The use of indigenous knowledge systems for short and long range rainfall prediction and farmers’ perceptions of science-based seasonal forecasts in Zimbabwe

Abstract

Purpose This paper aims to document indigenous knowledge systems (IKS) used for short- and long-range rainfall prediction by small holder farmers in three communities of Guruve District, in north-eastern Zimbabwe. The study also investigated farmers’ perceptions of contemporary forecasts and the reliability of both IKS and contemporary forecasts. Design/methodology/approach Data were collected among small holder farmers in Guruve District using household interviews and focus group discussions in three wards in the district, grouped according to their agro-climate into high and low rainfall areas. To get an expert view of the issues, key informant interviews were held with key agricultural extension personnel and traditional leaders. Findings Results obtained showed show high dependence on IKS-based forecasts in the district. Over 80 per cent of the farmers used at least one form of IKS for short- and long-range forecasting, as they are easily understood and applicable to their local situations. Tree phenology, migration and behaviour of some bird species and insects, and observation of atmospheric phenomena were the common indicators used. Tree phenology was the most common with over 80 per cent of farmers using this indicator. While some respondents (60 per cent) viewed forecasts derived from IKS as more reliable than science-based forecasts, 69 per cent preferred an integration of the two methods. Originality/value The simplicity and location specificity of IKS-based forecasts makes them potentially useful to smallholder farmers, climate scientists and policymakers in tracking change in these areas for more effective climate change response strategies and policymaking.

Local Ecological Knowledge on Climate Change and Ecosystem-Based Adaptation Strategies Promote Resilience in the Middle Zambezi Biosphere Reserve, Zimbabwe

“…Farmers' perceptions of climate change in the study area are in line with empirical data and other studies on farmers perceptions inhabiting marginal areas in Zimbabwe [ 23 , 41 , 42 ]. Findings are also similar to other studies in Zimbabwe such as Guruve District where Gwenzi et al [ 43 ] and Hwedza and Makoni [ 44 ] have reported unpredictable rainfall, declining rainfall, and increasing temperatures as some of the indicators of climate change. Local ecological knowledge on climate patterns and impacts has been documented in other studies in different parts of Africa [ 45 – 48 ].…”

Best of both worlds : Co-producing climate services that integrate scientific and indigenous weather and seasonal climate forecast for water management and food production in Ghana

“…This limits the acceptability and use of forecast information (Cash et al,2003;Okello et al, 2012;Karpouzoglou et al, 2016). Consequently, local farmers across Africa highly depend on indigenous forecasts for most farm decision making, including in Ghana (Gyampoh et al, 2009;Nyantakyi-Frimpong, 2013), Zimbabwe (Gwenzi et al, 2016), Burkina Faso (Roncoli et al, 2002) and South Africa (Zuma-Netshiukhwi et al, 2013).…”

“…The survey revealed that adaptive farm decisions of farmers are generally based on information generated from indigenous and scientific forecasts. While farmers were quick to acknowledge the limitations in their personal forecast they, however, considered it better for decision making than the scientific forecast provided by Ghana Meteorological Agency as this was perceived to be generic and not locally specific to their community and needs (See also Gwenzi et al, 2016;Zuma-Netshiukhwi et al, 2013). Information systems within the study area were identified to provide scientific forecast information whereas indigenous forecasts were tied to farmers' observation matched with experience.…”

“…(2002), and Zuma-Netshiukhwi et al (2013) observed that farmers highly matched with long time experiences. Also,Gwenzi et al (2016),Roncoli et for their farm decision making. These forecasts are based on observation Results show that almost half of the farmers rely on their indigenous forecast particular time period for adaptive decision making.…”

Towards a new generation of climate information systems : information systems and actionable knowledge creation for adaptive decision-making in rice farming systems in Ghana

“…The survey revealed that adaptive farm decisions of farmers are generally based on information generated from indigenous and scientific forecasts. While farmers were quick to acknowledge the limitations in their personal forecast they however considered it better for decision making than the scientific forecast provided by Ghana Meteorological Agency as this was perceived to be generic and not locally specific to their community and needs (see also Gwenzi, Mashonjowa, Mafongoya, Rwasoka, & Stigter, 2016;Zuma-Netshiukhwi, Stigter, & Walker, 2013). Information systems within the study area were identified to provide scientific forecast information whereas indigenous forecasts were tied to farmers observation matched with experience.…”