Md. Gulam Kibria
IDRC-SAWA Fellow Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka - 1000, Bangladesh
Debanjali Saha
IDRC-SAWA Fellow Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka - 1000, Bangladesh
Tamanna Kabir
IDRC-SAWA Fellow Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka - 1000, Bangladesh
Taznin Naher,
IDRC-SAWA Fellow Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka - 1000, Bangladesh
Sultana Maliha,
IDRC-SAWA Fellow Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka - 1000, Bangladesh
M. Shahjahan Mondal
Professor Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka - 1000, Bangladesh
Storm surge, Coastal region, Livelihood, Food security, Water management
Dacope upazila, Khulna district.
Food Safety and Security
Livelihood
1. The Study Area There are 139 polders in the coastal areas of Bangladesh (Khan 2014). In Dacope upazila, located at 22.5722°N latitude and 89.5111°E longitude in Khulna district, are three polders, named polder 31, 32, and 33. The losses and damages in polders 31 and 32 had been very significant after Alia. So, for this study, these two polders were selected.
2. Methodology and Data Collection For this study, the damages and losses caused by Aila were assessed from primary and secondary information. These damages include agricultural damages and losses of livelihoods. Changes in land use pattern were detected through Landsat image analysis. Coping strategies adopted by the local people to counteract the impacts of the damages caused by the cyclone were analysed, based on their information. The role of strategies to attain food security was evaluated using indicators like availability, access, and stability of food provision (Ecker 2010; FAO 2013). Also, livelihood security by ensuring crop cultivation throughout the year was considered an indicator for the reduction of food insecurity. The information on damages in the study area was collected using Participatory Rural Appraisal (PRA) tools such as Focus Group Discussions (FGDs), Key Informant Interviews (KIIs), individual interviews, and resource mapping. Remote sensing software, ERDAS Imagine 9.2, was used for land use classification of the collected Landsat images (ERDAS 1999). First, all bands of each Landsat image were layer-stacked, then the study area was clipped from the large layer-stacked images. Next, all images were classified using a maximum likelihood classifier method (supervised classification) with pixel training data sets, resulting in land-cover maps of six different classes (Tsarouchi et al 2014). Land types were classified as water, bare land, agricultural land, shrimp cultivation area, forest, and inundated area. ArcGIS 10 was used to calculate each land type’s area percentage. On the basis of the collected field information and local farmers’ perceptions, a decision model was developed. Such models have been developed in the past to understand how farmers make decisions in the real world and the steps they go through in the process (Intal & Valera 1990; Lampayan et al 1994; Saleh et al 2002). For the development of a framework of the model, the production of monsoon rice, level of soil salinity and amount of fresh irrigation water were considered. A crop model, “FAO AquaCrop” was used to simulate the yield of dry-season crops (Hsiao et al 2009; Raes et al 2009; Steduto et al 2009). Primarily, reference crop evapotranspiration was calculated using an ET0 calculator (Allen et al 1998) and used as an input of climate data. Relevant conservative data available in the crop library of AquaCrop and in its Reference Manual (Raes et al 2012) were used, and the other climatic and crop parameters were collected from the field to simulate present yield (Stricevic et al 2011; Bhattacharya & Panda 2013). Future crop yield was predicted using the climate data of future years for the IPCC climate change scenario A1B (IPCC 2007) mostly used in Bangladesh. Finally, some qualitative and semi-quantitative information regarding changes over the indicators of food security was collected through FGDs with different groups. Relevant data were collected from three field visits to the two polders and to relevant governmental and non-governmental organizations. 15 FGDs were conducted with farmers, fishermen, and wage labourers. These groups comprised both men and women.
SAWAS 5(1) - pp(26-43) 2015 SaciWATERs
Journal