1 / 29

Meteosat Flow Forecasting and Drought Monitoring

Meteosat Flow Forecasting and Drought Monitoring. Mark de Weerd, MSc. EARS Earth Environment Monitoring BV Delft, The Netherlands. EARS Earth Environment Monitoring BV. Remote sensing company since 1977 Delft, the Netherlands Energy & Water Balance Monitoring

lindabrandon
Download Presentation

Meteosat Flow Forecasting and Drought Monitoring

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Meteosat Flow Forecasting andDrought Monitoring Mark de Weerd, MSc. EARS Earth Environment Monitoring BV Delft, The Netherlands

  2. EARS Earth Environment Monitoring BV • Remote sensing company since 1977 • Delft, the Netherlands • Energy & Water Balance Monitoring • Climate, Water and Food applications: • River flow forecasting • Drought monitoring • Crop yield forecasting • Crop insurance

  3. MTSat FY2c METEOSAT IOC Meteosat MSG

  4. Precipitation Evaporation Heat Radiation Flow Energy en Water Balance

  5. Meteosat FengYun-2 WMO stations Hydrological model River flow forecasting Precipitation Rainfall processing Clouds Drought monitoring Drought processing Evaporation VIS & TIR Energy balance processing Temperature Albedo Crop growth model Crop yield forecasting Radiation Energy and Water Balance Monitoring System (EWBMS)

  6. Rainfall processing cold high medium high medium low • Meteosat TIR • Cloud top temperature • Cloud level • Cloud level durations (CDi) • GTS rain gauge data (R) • Regression: • R = a0+a1CD1+a2CD2+ …. • Calculate rainfall field 6

  7. Rainfall product

  8. Evapotranspiration processing HourlyTIR Potential evaporation Radiation In = (1-Ao) Ig – Lu LEp= 0.8 In Rel. evaporation To,Ta, Ao,t RE=LE/LEp Sensible heat flux Actualevaporation Atm.corr. H =  (To-Ta) LE = In - H TIR VIS Cloud? constant “Bowen ratio” Ac , tc In = (1-Ao) tc Ig LE = 0.8*RE*In HourlyVIS

  9. Actual evapotranspiration product

  10. Time series (daily, 10-daily)

  11. Complete river basins

  12. Example project: Yellow River basin (2006-2009) Upper Yellow River Second largest river basin of China Wei River

  13. GMS / FY2precipitation data

  14. GMS / FY2 evapotranspiration data 1st quarter 2000 2nd quarter 2000 4th quarter 2000 3rd quarter 2000

  15. Water balance validation Upper Yellow River

  16. Land component: 2-dimensional diffusion process Surface & sub-surface flow Large Scale Hydrological Model (LSHM) Ql(t) Ql(t) Q(t) Hydrological Model by UNESCO IHE River flow component: Muskingum-Cunge routing EWBMS Precipitation & Evapotranspiration Q(t)

  17. Wei River flow simulation R2 = 0.75 Vol. error = 4% R2 = 0.80 Vol. error = 11%

  18. Wei River 24 hr forecast RMSE = 110 m3/s RRMSE = 0.37 COE = 0.75 R2 = 0.79

  19. High level interest at the2nd International Yellow River ForumZhengzhou, October 2005

  20. Yellow River project evaluation • By a Chinese high-level scientific commission • Classification: “World Leading Level” • 2nd Prize China Ministry of Water Resources

  21. Niger Basin project (2014-2017) • Niger Basin Authority (NBA), Niamey, Niger • Operational implementation • Drought monitoring • River flow forecasting

  22. Implementation project components • Meteosat receiver • PC network • Software • Pre-processing • EWBMS • LSHM • Utility GIS • Calibration & Validation • Training

  23. Meteosat antenna

  24. Receiving and processing office

  25. Training

  26. India Meteosat Indian Ocean Data Coverage (IODC)

  27. India

  28. Conclusions • Operational water monitoring and flow forecasting system • Distributed precipitation and evapotranspiration data Data: • Has at least a daily temporal resolution and a 5 km spatial resolution. • Is transboundary, uniform, objective and cost effective

  29. Thank you for your attention mark@ears.nl www.ears.nl

More Related