Droughts and changing rainfall patterns due to natural climate variability and climate change, threaten the livelihoods of Malawi's smallholder farmers, who constitute 80% of the population. Provision of seasonal climate forecasts (SCFs) is one means to potentially increase the resilience of rainfed farming to drought by informing farmers in their agricultural decisions. Local knowledge can play an important role in improving the value of SCFs, by making the forecast better-suited to the local environment and decision-making. This study explores whether the contextual relevance of the information provided in SCFs can be improved through the integration of farmers’ local knowledge in three districts in central and southern Malawi. A forecast threshold model is established that uses meteorological indicators before the rainy season as predictors of dry conditions during that season. Local knowledge informs our selection of the meteorological indicators as potential predictors. Verification of forecasts made with this model shows that meteorological indicators based on local knowledge have a predictive value for forecasting dry conditions in the rainy season. The forecast skill differs per location, with increased skill in the Southern Highlands climate zone. In addition, the local knowledge indicators show increased predictive value in forecasting locally relevant dry conditions, in comparison to the currently-used El Niño-Southern Oscillation (ENSO) indicators. We argue that the inclusion of local knowledge in the current drought information system of Malawi may improve the SCFs for farmers. We show that it is possible to capture local knowledge using observed station and climate reanalysis data. Our approach could benefit National Meteorological and Hydrological Services in the development of relevant climate services and support drought-risk reduction by humanitarian actors.

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Most people of Malawi are dependent on rainfed agriculture for their livelihoods. This leaves them vulnerable to drought and changing rainfall patterns due to climate change. Over time, farmers have adopted local strategies and knowledge that help reducing the overall vulnerability to climate variability shocks. One other option to increase the resilience of rainfed farmers to drought, is providing forecast information on the upcoming rainfall season. Forecast information has the potential to inform farmers in their decisions surrounding agricultural strategies. However, significant challenges remain in the provision of forecast information. Often, the forecast information is not tailored to farmers, resulting in limited uptake of forecast information into their agricultural decision-making. Therefore, this study explores whether drought forecast information can be linked to existing farmers strategies and local knowledge on predicting future rainfall patterns. During a period of three months in Malawi, participatory research approaches are used to create an understanding of what requirements drought forecast information should meet to effectively inform farmers in their decision-making. Consequently, a sequential threshold model was established that relates annually monitored meteorological indicators before the rainy season, to the occurrence of dry conditions during the season. Dry conditions were expressed in the drought indicators that farmers require for their agricultural decision-making. Additionally, using interviews among stakeholders and a visualisation of the current information flow, further insights on the current drought information system were developed. Although farmers have their own strategies and timing of decision-making, this research has generalized some of the opinions and strategies to develop the ‘requirements’ which a contextualized forecast should meet. In August farmers require a prediction of the onset of the rainy season, typically starting mid-November. In addition, an update on the timing of the onset of rains is required in beginning of November. An overall indication of the ‘dryness’ of the rainy season is required in September. Here, ‘dryness’ is characterized by the number of dry spells, a composite ‘drought index’ of associated rainfall variables by the farmers. The forecast should be on a scale that is locally relevant (EPA level). This research consequently established a forecasting model, based on meteorological variables from local knowledge which can complement the forecast variables from the DCCMS. The results of forecast verification show that meteorological indicators based on local knowledge have a predictive value for forecasting drought indicators. Subsequently, skill analysis of forecasting incorporating all the above dimensions shows that the accuracy of the forecast differs per location with an increased skill to the Southern locations. In addition, it is also location dependent whether the contribution of wind, temperature or ENSO indicators gives the most predictive value. The results show that a combination of all indicators have the best predictive value. In addition, the results show that local knowledge indicators have an increased predictive value in forecasting the locally relevant critical events in comparison to the currently used ENSO-related indicators by the DCCMS. Additional research is needed to further analyse certain aspects of this research, such as research on the robustness of the model used. Research on the risk farmers are willing to take in their respective decisions could act as another requirement the forecast skill should meet. This highlights the importance of having continuous feedback from the farmers, since farmers may experience adverse impacts from wrongly informed decisions. Despite these limitations, it is argued that the inclusion of local knowledge in the current drought information system of Malawi may improve the provision of forecast information for farmers and shows that it is possible to capture local knowledge in a technical approach. The findings have relevant implications for other stakeholders, such as humanitarian and meteorological organisations, that are implementing drought-risk reduction approaches and climate services.

This study investigates the many dynamics of the Manyame Catchment and comes up with recommendations on how to adapt or become more resilient to the risks at hand. The bad politics and forthcoming economic situation of Zimbabwe has led to instability and dramatic inflation over the last decade. This has resulted in a terrible investment climate, limited aid received from foreign countries and an outflow of educated population. Exploitation of water resources by industries, mines and urban centres located close to the rivers resulted in a decline in the quality and quantity of the environment. Especially the Manyame River Catchment, that supplies the capital Harare and flows north into the Zambezi, has been greatly affected. The catchment suffers from several pollution sources such as agriculture, mining, industrial dumps and wastewater inflow. Poor management and the deterioration of the drinking water supply and sanitation infrastructure has led to the recent outbreak of cholera. Although the Manyame Catchment has enough water, another main issue is the spatial distribution of its water resources. In some areas there are dams, but no farmers to utilize the water. In other areas farmers are desperate for water, but don’t receive any. The increasing dry spells due to climatic changes, has had disastrous effects for the non-irrigating smallholder farmers dependent on their maize production for survival, while floods created by the backwater curve from the Cahora Bassa Dam in the Lower Manyame sub-catchment have washed away the livestock, crops and infrastructure on the fertile areas in the flood plains. The situation stresses for better awareness, monitoring and guardance of the water resources. This will provide information for improvements in the planning, policy and management of water resources. Although the history of Zimbabwean governance would suggest it is purely acting on crisis management, proactive planning would be preferable to the alternative; to wait for the aquifers to dry up only for people to realize the real value of water.