On the Sensitivity of Standardized-Precipitation-Evapotranspiration and Aridity Indexes Using Alternative Potential Evapotranspiration Models

被引:18
|
作者
Tegos, Aristoteles [1 ,2 ]
Stefanidis, Stefanos [3 ]
Cody, John [2 ]
Koutsoyiannis, Demetris [1 ]
机构
[1] Natl Tech Univ Athens, Sch Civil Engn, Lab Hydrol & Water Resources Dev, Heroon Polytechneiou 9, Zografos 15780, Greece
[2] Ryan Hanley Ltd Ireland, 170-173 Ivy Exchange,Granby Pl,Parnell Sq W, Dublin D01 N938, Ireland
[3] Aristotle Univ Thessaloniki, Sch Forestry & Nat Environm, Lab Mountainous Water Management & Control, Thessaloniki 54124, Greece
关键词
drought; standardized precipitation-evapotranspiration index; aridity index; parametric PET model; California; DROUGHT INDEXES;
D O I
10.3390/hydrology10030064
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
This paper examines the impacts of three different potential evapotranspiration (PET) models on drought severity and frequencies indicated by the standardized precipitation index (SPEI). The standardized precipitation-evapotranspiration index is a recent approach to operational monitoring and analysis of drought severity. The standardized precipitation-evapotranspiration index combines precipitation and temperature data, quantifying the severity of a drought as the difference in a timestep as the difference between precipitation and PET. The standardized precipitation-evapotranspiration index thus represents the hydrological processes that drive drought events more realistically than the standardized precipitation index at the expense of additional computational complexity and increased data demands. The additional computational complexity is principally due to the need to estimate PET within each time step. The standardized precipitation-evapotranspiration index was originally defined using the Thornthwaite PET model. However, numerous researchers have demonstrated the standardized precipitation-evapotranspiration index is sensitive to the PET model adopted. PET models requiring sparse meteorological inputs, such as the Thornthwaite model, have particular utility for drought monitoring in data scarce environments. The aridity index (AI) investigates the spatiotemporal changes in the hydroclimatic system. It is defined as the ratio between potential evapotranspiration and precipitation. It is used to characterize wet (humid) and dry (arid) regions. In this study, a sensitivity analysis for the standardized precipitation-evapotranspiration and aridity indexes was carried out using three different PET models; namely, the Penman-Monteith model, a temperature-based parametric model and the Thornthwaite model. The analysis was undertaken in six gauge stations in California region where long-term drought events have occurred. Having used the Penman-Monteith model as the PET model for estimating the standardized precipitation-evapotranspiration index, our findings highlight the presence of uncertainty in defining the severity of drought, especially for large timescales (12 months to 48 months), and that the PET parametric model is a preferable model to the Thornthwaite model for both the standardized precipitation-evapotranspiration index and the aridity indexes. The latter outcome is worth further consideration for when climatic studies are under development in data scarce areas where full required meteorological variables for Penman-Monteith assessment are not available.
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页数:13
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