The relationship between water intake rates, paddy ponding depth, and farmers’ water management techniques
The relationship between water intake rates, paddy ponding depth, and farmers’ water management techniques
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取水率、稻田积水深度与农民用水管理技术之间的关系
DOI：
10.1007/s10333-004-0035-6
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发表时间：
2004
影响因子：
2.2
通讯作者：
Tomokazu Haraguchi
中科院分区：
文献类型：
--
作者：
Mitsumasa Anan;K. Yuge;Y. Nakano;T. Funakoshi;Tomokazu Haraguchi
日本农民根据过去的经验和偏好，考虑天气和可用水等因素来管理灌溉用水（以下定义为“经验水管理”）。他们精心控制自己稻田的进水和排水速度，以保持最佳的积水深度。但是，由于农民数量的减少，这些管理良好的系统将发生巨大变化。因此，有必要明确最佳积水深度是否将保持在传统允许的主河流取水量范围内。本研究的第一个目的是量化稻田的实际用水量，这是农民根据他们的经验进行水管理的结果。以一个面积约230公顷的水田为例，研究了经验水管理下当前取水率的意义。通过对17个灌排渠道点的流量测定，研究了整个区域的取水量和需水量。采用自动测量系统，通过对某小区入、出水流量逐时变化的测量，研究了农户经验性水管理的特征，并提出了一种确定稻田水管理模式的推理方法。在坦克模型中引入了新的推理方法，体现了指挥区水资源管理的特点。采用混合复数进化算法（SCE-UA）对模型参数进行优化。结果表明，考虑农户的经验用水管理后，模型的精度有所提高。通过模拟量化了应用于指挥区域的最佳水量。第二个目标是预测农民人数减少对未来用水条件的影响。模拟结果表明，在不保持农户经验用水管理的情况下，整个指挥区维持最优积水深度是困难的。换句话说，结果表明，有效用水需要一个自动水管理系统或一个新的管道系统，以取代农民目前的经验性水管理。
Japanese farmers manage their irrigation water based on their past experiences and preferences, considering such factors as weather and available water (hereafter defined as “empirical water management”). They elaborately control the intake and drainage rates of their own paddy fields to maintain optimal ponding depths. But these well-managed systems will drastically change because of the decreasing number of farmers. Therefore, it is necessary to clarify if the optimal ponding depth will be maintained within the limits of traditionally-allowed water intake rate from the main river. The first objective of this study was the quantification of actual water use in the paddy fields, resulting from the farmers’ water management on the basis of their experience. The significance of the present water intake rate under empirical water management was studied for a paddy field command area of about 230 ha. Water intake rates and the water requirements of the whole area were investigated by measuring the flow rate at 17 points of irrigation and drainage canals. Characteristics of the farmers’ empirical water management were investigated by measuring the hourly changes in inflow and outflow rates for a sub-area using an automatic measurement system, and an inferential method of determining water management patterns for the paddy fields was proposed. The newly-proposed inferential method was introduced in the tank model, which expresses the characteristics of water management in the command area. The Shuffled Complex Evolution Algorithm (SCE-UA) method was used for optimizing the model parameters. It was proven that the model accuracy improved when the farmers’ empirical water management was taken into account. The optimal amount of water to be applied to the command area was quantified by the simulation. The second objective was to predict the effect of the decreasing number of farmers on future water use conditions. The simulated result indicates the difficulty of maintaining optimal ponding depth for the whole command area when the farmers’ empirical water management is not maintained. In other words, results indicated that efficient water use requires an automatic water management system or a new pipeline system to replace the farmers’ present empirical water management.