Uncertainties in climate change projection can originate from various sources and cause challenges. Thus, two specific approaches were developed in this study, for use in the selection of global climate models and in the assessment of drought occurrence. Considering the bias-corrected data, the performance of global climate models was evaluated using statistical methods, and the 14 best-ranked models were selected. These climate scenarios were used in the Long Ashton Research Station (LARS) downscaling model to obtain the precipitation and temperature time series. Identification of unit Hydrographs And Component flows from Rainfall, Evaporation, and Streamflow (IHACRES) was used to model the runoff time series. Standardized precipitation and runoff indices were considered to assess the probability of meteorological and hydrological droughts. Finally, the Bayesian method was used to analyse the uncertainty assessment of drought occurrence. This methodology was applied in the Karkheh River basin and presented the moderate drought condition as the most probable state.
Salimian N., Nazari S. and Ahmadi A. (2021) Assessment of the uncertainties of global climate models in the evaluation of standardized precipitation and runoff indices: a case study. Hydrological Sciences Journal 66(9): 1419-1436. 10.1080/02626667.2021.1937178
@article{Salimian2021,
Title = {Assessment of the uncertainties of global climate models in the evaluation of standardized precipitation and runoff indices: a case study},
Author = {Salimian, Niloofar and Nazari, Sara and Ahmadi, Azadeh},
Editor = {},
Journal = {Hydrological Sciences Journal},
Year = {2021},
Pages = {1419-1436},
Volume = {66},
Doi = {10.1080/02626667.2021.1937178},
Abstract = {Uncertainties in climate change projection can originate from various sources and cause challenges. Thus, two specific approaches were developed in this study, for use in the selection of global climate models and in the assessment of drought occurrence. Considering the bias-corrected data, the performance of global climate models was evaluated using statistical methods, and the 14 best-ranked models were selected. These climate scenarios were used in the Long Ashton Research Station (LARS) downscaling model to obtain the precipitation and temperature time series. Identification of unit Hydrographs And Component flows from Rainfall, Evaporation, and Streamflow (IHACRES) was used to model the runoff time series. Standardized precipitation and runoff indices were considered to assess the probability of meteorological and hydrological droughts. Finally, the Bayesian method was used to analyse the uncertainty assessment of drought occurrence. This methodology was applied in the Karkheh River basin and presented the moderate drought condition as the most probable state.},
}
TY - JOUR
AU - Salimian, Niloofar
AU - Nazari, Sara
AU - Ahmadi, Azadeh
TI - Assessment of the uncertainties of global climate models in the evaluation of standardized precipitation and runoff indices: a case study
T2 - Hydrological Sciences Journal
PY - 2021
SP - 1419-1436
VL - 66
DO - 10.1080/02626667.2021.1937178
AB - Uncertainties in climate change projection can originate from various sources and cause challenges. Thus, two specific approaches were developed in this study, for use in the selection of global climate models and in the assessment of drought occurrence. Considering the bias-corrected data, the performance of global climate models was evaluated using statistical methods, and the 14 best-ranked models were selected. These climate scenarios were used in the Long Ashton Research Station (LARS) downscaling model to obtain the precipitation and temperature time series. Identification of unit Hydrographs And Component flows from Rainfall, Evaporation, and Streamflow (IHACRES) was used to model the runoff time series. Standardized precipitation and runoff indices were considered to assess the probability of meteorological and hydrological droughts. Finally, the Bayesian method was used to analyse the uncertainty assessment of drought occurrence. This methodology was applied in the Karkheh River basin and presented the moderate drought condition as the most probable state.
ER -
