Next Article in Journal
Potential Effects of Climate and Human Influence Changes on Range and Diversity of Nine Fabaceae Species and Implications for Nature’s Contribution to People in Kenya
Next Article in Special Issue
Climate Drivers and Sources of Sediment and Organic Matter Fluxes in Intermittent Rivers and Ephemeral Streams (IRES) of a Subtropical Watershed, USA
Previous Article in Journal
Frequency Associations between East Asian Jet Streams and the Temperature over the Barents–Kara Sea Region/Arctic Oscillation in Winter
Open AccessArticle

Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios

1
College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
2
Agricultural and Biological Engineering Department, Indian River Research and Education Center, University of Florida, Fort Pierce, FL 34945, USA
3
Three Gorges Hydrology and Water Resources Survey, Bureau of Hydrology, Yangtze River Water Conservancy Commission, Yichang 443000, China
*
Author to whom correspondence should be addressed.
Climate 2020, 8(10), 108; https://doi.org/10.3390/cli8100108
Received: 27 August 2020 / Revised: 27 September 2020 / Accepted: 29 September 2020 / Published: 30 September 2020
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. View Full-Text
Keywords: GCM; bias correction methods; hydrological simulation; climate change GCM; bias correction methods; hydrological simulation; climate change
Show Figures

Figure 1

MDPI and ACS Style

Tan, Y.; Guzman, S.M.; Dong, Z.; Tan, L. Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios. Climate 2020, 8, 108.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop