2022 Fiscal Year Final Research Report
Global inundation area estimation by assimilating multi-sensor satellite observations into a hydrodynamic model
| Project/Area Number |
20K22428
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Multi-year Fund |
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| Review Section |
0303:Civil engineering, social systems engineering, safety engineering, disaster prevention engineering, and related fields
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| Research Institution | The University of Tokyo |
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Principal Investigator |
ZHOU XUDONG 東京大学, 生産技術研究所, 特任助教 (20876239)
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| Project Period (FY) |
2020-09-11 – 2023-03-31
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| Keywords | Water surface area / Hydrodynamic model / Data assimilation / Model development |
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| Outline of Final Research Achievements |
Analyzed the global distribution pattern of remote sensing water surfaces and the advantages and disadvantages by comparing it with models. Results show that in areas with high vegetation coverage, remote sensing data underestimates the water surface area, while in areas with intense human activities, the model overestimates the simulation of water surfaces. Developed an evaluation system for hydrodynamic simulation results based on remote sensing data. By using runoff, remote sensing water surface elevation, and remote sensing water surface area, the system achieves automated evaluation of CaMa-Flood simulation results through comprehensive evaluation metrics. The system can also be extended to compare with results from other models. Preliminarily developed a model assimilation method using remote sensing data. By assimilating remote sensing water surface data in different ways, the simulation accuracy of hydrodynamic models has been improved.
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| Free Research Field |
水文学
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| Academic Significance and Societal Importance of the Research Achievements |
Deepening understanding of remote sensing water surfaces and providing new insights into improving models using sensed data. Relevant research is of great significance for improving flood forecasting and defense capabilities, reducing disaster losses, and improving flood prevention measures.
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