Abstract/Summary

This paper explores the traditional indicators that small-scale farmers in Gaza province in southern Mozambique use to predict drought events on their rain-fed farms. It analyzes the contextual situation regarding the accuracy and reliability of the traditional prediction methods under the current weather and conditions of climate uncertainty and variability, and the opportunities that their prediction methods can bring to reduce their current and future exposure and vulnerabilities to drought. Farmers use a total of 11 traditional environmental indicators to predict drought, either individually or combined, as required to increase their prediction certainty. However, the farmers perceive that current unpredictability, variability, and changes in weather and climate have negatively affected the interpretation, accuracy, and reliability of most of their prediction indicators, and thus their farming activities and their ability to predict and respond to drought. This, associated with the reduced number of elders in the community, is causing a decline in the diversity, and complexity of interpretation of indicators. Nonetheless, these difficulties have not impeded farmers from continuing to use their preferred prediction methods, as on some occasions they continue to be useful for their farming-related decisions and are also the main, or sometimes only, source of forecast. Considering the role these methods play in farmers’ activities, and the limited access to meteorological forecasts in most rural areas of Mozambique, and the fact that the weather and climate is expected to continually change, this paper concludes that it is important to enhance the use of traditional prediction methods. However, the increase of the accuracy and reliability, and continued existence of the methods depends on the farmers’ own abilities to enhance, preserve, and validate them by tailoring the traditional methods used to work with the new environmental, weather, and climatic conditions, or through the development of new methods.