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Yu-Ting Tsai and Ching-Piao Tsai
Deep learning techniques have revolutionized the field of artificial intelligence by enabling accurate predictions of complex natural scenarios. This paper proposes a novel convolutional neural network (CNN) model that involves deep learning technologies...
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Jong Seok Lee, Min Hyeok Lee, Yoon-Young Chun and Kun Mo Lee
The purpose of this paper is to compare the degree of uncertainty of the water scarcity footprint using the Monte Carlo statistical method and block bootstrap method. Using the hydrological data of a water drainage basin in Korea, characterization factor...
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Younghun Jung, Ju-Young Shin, Hyunjun Ahn and Jun-Haeng Heo
The spatial and temporal structures of extreme rainfall trends in South Korea are investigated in the current study. The trends in the annual maximum rainfall series are detected and their spatial distribution is analyzed. The scaling exponent is employe...
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Wenpeng Wang, Yuanfang Chen, Stefan Becker and Bo Liu
Hydrometeorological data are commonly serially dependent and thereby deviate from the assumption of independence that underlies the Spearman rho trend test. The presence of autocorrelation will influence the significance of observed trends. Specifically,...
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