Date

2022-9-2

Author

Çaktu, Yasemin

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This study aims to investigate climate change effect on precipitation, temperature and discharge in Havran basin which has thousands of decares of agricultural lands. Changes in precipitation and temperature were determined using 10 global climate models (GCMs) for total precipitation and 13 GCMs for average temperature from Coupled Model Intercomparison Project Phase 6 (CMIP6) for the historical period, SSP2-4.5 (moderate-case) and SSP5-8.5 (worst-case) scenarios. Both station observations and ERA5-Land reanalysis datasets are employed for bias correction of the GCM data with Quantile Mapping (QM), Quantile Delta Mapping (QDM) and Detrended Quantile Mapping (DQM) methods. Performance evaluation of bias corrected GCM data is conducted to demonstrate both model and bias correction performance for individual models and ensemble means. QDM and DQM outperform the QM method. QDM method is chosen for further evaluation. The resulting data is employed in GR2M hydrological model for the calculation of monthly discharge. The hydrological modeling is performed for five subbasins of Havran basin with ensemble means and individual models. The resulting precipitation, temperature and discharge were subjected to trend analysis in the historical period (1975-2014), near future period (2015-2044), mid future period (2045-2074) and far future period (2075-2100) for both scenarios. According to the results, there is an increasing trend in temperature in all parts of the basin for both SSP2-4.5 and SSP5-8.5 scenarios for all future periods where the increase is estimated to be up to 5oC by the end of the century. The worst-case scenario indicates there will be a 120 mm decrease in precipitation by the end of the century. Overall precipitation in the basin is decreasing however changes in the precipitation are not statistically significant. Consequently, discharge in the basin shows decreasing characteristics with up to % 36 decrease by the end of the century in the worst-case scenario.

Subject Keywords

Climate Change, Climate Model, GR2M

URI

https://hdl.handle.net/11511/99583

Collections

Graduate School of Natural and Applied Sciences, Thesis