The success of anticipatory action (AA) in climate change related disaster risk reduction depends largely on the ability to accurately predict adverse weather events and to subsequently take appropriate and timely action. The current seasonal climate forecasts obtained through national and global forecasting centers such as the Zimbabwe Meteorological Services Department (MSD) and the European Center for Medium-Range Weather Forecasts (ECMWF) have been found to have several limitations including limited skill in intra-seasonal variability which is vital in most processes, lack of accessibility, difficult interpretability and applicability to local communities. As a result, calls for the integration of Indigenous Knowledge Systems (IKS)-based climate services in seasonal climate forecasting to bolster the efficacy and accuracy of forecasts are increasing.
The study employed a mixed methods approach combining a survey of 200 household heads, document reviews and key informant interviews with IKS specialists, AA community of practice members and disaster risk reduction specialists.
This article presents the findings of a study carried out in four semi-arid districts of Zimbabwe (Mbire, Matobo, Binga, and Mudzi) to assess the feasibility of integrating IKS into the drought AA mechanism at national, district, and ward level. We find that 82% of the surveyed households used indigenous knowledge systems for seasonal climate forecasting and extreme weather forecasting combined with scientific forecasts. Respondents demonstrated preference for triangulated forecasting to increase reliability. Both the meteorological approaches to seasonal climate forecasting and the IKS based forecasting had different strengths and weaknesses.
Based on the found gaps in current seasonal forecasting techniques, local applicability, and limited quantitative analysis in IKS, this study provides a guideline on how scientific and IKS forecasting can be triangulated for leveraging forecasting information in Zimbabwe. The use of IKS may be of utmost relevance to agencies and entities seeking the achievement of drought risk reduction through AA programmes.