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Optimum Abstraction of Groundwater for Sustaining Groundwater Level and Reducing Irrigation Cost

机译:优化地下水开采量以维持地下水位并降低灌溉成本

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Adaptation to increasing irrigation cost due to declination of groundwater level is a major challenge in groundwater dependent irrigated region. The objective of this study is to estimate the optimum abstraction of groundwater for irrigation for sustainable management of groundwater resources in Northwest Bangladesh. A data-driven model using a support vector machine (SVM) has been developed to estimate the optimum abstraction of groundwater for irrigation and a multiple-linear regression(MLR)-based model has been developed to estimate the reduction of the irrigation cost due to the elevation of the groundwater level. The application of the SVM model revealed that the groundwater level in the area can be kept within the suction lift of a shallow tube-well by reducing pre-monsoon groundwater-dependent irrigated agriculture by 40%. Adaptive measures, such as reducing the overuse of water for irrigation and rescheduling harvesting, can keep the minimum level of groundwater within the reach of shallow tube-wells by reducing only 10% of groundwater-based irrigated agriculture. The elevation of the groundwater level through those adaptive measures can reduce the irrigation cost by 2.07 x 103 Bangladesh Taka (BDT) per hectare in Northwest Bangladesh, where the crop production cost is increasing due to the decline of the groundwater level. It is expected that the study would help in policy planning for the sustainable management of groundwater resources in the region.
机译:在地下水依赖的灌溉地区,由于地下水位下降而适应增加的灌溉成本是一项重大挑战。这项研究的目的是估算孟加拉国西北部用于地下水可持续管理的灌溉用水的最佳提取量。已经开发了使用支持向量机(SVM)的数据驱动模型来估计灌溉用水的最佳提取量,并且已经开发了基于多线性回归(MLR)的模型来估计灌溉成本的降低。地下水位的高程。 SVM模型的应用表明,通过将季风前依赖地下水的灌溉农业减少40%,可以将该地区的地下水位保持在浅管井的吸力提升范围内。诸如减少灌溉用水过多和重新安排收割时间之类的适应性措施,仅减少了10%的以地下水为基础的灌溉农业,就可以将最低水平的地下水保持在浅管井的范围内。通过这些适应性措施提高地下水位可以使孟加拉西北部每公顷的灌溉成本降低2.07 x 103孟加拉国塔卡(BDT),该国的农业生产成本由于地下水位的下降而增加。预期该研究将有助于该区域地下水资源可持续管理的政策规划。

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