Projecting aridity from statistically downscaled and bias-corrected variables for the Gediz Basin, Turkey
Due to climatological changes, a study was conducted in the Gediz Basin, Turkey, where agricultural production holds an important place. In the study prepared, 12 general circulation models (GCMs) were utilized under representative concentration pathway (RCP)4.5, RCP6.0, and RCP8.5 scenarios of the...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2022-08-01
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| Series: | Journal of Water and Climate Change |
| Subjects: | |
| Online Access: | http://jwcc.iwaponline.com/content/13/8/3061 |
| _version_ | 1811209425688461312 |
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| author | Umut Kirdemir Umut Okkan Okan Fistikoglu |
| author_facet | Umut Kirdemir Umut Okkan Okan Fistikoglu |
| author_sort | Umut Kirdemir |
| collection | DOAJ |
| description | Due to climatological changes, a study was conducted in the Gediz Basin, Turkey, where agricultural production holds an important place. In the study prepared, 12 general circulation models (GCMs) were utilized under representative concentration pathway (RCP)4.5, RCP6.0, and RCP8.5 scenarios of the fifth assessment report (AR5) of IPCC for the period 2015–2050. The statistical downscaling methods were employed and the projections were derived right after applying the weighted-averaged ensemble mean by the Bayesian Model Averaging (BMA) method and bias correction by equidistant quantile mapping (EDQM). The temperature-based potential evapotranspiration (PET) formulas were modified in accordance with the Penman–Monteith method and the aridity indexes were calculated by UNEP's formula. According to the projections, the mean annual temperature increases between 1.5 and 2.2 °C and the mean total annual PET increases between 5 and 8% are foreseen in the Gediz Basin for the near future. It is foreseen that a semi-arid climate regime may predominate over the region for all of the RCP scenarios under the increasing dryness in basin climate. In addition, it was obtained in the study that sub-humid climate state occurrence for all of the regions included by the basin may be unexpected in the future for the RCP8.5 scenario. The presence of semi-arid climate conditions may be more potent with the increasing trend of radiative forcing over time.
HIGHLIGHTS
Artificial intelligence methods were performed for downscaling.;
A multi-model ensemble strategy was carried out for climate projection.;
A robust bias-correction method was utilized.;
Climate change forecasts were integrated with aridity concepts.;
Spatio-temporal aridity changes were presented for the future term.; |
| first_indexed | 2024-04-12T04:39:09Z |
| format | Article |
| id | doaj.art-940912444aaf477090ffcb92aa0ff0e3 |
| institution | Directory Open Access Journal |
| issn | 2040-2244 2408-9354 |
| language | English |
| last_indexed | 2024-04-12T04:39:09Z |
| publishDate | 2022-08-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Journal of Water and Climate Change |
| spelling | doaj.art-940912444aaf477090ffcb92aa0ff0e32022-12-22T03:47:43ZengIWA PublishingJournal of Water and Climate Change2040-22442408-93542022-08-011383061308210.2166/wcc.2022.109109Projecting aridity from statistically downscaled and bias-corrected variables for the Gediz Basin, TurkeyUmut Kirdemir0Umut Okkan1Okan Fistikoglu2 The Graduate of School of Natural and Applied Sciences, Hydraulic, Hydrology and Water Resources Division, Dokuz Eylul University, Izmir 35160, Turkey Department of Civil Engineering, Balikesir University, Balikesir, Turkey Department of Civil Engineering, Dokuz Eylul University, Izmir, Turkey Due to climatological changes, a study was conducted in the Gediz Basin, Turkey, where agricultural production holds an important place. In the study prepared, 12 general circulation models (GCMs) were utilized under representative concentration pathway (RCP)4.5, RCP6.0, and RCP8.5 scenarios of the fifth assessment report (AR5) of IPCC for the period 2015–2050. The statistical downscaling methods were employed and the projections were derived right after applying the weighted-averaged ensemble mean by the Bayesian Model Averaging (BMA) method and bias correction by equidistant quantile mapping (EDQM). The temperature-based potential evapotranspiration (PET) formulas were modified in accordance with the Penman–Monteith method and the aridity indexes were calculated by UNEP's formula. According to the projections, the mean annual temperature increases between 1.5 and 2.2 °C and the mean total annual PET increases between 5 and 8% are foreseen in the Gediz Basin for the near future. It is foreseen that a semi-arid climate regime may predominate over the region for all of the RCP scenarios under the increasing dryness in basin climate. In addition, it was obtained in the study that sub-humid climate state occurrence for all of the regions included by the basin may be unexpected in the future for the RCP8.5 scenario. The presence of semi-arid climate conditions may be more potent with the increasing trend of radiative forcing over time. HIGHLIGHTS Artificial intelligence methods were performed for downscaling.; A multi-model ensemble strategy was carried out for climate projection.; A robust bias-correction method was utilized.; Climate change forecasts were integrated with aridity concepts.; Spatio-temporal aridity changes were presented for the future term.;http://jwcc.iwaponline.com/content/13/8/3061aridity indexbayesian model averagingequidistant quantile mappingstatistical downscaling |
| spellingShingle | Umut Kirdemir Umut Okkan Okan Fistikoglu Projecting aridity from statistically downscaled and bias-corrected variables for the Gediz Basin, Turkey Journal of Water and Climate Change aridity index bayesian model averaging equidistant quantile mapping statistical downscaling |
| title | Projecting aridity from statistically downscaled and bias-corrected variables for the Gediz Basin, Turkey |
| title_full | Projecting aridity from statistically downscaled and bias-corrected variables for the Gediz Basin, Turkey |
| title_fullStr | Projecting aridity from statistically downscaled and bias-corrected variables for the Gediz Basin, Turkey |
| title_full_unstemmed | Projecting aridity from statistically downscaled and bias-corrected variables for the Gediz Basin, Turkey |
| title_short | Projecting aridity from statistically downscaled and bias-corrected variables for the Gediz Basin, Turkey |
| title_sort | projecting aridity from statistically downscaled and bias corrected variables for the gediz basin turkey |
| topic | aridity index bayesian model averaging equidistant quantile mapping statistical downscaling |
| url | http://jwcc.iwaponline.com/content/13/8/3061 |
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