Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/7637
Title: Landslide disaster Risks Management in Murang’a County, Kenya: Scientific and Indigenous knowledge Nexus
Authors: Maina Njiraini, John
Keywords: Landslide
Disaster
Risks Management
Indigenous Knowledge Nexus
Murang’a County
Issue Date: 2023
Publisher: Moi University
Abstract: Murang‘a County has recently experienced serious, deadly and recurrent landslides but not much research has been done about the disasters. The integration of scientific and indigenous knowledge is rare study option despite the indigenous people being among the key players in disaster management cycle. The general objective of the study is seeking an understanding of landslide disaster risks through scientific and indigenous knowledge. The specific objectives are mapping and delineating landslide disaster risk zones based on the two levels of knowledge, assessing their nexus, comparing the risk zones with landslide inventories, assessing landslides effects and finally studying the prevailing Early Warning Systems (EWS) in both contexts. The study is anchored on the Systems Theory and the Concept of Integration. The study adopted mixed methods sequential explanatory research design. Primary data were collected through proportionate household questionnaires administered to a total of 336 household heads who were selected through systematic random sampling from nine purposively selected study locations spread across six sub-counties. Complementing the questionnaires‘ data were eight Key Informants Interviews (KIIs) and six Focus Group Discussions (FGDs) for participants who were purposively and randomly selected respectively. Quantitative data were analyzed using IBM-SPSS package for descriptive statistics through percentages and frequencies and further inferential statistics analyzed through correlation analysis. Primary qualitative data obtained through KIIs and FGDs were analyzed through content analysis. Secondary data obtained from remote sensing were quantitatively analyzed in ArcGIS software through overlay analysis of the GRID factors in Simple Linear and Weighted-Linear Combination (WLC) in Multi-Criteria Evaluation (MCE). The study showed that a significant number of respondents (r=0.862) reported to have experienced a landslide at least once in their lifetime. Also, a significant number (r=0.806) described rainfall and slope/gradient as major landslide causal/trigger factors. The research further established that there existed nexus between scientific and indigenous knowledge due to convergence in the considered ‗most influential and prominent‘ landslide causal/trigger factors identified as rainfall, elevation, slope, soils and land-use land-cover; landslide disaster risk zones which mapped the northern parts of the county, towards the Aberdares Ranges, as being the ‗high landslide risks areas‘ while the southern parts as being the ‗low landslide risk areas‘ zones; conformity of the landslide zones with the March-April-May (MAM) 2018 landslide inventories; regarding the Early Warnings Systems (EWS), some of the locally upheld systems mentioned by the indigenous people over the years had basis in science. The research is key in advancing the knowledge in the following ways: better understanding of the spatial distribution of landslide risk zones in Murang‘a County, the linkage and possible integration of the contemporary and indigenous methods in landslide management, the effects of landslides and landslide disasters‘ EWS. In conclusion, both scientific and indigenous knowledge of landslide disasters should be mainstreamed in an inclusive landslide disaster risk management. Landslides being highly localized, the study recommends further localized research targeting only the households affected by the disasters to gain closer understanding according to their knowledge and experiences.
URI: http://ir.mu.ac.ke:8080/jspui/handle/123456789/7637
Appears in Collections:School of Arts and Social Sciences

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