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Yang Liu and Qianqian Zhang
Analyzing 165 data from five national control sites in Baiyangdian Lake, this study unveils its spatiotemporal pattern of water quality. Utilizing machine learning and multivariate statistical techniques, this study elucidates the effects of rainfall and...
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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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Hengzhi Hu, Hanwei Yang, Jiahong Wen, Min Zhang and Yanjuan Wu
Under climate warming, the frequency and intensity of extreme rainstorms-induced urban pluvial floods are significantly increasing, leading to severe flooding risks in megacities. An integrated model that incorporates rainfall processing, waterlogging si...
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Wenping Xu, Wenzhuo Li, David Proverbs and Wenbo Chen
Humanitarian supply chains play a major role in enabling disaster-affected areas to recover in a timely manner and enable economic and social activities to be restored. However, the sudden onset and increasing frequency of natural disasters such as flash...
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Mu Duan, Yunbo Zhang, Ran Liu, Shen Chen, Guoquan Deng, Xiaowei Yi, Jie Li and Puwei Yang
Satellite sensors are one of the most important means of collecting real-time geospatial information. Due to their characteristics such as large spatial coverage and strong capability for dynamic monitoring, they are widely used in the observation of rea...
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