Forecasting water demand under climate change using artificial neural network: a case study of Kathmandu Valley, Nepal

Abstract

Abstract With a water demand of 370 MLD, Kathmandu Valley is currently facing a water shortage of 260 MLD. The Melamchi Water Supply Project (MWSP) is an interbasin project aimed at diverting 510 MLD of water in three phases (170 MLD in each phase). Phase I of the project was expected to complete by 2018. Water demand forecasting is the first and important activity in managing water supply. Using the socio-economic factors of number of connections, water tariff and ratio of population to number of university students and climatic factor of annual rainfall, artificial neural network (ANN) was used to predict the water demand of Kathmandu Valley until the year 2040. The analysis suggests that, even after the completion of Phase I of MWSP, the water scarcity in the valley will be 160 MLD in 2020. Therefore, Phase II of MWSP should be completed within 2025 and Phase III should be completed by 2040. The result of this study aids KUKL for better management of the water system. In addition, this research can help in decision making to construct the second and third phase for MWSP, the construction date of which still has not been decided.