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Enhance your water management with EARS Earth Environment Monitoring for river flow forecasting, drought monitoring, and crop yield forecasting. Utilize Meteosat data for precise energy and water balance monitoring.
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Meteosat Flow Forecasting andDrought 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 • Climate, Water and Food applications: • River flow forecasting • Drought monitoring • Crop yield forecasting • Crop insurance
MTSat FY2c METEOSAT IOC Meteosat MSG
Precipitation Evaporation Heat Radiation Flow Energy en Water Balance
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)
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
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
Example project: Yellow River basin (2006-2009) Upper Yellow River Second largest river basin of China Wei River
GMS / FY2 evapotranspiration data 1st quarter 2000 2nd quarter 2000 4th quarter 2000 3rd quarter 2000
Water balance validation Upper Yellow River
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)
Wei River flow simulation R2 = 0.75 Vol. error = 4% R2 = 0.80 Vol. error = 11%
Wei River 24 hr forecast RMSE = 110 m3/s RRMSE = 0.37 COE = 0.75 R2 = 0.79
High level interest at the2nd International Yellow River ForumZhengzhou, October 2005
Yellow River project evaluation • By a Chinese high-level scientific commission • Classification: “World Leading Level” • 2nd Prize China Ministry of Water Resources
Niger Basin project (2014-2017) • Niger Basin Authority (NBA), Niamey, Niger • Operational implementation • Drought monitoring • River flow forecasting
Implementation project components • Meteosat receiver • PC network • Software • Pre-processing • EWBMS • LSHM • Utility GIS • Calibration & Validation • Training
India Meteosat Indian Ocean Data Coverage (IODC)
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
Thank you for your attention mark@ears.nl www.ears.nl