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4 th Internat. Symposium on Flood Defence – Toronto/CA Sensitivity analysis of lapse rate and corresponding elevation of the snowline Limited data availability.

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Presentation on theme: "4 th Internat. Symposium on Flood Defence – Toronto/CA Sensitivity analysis of lapse rate and corresponding elevation of the snowline Limited data availability."— Presentation transcript:

1 4 th 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 Flux DSS/DESIGNER  Tributary catchments: hydrological model HQsim  Glacier melt: energy- balance model SES

6 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

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 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?

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  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.]zonenumber of stations 700 – 1000submontan – 1800montan – 2000subalpin – 2300alpin3 2850alpin1 (used as reference)

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

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

14 Analysis/Results – Elevation of 0°C-Temperature Line warm and dry cold and wetmoderate 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 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

17 Thanks for your attention photo: USI/Ibk


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