4th Internat. Symposium on Flood Defence – Toronto/CA

Sensitivity analysis of lapse rate and corresponding elevation of the snowline

Limited data availability and its impact on snow and glacier melt

Rinderer M., Achleitner S., Asztalos J., Kirnbauer R.

According tomy model

it‘s snowingup there!

Outline

Introduction

Aims and Questions

Method

Analysis and Results

Conclusions

Perspectives

Introduction – Roll of Snow and Glacier Melt Modelling

Fluvial regime of mountainous regions Intermediate-term and long-term retention of precipitation -> influence on

amount of runoff generated during a rainfall event (1) Elevation of the temporary snowline (snow/rain) (2) System conditions: snowfree: immediate runoff/infiltration; snow-

covered: temporary absorption and retention by the snow cover

Water is released in warmer periods Days, weeks, month later

Not only precipitation but also snow and glacier melt influence fluvial regime

Importance for flood forecasting in glaciated areas

Introduction – Flood Forecasting System HOPI

Hybrid-model concept Main river course:

hydraulic model FluxDSS/DESIGNER

Tributary catchments: hydrological model HQsim

Glacier melt: energy-balance model SES

Introduction – Snow and Ice Melt Model SES

photo: USI/Ibk

Physically-based, spatially distributed, energy balance model Based on a snow melt model by Blöschl et al. (1987) and

Blöschl et al. (1991), further developed by Ansztalos (2004) grid based model (1) distributed accumulation of snow (2) snow, firn and ice melt in a glaciated catchment resulting runoff calculated for individual grid elements is

routed to the catchment outlet using a Nash-Cascade approach

Meteologolical input lapse rate air temperature

Introduction – Determination of Snowline

Modelling snowline: Not a straight line but a zone of

transition Simulated using a lower and an

upper temperature-boundary to separate snowfall from rain

In the transition-zone a portion is considered to be snow, the rest rain

Highest weather station measuring air temperature situated at 2850 m a.s.l.

Glaciated area ~ 3000 – 3700 m a.s.l.

-> Temperature extrapolated to glaciated area using linear regression method

photo: USI/Ibk

Questions

1. How well is the temperature in the snow- and ice-region estimated by the simple linear regression method?

2. Which set of stations is most reliable for calculating lapse rate and corresponding elevation of the snowline?

3. How sensitive is the approach to limited data availability?

Method – Study Area Ötztal

45km SW Innsbruck Total area: 895 km² ~ 13% glaciated ~ 700 – 3700m a.s.l. ~ 50 % > 2500m a.s.l. 22 weather stations

Method – Event Selection

Data available 1994 – 2001

-> August 1999

Showing typical warm periods -> runoff induced by melting

Typical cold weather period -> runoff influenced by snowfall

photo: TirolAtlas

Excluding station „Pitztaler Gletscher“ 2850 m a.s.l. -> reference Assort groups of weather stations depending on elevation and number

Estimation of mean lapse rate and corresponding 0°C-temperature line as well as temperature reconstruction at 2850 m a.s.l.

using linear regression method and various sets of data (availability-scenarios)

Method – Mean Lapse Rate and 0°C-Temperature Line

elevation [m a.s.l.] zone number of stations

700 – 1000 submontan 6

1000 – 1800 montan 6

1800 – 2000 subalpin 6

2000 – 2300 alpin 3

2850 alpin 1 (used as reference)

Analysis/Results – Air Temperature at 2850 m a.s.l.

-2

0

2

4

6

8

10

12

14

16ai

r te

mp

erat

ure

at

2850

m a

.s.l.

[°C

]

9.8.99 11.8.99 13.8.99 15.8.99 17.8.99 19.8.99 21.8.99

date

measured at2850 m a.s.l. stations 700 - 2850

stations 1800 - 2300stations 1000 - 2300

stations 700 - 2300stations 700 - 2000

stations 700 - 1800

warm and dry cold and wet moderate to warm and wet

Analysis/Results – Mean Lapse Rate

-1.0

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

lap

se

rate

[°C

/100

m]

9.8.99 11.8.99 13.8.99 15.8.99 17.8.99 19.8.99 21.8.99

date

reconstructed

stations 700 - 2850

stations 1800 - 2300stations 1000 - 2300

stations 700 - 2300stations 700 - 2000

stations 700 - 1800

dT

/dz

[°C

/100

m]

warm and dry cold and wet moderate to warm and wet

Analysis/Results – Elevation of 0°C-Temperature Line

2000

2500

3000

3500

4000

4500

5000

5500

6000

6500

7000

elev

atio

n o

f 0°

C-t

emp

erat

ure

lin

e [m

a.s

.l.]

9.8.99 11.8.99 13.8.99 15.8.99 17.8.99 19.8.99 21.8.99

date

reconstructed

stations 700 - 2850

stations 1800 - 2300stations 1000 - 2300

stations 700 - 2300stations 700 - 2000

stations 700 - 1800

warm and dry cold and wet moderate to warm and wet

Conclusions – Temperature Extrapolation

The more measurements of weather stations of different elevation are available the better the extrapolation results

Considering only the (few) stations at high altitude may not directly result in more plausible estimations …

… but causes high variability Mean lapse rate is a major simplification of stratification of the

atmosphere An error in one or two °C/100m considerably influences the

elevation of the snowline … … and therefore may lead to false simulation of snowfall or

rainfall in large parts of the glaciated area -> use of more complex method

1. How sensitive are more complex methods for estimation of lapse rate and corresponding snowline?

2. How sensitive is the simulated runoff to errors in estimation of the snowline in the headwaters? in the lower course?

3. What kind of influence has incorrect snowline modeling to runoff estimation of the total Inn catchment (~7000 km²)

Perspectives

Thanks for your attention

photo: USI/Ibkrinderer@alpS-gmbh.com