting to drip irrigation were balanced by a reduction in sprinkler irrigation due to conversion to surface irrigation. In contrast, the L3 method estimated 50% lower water demand than that provided by L1 or L2, since the supply of water was insufficient. The irrigation network was designed 50 years ago and no longer corresponds to the needs of current farmers. Farm typology was also shown to be a method that accounted for farm diversity; water demand estimated based on typology differed by only 5% from that obtained by summing the needs of individual farms.Digital Object Identifier http://dx.doi.org/10.1002/ird.652
机译:对大规模灌溉区的需水量进行精确估算是水管理的关键要求。大多数估计需水量的方法都使用生物物理模型和耕作模式,但并未考虑到广泛的实际耕作方式。结果,这些方法仅允许估计理论需水量。这项研究的目的是使用有关灌溉周界的若干知识水平(例如作物需水量,种植方式,灌溉技术和施水深度(WAD))来分析评估灌溉需水量的不同方法。这些知识大部分与耕作方式有关,可能会有所不同。农场类型学是解决耕作方式变异性的一种适当方法。这些方法在突尼斯北部的灌溉计划中得到了应用。周边细分为两个部分:第一个部分设计用于地表灌溉,第二个部分用于喷灌。第一种方法是根据实际种植模式并假设农民使用计划的灌溉技术并满足植物需水量(L 1 )来估算计划规模的需水量。但是,农民没有使用计划的灌溉技术。取而代之的是,它们结合了地表,喷头和滴灌技术,具体取决于所种植的农作物。第二种方法使用农场类型学的结果检验了当前的灌溉技术,该方法提供了每种作物灌溉系统下的面积(L 2 )。这两种方法在方案规模上提供了理论上的用水需求模型。但是,水需求还需要考虑实际的WAD(L 3 )。进行了实地调查以评估每种作物灌溉技术的WAD。方法L 1 和L 2 在周长范围内显示出相似的需水量估算,而通过减少滴灌来平衡滴灌获得的节水量得以平衡喷灌由于转换为地面灌溉。相反,L 3 方法估计的需水量比L 1 或L 2 少50%,因为供水量是不足。灌溉网络是50年前设计的,不再符合当前农民的需求。农场类型学也被证明是解决农场多样性的一种方法。根据类型学估算的需水量与各个农场的需求求和相差仅5%。数字对象标识符http://dx.doi.org/10.1002/ird.652

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