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High resolution water scarcity analysis for cotton cultivation areas in Punjab, Pakistan

机译:巴基斯坦旁遮普邦棉花种植区的高分辨率缺水分析

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摘要

The Water Scarcity Footprint (WSF) serves as a method to estimate the local impacts associated with water consumption in a certain region by considering the volume of water consumed and local water scarcity. Despite the broad application of the WSF on a country and river basin level, the need for further regionalization was recently emphasized by several authors.In this study, water scarcity factors are calculated on high spatio-temporal resolution for 17 irrigation subdivisions located in Punjab, Pakistan on a monthly level based on the WAVE + method using data provided by the hydrological model SWAT and hydraulic model Feflow. The calculated "water deprivation indices" (WDIs) are applied to quantify the WSF of cotton and wheat produced in the study area and compared to the WSFs obtained by using existing WDIs with lower spatial and temporal resolution.The calculated WDIs show a high variability in water scarcity throughout the year from 0.1 to 1.0 m(deprived)(3)/m(consumed)(3). The production weighted average WSF of cotton calculated with the regionalized WDIs amounts to 2333 m(deprived)(3) per ton, whilst the cotton produced in the south of the study area has a twice as high WSF as the cotton from the northern irrigation subdivisions. The result calculated based on the high resolution WDIs is more than 60% higher than the WSF calculated with the WDIs on the basin level. The regionalized WSF of wheat amounts to 1821 m(deprived)(3) per ton, which aligns with the WSF calculated with the basin specific WDIs.The study underlines the need for water scarcity factors on high spatial (e.g. irrigation subdivision) and temporal (monthly) resolution to provide robust WSF results.
机译:水资源短缺足迹(WSF)可作为一种方法,通过考虑用水量和当地水资源短缺来估计与某个地区的用水有关的当地影响。尽管WSF在国家和流域层面上得到了广泛的应用,但几位作者最近仍强调了进一步分区的必要性。在这项研究中,根据高时空分辨率计算了旁遮普邦17个灌溉分区的缺水因子,根据WAVE +方法,使用水文模型SWAT和水文模型Feflow提供的数据按月对巴基斯坦进行评估。计算得出的“缺水指数”(WDI)用于量化研究区域生产的棉花和小麦的WSF,并将其与使用现有的WDI时空分辨率较低的WSF进行比较。全年缺水量为0.1至1.0 m(剥夺)(3)/ m(消耗)(3)。用区域化WDI计算得出的棉花生产加权平均WSF为每吨2333 m(剥夺)(3),而研究区域南部生产的棉花的WSF则是北部灌溉分区的棉花的两倍。根据高分辨率WDI计算得出的结果比基于流域水平WDI计算得出的WSF高出60%以上。小麦的区域性WSF达每吨1821 m(剥夺)(3),与根据流域特定WDI计算的WSF一致。该研究强调在高空间(例如灌溉分区)和时间(每月)分辨率以提供可靠的WSF结果。

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