Integrating indigenous knowledge with scientific seasonal forecasts for climate risk management in Lushoto district in Tanzania

Type Working Paper
Title Integrating indigenous knowledge with scientific seasonal forecasts for climate risk management in Lushoto district in Tanzania
Author(s)
Publication (Day/Month/Year) 2015
URL https://cgspace.cgiar.org/bitstream/handle/10568/56996/Working Paper 103.pdf?sequence=1&isAllowed=y
Abstract
Improving food security needs appropriate climate related risk management strategies. These
include using climate information to guide farm level decision-making. Progress has been made
in providing climate services in Tanzania but there are significant gaps with regard to downscaled
location specific forecasts, as well as generating timely, reliable and user friendly information.
Majority of the farmers have been using indigenous knowledge (IK) forecasts to predict weather
through observing the behavior of large animals, birds, plants, insects, and the solar system. IK is
not often documented and is mainly sustained from one generation to another through oral history
and local expertise, creating a wide inter-generational gap between its custodians and the young
people. This study identifies and documents existing IK in weather forecasting in Lushoto
district, northern Tanzania, and aims at promoting the integration of IK and scientific weather
forecasting for climate risk management. Historical rainfall data was used in combination with
data collected through household surveys, focus group discussions and key informant interviews.
Majority of the farmers (56%) indicated that weather forecasts using IK were more reliable and
specific to their location compared to scientific forecasts. Comparison was made of the seasonal
March-April-May (MAM) forecasts in 2012 from IK and Tanzania Meteorological Agency
(TMA), with both approaches predicting a normal rainy season. The IK forecasts were, however,
more reliable in the long rainy MAM season compared to the short rainy October-NovemberDecember
season. To improve accuracy, systematic documentation of IK and establishment of a
framework for integrating IK and TMA weather forecasting is needed. There is also a need to
establish an information dissemination network and entrench weather forecasting within the
District Agricultural Development Programmes.

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