Use of Indigenous Knowledge Systems and Scientific Methods for Climate Forecasting in Southern Zambia and North Western Zimbabwe.

ITIKI: bridge between African indigenous knowledge and modern science of drought prediction

“…The second challenge of weather forecasting emanates from very poor utilisation of the Seasonal Climate Forecasts (SCFs) by the very farmers that grow the food for the masses. The content, format and dissemination channels used do not address the farmers' needs; the farmers have in turn continued to rely on their indigenous knowledge forecasts (IKFs) to derive critical cropping decisions (Mugabe, Mubaya, Nanja et al 2010;Ziervogel, Bithell et al 2005). Though being very rich and relevant to the farmers' context, there is evidence that IKFs are an endangered species in dire need of conservation and revamping (Roncoli 2006;Orlove, Carla et al 2009).…”

“…However, the utilisation of this information by the small-scale farmers whose crops/livestock depend solely on rainfall is still below par (Ziervogel, Calder 2003;and Ziervogel, Bithell et al 2005). Studies (Luseno, McPeak et al 2003;and Mugabe, Mubaya, Nanja et al 2010) reveal that over 80% of farmers in some parts of Ethiopia, Kenya, Zambia and Zimbabwe relied on IKFs. However, IKFs are currently facing challenges from various quarters especially from climate change, urbanisation and population growth.…”

“…Examples of indigenous knowledge on weather/climate include: observing clouds and stars/sun/moon; watching the behaviour of livestock, wildlife or local flora; reading the intestines of slaughtered animals and interpreting dreams or the patterns in which pairs of shoes fall when repeatedly thrown (Luseno, McPeak et al 2003;Roncoli 2006;Mugabe, Mubaya, Nanja et al 2010). Despite this categorisation, interpretation of IK is based on extremely site-specific patterns (Hammer, Hansen et al 2001).…”

“…The integration of General Circulation Models (GCMs), usually with sea surface temperature (SST) forcing, typically over a period of 50 or more days; (3) multivariate Empirical Approaches -the ability to predict seasonal rainfall totals several months in advance is due to the exchanges of energy between the oceans and the atmosphere, which includes the weather systems that produce rainfall. In practice, quantification of the interaction between the ocean and atmosphere in empirical studies typical of those which lead to forecasting schemes is assumed to be represented by sea surface temperature anomalies (SSTAs) alone and (4) numerical and Statistical Approaches Researchers (Mercer, Kelman et al 2010;Mugabe, Mubaya, Nanja et al 2010;Ziervogel, Opere 2010) today concur that indigenous knowledge and modern science complement each other. In Dondeyne, Emanuel et al (2003), for example, bridging local farmers' and scientists knowledge through participatory research led to more appropriate technologies.…”

“…First, the accumulated knowledge has always worked for the locals (Aparna, Trivedi 2011); the debate here can only be on the level of success. On the other hand, the western approaches to weather prediction are hardly utilised by the mostly illiterate farmers most of whom live in the remote villages where modern technologies such as televisions and internet are still a foreign concept (Luseno, McPeak et al 2003;Grasso 2007;Mugabe, Mubaya, Nanja et al 2010;Masinde, Bagula et al 2012b). Secondly, implementing modern drought prediction technologies is still a costly affair for most African countries whose priority list is filled with items such as ‗providing basic education', ‗implementing democratic constitution', ‗peace initiatives', ‗providing basic healthcare', and so on.…”