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Time series analysis of water use and indirect reuse within a HUC-4 basin (Wabash) over a nine year period

机译:在九年内HUC-4盆地(WABASH)内的水使用和间接重复使用的时间序列分析

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Anthropogenic water use and reuse represent major components of the water cycle. In the context of climate change, water reuse and recycling are considered necessary components for an integrated water management approach. Unplanned, or de facto, indirect water reuse occurs in most of the U.S. river systems, however, there is little real-time documentation of it. Despite the fact that there are national and state agencies that systematically collect data on water withdrawals and wastewater discharges, their databases are organized and managed in a way that makes it challenging to use them for water resource management analysis. The ability to combine reported water data to perform large scale analysis about water use and reuse is severely limited. In this paper, we apply a simple but effective methodology to complete a time series watershed-scale analysis of water use and unplanned indirect reuse for the Wabash River Watershed. Results document the occurrence of indirect water reuse, ranging from 3% to 134%, in a water-rich area of the U.S. The time series analysis shows that reported data effectively describe the water use trends through nine years, from 2009 to 2017, clearly reflecting both anthropogenic and natural events in the watershed, such as the retirement of thermoelectric power plants, and the occurrence of an extreme drought in 2012. We demonstrate the feasibility and significance of using available water datasets to perform large scale water use analysis, describe limitations encountered in the process, and highlight areas for improvement in water data management.
机译:人为用水和再利用代表水循环的主要组成部分。在气候变化的背景下,水再利用和再循环被认为是综合水管理方法的必要组成部分。在大多数美国河流系统中发生了意外,间接的水重用,然而,它几乎没有实时文件。尽管有国家和州各机构系统地收集有关措施和废水排放的数据,但他们的数据库是以一种使其充分利用它们进行水资源管理分析的方式组织和管理的数据库。将报告的水数据结合的能力对水使用和重用进行大规模分析严重限制。在本文中,我们应用了一个简单但有效的方法,以完成水平的时间序列流域水平分析,对Wabash河流域的无计划间接重用。结果记录了间接水再利用的发生,范围从3%至134%,在美国的富含水域地区,时间序列分析显示,报告的数据有效地描述了九年来的水分趋势,从2009年到2017年,显然反映了流域中的人为和自然事件,例如热电发电厂的退休以及2012年的极端干旱的发生。我们展示了使用可用水数据集进行大规模用水量分析的可行性和意义,描述了限制在过程中遇到,并突出显示水数据管理的改进领域。

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