Development of high resolution global-flood forecasting system with long lead time
| Project/Area Number |
21K14386
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 25030:Disaster prevention engineering-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
馬 文超 東京大学, 生産技術研究所, 特任研究員 (60743101)
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Project Status |
Granted (Fiscal Year 2021)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2023: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2022: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2021: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Keywords | flood forecasting / ensemble system |
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| Outline of Research at the Start |
This project will develop a world-leading and computing cost-effective ensemble forecasting system for issuing quick and reliable flood warnings. We will estimate the return period of river discharge for each forecasted ensemble member, and to compare multiple sourced ensemble forecasting results.
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| Outline of Annual Research Achievements |
To achieve the 1st year’s target, I have finished downloading historical data from the ECMWF center. After that, decoding the original data for running the land surface model, MATSIRO, and CaMa-flood is finished from 2001 to 2020. Decoding ECMWF forcing data involves spatial and temporal downscaling. Simulation of the land surface model and CaMa-flood have been smoothly carried out. Using this forcing dataset, we successfully get more than eight days of forecasting, which is more than five times longer than our previous flood forecasting achievement (39 hours by MSM, in Japan only).These historical results will contribute to analyzing historical river water depth worldwide. The automatic system is partly built and will finish construction in the 2nd year.
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| Current Status of Research Progress |
Current Status of Research Progress
4: Progress in research has been delayed.
Reason
Due to the impact of the slow delivery of electronic chips and other products in the spring of 2021, the scheduled server received it at the end of July, four months later than the project expected. However, after receiving the device, the forcing data preparation and analysis proceed as scheduled.
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| Strategy for Future Research Activity |
This year, I will finish constructing the automatic data decoding in real time to provide near-real-time flood forecasting results. Also, based on the historical flood results analysis, the return period on a global scale will be prepared. After that, the first version of high accuracy flood forecasting system is expected to be available.
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Report
(1 results)
Research Products
(2 results)
