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Benjamin Burrichter, Julian Hofmann, Juliana Koltermann da Silva, Andre Niemann and Markus Quirmbach
This study presents a deep-learning-based forecast model for spatial and temporal prediction of pluvial flooding. The developed model can produce the flooding situation for the upcoming time steps as a sequence of flooding maps. Thus, a dynamic overview ...
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Helani Perera, Nipuna Senaratne, Miyuru B. Gunathilake, Nitin Mutill and Upaka Rathnayake
Satellite Rainfall Products (SRPs) are now in widespread use around the world as a better alternative for scarce observed rain gauge data. Upon proper analysis of the SRPs and observed rainfall data, SRP data can be used in many hydrological applications...
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Hailiang Zhang, Junjian Liu, Huoqing Li, Xianyong Meng and Ablimitijan Ablikim
Soil moisture is a critical parameter in numerical weather prediction (NWP) models because it plays a fundamental role in the exchange of water and energy cycles between the atmosphere and the land surface through evaporation. To improve the forecast ski...
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Ratiranjan Jena, Biswajeet Pradhan and Abdullah M. Alamri
The eastern region of India, including the coastal state of Odisha, is a moderately seismic-prone area under seismic zones II and III. However, no major studies have been conducted on earthquake probability (EPA) and hazard assessment (EHA) in Odisha. Th...
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Andi Besse Rimba, Martiwi Diah Setiawati, Abu Bakar Sambah and Fusanori Miura
Flooding has been increasing since 2004 in Japan due to localized heavy rainfall and geographical conditions. Determining areas vulnerable to flooding as one element of flood hazard maps related to disaster management for urban development is necessary. ...
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