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dc.contributor.authorMahoo, H.F.en_US
dc.contributor.authorMbungu Wen_US
dc.contributor.authorYonah Ien_US
dc.contributor.authorRadeny, Maren A.O.en_US
dc.contributor.authorKimeli, Philipen_US
dc.contributor.authorKinyangi, Jamesen_US
dc.date.accessioned2015-03-09T14:22:36Zen_US
dc.date.available2015-03-09T14:22:36Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/56996en_US
dc.titleIntegrating Indigenous Knowledge with Scientific Seasonal Forecasts for Climate Risk Management in Lushoto District in Tanzaniaen_US
cg.identifier.ccafsprojectEA_CSVen_US
cg.identifier.ccafsprojectFP2_GFCSen_US
dcterms.abstractImproving 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-November- December 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.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.bibliographicCitationMahoo H, Mbungu W, Yonah I, Recha J, Radeny M, Kimeli P, Kinyangi J. 2015. Integrating Indigenous Knowledge with Scientific Seasonal Forecasts for Climate Risk Management in Lushoto District in Tanzania. CCAFS Working Paper no. 103. Copenhagen, Denmark: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).en_US
dcterms.isPartOfCCAFS Working Paperen_US
dcterms.issued2015-03-09en_US
dcterms.languageenen_US
dcterms.subjectagricultureen_US
dcterms.subjectfood securityen_US
dcterms.subjectforecastingen_US
dcterms.subjectclimate changeen_US
dcterms.subjectrisk managementen_US
dcterms.typeWorking Paperen_US
cg.subject.ccafsCLIMATE SERVICES AND SAFETY NETSen_US
cg.coverage.regionAfricaen_US
cg.coverage.regionEastern Africaen_US
cg.coverage.countryTanzaniaen_US
cg.contributor.crpClimate Change, Agriculture and Food Securityen_US
cg.coverage.iso3166-alpha2TZen_US
cg.creator.identifierMaren Radeny: 0000-0001-6470-8372en_US
cg.number103en_US


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