Return Level Analysis of Hanumante River using Structured Expert Judgment

Abstract

Like other cities in Kathmandu Valley, Bhaktapur faces rapid urbanisation and population growth. Unsafe, new settlements are partly located at the floodplains and the government lags behind in implementing proper land-use policy to control unrestrained settlement. The rivers are not only constrained by uncontrolled settlements, but also by insufficient width and freeboard of bridges, and waste blockages causes problems. Combined with more extreme rain events during the monsoon due to climate change, flooding has become a reoccurring problem in Bhaktapur. To gain better understanding of the river and the corresponding flood risk, historical data is essential. Unfortunately, historical databases of water levels are non-existent for this river. Only starting from monsoon 2019, water levels and discharge have been measured on a regular basis. To reconstruct the missing historical data for a return level analysis, this research introduces the Classical Model for Structured Expert Judgment (SEJ) in combination with citizen science (CS). The objective of this research was to use Structured Expert Judgment in a flood risk analysis for the city of Bhaktapur. As a result of using SEJ, we were able to obtain sufficient water level data and estimate the return levels of extreme water levels of Hanumante river by fitting a Generalized Extreme Value distribution (GEV). This eventually led to a reverse Weibull fit, which in this case does not seem accurate. This research discusses in detail the advantages and issues of using Structured Expert Judgement in situations like this and also discusses the reliability of the results.