USE OF TRADITIONAL KNOWLEDGE TO FORECAST FLOOD:EVIDENCE FROM RIVERINE FLOODPLAIN IN BANGLADESH
USE OF TRADITIONAL KNOWLEDGE TO FORECAST FLOOD:EVIDENCE FROM RIVERINE FLOODPLAIN IN BANGLADESH
Author(s): Sanaul Haque MondalSubject(s): Geography, Regional studies, Environmental Geography
Published by: Географски институт »Јован Цвијић« САНУ
Keywords: traditional knowledge; knowledge transmission; flood; people living near the river; Bangladesh
Summary/Abstract: Traditional knowledge (TK) on disaster provides useful forecasting information for the hazard-prone communities. However, the documentation of TK is inadequate in the context of Bangladesh, puttingit at risk of extinction. The goal of the study is to evaluate the ability of the people living near the river to forecast floods using their TK. This study collected data from the people living near the river in Bangladesh in 2019 using a questionnaire survey with 377 respondents and focus group discussions. The data from the questionnaire survey was assessed using descriptive and inferential statistical tests. Data analyses were performed in SPSS version 26. Respondents' awareness of TK to forecast floods in riverine contexts was classified into categories: weather phenomena, cloud formation, rainfall patterns, river behavior, and observing plants and animals’ behavior. This study revealed that 97.3% of respondents were aware of at least one cue to forecast flood hazards in their area. The findings suggested that the respondents' gender and profession significantly influenced their awareness of using TK to forecast floods by observing the behaviors of plants and animals. For the people living near the river, TK plays a crucial role as they reside in remote areas with inadequate national-level warning systems. These findings will contribute to the current discourse regarding the integration of TK in disaster management practices.
Journal: Зборник радова Географског института "Јован Цвијић" САНУ
- Issue Year: 75/2025
- Issue No: 2
- Page Range: 167-182
- Page Count: 16
- Language: English
