Parametric assessment of seasonal drought risk to crop production in Bangladesh

Droughts are more damaging when they occur during crop growing season. This research assessed the spatial distribution of drought risks to crops in Bangladesh. Catastrophe theory-based weighting method was used to estimate drought hazard, exposure, and risk by avoiding potential human bias. Ten majo...

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Main Authors: Alamgir, Mahiuddin, Mohsenipour, Morteza, Homsi, Rajab, Wang, Xiaojun, Shahid, Shamsuddin, Shiru, Mohammed Sanusi, Alias, Nor Eliza, Yuzir, Ali
Format: Article
Language:English
Published: MDPI AG 2019
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Online Access:http://eprints.utm.my/id/eprint/87950/1/MahiuddinAlamgir2019_ParametricAssessmentofSeasonalDroughtRisk.pdf
http://eprints.utm.my/id/eprint/87950/
http://dx.doi.org/10.3390/su11051442
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Institution: Universiti Teknologi Malaysia
Language: English
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Summary:Droughts are more damaging when they occur during crop growing season. This research assessed the spatial distribution of drought risks to crops in Bangladesh. Catastrophe theory-based weighting method was used to estimate drought hazard, exposure, and risk by avoiding potential human bias. Ten major crops, including eight different types of rice, wheat, and potato, were selected for evaluation of drought risk. Results showed that 32.4%, 27.2%, and 16.2% of land in Bangladesh is prone to extreme Kharif (May-October), Rabi (November-April), and pre-Kharif (March-May) droughts, respectively. Among the major crops, Hybrid Boro rice cultivated in 18.2% of the area is found to be highly vulnerable to droughts, which is followed by High Yield Varity (HYV) Boro (16.9%), Transplant Aman (16.4%), HYV Aman (14.1%), and Basic Aman (12.4%) rice. Hybrid Boro rice in 12 districts, different varieties of Aman rice in 10 districts, and HYV Boro rice in 9 districts, mostly located in the north and northwest of Bangladesh, are exposed to high risk of droughts. High frequency of droughts and use of more land for agriculture have made the region highly prone to droughts. The methodology adopted in this study can be utilized for unbiased estimation of drought risk in agriculture in order to adopt necessary risk reduction measures.