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Yeon Moon Choo, Deok Jun Jo, Gwan Seon Yun and Eui Hoon Lee
Frequent localized torrential rains, excessive population density in urban areas, and increased impervious areas have led to massive flood damage that has been causing overloading of drainage systems (watersheds, reservoirs, drainage pump sites, etc.). F...
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Futo Ueda, Hiroto Tanouchi, Nobuyuki Egusa and Takuya Yoshihiro
River water-level prediction is crucial for mitigating flood damage caused by torrential rainfall. In this paper, we attempt to predict river water levels using a deep learning model based on radar rainfall data instead of data from upstream hydrological...
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Davide Fronzi, Gagan Narang, Alessandro Galdelli, Alessandro Pepi, Adriano Mancini and Alberto Tazioli
Forecasting of water availability has become of increasing interest in recent decades, especially due to growing human pressure and climate change, affecting groundwater resources towards a perceivable depletion. Numerous research papers developed at var...
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Rongliang Cheng, Xiaofeng Han and Zhiqiang Wu
It is of great significance to identify the spatiotemporal stress distribution characteristics to ensure the safety of a super-high arch dam during the initial operation stage. Taking the 285.5 m-high Xiluodu Dam as an example, the spatiotemporal distrib...
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Yangqing Xu, Yuxiang Zhao, Qiangqiang Jiang, Jie Sun, Chengxin Tian and Wei Jiang
During the construction of deep foundation pits in subways, it is crucial to closely monitor the horizontal displacement of the pit enclosure to ensure stability and safety, and to reduce the risk of structural damage caused by pit deformations. With adv...
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Song Xue, Jingyan Chen, Sheng Li and Huaai Huang
Early warning of safety risks downstream of small reservoirs is directly related to the safety of people?s lives and property and the economic and social development of the region. The lack of data and low collaboration in downstream safety management of...
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Kidoo Park, Yeongjeong Seong, Younghun Jung, Ilro Youn and Cheon Kyu Choi
The methods for improving the accuracy of water level prediction were proposed in this study by selecting the Gated Recurrent Unit (GRU) model, which is effective for multivariate learning at the Paldang Bridge station in Han River, South Korea, where th...
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Yue Zhang, Zimo Zhou, Jesse Van Griensven Thé, Simon X. Yang and Bahram Gharabaghi
Climate change and urbanization have increased the frequency of floods worldwide, resulting in substantial casualties and property loss. Accurate flood forecasting can offer governments early warnings about impending flood disasters, giving them a chance...
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Sen Zhang, Shuai Xie, Yongqiang Wang, Yang Xu, Zheng Zhang and Benjun Jia
Accurate forecasting of the tail water level (TWL) is of great importance for the safe and economic operation of hydropower stations. The prediction accuracy is significantly influenced by the backwater effect of downstream tributaries and the operation ...
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Jiaxing Xu, Hongxiang Fan, Minghan Luo, Piji Li, Taeseop Jeong and Ligang Xu
Water level is an important indicator of lake hydrology characteristics, and its fluctuation significantly affects lake ecosystems. In recent years, deep learning models have shown their superiority in the long-time range prediction of hydrology processe...
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