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The regions of east Africa are facing unprecedented drought impacts at present and it is expected to intensify with climate change. Impact based forecast can give critical information for disaster preparedness, adaptation, and anticipatory action thereby increasing communities’ resilience. Probabilistic forecasts with uncertainty metrics have in the past provided early warning information for early actions. However, the complexity of drought as a disaster, encompassing and effecting wide range of socio-economic activities with interlinked compounding and cascading effect often makes drought impact forecasting bound to be less effective and robust (Boult et al. 2022). Moreover, drought impacts which are subjected to the influence of other high-impact weather related events, increases the difficulty to ascertain the extent of the impact. Therefore, drought impact forecasting should be viewed as a dynamic process that involves multi-stakeholders to realize its full potential of triggering early action (de Brito 2021). In such a scenario, the availability of an open, and widely accessible information portal can be effective in ensuring early waning information is disseminated widely across all stakeholders to trigger timely action. This study demonstrates an automatic impact-based drought forecast system to be integrated with existing East Africa Drought Watch (EADW) web portal. For the last two-to-three years, EADW has proven to be single window portal for major hazard related information dissemination for disaster early warning and action. The proposed automatic impact-based drought forecast system is based on TMAST ALERT probabilistic soil moisture and Water Requirement Satisfaction Index (WRSI) forecast using their data Application Programming Interface (API). TAMSAT ALERT is region specific validated, calibrated data source and its effectiveness assessed in impact-based forecast for the region (Boult et al. 2020, Busker et. al 2022). CLIMADA, an open-source software for climate risk assessment was used for integrating the soil moisture hazard data with exposure, and vulnerability to forecast socio-economic impact of drought. The current version of the system, directed for agriculture drought IBF, uses Spatially-Disaggregated Crop Production Statistics Data in Africa and WRSI maize crop unimodal relationship as impact function. The probabilistic forecast of WRSI is used to generate the Impact Based Forecasting (IBF), impact versus probability matrix for region specific map generation. Finally, implications for early warning and early action on agricultural practices in the Eastern Africa region are discussed. 1. Boult, Victoria L., et al. "Towards drought impact-based forecasting in a multi-hazard context." Climate Risk Management 35 (2022): 100402. 2. de Brito, Mariana Madruga. "Compound and cascading drought impacts do not happen by chance: A proposal to quantify their relationships." Science of the Total Environment 778 (2021): 146236. 3. Boult, Victoria L., et al. "Evaluation and validation of TAMSAT‐ALERT soil moisture and WRSI for use in drought anticipatory action." Meteorological Applications 27.5 (2020): e1959. 4. Busker, T., de Moel, H., van den Hurk, B., Asfaw, D., Boult, V., and Aerts, J.: Impact-based drought forecasting for agro-pastoralists in the Horn of Africa drylands, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-255, https://doi.org/10.5194/iahs2022-255, 2022. |
