澳大利亚范围内的极端降雨和洪水预测

C. Wasko, D. Guo, M. Ho, R. Nathan, E. Vogel
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摘要

工程设计、洪泛区管理和水资源规划都需要对极端降雨和洪水进行估计。然而,当我们为未来规划和设计时,由于气候变化,我们过去使用的历史记录不再代表未来。我们的气候系统正在经历许多变化:不断上升的温度增加了饱和蒸汽压,增加了极端降雨;环流模式的变化正在改变降雨事件的频率;年平均降雨量和降雨间隔时间的变化对降雨前土壤水分状况有影响。因此,如果我们要在未来的设计、规划和决策中正确地指定风险水平,所有这些变化都需要在我们对极端降雨和洪水的估计中考虑进去。在这里,我们预测了澳大利亚不同气候下的极端降雨和洪水(以频率曲线的形式),并在此过程中开发了一种简单、可靠的方法,可以很容易地用于洪水预测。我们首先利用观测到的降雨量、潜在蒸散发(PET)和河流流量对467个水文参考站的降雨径流模型GR4J进行校准。校准使用了一种新的目标函数,旨在匹配洪水分位数。然后根据洪水频率、纳什-苏特克利夫效率(NSE)和年最大值的趋势对所有流域的水文模型进行评估,以确保捕获引起洪水频率变化的过程。为了在未来的预测中使用,我们从澳大利亚气象局(
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Australia-wide projections of extreme rainfall and flooding
: Engineering design, floodplain management, and water resources planning all require estimates of extreme rainfall and flooding. However, as we plan and design for the future, the historical records we have used in the past are no longer representative of the future due to climate change. Our climate system is experiencing many changes: rising temperatures are increasing the saturation vapor pressure increasing extreme rainfalls; changes in circulation patterns are shifting the frequency of rainfall events; and changes in the mean annual rainfall and time between rainfall events are impacting on the soil moisture conditions before a rainfall event. Hence, if we are to correctly specify the level of risk in future design and planning and decisions, all these changes need to be accounted for in our estimates of extreme rainfall and flooding. Here, we project extreme rainfall and flooding (in the form of frequency curves) across Australia’s diverse climate and, in doing so, develop a simple, robust methodology that can be readily used for flood projections. We first calibrate the rainfall-runoff model GR4J across 467 Hydrologic Reference Stations using observed rainfall, potential evapotranspiration (PET), and streamflow. The calibration uses a novel objective function which aims to match flood quantiles. The hydrological models across all catchments are then evaluated in terms of flood frequency, Nash-Sutcliffe Efficiency (NSE), and the trend in annual maxima, to ensure that the processes causing changes in flood frequency are captured. For use in future projections, rainfall and PET climate model data from four GCMs and four different bias-correction methods are obtained from the Australian Bureau of Meteorology (
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