GIS-based modelling of glacial sediment balance

Zemp Michael, Kääb Andreas, Hoelzle Martin and Haeberli Wilfried

Glaciology and Geomorphodynamics Group, Department of Geography
University of Zurich, Switzerland



 

Abstract


In view of ongoing atmospheric warming, there is concern as to whether retreating glaciers uncover a rocky or sedimentary bed. Sedimentary beds are abundant in high-mountain areas and represent - if exposed - a severe potential for outbursts of periglacial lakes and debris flows. This paper assesses the utilization of GIS to derive process relevant parameters of glacial sediment balance from a Digital Elevation Model ("DEM"). The method was automated, and tested on 84 Swiss Alpine glaciers. Essentially, this approach may provide basis elements for the quantification of periglacial debris production and the compiling of a global inventory of land ice masses within the Glacier Land Ice Measurement from Space ("GLIMS") project.




 

Introduction


As a consequence of ongoing atmospheric warming, most Alpine glaciers retreat. Swiss Alpine glaciers lost about 27 % of surface area and about 30 % of ice volume in the period of 1850 to 1973 (MAISCH et al., 1999a). As a consequence increasing areas of former glacier beds become exposed. Characteristics of such newly exposed glacier beds greatly influence sediment flux in meltwater streams, the formation of potentially dangerous periglacial lakes and debris flow activity on steep morainic slopes (HAEBERLI et al., 1997).

The question whether glaciers erode into bedrock or build up thick sedimentary beds leads to the question of the processes of glacial erosion and sedimentation and of glacial sediment balance. These processes are complex and (since taking place at the glacier bed) are difficult and expensive to be measured. Measurements of sediment flux in meltwater streams by DREWERY (1986) show that the sediment balance of alpine glaciers is dominated by the periglacial debris input, whereas glacial erosion is less important.

This paper presents a GIS-based approach to the glacial sediment balance of alpine glaciers.




 

Erosion-Sedimentation Index Ies


The sediment balance of a glacierized mountain catchment, i.e. the ratio between debris input from the surrounding rock walls and debris evacuation by the meltwater stream, cannot be measured directly. Therefore, the main factors influencing the governing processes have been organized by HAEBERLI (1986) into an index ("Ies") of glacier erosion and sedimentation (Fig. 1), which discriminates between glaciers eroding into bedrock and those building up sedimentary beds:
 
 
erosion-sedimentation index

where a·C represents debris production in which  a is a factor indicating whether debris is furnished to the ablation area (1.0) as well as to the accumulation area (0.5). C is the mean height of debris-providing cliffs (100 m). (P-b)·S·Jk reflects the transport capacity of the meltwater stream where P is the annual precipitation (m), b is the annual glacier mass balance (m), S is the total surface area of the glacier (km2), J is the inclination of the sub-/proglacial meltwater stream and k is a constant from river hydraulics (1.6). L is the glacier length (km). The dimension-less units in this ratio of factors are chosen so that numbers around 1 result.
 
Ies - processes and parameters involved

Fig. 1:  Sheme explaining the erosion-sedimentation index ("Ies"), the processes and parameters involved.

 
The Ies has been developed as a  "rule of thumb" and allows a rough assessment of glacial sediment balance. WENZEL (1992) applied this approach to investigate glaciers in the Valais Alps, Switzerland. He used glacier inventory data, maps, aerial photography and field observations to derive the needed Ies-parameters for each glacier. To verify his approach he compared his results to the debris characteristic found in the glacier forefields. MAISCH et al. (1999b) tested the Ies-index with systematically classified glacier forefields from the revised Swiss glacier inventory.
 


 

Parameter Extraction


Improvements in resolution and quality of Digital Elevation Model ("DEM") allowed the conversion of the Ies from a "rule of thumb" into a GIS-based approach of the glacial sediment balance. Therefore, methods to extract the needed Ies-parameter from DEM have been developed. The methods are based on a hierarchical system for the extraction of geomorphometric parameters and  objects presented by SCHMIDT and DIKAU (1999) (Fig. 2). The system is based on the extraction of primary geomorphometric parameters. In a second step these parameters are analyzed to derive geomorphometric objects. These objects are the basis of a hierarchical system consisting of object analysis and object aggregation leading to representative geomorphometric parameters and geomophometric objects of a higher scale.

extraction of geomorphometric parameters and objects

Fig. 2:  System of methods for the extraction of geomorphometric parameters and objects (slightly modified after SCHMIDT and DIKAU, 1999).
 

For the Ies-parameter extraction, a digital elevation model ("DEM25") with a resolution of 25 meters and digitized glacier outlines and central flowlines from the new Swiss glacier inventory SGI2000 (PAUL et al., 2002 and KÄÄB et al., 2002) were used. Glacier outlines ("GLACIER1973") and central flowlines ("CFL1850") date from the year 1973. Fig. 3 shows the used data a.e. of Rotblatt glacier #3.

The methods were developed in ArcGIS 8.1 Desktop and Workstation.
 

Rotblatt glacier #3
 
Fig. 3: Rotblatt glacier #3. Glacier outline 1973 (blue), central flowline 1850 divided in CFLforefield1850 (green) and CFL1973 (orange). Hillshading derived from the DEM25 © Swiss Federal Office of Topography (BA024341).
 
