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首页> 外文期刊>Journal of Hydrology >Rainwater catchment system design using simulated future climate data
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Rainwater catchment system design using simulated future climate data

机译:利用模拟未来气候数据设计雨水集水系统

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Rainwater harvesting techniques are used worldwide to augment potable water supply, provide water for small-scale irrigation practices, increase rainwater-use efficiency for sustained crop growth in arid and semi-arid regions, decrease urban stormwater flow volumes, and in general to relieve dependency on urban water resources cycles. A number of methods have been established in recent years to estimate reliability of rainwater catchment systems (RWCS) and thereby properly size the components (roof catchment area, storage tank size) of the system for a given climatic region. These methods typically use historical or stochastically-generated rainfall patterns to quantify system performance and optimally size the system, with the latter accounting for possible rainfall scenarios based on statistical relationships of historical rainfall patterns. To design RWCS systems that can sustainably meet water demand under future climate conditions, this paper introduces a method that employs climatic data from general circulation models (GCMs) to develop a suite of catchment area vs. storage size design curves that capture uncertainty in future climate scenarios. Monthly rainfall data for the 2010-2050 time period is statistically downscaled to daily values using a Markov chain algorithm, with results used only from GCMs that yield rainfall patterns that are statistically consistent with historical rainfall patterns. The process is demonstrated through application to two climatic regions of the Federated States of Micronesia (FSM) in the western Pacific, wherein the majority of the population relies on rainwater harvesting for potable water supply. Through the use of design curves, communities can provide household RWCS that achieve a certain degree of storage reliability. The method described herein can be applied generally to any geographic region. It can be used to first, assess the future performance of existing household systems; and second, to design or modify systems that will yield adequate storage for future climate conditions. (C) 2015 Elsevier B.V. All rights reserved.
机译:全世界都使用雨水收集技术来增加饮用水供应,为小规模灌溉实践提供水,提高雨水利用效率,以促进干旱和半干旱地区的作物可持续生长,减少城市雨水流量,并总体上减轻依赖在城市水资源循环中。近年来,已经建立了许多方法来估计雨水集水系统(RWCS)的可靠性,从而针对给定的气候区域适当确定系统的组件大小(屋顶集水面积,储水箱尺寸)。这些方法通常使用历史或随机生成的降雨模式来量化系统性能并优化系统大小,而后者则基于历史降雨模式的统计关系来考虑可能的降雨情况。为了设计可在未来气候条件下可持续满足水需求的RWCS系统,本文介绍了一种方法,该方法利用来自一般循环模型(GCM)的气候数据来绘制一套集水面积与储水量的设计曲线,以捕获未来气候中的不确定性场景。使用马尔可夫链算法将2010-2050年期间的月降雨量数据统计缩减为每日值,其结果仅用于GCM,这些GCM产生的降雨模式在统计上与历史降雨模式一致。通过将其应用到西太平洋密克罗尼西亚联邦(FSM)的两个气候区域来证明这一过程,其中大部分人口依靠雨水收集来提供饮用水。通过使用设计曲线,社区可以提供可实现一定程度的存储可靠性的家用RWCS。本文描述的方法通常可以应用于任何地理区域。它可以用于首先评估现有家庭系统的未来性能;其次,设计或修改可为未来气候条件提供足够存储的系统。 (C)2015 Elsevier B.V.保留所有权利。

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