Journal of
Geography and Regional Planning

  • Abbreviation: J. Geogr. Reg. Plann.
  • Language: English
  • ISSN: 2070-1845
  • DOI: 10.5897/JGRP
  • Start Year: 2008
  • Published Articles: 386

Full Length Research Paper

Indigenous knowledge in seasonal rainfall prediction in Tanzania: A case of the South-western Highland of Tanzania

  Ladislaus B. Chang’a1,2*, Pius Z. Yanda2 and James Ngana2  
  1Tanzania Meteorological Agency, Dar es Salaam, Tanzania. 2Institute of Resource Assessment, University of Dar es Salaam, Tanzania.
Email: [email protected], [email protected]

  •  Accepted: 01 March 2010
  •  Published: 07 April 2013

Abstract

 

This paper describes how farmers in the South-Western Highland of Tanzania predict rainfall using local environmental indicators and astronomical factors. The perceptions of the local communities on conventional weather and climate forecasts were also assessed. The study was conducted in Rungwe and Kilolo districts in Mbeya and Iringa regions respectively. Participatory rural appraisal methods, key informant interviews and focus group discussions were used in data collection and the collected data was analyzed using statistical package for social science. It has been found that plant phenology is widely used by local communities in both districts in seasonal rainfall forecasting. Early and significant flowering of Mihemi (Erythrina abyssinica) and Mikwe (Brachystegiaspeciformis) trees from July to November has been identified to be one of the signals of good rainfall season. The behaviour of Dudumizi bird has been singled out as one of the best indicator for rainfall. Both Indigenous Knowledge specialists and TMA experts have predicted 2009/2010 rainfall season to feature normal to above normal rainfall. Systematic documentation and subsequent integration of Indigenous Knowledge into conventional weather forecasting system is recommended as one of the strategy that could help to improve the accuracy of seasonal rainfall forecasts under a changing climate.

 

Key words: Climate variability, seasonal forecasting, El Nino, Dudumizi, indigenous knowledge.