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TOCO_DR: Theory of change observatory on disaster resilience


Humanitarian disasters such as droughts expose approximately 10 million people in Sub-Saharan Africa to food, water and energy insecurity. Besides the humanitarian consequences disasters such as floods also heighten investment risks due to creation of "stranded assets" such as wastewater treatment plants in developing countries. Global climate models can be used to identify the geographical distribution of disaster risk but without being able to specify the regional intensity, frequency and duration of events. In Sub-Saharan Africa the difference between what models forecast and the reality of dryness has come to be known as the "East Africa Climate paradox". Because of model inconsistency, it is difficult for investors and decision makers to be forewarned about impending events and to respond when they occur. Two recent policy trends have however converged to enhance the potential for Cyber-enabled Effective Disaster Response: (a) the expansion of Regional Early Warning Systems (REWS) and (b) a growing demand for open data platforms to enhance accountability of decision-making processes. For instance, the Africa Data Consensus (ADC) resolved to emphasize the role of open data networks to support coherent decision-making through better organization of data and models. From a scientific standpoint Agent Based Modelling has also begun to advocate more forcefully for engagement of stakeholders to develop and calibrate models. In this regard, our prior research to pilot-test the Wastewater Reuse Effectiveness Index (WREI) for Sustainable Development Goal 6.3 revealed the potential of down-scaled models to advance circular economy pathways, such as wastewater recycling with potential to mitigate disaster risk. The overall aim of the Theory of change Observatory project will therefore be to enhance regional capacity to develop, pilot-test and validate regional climate models that enables the prediction, assessment and response to effects of droughts and flood risk by: (Obj 1) Developing a place-based observatory based on principles of dispersed data handling and reuse (Work Package (WP) 1,4); (Obj 2) Co-curating and co-designing regional research that focuses on down-scaling and coupling robust models of disaster risk monitoring(WP2,3); and (Obj 3) Pilot-testing and validating composite indices as a means of knowledge translation with the objective of building a theory of change on disaster resilience (WP5). (AU)

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