EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Understanding drought indicator-to-impact relationships to improve drought monitoring and early warning: Thailand as a case study 

Maliko Tanguy1, Lucy Barker1, Michael Eastman2, Chaiwat Ekkawatpanit3, Daniel Goodwin4, Jamie Hannaford1,5, Ian Holman6, Eugene Magee1, Liwa Pardthaisong7, Simon Parry1, Dolores Rey8, and Supattra Visessri9
Maliko Tanguy et al.
  • 1Water Resources, UK Centre for Ecology & Hydrology (UKCEH), Wallingford, United Kingdom (
  • 2UK Applied Sciences, Met Office, Exeter, United Kingdom
  • 3Water Resources Engineering Division, King Mongkut's University of Technology, Thonburi, Thailand
  • 4School of Social Sciences, University of Tasmania, Tasmania, Australia
  • 5Irish Climate Analysis and Research UnitS (ICARUS), Maynooth University, Maynooth, Ireland
  • 6Cranfield Water Science Institute, Cranfield University, Cranfield, United Kingdom
  • 7Department of Geography, Faculty of Social Sciences, Chiang Mai University, Thailand
  • 8European Commission - Joint Research Centre, Seville, Spain
  • 9Department of Water Resource Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand

Thailand has already been experiencing an increase in severity and duration of its droughts as a consequence of the changing climate. Developing a reliable drought monitoring and early warning system (DMEWS) is an integral part of strengthening a country’s resilience to droughts. However, for DMEWS to be useful for stakeholders, the indicators they monitor should be translatable to potential drought impacts on the ground and, ideally, inform mitigating actions. Here, we analyse these drought indicator-to-impact relationships in Thailand, using a novel combination of correlation analysis and random forest modelling. In the correlation analysis, we study the link between meteorological drought indicators and high-resolution remote sensing vegetation indices used as proxies for general crop health and forest growth. Our analysis shows that these links vary greatly depending on land use (cropland vs. forest), season (wet vs. dry) and region (north vs. south). The random forest models built to estimate regional crop productivity provided a more in-depth analysis of the crop- and region-specific value of different drought indicators. The results highlighted seasonal patterns of drought vulnerability for individual crops, usually linked to their growing season, although the effect was somewhat masked in irrigated regions (North). This new high-resolution knowledge of crop- and region-specific indicator-to-impact links can be used as the basis of targeted mitigation actions in an improved DMEWS in Thailand. In addition, the framework developed here can be applied elsewhere in the Southeast Asia region, as well as other drought-vulnerable areas internationally, in particular those that are data sparse.  

How to cite: Tanguy, M., Barker, L., Eastman, M., Ekkawatpanit, C., Goodwin, D., Hannaford, J., Holman, I., Magee, E., Pardthaisong, L., Parry, S., Rey, D., and Visessri, S.: Understanding drought indicator-to-impact relationships to improve drought monitoring and early warning: Thailand as a case study , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13769,, 2023.