A Prediction of Future Drought in Thailand under Changing Climate by Using SPI and SPEI Indices

doi: 10.14456/mijet.2020.12


  • Somphinith Muangthong somphinith.mu@rmuti.ac.th
  • Winai Chaowiwat Hydro Informatics Institute
  • Kanoksri Sarinnapakorn Hydro Informatics Institute
  • Khanittha Chaibandit Rajamangala University of Technology Isan, Nakhon Ratchasima


climate change, gamma-gamma transformation, bias correction, standardized precipitation index, standardized precipitation evaporation index


Climate change is the main cause of the water disasters; directly impacted flood and drought that occur from excess and shortage of water in several areas. Drought risk areas have tendency to suffer from greater severity and higher frequency of disaster in future. Therefore, it is necessary to conduct drought prediction in order to understand water stress conditions in drought hotspots or drought prone areas. Meteorological drought indicators can be calculated from rainfall and temperature. The standardized precipitation index (SPI) and standardized precipitation evaporation index (SPEI) are used in temporal analysis of drought severity. This study aims to predict and compare future droughts under changing climate. The observed climate data from weather stations in Thailand and 10 GCM climate datasets under CMIP5 project were used as inputs. The gamma-gamma transformation method was applied to correct biases of GCM precipitation and temperature data. SPI and SPEI indices were calculated for each weather station to describe drought situation. The number of drought events and their severity were calculated and presented on a drought risk map. The consistency index was used to identify hotspot areas from multiple SPI and SPEI results. These results would raise drought awareness of related government agencies in order to prepare the water plans to cope with water shortage in the drought risk areas.


Download data is not yet available.

Author Biographies

Winai Chaowiwat, Hydro Informatics Institute

Hydro Informatics Institute, Bangkok, Thailand

Kanoksri Sarinnapakorn, Hydro Informatics Institute

Hydro Informatics Institute, Bangkok, Thailand 

Khanittha Chaibandit, Rajamangala University of Technology Isan, Nakhon Ratchasima

Faculty of Engineering and Architecture, Rajamangala University of Technology Isan

Nakhon Ratchasima, Thailand


[1] Mika, J., Horvath, S., Makra, L. and Dunkel, Z. (2005) The Palmer drought severity index (PDSI) as an indicator of soil moisture. Physics and Chemistry of the Earth, 30, 223–230. https://doi.org/10.1016/j.pce.2004.08.036.
[2] World Meteorological Organization, (2012) Standardized Precipitation Index User Guide (M. Svoboda, M. Hayes and D. Wood). (WMO-No. 1090), Geneva.
[3] Vicente-Serrano S.M., Santiago Beguería, Juan I. López-Moreno, (2010) A Multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index - SPEI. Journal of Climate 23: 1696-1718.
[4] http://spei.csic.es/home.html
[5] Keyantash, J. and J. Dracup., (2002) The quantification of drought: an evaluation of drought indices. Bulletin of the American Meteorological Society 83, 1167-1180.
[6] Kim, D.W. and H.R. Byun, (2009) Future pattern of Asian drought under global warming scenario. Theor. Appl. Climatol., 98, 137-150.
[7] Giorgi, F., and X. Bi, (2005) Updated regional precipitation and temperature changes for 21st century from ensembles of recent AOGCM simulations, Geophys. Res. Lett. 32, L21715, doi:10.1029/2005GL02-4288





Research Papers