Hydrology and Earth System Sciences (Apr 2017)

Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones

  • D. Guo,
  • S. Westra,
  • H. R. Maier

DOI
https://doi.org/10.5194/hess-21-2107-2017
Journal volume & issue
Vol. 21, no. 4
pp. 2107 – 2126

Abstract

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Assessing the factors that have an impact on potential evapotranspiration (PET) sensitivity to changes in different climate variables is critical to understanding the possible implications of climatic changes on the catchment water balance. Using a global sensitivity analysis, this study assessed the implications of baseline climate conditions on the sensitivity of PET to a large range of plausible changes in temperature (T), relative humidity (RH), solar radiation (Rs) and wind speed (uz). The analysis was conducted at 30 Australian locations representing different climatic zones, using the Penman–Monteith and Priestley–Taylor PET models. Results from both models suggest that the baseline climate can have a substantial impact on overall PET sensitivity. In particular, approximately 2-fold greater changes in PET were observed in cool-climate energy-limited locations compared to other locations in Australia, indicating the potential for elevated water loss as a result of increasing actual evapotranspiration (AET) in these locations. The two PET models consistently indicated temperature to be the most important variable for PET, but showed large differences in the relative importance of the remaining climate variables. In particular for the Penman–Monteith model, wind and relative humidity were the second-most important variables for dry and humid catchments, respectively, whereas for the Priestley–Taylor model solar radiation was the second-most important variable, with the greatest influence in warmer catchments. This information can be useful to inform the selection of suitable PET models to estimate future PET for different climate conditions, providing evidence on both the structural plausibility and input uncertainty for the alternative models.