Abstract
Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems.
Highlights
After precipitation, evapotranspiration is the largest component of the terrestrial hydrological budget and critical for water resources evaluation and sustainable water management policies (Liu andPhinn, 2003, Portugali et al, 1994, Wu, 2002)
The term potential evapotranspiration represents the ET, which would occur under optimal conditions where evapotranspiration is not limited by factors such as soil moisture
The 6-selected empirical temperature based potential evapotranspiration (PETS) formulae were applied to long-term mean monthly temperature data for the Shannon River Basin District within a GIS
Summary
Evapotranspiration is the largest component of the terrestrial hydrological budget and critical for water resources evaluation and sustainable water management policies (Liu andPhinn, 2003, Portugali et al, 1994, Wu, 2002). Evapotranspiration is responsible for transferring moisture from the surface to the atmosphere in vapor form. Evapotranspiration includes two processes that occur simultaneously in the soil-plantatmosphere system, direct evaporation of moisture from the surface, and the exchange of water vapor, which occurs within the leaves of plants (transpiration) (Swenson and Wahr, 2006, Wilson et al, 2001). Evapotranspiration represents the most active of land- based hydrological processes, with approximately 65% of precipitation being evaporated and transpired (Kite and Droogers, 2000, Shukla and Mintz, 1982). Evapotranspiration fulfills numerous roles throughout its cycle It accomplishes energy (heat) and mass (water vapor) transfer between the Ear surface and atmosphere, and is the most active mechanism connecting the atmosphere, hydrosphsophere, lithosphere and biosphere (Zhao et al, 2004, Kite and Droogers, 2000, Zhang et al, 2001). Potential evapotranspiration remains one of the least satisfactorily explained processes in the hydrological cycle, principally because of its spatial variability (Andréassian, 2004, Andréassian et al, 2004, Oudin et al, 2005)
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