MONITORING OF WATER IS

STRATEGIC TO HYDRO-QUEBEC

11

River Systems

Water = 95% of power production

22

How much water will be available to feed eachpower plants (currently, in the next 24 hours,… in the next years)? How much water out of precipitationsand from the snow cover?

•Insure supply of water to meet production objectives and demands

•Maximum falling height

•Security of neighbouring communities

•Protection of natural habitats

•Minimum quantities of non-productive water

NEEDS

33

Historical trends in water levels : planning the current hydro-electric network and new

installations

NEEDS

44

Monitoring of snow and precipitations

WeatherWeather stationsstations

55

In-situ monitoring of SWE

± monthly measurements

66

Variabilité de l'équivalent en eau de la neige au sol (cm)

0

5

10

15

20

25

30

0 50 100 150 200 250

No échantillon

EEN

(cm

)

DIFFICULT TO ESTIMATE THE SWE

233 samples of snow over a 15 km long and 300 meters widecorridor on 17-18 of March 2002

77

900 km

NEEDS

Needs varyLarge and slow responding reservoirs

Small and fast responding reservoirs

Time of year (spring or fall runoff, rain over snow,…)

Soil moisture conditions

Data in support to hydrological forecasting tools/models

…

88

NEEDS

Snow = ± 40 % of power produced

Hydrological regimes are driven mostly by melting of snow cover as we go North

Information on snow cover evolution during the winter and specially in spring time.

99

SOME INTIATIVES TO MEET NEEDS

Satellite remote sensing

EQEAU: RADARSAT

SSM/I: passive microwaves

1010

AIRBORNE GAMMA SENSORS

Analyse application of technique over northern regions(moss and bogs)

1111

SNOWPOWER

International three years project (Germany, Switzerland, Austria, Sweden, Canada)

Development of in-situ monitoring of SWE and snow cover density in real time

Based on measurements of the dielectric caracteristics of the snow pack.

1212

IN-SITU COSMIC RAYS SENSORS

Gamma ajustées vs données terrain

0,002,004,006,008,00

10,0012,0014,0016,0018,0020,00

2002-02

-16

2002-02

-23

2002-03

-02

2002-03

-09

2002-03

-16

2002-03

-23

2002-03

-30

2002-04

-06

date

EEN

en

cm

gamma corrigée pour biais

Chapais - site 1

Chapais - site 2

Chapais - près stationgamma

1313

Laser sensors

Coupling of models

Rainsat

Weather RADARs

G P R

N R C (EDF)

OTHERS AVENUES WERE ASSESSED

1414

H.Q. Current initiatives Hydrometeorological Data

Discharge measurements – Doppler Velocity Index: successful field tests

Margin of error ~ 5% River models Q2D

Application to open flow and flow underice.

1515

H.Q. Current initiatives Hydrometeorological Data

GMON (Gamma MONitoring)

SWE from GMON at SHA compared to manual sampling (estimated margin of error in red)

0

6

12

18

24

30

05-oct-05

04-nov-05

04-déc-05

03-janv-06

02-févr-06

04-mars-06

03-avr-06

03-mai-06

02-juin-06

SWE

(cm

)

Relative contribution of the soil to the signal detected as a function of its location relative to the base of the GMON, at 3 meters above

ground (case with a SWE of 10 cm)

0,000,020,040,060,080,10

0 1 2 3 4 5 6 7 8 9 10

distance from GMON (meters)

+

Soil moisture (additional work required)

1616

H.Q. Current initiatives Hydrometeorological Data

SSM/I: SWE over northern regions using linear regression and multiple linear regressions.

Information derived automatically: distribution map of SWE and the error distribution.

1717

H.Q. Current initiatives Hydrometeorological Data

Passive micro-waves

data

Passive micro-waves

data

Linear RegressionsLR and MLR

Linear RegressionsLR and MLR

Réseaux de neuronesRNA

Réseaux de neuronesRNA

Physical ApproachHUT model

AP

Physical ApproachHUT model

AP

SWE < 150 mm SWE 100 – 150 mm SWE > 10 mm

Error ~ 15 -20 % Error ~ 10 –15 % Error ~ 10 %

1818

H.Q. Current initiatives Hydrometeorological Data

Merging data over a gridSSM/I derived data In-situ data

Margin of error Margin of error

Thank you