Tropical drought risk: estimates combining gridded vulnerability and hazard data

Droughts are causing severe damages to water abundant tropical countries worldwide. Their resilience to water shortages tends to be low, often due to a lack of water infrastructure. Moreover, drought characteristics and risk in tropical catchments are poorly understood, which makes it difficult to select adequate adaptation measures. Thus, reliable methodologies to evaluate spatially distributed drought risk in data scarce tropical catchments are urgently needed. We combined drought hazard and vulnerability related information to assess drought risk in four rural tropical study regions, the Muriaé, subcatchment of the Paraíba do Sul in Southeast Brazil, the Tempisque-Bebedero in North Costa Rica, the upper part of the Magdalena basin, Colombia and the Srepok, a Mekong tributary shared by Cambodia and Vietnam. Drought hazard was defined based on three variables, daily river discharge and precipitation and vegetation condition. Conditions below defined thresholds were transformed into a cumulative drought index. To assess vulnerability, we reclassified and weighted globally and regionally available gridded socioeconomic data to represent the potential of a drought to cause damages in selected socioeconomic sectors of rural tropical regions. Besides illustrating the relative severity of each indicator value, we developed drought risk maps combining hazard and vulnerability severity for each grid cell. While for the Muriaé our results clearly identified the downstream area as being exposed to severe drought risk, the Tempisque showed highest risk along the major streams and related irrigation systems. Risk hotspots in the Upper Magdalena were found in the central valley and the dryer Southeast and in the Srepok in the agricultural areas of Vietnam and downstream in Cambodia. Plausibility of results was confirmed by local scientists and stakeholders, who evaluated the results for each indicator and risk hotspot. The presented risk assessment methodology for data scarce and rural tropical areas offers a holistic, science based and innovative solution to provide relevant drought related information. Being applied to individual catchments, the findings described in this article will enable the selection of data sets, indices and their classification - depending on basin size, spatial resolution and seasonality. At its current stage, the outcomes of this study provide relevant information for regional planners and water managers dealing with the control of future drought disasters in tropical regions.