评估气候变化对澳大利亚东南部积雪和河流影响的实用方法

G. Burns, K. Fowler, A. Horne
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摘要

在全球范围内,气候变化对融雪的影响日益受到关注。降雪通常是河流流量的关键组成部分,因为它在调节季节性和持久性方面起着至关重要的作用。然而,在澳大利亚,积雪是断断续续的,空间有限,缺乏公开的积雪数据记录。因此,在水流分析中,降雪常常被忽略。这项研究提出了一种实用的方法,在检查由于气候变化的影响对供水和水文的风险时,明确考虑与积雪的相互作用。虽然澳大利亚的积雪面积相对较小,但受影响的集水区对供水很重要。以前的研究范围有限(例如,专注于商业结果,如滑雪季节的变化),而且考虑到供水和水文影响的公开研究很少。本文提出的方法旨在适用于降雪量和覆盖数据有限的地区,以及更广泛的区域水资源评估。我们以墨累-达令盆地南部为例,将降雪模块整合到月降雨量-径流模型框架中。面临的挑战包括,现有的雪模式可能很复杂,需要输入大气通量等数据,而这些数据在该地区并不容易获得。为了解决这个问题,我们结合了一个简单的温度相关阈值来确定积雪覆盖,该阈值基于现有的广泛使用的月时间步积雪模块(Xu et al, 1996)。基于2000-2014年遥感影像的雪度数据集(Thompson, 2015),我们发现该方法可以在澳大利亚东南部几个气候不同的积雪覆盖地区复制雪动态,增加了气候变化下适用性的信心。然后将雪模块添加到现有的月降雨径流模型中(WAPABA, Wang et al, 2011)。这一过程被应用于雪山(澳大利亚最大的高山地区),以便对气候变化对河流和积雪的影响进行“压力测试”。正如预期的那样,结果表明,未来积雪面积和持续时间都可能显著减少。结果显示
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A practical approach to assessing climate change impacts on snow cover and streamflow in southeast Australia
: Globally, the impact of climate change on snow melt has become a growing concern. Snowfall is often a critical component of streamflow as it plays a crucial role in regulating seasonality and persistence. However, in Australia, snow cover is both intermittent and limited in space, with a lack of publicly available snow data records. As a result, snowfall is often neglected within streamflow analysis. This study presents a practical method to explicitly consider interactions with snow cover when examining risk to water supply and hydrology due to the impact of climate change. Although snow coverage in Australia is relatively small, the catchments affected are important for water supply. Previous studies have been limited in scope (e.g., focused on commercial outcomes such as changes to the ski season), and publicly available studies considering implications for water supply and hydrology are rare. The method presented here aims to be readily applicable in areas with limited data on snow fall and coverage, and within the context of broader regional water resource assessments. We integrate a snow module into a monthly rainfall-runoff modelling framework using the southern Murray-Darling Basin as a case study. Challenges include that existing snow models can be complicated, requiring data inputs such as atmospheric fluxes that are not readily available for this region. To address this, we incorporate a simple temperature-dependent threshold to determine snow cover based on an existing widely used monthly-timestep snow module (Xu et al, 1996). Calibrated to a snow extent dataset based on remote sensing imagery over 2000-2014 (Thompson, 2015), we found the method can replicate snow dynamics across several climatically-distinct snow-covered areas in south-east Australia, increasing confidence in applicability under climate change. The snow module was then added to an existing monthly rainfall runoff model (WAPABA, Wang et al, 2011). This process was applied to the Snowy Mountains (Australia’s largest alpine region) to allow a “stress test” of climate change impacts on streamflow and snow cover. As expected, results suggest that both snow coverage and duration will likely significantly reduce in the future. Results suggest
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