Data-driven Seasonal Hydrologic Prediction Using Earth Observing Satellites

KAKEN

About This Project

Japan Grant Number
JP18KK0117 (JGN)
Funding Program
Grants-in-Aid for Scientific Research
Funding Organization
Japan Society for the Promotion of Science

Kakenhi Information

Project/Area Number
18KK0117
Research Category
Fund for the Promotion of Joint International Research (Fostering Joint International Research (B))
Allocation Type
  • Multi-year Fund
Review Section / Research Field
  • Medium-sized Section 22:Civil engineering and related fields
Research Institution
  • The University of Tokyo
Project Period (FY)
2018-10-09 〜 2024-03-31
Project Status
Completed
Budget Amount*help
17,810,000 Yen (Direct Cost: 13,700,000 Yen Indirect Cost: 4,110,000 Yen)

Research Abstract

Regarding the estimation of river discharge, this study aimed to enhance discharge data for large rivers. Specifically, discharge was estimated using river water level data obtained from satellite altimeters, which are observed regularly, extensively, and at high frequency. The long-term variability of global river discharge was estimated, and the study investigated how climate modes (e.g., ENSO) modulate it. By combining Pekel's global surface water data with HydroLAKES data, the long-term monthly variability of 1.4 million global lakes over the past 34 years was analyzed. A data-driven land surface model was developed and used to detect human impacts on long-term global water storage changes. Climate reconstructions based on tree rings were applied to detect turning points in the hydroclimate of inland East Asia.

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