Flood Risk Mapping of Kankai Basin: A Case Study of Shivasatakshi Municipality and Kankai Municipality - Pudasaini, Sujan; Gautam, Narayan Prasad; Shrestha, Anup (Kathford Journal of Engineering and Management, 2023)
Floods are probably the most frequent, widespread, and disastrous hazards in the world. It causes loss of life, casualties, financial loss, and displacement. Heavy monsoons, fragile geography, and constructions along the embankments cause the river to flood. The increase of population and squatter settlement of landless people living at the bank of the river has tremendous pressure on encroachment of flood plain making them vulnerable to flood damage. This study aims to develop HEC-RAS models for the Kankai River basin for preparation of 1D flood plain maps, vulnerability, risk assessment of RCC building in Shivasatakshi Municipality ward 10, and Kankai Municipality ward 4. Flood frequency analysis for 2, 10, 25, 50, 100, 200 and 1000 years return was carried out by Log Pearson III, Gumbel and Log Normal method based on maximum instantaneous flow recorded at Mainachuli station. The result of flood frequency analyzed by Log Normal method for 2, 10, 25, 50, 100, 200 and 1000 years return period floods shows higher among the results obtained using different methods. The flooding impact of the Kankai River being a large catchment with braided river form inundates vast downstream flood plain regions during high flood levels. With numerous people living along the river and downstream plains, flood risk is predominately high in the Kankai River catchment. With increasing flood intensity, higher flood depth increases and lower flood depth decreases. The inundation of a large area of Shivasatakshi Municipality ward 10 and Kanaki Municipality ward 4 at the bank of the Kankai river indicates that human lives and the physical infrastructure will be more vulnerable to flood disasters in the future. According to a study, the largest areas affected by floods with return periods of 2, 10, 25, 50, 100, 200, 1000 years, respectively, are 1843.24 ha, 1967.96 ha, 2016.32 ha, 2049.48 ha, 2079.64 ha, 2109.4 ha and 2176.08 ha of the whole basin. As a result, the study may help in future disaster planning and management.