2019 Fiscal Year Annual Research Report
Estimating Groundwater flow using satellite observation, river model and hydrological coherency
| Project/Area Number |
19F19799
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| Research Institution | The University of Tokyo |
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Principal Investigator |
山崎 大 東京大学, 生産技術研究所, 准教授 (70736040)
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| Co-Investigator(Kenkyū-buntansha) |
PELLET VICTOR 東京大学, 生産技術研究所, 外国人特別研究員
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| Project Period (FY) |
2019-11-08 – 2022-03-31
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| Keywords | water budget / remote sensing / global hydrology |
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| Outline of Annual Research Achievements |
We first focus on the Amazon river system, the largest of the world. All datasets have been gathered and pre-processed on common space/time grid resolution. Uncertainty assessment has been performed for all the satellite estimates. The integration methodology has been developed in order to take into account the upstream/downstream dependency in the Amazon river system. Preliminary results have shown that signal to noise ratio was too low to accurately estimate groundwater flow exchange at large scale over the amazon. This is due to the large uncertainty is the evaporation estimate over the floodplain. Experiment will be conducted over the Mississippi to investigate if satellite information can be used to estimate aquifer groundwater flow. As the Mississippi is better monitored, uncertainty is expected to be lower. For now, we have then focus on estimating the entire horizontal flow (River Discharge + Groundwater) using the methodology over the Amazon. This allow to reconstruct River discharge accurately even over un-monitored basin. These observation could then be assimilated by a hydrological model. The potential benefit of these virtual station for hydrological modelling will be investigated in the next fiscal year. Three presentation have been made based on these results at international conference and a paper is in preparation.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
If there's too much uncertainty is the satellite observation to estimate groundwater flows over the Amazon, reconstructing the entire horizontal flow (river discharge + groundwater flow) from spatial observation is very promising. The methodology allow to obtain river discharge at any point of the river system (e.g. virtual station) using spatial observation of the other water components. In this way, the reconstructed river discharge, is hydrologically consistent and deals with natural discharge (as water management can be seen in GRACE observations). Furthermore, these virtual could be assimilated in a LSM. As Land surface model barely assimilate other water component but the river discharge, the proposed methodology is capable to integrate all the spatial information available for the water balance at point (virtual) site that can be handled by LSM.
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| Strategy for Future Research Activity |
The year’s research will be dedicated in 1) assess the benefit of the pre-developed virtual observations of the river discharge for CaMa-Flood model in the use of assimilation. 2) pursuing the analysis of the water cycle at fine spatial and temporal scale. The total water storage change, monitored by GRACE satellite, can be downscaled using the three other water components (precipitation, evaporation, river discharge) this will allow to obtain sub-monthly information. River network from CaMa-Flood model will then be used to close the water cycle at fine grid scale using satellite observation with the model outputs. 3) As mentioned earlier, experiment for estimating groundwater flow will be conducted on the Mississippi basin. Finally, the water cycle of the Congo basin will be investigated to characterize the water balance over its main wetland in the “Cuvette Centrale” region.
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