Assessment of the uncertainties of global climate models in the evaluation of standardized precipitation and runoff indices: a case study

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 perf...

Full description

Saved in:
Bibliographic Details
Published in:Hydrological sciences journal 2021-07, Vol.66 (9), p.1419-1436
Main Authors: Salimian, Niloofar, Nazari, Sara, Ahmadi, Azadeh
Format: Article
Language:English
Subjects:
Atmospheric precipitations
Bayesian analysis
Bayesian method
Climate change
Climate models
Drought
Evaporation
Global climate
Global climate models
Hydrologic drought
Hydrology
Mathematical models
Precipitation
Precipitation and runoff
Probability theory
Rain
Rainfall
River basins
Runoff
standardized precipitation index
standardized runoff index
Statistical analysis
Statistical methods
Stream discharge
Stream flow
Time series
Uncertainty
Unit hydrographs
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0262-6667
2150-3435
DOI:10.1080/02626667.2021.1937178