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

1. 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.

2. According to my model it‘s snowing up there!

3. Outline • Introduction • Aims and Questions • Method • Analysis and Results • Conclusions • Perspectives

4. 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

5. 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

6. Introduction – Snow and Ice Melt Model SES • 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 photo: USI/Ibk

7. 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

8. Questions • How well is the temperature in the snow- and ice-region estimated by the simple linear regression method? • Which set of stations is most reliable for calculating lapse rate and corresponding elevation of the snowline? • How sensitive is the approach to limited data availability?

9. 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

10. 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

11. Method – Mean Lapse Rate and 0°C-Temperature Line • 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)

12. warm and dry cold and wet moderate to warm and wet Analysis/Results – Air Temperature at 2850 m a.s.l.

13. Analysis/Results – Mean Lapse Rate warm and dry cold and wet moderate to warm and wet

14. Analysis/Results – Elevation of 0°C-Temperature Line warm and dry cold and wet moderate to warm and wet

15. 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

16. Perspectives • How sensitive are more complex methods for estimation of lapse rate and corresponding snowline? • How sensitive is the simulated runoff to errors in estimation of the snowline • in the headwaters? • in the lower course? • What kind of influence has incorrect snowline modeling to runoff estimation of the total Inn catchment (~7000 km²)

17. Thanks for your attention rinderer@alpS-gmbh.com photo: USI/Ibk