Sri Lanka has been undergoing the impact of population ageing. Many structural and behavioral changes begin to occur in the population as a result of this demographical shift. Reemployment after the formal retirement of employees increasingly becomes usual routinely marking it as a significant trend it in the economy. Therefore, there should be some significant determinants which determine this behavior of working after retirement in Sri Lanka. A quantitative and exploratory research study was launched as a field study depending on a comprehensive literature review. Six determinants were identified which impact to Post-Retirement Employment in Sri Lanka through the analysis. A new questionnaire was developed and then standardized after furnishing the pilot survey and reviewing by scholars, peers and other related third parties. Primary data was gathered from 97 post-retired employees. Since it was a one-time data collection, the study could be addressed as a cross-sectional study.

The downstream low-lying regions of the Kelani River, including some areas in the Districts of Colombo and Gampaha, Sri Lanka, frequently face severe inundations due to extreme rainfalls in the upper basin. In the present study, 1-D and 2-D hydrodynamic models in HEC-RAS have been used to examine the flood inundations in the tidal influenced Kelani River with ground observations and remote sensing. The HEC-RAS model has been used to produce a flood hazard map for hazard assessment in the lower Kelani River basin under different return periods. Furthermore, expected discharges for different return periods have been estimated using the hydrological model HEC–HMS with the updated intensity depth frequency curves for the Kelani River basin. Sentinel 1 imagery and field survey results are used to validate the simulated flood inundation extent; hydrodynamic model results validated against observed stage measurements; hydrological model validated against discharge measurements. Further, the validated hydrodynamic model showed the high capability to capture flow processes (Nash-Sutcliffe coefficient = 0.90 and Pearson coefficient of correlation = 0.95) along with inundation extent (Success Index = 0.90) of selected historical extreme events. Then the hydrological model is used to predict the flows of the Kelani River basin with a good agreement (Nash-Sutcliffe coefficient = 0.91 and the Pearson coefficient of correlation = 0.93). Finally, flood risk zoning for different return periods are developed based on the present model which would be a useful benchmark to design and implement flood control and mitigation measures for the river basin.