Study areas and sample size The study was conducted at four villages namely, Islampur, Sarker Haty, Paschim Kholapara and Dhubajhora of Mithamoin upazila in Kishoregonj district. The villages were selected on the basis of high vulnerability to natural calamities. A total of 120 farmers (i.e., 30 from each village) were selected for primary data collection on the basis of farm size category (i.e., small, medium and large) following stratified random sampling technique. Primary data were collected from the respondents by using a structured questionnaire during November 2017 to February 2018. Key informant interviews (KII) and focus group discussions (FGD) were also conducted for data collection.
Analytical Techniques Descriptive statistics: Descriptive statistics like sum, averages, percentages, etc. were calculated to identify the farmers’ socioeconomic status and address their farming practices. Profitability analysis: Profitability of crop production per hectare, from the view point of individual farmers was measured in terms of gross return, gross margin, net return and benefit cost ratio (undiscounted). The formula needs for the calculation of profitability are discussed below:
GR = P × Q ; GM = GR – TVC ; NR = GR – (TFC + TVC) ; BCR = GR ÷ (TFC + TVC)
Where, GR = Gross return; P = Sales price of the product (Tk.); Q = Yield per hectare (unit); GM = Gross margin; TVC = Total variable cost; NR = Net return; TFC = Total fixed cost (Tk.); and BCR = Benefit cost ratio.
Transcendental production model In order to investigate the extent of influence of the determinants on profitability of crop production, the transcendental production model was used (Gujarati, 2003). In the present study, the following transcendental production model was used to identify the level of influence of the factors influencing profitability of crop production in the haor areas.
Cropping intensity index (CII) : Cropping intensity index was constructed to measure the cropping intensity in a given cropland per year (Uddin and Dhar, 2018). The following formula was used for calculation: Cropping intensity = (AreaGC ÷ AreaNC) × 100
Where, AreaGC = Gross cropped area (ha); and AreaNC = Net cropped area (ha).
Livelihood component framework (LCF): Livelihood component framework was constructed to measure the impact of production practices on haor farmers’ asset possession, activities and strategies, well being, and external policies and institutions (Uddin and Dhar, 2017).
Severity ranking model (SRM) : The severity of damage in haor farmers’ agricultural and livelihood activities due to the occurrences of different natural disasters was quantified and represented using severity ranking model (SRM). The major components of the model were identified as agriculture, assets and livelihood items. The sub-components of agriculture, assets and livelihood items were crop, livestock, poultry, and homestead and agroforestry; cultivable land, household area and physical assets; and drinking water, sanitation, education and employment; respectively. The damage of the natural calamities (i.e., early flood, drought and hailstorm) were characterized as extreme (severity point = 4), high (severity point = 3), medium (severity point = 2) and low (severity point = 1). The component severity score (CSS) of each sub-component of the model was estimated using the following formula:
CSSN = (NE × SPE) + (NH × SPH) + (NM × SPM) + (NL × SPL)
Where, CSSN = Component severity score in case of early flood, drought and hailstorm; NE = Number of farmers in extreme damage level; SPE = Severity point of extreme damage level; NH = Number of farmers in high damage level; SPH = Severity point of high damage level; NM = Number of farmers in medium damage level; SPM = Severity point of medium damage level; NL = Number of farmers in low damage level; and SPL = Severity point of low damage level.
The CSS of each sub-component could range from 120 to 480. The model severity score (MSS) of each sub-component was computed using the following formula: MSS = CSSF + CSSD + CSSH
Where, CSSF = Component severity score in case of early flood; CSSD = Component severity score in case of drought; and CSSH = Component severity score in case of hailstorm.
The MSS of each sub-component could range from 360 to 1440. The severity of destruction due to natural calamities was ranked on the basis of MSS of each subcomponent.