The analysis of influential factors for urban water supply system considering causality with time-series data

Abstract

Recently, the research on critical infrastructures have been extended its boundary and some previous research analysed interdependency between infrastructures tried to suggest operation and management policy of the infrastructure. This highlighted the importance of systemic approach such as System Dynamics. But there still exist the limit to select the modelling component in terms of causality. In this study, convergent cross mapping was applied to time series variables in Songpa-gu and Gangdong-gu in Seoul, South Korea. Selected variables include operating variable of water supply system, floating population and meteorological variables and 330 observations were collected. The result shows that daily average temperature and floating population that are equivalent to mobile population influences to the daily water supply, and vice versa. Other weather factors such as average precipitation and wind speed showed little causality with the daily water supply. The influential factors of water supply system can be investigated with convergent cross mapping and the result can be utilized for the pre-process of other methodology such as LSTM in short-term water demand prediction. It is expected to collect more available data to improve this study further.