2021 Fiscal Year Research-status Report
Data-driven Seasonal Hydrologic Prediction Using Earth Observing Satellites
| Project/Area Number |
18KK0117
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| Research Institution | The University of Tokyo |
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Principal Investigator |
金 炯俊 東京大学, 生産技術研究所, 特任准教授 (70635218)
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| Co-Investigator(Kenkyū-buntansha) |
渡部 哲史 京都大学, 防災研究所, 特定准教授 (20633845)
内海 信幸 京都先端科学大学, ナガモリアクチュエータ研究所, 助教 (60594752)
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| Project Period (FY) |
2018-10-09 – 2023-03-31
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| Keywords | lake surface area / remote sensing / water big data |
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| Outline of Annual Research Achievements |
Pandemic situation has not been alleviated enough, and, therefore, we could not take any international travel to exchange. Instead, we heavily utilized remote meeting solutions and could make several significant achievements. Referring to Pekel’s global surface water data, in total, 1.4 million global lakes listed in the HydroLAKES database have been investigated for their long-term monthly variability during recent 34 years. Originally, it was planned to utilize Google Earth Engine, but we successfully implemented a set of native analysis codes and achieved a significant performance gain. This is the first dataset available in the world. Two papers are under preparation, and these dataset will be available to the public onward. It has been found that the global lake surface area is slowly decreasing during recent two decades, and the seasonal variations is gradually increasing.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
Originally, it was planned to utilize Google Earth Engine, but we successfully implemented a set of native analysis codes and achieved a significant performance gain.
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| Strategy for Future Research Activity |
In the next fiscal year, we will investigate the relationship between the variability of global lake surface area and various climate modes such as ENSO, NAO, and AO. Further, AI-based lake area prediction model will be developed to investigate the possibility of data-driven seasonal prediction.
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| Causes of Carryover |
新型コロナウィルス感染症による移動制限・自粛により出張が取りやめとなった。また、
採用予定だった外国人研究員が長期間来日ができず、その後本人の申し出により、採用見送りとなったため。今年度新たに研究員を募集し採用予定であり、その人件費に充当、および、渡航が緩和されたことにより、海外出張を積極的に行い、海外研究者との連携を加速させる予定。
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