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Climate-Adaptive Potential Crops Selection in Vulnerable Agricultural Lands Adjacent to the Jamuna River Basin of Bangladesh Using Remote Sensing and a Fuzzy Expert System

Authors :
Kazi Faiz Alam
Tofael Ahamed
Source :
Remote Sensing, Vol 15, Iss 8, p 2201 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Agricultural crop production was affected worldwide due to the variability of weather causing floods or droughts. In climate change impacts, flood becomes the most devastating in deltaic regions due to the inundation of crops within a short period of time. Therefore, the aim of this study was to propose climate-adaptive crops that are suitable for the flood inundation in risk-prone areas of Bangladesh. The research area included two districts adjacent to the Jamuna River in Bangladesh, covering an area of 5489 km2, and these districts were classified as highly to moderately vulnerable due to inundation by flood water during the seasonal monsoon time. In this study, first, an inundation vulnerability map was prepared from the multicriteria analysis by applying a fuzzy expert system in the GIS environment using satellite remote sensing datasets. Among the analyzed area, 42.3% was found to be highly to moderately vulnerable, 42.1% was marginally vulnerable and 15.6% was not vulnerable to inundation. Second, the most vulnerable areas for flooding were identified from the previous major flood events and cropping practices based on the crop calendar. Based on the crop adaptation suitability analysis, two cash crops, sugarcane and jute, were recommended for cultivation during major flooding durations. Finally, a land suitability analysis was conducted through multicriteria analysis applying a fuzzy expert system. According to our analysis, 28.6% of the land was highly suitable, 27.9% was moderately suitable, 19.7% was marginally suitable and 23.6% of the land was not suitable for sugarcane and jute cultivation in the vulnerable areas. The inundation vulnerability and suitability analysis proposed two crops, sugarcane and jute, as potential candidates for climate-adaptive selection in risk-prone areas.

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.9cbc2c3d03744dd8c217f8bd9983b5b
Document Type :
article
Full Text :
https://doi.org/10.3390/rs15082201