Potential evapotranspiration-related uncertainty in climate change impacts on river flow: An assessment for the Mekong River basin
Potential evapotranspiration-related uncertainty in climate change impacts on river flow: An assessment for the Mekong River basin
复制标题
DOI：
10.1016/j.jhydrol.2013.12.010
复制
发表时间：
2014-03
影响因子：
6.4
通讯作者：
J. Thompson;A. Green;D. Kingston
中科院分区：
文献类型：
--
作者：
J. Thompson;A. Green;D. Kingston
开发了湄公河的六个MIKE SHE模型，每个模型都采用使用替代方法获得的潜在蒸散量（PET）：Blaney-Criddle（BC），Hamon（HM），Hargreen-Samani（HS），Linacre（LN），Penman（PN）和Priestley-Taylor（PT）。基线（1961-1990）PET变化，PT其次是HS提供最低的总数，LN和BC最高。最大的年平均PET是最小的1.5倍以上。每个模型的独立校准导致不同的优化参数集，这些优化参数集减轻了基线PET中的差异。每个模型的性能为“优秀”（月NSE > 0.85）或“非常好”（NSE：0.65-0.85）。研究了基于全球平均温度上升2 °C的七个大气环流模型的情景。降水量变化中的GCM间差异比PET变化中的GCM间差异大得多（按百分比计算，大2.5-10倍）。降水变化包括流域范围内的增加或减少，以及空间变化的变化方向，而PET增加所有的情况。BC和HS产生的变化最小，LN和HM产生的变化最大。PET方法确实会影响情景排放。然而，平均排放量变化的GCM相关不确定性平均比PET方法相关不确定性大3.5倍。情景与流域范围内的降水增加（减少）诱导增加（减少）的平均流量，无论PET方法。放电的变化幅度取决于PET方法;产生最小PET增加的方法导致放电的较大增加或较小下降。由于PET方法的平均流量的变化方向的不确定性发生在空间可变的降水变化的情况下，虽然这是有限的几个测量站和差异相对较小。对于所有的情况下，PET方法相关的不确定性的变化方向，在高和低流量发生，但季节性分布的排放基本上不受影响。因此，虽然PET方法确实影响排放预测，但大气环流模式之间降水气候变化信号的变化是一个更大的不确定性来源。
Six MIKE SHE models of the Mekong are developed, each employing potential evapotranspiration (PET) derived using alternative methods: Blaney–Criddle (BC), Hamon (HM), Hargreaves–Samani (HS), Linacre (LN), Penman (PN) and Priestley–Taylor (PT). Baseline (1961–1990) PET varies, with PT followed by HS providing the lowest totals, LN and BC the highest. The largest mean annual PET is over 1.5 times the smallest. Independent calibration of each model results in different optimised parameter sets that mitigate differences in baseline PET. Performance of each model is “excellent” (monthly NSE > 0.85) or “very good” (NSE: 0.65–0.85). Scenarios based on seven GCMs for a 2 °C increase in global mean temperature are investigated. Inter-GCM variation in precipitation change is much larger (in percentage terms by 2.5–10 times) than inter-GCM differences in PET change. Precipitation changes include catchment-wide increases or decreases as well as spatially variable directions of change, whereas PET increases for all scenarios. BC and HS produce the smallest changes, LN and HM the largest. PET method does impact scenario discharges. However, GCM-related uncertainty for change in mean discharge is on average 3.5 times greater than PET method-related uncertainty. Scenarios with catchment-wide precipitation increases (decreases) induce increases (decreases) in mean discharge irrespective of PET method. Magnitude of change in discharge is conditioned by PET method; larger increases or smaller declines in discharge result from methods producing the smallest PET increases. Uncertainty in the direction of change in mean discharge due to PET method occurs for scenarios with spatially variable precipitation change, although this is limited to few gauging stations and differences are relatively small. For all scenarios, PET method-related uncertainty in direction of change in high and low flows occurs, but seasonal distribution of discharge is largely unaffected. As such, whilst PET method does influence projections of discharge, variation in the precipitation climate change signal between GCMs is a much larger source of uncertainty.