Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios
Global climate change is presenting a variety of challenges to hydrology and water resources because it strongly affects the hydrologic cycle, runoff, and water supply and demand. In this study, we assessed the effects of climate change scenarios on hydrological variables (i.e., evapotranspiration a...
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doaj-3325a7a08939448481fc427db63267fd2020-11-25T03:51:25ZengMDPI AGClimate2225-11542020-09-01810810810.3390/cli8100108Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate ScenariosYaogeng Tan0Sandra M. Guzman1Zengchuan Dong2Liang Tan3College of Hydrology and Water Resources, Hohai University, Nanjing 210098, ChinaAgricultural and Biological Engineering Department, Indian River Research and Education Center, University of Florida, Fort Pierce, FL 34945, USACollege of Hydrology and Water Resources, Hohai University, Nanjing 210098, ChinaThree Gorges Hydrology and Water Resources Survey, Bureau of Hydrology, Yangtze River Water Conservancy Commission, Yichang 443000, ChinaGlobal climate change is presenting a variety of challenges to hydrology and water resources because it strongly affects the hydrologic cycle, runoff, and water supply and demand. In this study, we assessed the effects of climate change scenarios on hydrological variables (i.e., evapotranspiration and runoff) by linking the outputs from the global climate model (GCM) with the Soil and Water Assessment Tool (SWAT) for a case study in the Lijiang River Basin, China. We selected a variety of bias correction methods and their combinations to correct the lower resolution GCM outputs of both precipitation and temperature. Then, the SWAT model was calibrated and validated using the observed flow data and corrected historical GCM with the optimal correction method selected. Hydrological variables were simulated using the SWAT model under emission scenarios RCP2.6, RCP4.5, and RCP8.5. The results demonstrated that correcting methods have a positive effect on both daily precipitation and temperature, and a hybrid method of bias correction contributes to increased performance in most cases and scenarios. Based on the bias corrected scenarios, precipitation annual average, temperature, and evapotranspiration will increase. In the case of precipitation and runoff, projection scenarios show an increase compared with the historical trends, and the monthly distribution of precipitation, evapotranspiration, and runoff shows an uneven distribution compared with baseline. This study provides an insight on how to choose a proper GCM and bias correction method and a helpful guide for local water resources management.https://www.mdpi.com/2225-1154/8/10/108GCMbias correction methodshydrological simulationclimate change |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yaogeng Tan Sandra M. Guzman Zengchuan Dong Liang Tan |
spellingShingle |
Yaogeng Tan Sandra M. Guzman Zengchuan Dong Liang Tan Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios Climate GCM bias correction methods hydrological simulation climate change |
author_facet |
Yaogeng Tan Sandra M. Guzman Zengchuan Dong Liang Tan |
author_sort |
Yaogeng Tan |
title |
Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios |
title_short |
Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios |
title_full |
Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios |
title_fullStr |
Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios |
title_full_unstemmed |
Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios |
title_sort |
selection of effective gcm bias correction methods and evaluation of hydrological response under future climate scenarios |
publisher |
MDPI AG |
series |
Climate |
issn |
2225-1154 |
publishDate |
2020-09-01 |
description |
Global climate change is presenting a variety of challenges to hydrology and water resources because it strongly affects the hydrologic cycle, runoff, and water supply and demand. In this study, we assessed the effects of climate change scenarios on hydrological variables (i.e., evapotranspiration and runoff) by linking the outputs from the global climate model (GCM) with the Soil and Water Assessment Tool (SWAT) for a case study in the Lijiang River Basin, China. We selected a variety of bias correction methods and their combinations to correct the lower resolution GCM outputs of both precipitation and temperature. Then, the SWAT model was calibrated and validated using the observed flow data and corrected historical GCM with the optimal correction method selected. Hydrological variables were simulated using the SWAT model under emission scenarios RCP2.6, RCP4.5, and RCP8.5. The results demonstrated that correcting methods have a positive effect on both daily precipitation and temperature, and a hybrid method of bias correction contributes to increased performance in most cases and scenarios. Based on the bias corrected scenarios, precipitation annual average, temperature, and evapotranspiration will increase. In the case of precipitation and runoff, projection scenarios show an increase compared with the historical trends, and the monthly distribution of precipitation, evapotranspiration, and runoff shows an uneven distribution compared with baseline. This study provides an insight on how to choose a proper GCM and bias correction method and a helpful guide for local water resources management. |
topic |
GCM bias correction methods hydrological simulation climate change |
url |
https://www.mdpi.com/2225-1154/8/10/108 |
work_keys_str_mv |
AT yaogengtan selectionofeffectivegcmbiascorrectionmethodsandevaluationofhydrologicalresponseunderfutureclimatescenarios AT sandramguzman selectionofeffectivegcmbiascorrectionmethodsandevaluationofhydrologicalresponseunderfutureclimatescenarios AT zengchuandong selectionofeffectivegcmbiascorrectionmethodsandevaluationofhydrologicalresponseunderfutureclimatescenarios AT liangtan selectionofeffectivegcmbiascorrectionmethodsandevaluationofhydrologicalresponseunderfutureclimatescenarios |
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1724487931752611840 |