A science-policy assessment of the effect of severe droughts in Syria: A quasi-Bayesian analysis.

The management of prolonged droughts as an extreme event with low probability in Syria is challenging and different from developed countries. Syria is particularly vulnerable to severe drought events due to its complicated characteristics including water scarcity, geographical location, population size, and continuing war conditions. These facts emphasize the urgency to act before a drought occurs. The study of the available literature about this topic showed the imperfect characteristics of the relevant knowledge and information. They are heterogeneous, scarce, and uncertainty-laden. This situation is challenging and unreliable for policymakers to act and quantify drought risk mainly when uncertainty arises from different sources and cannot be decreased. Thus, a systematic and causal approach that uses a Quasi-Bayesian probabilistic method is proposed to provide drought risk assessment that can be sufficient for managing severed drought in the conditions that are prevalent for Syria. This approach is a decision-theoretic, not data-driven (i.e., experimental). The Factor Trees Model, FTM, is created based on the drought distinguishing features and its linkages to people’s lives in Syria. Three primary factors are suggested: the recurrence of drought events, area characteristics, and human behavior. Then, the Quasi-Bayesian Method is used in performing a simple analysis to assess the quality and reliability of two reports based on the FTM factors. Using our approach helps to categorize each report and compare reports, and update the flow of information adaptively to new scientific evidence. Although this approach has advantages and limitations, it is a valuable tool in situations of vague, unreliable, and limited information and knowledge. The need for further research is essential to evolve this approach due to the complexity of the Syrian context because the method should decrease the uncertainty in each stream of knowledge to better inform policymakers.