The Ies-parameter were extracted as followes:
The presented methods are described in more detail and discussed in ZEMP (2002).
 
 

gruben glacier, rock wall cells and rock fall cells

Fig. 4: Gruben glacier with extracted rock wall cells in grey and potential rock fall cells in orange.
 
 

extraction of glacier's debris providing rock wall height

Fig. 5: Simplified scheme explaining the extraction of a glacier's debris providing rock wall height within the GRID module of ArcInfo Workstation.




Automation and Results


The GIS-based parameter extraction was automated as AML-routine for ArcInfo 8.1 and tested with glaciers in the Valais Alps, Switzerland; the same glaciers that have been manually investigated by WENZEL (1992). Using the DEM25, GLACIER1973 and CFL1850 as input date, the AML-routine calculates the Ies-parameter. Fig. 6 shows the resulting 84 indexed glaciers, classified as rocky, sedimentary or mixed bed.

The used AML-routine is further presented and discussed in ZEMP (2002).
 

indexed glaciers in the Valais Alps, Switzerland


Fig. 6:  Indexed glaciers in the Valais Alps, Switzerland. Rocky beds in blue, mixed beds in green and sedimentary beds in red. Hillshading derived from the DEM25 © Swiss Federal Office of Topography (BA024341).



 

Comparison of the GIS-based Approach with WENZEL (1992)


From the 84 investigated glaciers 64 glaciers could directly be compared with the ones investigated by WENZEL (1992). For 20 glaciers WENZEL (1992) did not use the same glacier outlines, so the corresponding glaciers could not directly be compared. However, the results from the GIS-based approach were compared with forefield classification (Fig. 7) and manually estimated Ies-index from WENZEL (1992) (Fig. 8).

The comparison of the results from the GIS-based approach with the forefield classification (Fig. 7) shows an overall accuracy of 55.6%. For 32.4% of the investigated glaciers there is a difference of 1 class. For 12 % of the glaciers the GIS-based approach predicts the opposite of what can be found in the glacier forefield. For the comparison of his manually indexed glaciers with the classified forefields, WENZEL (1992) found an overall accuracy of 59.3 %. The comparison of the indexed glacier with the forefield from 1850 can be problematic due to the possibility of changing erosion-sedimentation characteristics of a retreating glacier.


 
Forefield (WENZEL 1992)
1
2 3 Total
Predicted bed
(ZEMP 2002)
1 8 2 1 11
2 7 10 5 22
3 7 6 18 31
22 18 24 64
Correct in % 36.4 55.6 75.0 55.6
Difference of 1 class in % 31.8 44.4 20.8 32.4
Difference of two classes in % 31.8 0.0 4.2 12.0
Total in % 100.0

Fig. 7:  Comparison of the GIS-based approach with the forefield classification from WENZEL (1992). 1 = rocky bed, 2 = mixed bed, 3 = sedimentary bed.

Comparing the indexed glaciers from the GIS-based approach with the ones from the manual approach from WENZEL (1992) (as shown in Fig. 8) an overall accuracy of 86.4 % was found; a difference of one class for 13.6 % and no glacier where the two approaches came to a totally different result.
 

Predicted bed (WENZEL 1992)
1
2 3 Total
Predicted bed
(ZEMP 2002)
1 10 1 0 11
2 1 18 3 22
3 0 4 27 31
11 23 30 64
Correct in % 90.9 78.3 90.0 86.4
Difference of 1 class in % 9.1 21.7 10.0 13.6
Difference of two classes in % 0.0 0.0 0.0 0.0
Total in % 100.0

Fig. 8:  Comparison of the GIS-based approach with the manually approach from WENZEL (1992). 1 = rocky bed, 2 = mixed bed, 3 = sedimentary bed.



 

Conclusions and Perspectives


GIS-based methods to extract the needed Ies-parameter from DEM have been developed and successfully automated with an AML-routine for ArcInfo Workstation. The results lead to the following conclusions: The presented GIS-based approach may provide basis elements for: There is a large potential for the combination of GIS-based modelling with DEM and methods of remote sensing in geomorphodynamics and natural hazard analysis in high mountain areas.



Acknowledgments


The presented paper is financially supported by the Swiss Glaciological Commission and the Swiss Academy of Sciences. Sincere thanks are given to Frank Paul and Andreas Wipf for their hard work digitizing the glacier outlines, Max Maisch for putting the data of Swiss Glacier Inventory to the author's disposal and Regula Frauenfelder for the fruitful discussions on rock wall weathering. Special thanks go to Esri Switzerland for supporting this study with access to its software and its technical knowledge.



References


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SCHMIDT, J. and DIKAU, R. (1999): Extracting geomorphometric attributes and objects from digital elevation models - semantics, methods, future needs. In: DIKAU, R., SAURER, H. (1999).

WENZEL, J. (1992): Erosion und Sedimentation von Gebirgsgletschern. Diplomarbeit, Universität Trier.

ZEMP, M. (2002): GIS-basierte Modellierung der glazialen Sedimentbilanz. Diplomarbeit, Geographisches Institut der Universität Zürich.



 

Author Information

 
Michael Zemp:
Anreas Kääb:
Martin Hoelzle:
Wilfried Haeberli: haeberli@geo.unizh.ch
 
Physical Geography Division
Departement of Geography
University of Zurich-Irchel
Winterthurerstr. 190
CH-8057 Zurich
Switzerland