Prediction of Annual Evaporation Change in Dry Regions Using the Budyko-type framework (Case Study of Neishaboor-RokhWatershed)

Document Type : Original Article


1 PhD student, Water Engineering Department College of Agriculture, Ferdowsi University of Mashhad., Mashhad., Iran

2 Professor, Department of Water Engineering, Ferdowsi University of Mashhad., Mashhad., Iran

3 Associate professor, Water Engineering Department College of Agriculture, Ferdowsi University of Mashhad., Mashhad., Iran

4 Professor, Water Engineering Department College of Agriculture, Ferdowsi University of Mashhad., Mashhad., Iran


Prediction of the water balance components, including actual evaporation is important for water resources management and climate change adaptation. Physically-based or distributed hydrological models are too complicated and they need lots of data as inputs to estimate the water balance components. Also the accuracy and the quality of the inputs can affect the accuracy of the models’ prediction. In some cases, it is not needed to have an accurate estimation of the water balance components and a primary estimation of annual evaporation and runoff is adequate for the management of the catchments. For these purposes, the conceptual lumped models were developed for the primary studies of hydrology. One of the most applied lumped models is developed based on Budyko hypothesis. Budyko curves were applied for the steady-state catchments in which the soil water storage is negligible. In the Budyko framework, a new equation (Greve et al., 2016)was developed to estimate evaporation in non-steady-state situations where the soil water storage cannot be negligible. In this study, the new proposed model was calibrated for the non-steady-state catchment of Neishaboor-Rokh using the precipitation, potential evaporation and actual evaporation and then using the calibrated equation, actual evaporation was estimated for the historical (1971-2005) and future (2016-2050) period of CORDEXproject. Based on the actual evaporation from SWAT model, Greve et al. model parameters (y0 and k) were 0.24 and 1.54, respectively. The results showed that, under climate change, the precipitation rate would decrease by 0.48% and mean temperature, potential evaporation and actual evaporation would increase by 11.25%, 4.66% and 2.11%, respectively.


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