Projection of Changes in Stream Water Use Due to Climate Change

This study investigates the impact of rising temperatures on residential water use (RWU) in Seoul from 2015 to 2021, addressing the challenges of urban water sustainability under climate change. Using advanced models—convolutional neural networks (CNNs), long short-term memory (LSTM) Networks, eXtre...

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Bibliographic Details
Published in:Sustainability 2024-11, Vol.16 (22), p.10120
Main Authors: Seo, Young-Ho, Park, Junehyeong, Kim, Byung-Sik, Sung, Jang Hyun
Format: Article
Language:English
Subjects:
2010s (Decade) AD
2020 AD
2021 AD
Climate change
Deep learning
Environmental aspects
Forecasts and trends
Global warming
Machine learning
Precipitation
Residential water supply
Temperature
Time series
User statistics
Water resources management
Water shortages
Weather
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Summary:This study investigates the impact of rising temperatures on residential water use (RWU) in Seoul from 2015 to 2021, addressing the challenges of urban water sustainability under climate change. Using advanced models—convolutional neural networks (CNNs), long short-term memory (LSTM) Networks, eXtreme Gradient Boosting (XGBoost), and Bayesian Neural Networks (BNNs)—we examined RWU prediction accuracy and incorporated a method to quantify prediction uncertainties. As a result, the BNN model emerged as a robust alternative, demonstrating competitive predictive accuracy and the capability to account for uncertainties in predictions. Recent studies highlight a strong correlation between rising temperatures and increased RWU, especially during summer, with tropical nights (with temperatures above 25 °C) becoming more common; Seoul experienced a record 26 consecutive tropical nights in July 2024, underscoring a trend toward higher RWU. To capture these dynamics, we employed Shared Socioeconomic Pathway (SSP) scenarios and downscaled the KACE-1-0-G Global Climate Model (GCM) for Seoul, projecting a progressive increase in RWU: 0.49% in the F1 period (2011–2040), 1.53% in F2 (2041–2070), and 2.95% in F3 (2071–2100), with significant rises in maximum RWU across these intervals. Our findings highlight an urgent need for proactive measures to secure water resources in response to the anticipated increase in urban water demand driven by climate change.
ISSN:2071-1050
2071-1050
DOI:10.3390/su162210120