The study was conducted in Koyra upazilla of Khulna district located in the south-west Bangladesh and close to Bay of Bengal surrounded by the Sundarban at the south. The study period was from February to July 2014. Koyra upazilla is located between 22055'N Latitude and 89015'E Longitude with an altitude of 3.0-3.5 m from MSL. These communities were seriously affected by cyclone Aila in 2009 and faced enormous suffering to come back to normal lives [42]. The communities had to struggle for a long time to revive rice based livelihoods. Three unions i.e., Koyra Sadar, North Betkashi and Moharajpur at Koyra upazilla of Khulna district were selected for the study considering its geo-physical characteristics i.e., location, physical characteristics and relative vulnerability. Out of three villages in two villages irrigation facility is not available due to underground salinity. These villages are dominated by single rice crop with a rotation of controlled shrimp farming in one village. Both primary and secondary data were collected following quantitative and qualitative method of data collection. Primary data was collected by household questionnaire survey and following focus group discussions (FGD). The questionnaire survey helped to get detail idea of farmer’s on two categories of variables. Purposive sampling technique was applied to select unions and villages. One village from each of three unions was selected purposively considering relative vulnerability and hazards. Total 96 households were identified taking 36 households from each village following snowball sampling method. Two types of farmers were considered i.e., those cultivate rice in alleviated (raised) land is called high land and those cultivate rice in the plain land of crop field here by it is called beelland. Out of total 96 HHs, 48 farmers were for high (alleviated) land & other 48 farmers were for beel (low land) land. SRDI (2001) defines high land normally do not flooded during monsoon season that is hereby called high land. Here the author considered medium high land as beelland which normally flooded up to 90 cm depth during monsoon for more than two weeks to few months. 3 FGDs were conducted in three studied villages in presence of average 8-10 community people to resolve the issues not been able to cover by household questionnaire survey. Secondary information was collected from published documents using internet search, published relevant papers, unpublished reports, journals and having communicated with Koyra Upazila UNO Office, Koyra Upazila Department of Agriculture Extension Office under the district of Khulna. Variables for Socio-economic Status, Hazard Impacts and Factors helped livelihood restoration and Copping Practices of Rice Farmer: To fulfill the first objectives different variables and indictors were considered. These variables were taken to determine household socio-economic status, farmer knowledge on hazards, impact of hazards on coastal rice production, potential factors contributed to rice cultivation and the household copping strategies the communities experienced from the cyclone Aila response. Variables for Rice Production and Main Factors of Production: These Variables were used to define main factor of production and to estimate rice production. In this study an empirical model i.e., Cobb-Douglas production function was used, because the function was widely used in agricultural study for its simplicity [6]. Furthermore, this function allows either constant, increasing or decreasing marginal productivity, or not all the three and even any two at the same time. The model specified is given below: Yi= β0X1β1X2β2X3β3X4β4X5β5X6β6 X7β7 X8β8D1β9D2β10μ Above mentioned model can be estimated by using Ordinary Least Square Model (OLS) method. The Cobb-Douglas production function was transferred into log-linear form as: In Yi= β0+ β1In (X1) + β2In (X2) + β3In (X3) + β4In (X4) + β5In (X5) + β6In (X6) + β7In (X7) + β8In (X8) +β9D1+β10D2+ μ Where,Yi = Production of Aman rice (In mounds), β0 =Intercept, X1 = Area of Rice Cultivation (Acre), X2 = Seed and Seedling Cost (tk.), X3 = Human Labor (Man hours), X4 = Tillage Cost (tk.), X5 = Use of Fertilizer (kg), X6 = Use of Pesticide (gm.), X7 = Knowledge and Skill (years), X8 = Adaptation Practices ( no. of adaptation options), D1 = Land Types (High land =1; Beelland =0), D2 = Rice Variety (HYV=1; Local =0), β1 –β10 = Elasticity of coefficients, μ = Error term.Data obtained was analyzed using both descriptive and inferential statistics. Collected data was processed and written by using the computer program like MS Word, MS Excel, SPSS-20 and STATA. All socio-economic data was analyzed following descriptive statistics considering frequency, mean, median and using cross tabulation and ranking. Prioritization of potential factors was done based on its roles in helping rice farmers to come back to rice based livelihoods. Response scores were placed on a continuum (likert scale) as Very high, High, Medium, Less, Very Less and No response through assigned to responses are 5,4,3,2,1 and 0. Cross tabulation was done to assess knowledge level of farmers with adaptation practices. Household’s experiences to practices different copping strategies for rice farming were weighted by using likert-type scale. A correlation was drawn for adaptation options and for rice production. Un-paired t-test is done to estimate and compare production from high land and beell and. The report of this study was analyzed and written by following different analytical framework like likert scale, Cobb-Douglas production functions, Ordinary Least Square (OLS) analysis to find the share of inputs variables to rice production. Besides, the effect of different coping strategies and local practices on rice production was estimated by using linear regression.