A Hydrologic Drying Bias in Water-Resource Impact Analyses of Anthropogenic Climate Change
A Hydrologic Drying Bias in Water-Resource Impact Analyses of Anthropogenic Climate Change
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DOI：
10.1111/1752-1688.12538
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发表时间：
2017-08-01
影响因子：
2.4
通讯作者：
Dunne, Krista A.
中科院分区：
文献类型：
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作者：
Milly, P. C. D.;Dunne, Krista A.
在水资源规划中，淡水可获得性对人为气候变化(ACC)的敏感性通常是利用降水量和潜在蒸散量(E-P)作为输入的离线水文模型来分析的。由于E-P不是气候模型的输出，因此必须引入E-P的中间模型来连接气候模型和水文模型。使用了几种E-P方法。每种方法的适宜性可以通过注意到用于离线分析的可靠的E-P方法来评估，该方法应该能够再现气候模型在可以忽略的水分胁迫(E-W)地区和季节的实际蒸散中由ACC驱动的变化。我们将这种能力量化为七种常用的E-P方法，以及与可用能量的简单比例(仅能量方法)。除纯能量方法外，所有方法都倾向于大大高估与ACC相关的E-p增加。在离线水文模型中，与驱动气候模型中的水文通量相比，无论系统是否经历水分胁迫，E-p变化偏差都会导致实际蒸散量(E)的过度增加，从而导致径流变化的强烈负偏差。径流偏差在大小上与ACC引起的径流变化本身相当。这些结果表明，在许多水资源影响分析中，未来的水文干燥(增湿)趋势可能被系统性地高估(低估)。
For water-resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with offline hydrologic models that use precipitation and potential evapotranspiration (E-p) as inputs. Because E-p is not a climate-model output, an intermediary model of E-p must be introduced to connect the climate model to the hydrologic model. Several E-p methods are used. The suitability of each can be assessed by noting a credible E-p method for offline analyses should be able to reproduce climate models' ACC-driven changes in actual evapotranspiration in regions and seasons of negligible water stress (E-w). We quantified this ability for seven commonly used E-p methods and for a simple proportionality with available energy (energy-only method). With the exception of the energy-only method, all methods tend to overestimate substantially the increase in E-p associated with ACC. In an offline hydrologic model, the E-p-change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC-induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water-resource impact analyses.