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Uncertainty in climate change projections of discharge for the Mekong River Basin

机译:湄公河流域气候变化预测的不确定性

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The Mekong River Basin is a key regional resource in Southeast Asia forsectors that include agriculture, fisheries and electricity production. Herewe explore the potential impacts of climate change on freshwater resourceswithin the river basin. We quantify uncertainty in these projectionsassociated with GCM structure and climate sensitivity, as well as fromhydrological model parameter specification. This is achieved by runningpattern-scaled GCM scenarios through a semi-distributed hydrological model(SLURP) of the basin. Pattern-scaling allows investigation of specificthresholds of global climate change including the postulated 2 °Cthreshold of "dangerous" climate change. Impacts of a 2 °C rise inglobal mean temperature are investigated using seven different GCMs,providing an implicit analysis of uncertainty associated with GCM structure.Analysis of progressive changes in global mean temperature from 0.5 to6 °C above the 1961–1990 baseline (using the HadCM3 GCM) reveals a relativelysmall but non-linear response of annual river discharge to increasing globalmean temperature, ranging from a 5.4 % decrease to 4.5 % increase.Changes in mean monthly river discharge are greater (from ?16 % to+55 %, with greatest decreases in July and August, greatest increases inMay and June) and result from complex and contrasting intra-basin changes inprecipitation, evaporation and snow storage/melt. Whilst overall results arehighly GCM dependent (in both direction and magnitude), this uncertainty isprimarily driven by differences in GCM projections of future precipitation.In contrast, there is strong consistency between GCMs in terms of bothincreased potential evapotranspiration and a shift to an earlier and lesssubstantial snowmelt season. Indeed, in the upper Mekong (Lancangsub-basin), the temperature-related signal in discharge is strong enough tooverwhelm the precipitation-related uncertainty in the direction of changein discharge, with scenarios from all GCMs leading to increased river flowfrom April–June and decreased flow from July–August.
机译:湄公河流域是东南亚农业,渔业和电力生产等部门的重要区域资源。在这里,我们探讨了气候变化对流域内淡水资源的潜在影响。我们量化了与GCM结构和气候敏感性以及水文模型参数规范相关的这些预测的不确定性。这是通过流域半分布式水文模型(SLURP)运行模式规模的GCM方案实现的。模式定标允许调查全球气候变化的特定阈值,包括假定的“危险”气候变化的2°C阈值。使用七个不同的GCM对全球平均温度升高2°C的影响进行了调查,从而提供了与GCM结构相关的不确定性的隐式分析。分析了全球平均温度在1961-1990年基线以上0.5至6°C的逐步变化(使用HadCM3 GCM)揭示了年度河流流量对全球平均温度升高的相对较小但非线性的响应,范围从5.4%降低到4.5%升高,平均每月河流流量的变化更大(从?16%到+ 55%, 7月和8月降幅最大,5月和6月降幅最大)是由于流域内降水,蒸发和积雪/融雪的复杂变化形成鲜明对比。尽管总体结果高度依赖于GCM(在方向和大小上),但这种不确定性主要是由未来降水的GCM预测差异引起的;相比之下,就潜在蒸散量的增加以及向更早,更少量的转移而言,GCM之间具有很强的一致性。融雪的季节。的确,在湄公河上游(澜沧江流域),与温度相关的排放信号强度足以抵消与排放相关的降水变化方向的不确定性,所有GCM的情景都导致4月至6月河水流量增加而下降。 7月至8月的流量。

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