Utilization of Indigenous Knowledge (IK) Indicators in Weather Forecasting and Livelihood Planning in Coastal Regions of Tanzania

Community members at village level depend on weather information to plan and make decision on livelihood options. The livelihood options and well-being of rural smallholder farmers, pastoralists and fishers in Tanzania are facing ever increasing extreme weather events especially prolonged droughts, temperature rise and floods. This paper investigates traditional indicators which are useful for planning and decision making among farmers, pastoralists and fishers of Lushoto and Pangani in Tanga Region as well as Bagamoyo and Chalinze in Coast Region. Descriptive research method was employed to investigate how traditional indicators are useful for planning during long term (seasonal) and decision making during short term forecasting. Primary data were collected from Indigenous Knowledge (IK) teams, community members and leaders of Local Government Authority. Secondary data were obtained from different sources such as Gray literature, published journals, National Library, District Offices and Regional Officers were the highly consulted sources. Focus Group Discussion, Field Observation, transect walks and Key Informant interviews were the applied methods to systematically document behaviour of local indicators from one month to the next. During Focus Group in each District, elderly farmers, pastoralists and fishers were the sources of primary data. They shared experience on local indicators which they have been observing before the start of the season for the period of 30 years ago. Observation was conducted by IK teams who reported the indicators’ behaviour and seasonal events every after 14 days. Quantitative data were coded to Statistical Package for the Social Sciences version 20 (SPSS 20) tool and analysed using descriptive statistics to show the frequencies of rainfall, showers and drought events which were recorded during IK meetings and those from TMA. Thematic data analysis method integrated hermeneutics approach in analysing data from IK meeting minutes, FGD and KII. Long term forecast indicators successfully informed us on the procedures that lead into determining seasons for either good or poor distribution of rainfall in the next season. Short term traditional indicators were useful for decision making within a season. As long as seasons behave differently from one year to the next, the authors recommend observing indicators for several years and determine how indicators behave when the scientific seasonal outlooks are below normal, normal or above normal.

Authors

Publication Details

Journal
American Journal of Climate Change
Published
2025-01-01
DOI
https://doi.org/10.4236/ajcc.2025.142020
Primary Topic
Coastal and Marine Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Utilization of Indigenous Knowledge (IK) Indicators in Weather Forecasting and Livelihood Planning in Coastal Regions of Tanzania

H. F. Mahoo, Isack Baliyendeza Yonah, Sixbert Simon Mwanga, Mkombozi Joannes Mbekenga
American Journal of Climate Change
Coastal and Marine Management
article

Utilization of Indigenous Knowledge (IK) Indicators in Weather Forecasting and Livelihood Planning in Coastal Regions of Tanzania

H. F. Mahoo, Isack Baliyendeza Yonah, Sixbert Simon Mwanga, Mkombozi Joannes Mbekenga
article en

Abstract

Community members at village level depend on weather information to plan and make decision on livelihood options. The livelihood options and well-being of rural smallholder farmers, pastoralists and fishers in Tanzania are facing ever increasing extreme weather events especially prolonged droughts, temperature rise and floods. This paper investigates traditional indicators which are useful for planning and decision making among farmers, pastoralists and fishers of Lushoto and Pangani in Tanga Region as well as Bagamoyo and Chalinze in Coast Region. Descriptive research method was employed to investigate how traditional indicators are useful for planning during long term (seasonal) and decision making during short term forecasting. Primary data were collected from Indigenous Knowledge (IK) teams, community members and leaders of Local Government Authority. Secondary data were obtained from different sources such as Gray literature, published journals, National Library, District Offices and Regional Officers were the highly consulted sources. Focus Group Discussion, Field Observation, transect walks and Key Informant interviews were the applied methods to systematically document behaviour of local indicators from one month to the next. During Focus Group in each District, elderly farmers, pastoralists and fishers were the sources of primary data. They shared experience on local indicators which they have been observing before the start of the season for the period of 30 years ago. Observation was conducted by IK teams who reported the indicators’ behaviour and seasonal events every after 14 days. Quantitative data were coded to Statistical Package for the Social Sciences version 20 (SPSS 20) tool and analysed using descriptive statistics to show the frequencies of rainfall, showers and drought events which were recorded during IK meetings and those from TMA. Thematic data analysis method integrated hermeneutics approach in analysing data from IK meeting minutes, FGD and KII. Long term forecast indicators successfully informed us on the procedures that lead into determining seasons for either good or poor distribution of rainfall in the next season. Short term traditional indicators were useful for decision making within a season. As long as seasons behave differently from one year to the next, the authors recommend observing indicators for several years and determine how indicators behave when the scientific seasonal outlooks are below normal, normal or above normal.

American Journal of Climate ChangeVol. 14(02)
Climate action
Openalex Percentile: Top 80%
Coastal and Marine Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.