Author(s): Seo-Young Kang; Jiyoung Kim; Min Ji Kim; Tae-Woong Kim
Linked Author(s): Tae-Woong Kim
Keywords: Climate change LSTM PLS-SEM Water demand
Abstract: Due to the increasing regional disparities in water shortages caused by climate change, it is necessary to establish stable water supply measures. This study investigated social, economic, and environmental factors using PLS-SEM (Partial Least Square Structural Equation Model) to identify significant influencing factors on water demand. The identified influencing factors were used as input data to the Long Short-Term Memory (LSTM) model to forecast water demand in the Jeolla province, South Korea, considering climate change scenarios. The results are useful for developing stable water supply measures in response to demand fluctuations due to climate change.
Year: 2025