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

EARS Satellite data for Climate Water and Food

Meteosat Flow Forecasting andDrought Monitoring

Mark de Weerd, MSc.

EARS Earth Environment Monitoring BVDelft, The Netherlands

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

EARS Satellite data for Climate Water and Food

Meteosat

MSG

FY2c

METEOSAT IOC

MTSat

EARS Satellite data for Climate Water and Food

Energy en Water Balance

Radiation

Heat Evaporation Precipitation

Flow

EARS Satellite data for Climate Water and Food

Energy and Water Balance Monitoring System (EWBMS)

Rainfall

processingClouds

Temperature

Albedo

Energy balance

processing

WMO stations

Precipitation

Radiation

Evaporation

Crop growthmodel

Hydrologicalmodel

River flow forecasting

Crop yieldforecasting

Droughtprocessing

Droughtmonitoring

Meteosat

FengYun-2

VIS & TIR

EARS Satellite data for Climate Water and Food

66

Rainfall processing

•Meteosat TIR

•Cloud top temperature

•Cloud level

•Cloud level durations (CDi)

•GTS rain gauge data (R) •Regression:

R = a0+a1CD1+a2CD2+ ….

•Calculate rainfall field

0

2

4

6

8

10

12

160 180 200 220 240 260 280

Temperature (K)

Heig

ht (k

m)

cold

high

medium high

medium low

EARS Satellite data for Climate Water and Food

Rainfall product

EARS Satellite data for Climate Water and Food

Evapotranspiration processing

Hourly TIR

TIR VIS

Cloud?

To,Ta, Ao, t

Ac , tc

In = (1-Ao) Ig – Lu

In = (1-Ao) tc Ig

H = (To-Ta) LE = In - H

LEp= 0.8 In

RE=LE/LEp

LE = 0.8*RE*In

Atm.corr.

Hourly VIS

Radiation

Sensible heat flux

Potential evaporation

Actual evaporation

Rel. evaporation

constant “Bowen ratio”

EARS Satellite data for Climate Water and Food

Actual evapotranspiration product

EARS Satellite data for Climate Water and Food

Time series (daily, 10-daily)

EARS Satellite data for Climate Water and Food

Complete river basins

EARS Satellite data for Climate Water and Food

U pper Yellow R iverW ei R iver

2

1

3

45

6

7

8

Wei River

Upper

Yellow River

Second largest river basin of China

Example project: Yellow River basin (2006-2009)

EARS Satellite data for Climate Water and Food

GMS / FY2 precipitation data 1st quarter 2000 2nd quarter 2000

3rd quarter 2000 4th quarter 2000

EARS Satellite data for Climate Water and Food

GMS / FY2 evapotranspiration data

1st quarter 2000 2nd quarter 2000

3rd quarter 2000 4th quarter 2000

EARS Satellite data for Climate Water and Food

Water balance validation

-4

-2

0

2

4

6

8

10

12

Jul-0

5

Sep-

05

Nov

-05

Jan-

06

Mar

-06

May

-06

Jul-0

6

Sep-

06

Nov

-06

Jan-

07

Mar

-07

May

-07

Jul-0

7

Sep-

07

Nov

-07

Jan-

08

Mar

-08

May

-08

Jul-0

8

Net

Pre

cipi

tatio

n (m

m)

-2

-1

0

1

2

3

4

5

6

Riv

er D

isch

arge

(mm

)

Net precipitation 5 days-floating average

River discharge at Tangnaihai

0200400

600800

10001200

140016001800

Jul-0

5

Sep

-05

Nov

-05

Jan-

06

Mar

-06

May

-06

Jul-0

6

Sep

-06

Nov

-06

Jan-

07

Mar

-07

May

-07

Jul-0

7

Sep

-07

Nov

-07

Jan-

08

Mar

-08

May

-08

Jul-0

8

Wat

er (m

m)

Cum. evapotranspiration

Cum. net precipitation

Cum. precipitation

Cum. river discharge

Upper Yellow River

EARS Satellite data for Climate Water and Food

Land component:2-dimensional diffusion processSurface & sub-surface flow

Large Scale Hydrological Model (LSHM)

Q(t)

Ql(t)Ql(t)

River flow component:Muskingum-Cunge routing

Q(t)

EWBMS Precipitation &

Evapotranspiration

Hydrological Model by UNESCO IHE

EARS Satellite data for Climate Water and Food

Wei River flow simulation

R2 = 0.75 Vol. error = 4%

R2 = 0.80Vol. error = 11%

EARS Satellite data for Climate Water and Food

Wei River 24 hr forecast

RMSE = 110 m3/s RRMSE = 0.37

COE = 0.75 R2 = 0.79

EARS Satellite data for Climate Water and Food

22

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

EARS Satellite data for Climate Water and Food

• By a Chinese high-level scientific commission

• Classification: “World Leading Level”

• 2nd Prize China Ministry of Water Resources

Yellow River project evaluation

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)

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

EARS Satellite data for Climate Water and Food

Meteosat antenna

26

EARS Satellite data for Climate Water and Food

Receiving and processing office

27

EARS Satellite data for Climate Water and Food

Training

28

EARS Satellite data for Climate Water and Food

India

Meteosat Indian Ocean Data Coverage (IODC)

EARS Satellite data for Climate Water and Food

India

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

EARS Satellite data for Climate Water and Food

Thank you for your attention

[email protected]