Presentation is loading. Please wait.

Presentation is loading. Please wait.

EARS Satellite data for Climate Water and Food Meteosat Flow Forecasting and Drought Monitoring Mark de Weerd, MSc. EARS Earth Environment Monitoring BV.

Similar presentations


Presentation on theme: "EARS Satellite data for Climate Water and Food Meteosat Flow Forecasting and Drought Monitoring Mark de Weerd, MSc. EARS Earth Environment Monitoring BV."— Presentation transcript:

1 EARS Satellite data for Climate Water and Food Meteosat Flow Forecasting and Drought Monitoring Mark de Weerd, MSc. EARS Earth Environment Monitoring BV Delft, The Netherlands

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

3 EARS Satellite data for Climate Water and Food Meteosat MSG FY2c METEOSAT IOC MTSat

4 EARS Satellite data for Climate Water and Food Energy en Water Balance Radiation Heat Evaporation Precipitation Flow

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

6 EARS Satellite data for Climate Water and Food 6 6 Rainfall processing Meteosat TIR Cloud top temperature Cloud level Cloud level durations (CD i ) GTS rain gauge data (R) Regression: R = a 0 +a 1 CD 1 +a 2 CD 2 + …. Calculate rainfall field cold high medium high medium low

7 EARS Satellite data for Climate Water and Food Rainfall product

8 EARS Satellite data for Climate Water and Food Evapotranspiration processing Hourly TIR TIR VIS Cloud? T o,T a, A o, t A c, t c I n = (1-A o ) I g – L u I n = (1-A o ) t c I g H =  (T o -T a ) LE = In - H LE p = 0.8 I n RE=LE/LE p LE = 0.8*RE*I n Atm.corr. Hourly VIS Radiation Sensible heat flux Potential evaporation Actual evaporation Rel. evaporation constant “Bowen ratio”

9 EARS Satellite data for Climate Water and Food Actual evapotranspiration product

10 EARS Satellite data for Climate Water and Food Water balance validation EWBMS rainfall & evapotranspiration Same but cumulative SW Burkina Faso reported run-off: 2-8% (Mahe et al. 2008) EWBMS using Meteosat: 4.5%

11 EARS Satellite data for Climate Water and Food Time series (daily, 10-daily)

12 EARS Satellite data for Climate Water and Food Complete river basins

13 EARS Satellite data for Climate Water and Food Wei River Upper Yellow River Second largest river basin of China Example project: Yellow River basin (2006-2009)

14 EARS Satellite data for Climate Water and Food GMS / FY2 precipitation data

15 EARS Satellite data for Climate Water and Food GMS / FY2 evapotranspiration data 1st quarter 2000 2nd quarter 2000 3rd quarter 2000 4th quarter 2000

16 EARS Satellite data for Climate Water and Food Water balance validation Upper Yellow River

17 EARS Satellite data for Climate Water and Food Land component: 2-dimensional diffusion process Surface & sub-surface flow Large Scale Hydrological Model (LSHM) Q(t)Q(t) Ql(t)Ql(t) Ql(t)Ql(t) River flow component: Muskingum-Cunge routing Q(t)Q(t) EWBMS Precipitation & Evapotranspiration Hydrological Model by UNESCO IHE

18 EARS Satellite data for Climate Water and Food Wei River flow simulation R 2 = 0.75 Vol. error = 4% R 2 = 0.80 Vol. error = 11%

19 EARS Satellite data for Climate Water and Food Wei River 24 hr forecast RMSE = 110 m 3 /s RRMSE = 0.37 COE = 0.75 R 2 = 0.79

20 EARS Satellite data for Climate Water and Food Upper Yellow River flow simulation StationR2R2 Volume difference Jimai0.80+17.9 % Maqu0.82- 0.61% Jungong0.80+ 0.61% Tangnaihai0.80- 0.67%

21 EARS Satellite data for Climate Water and Food RMSE = 161 m 3 /s RRMSE = 0.17 COE = 0.84 R 2 = 0.93 Upper Yellow River 24 hr forecast

22 EARS Satellite data for Climate Water and Food 22 High level interest at the 2 nd International Yellow River Forum Zhengzhou, October 2005

23 EARS Satellite data for Climate Water and Food By a Chinese high-level scientific commission Classification: “World Leading Level” 2 nd Prize China Ministry of Water Resources Yellow River project evaluation

24 EARS Satellite data for Climate Water and Food Niger Basin Authority (NBA), Niamey, Niger Operational implementation Drought monitoring River flow forecasting Niger Basin project (2014-2017)

25 EARS Satellite data for Climate Water and Food Meteosat receiver PC network Software – Pre-processing – EWBMS – LSHM – Utility GIS Calibration & Validation Training Implementation project components

26 EARS Satellite data for Climate Water and Food Meteosat antenna 26

27 EARS Satellite data for Climate Water and Food Receiving and processing office 27

28 EARS Satellite data for Climate Water and Food Training 28

29 EARS Satellite data for Climate Water and Food India Meteosat Indian Ocean Data Coverage (IODC)

30 EARS Satellite data for Climate Water and Food India

31 EARS Satellite data for Climate Water and Food 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 Conclusions

32 EARS Satellite data for Climate Water and Food Thank you for your attention mark@ears.nl www.ears.nl


Download ppt "EARS Satellite data for Climate Water and Food Meteosat Flow Forecasting and Drought Monitoring Mark de Weerd, MSc. EARS Earth Environment Monitoring BV."

Similar presentations


Ads by Google