Ben Hudson- GE 132

June. July. A ugust. S eptem ber. O cto ber. N ovem be r. D ecem be r. Month u m e. (c u b ic m e ... f (c u b ic m e te rs. ) Speke Runoff Volume. Bujuku Runoff Volume Upper Kitandara Runoff Volume .... due to gravity, f is a form factor related to ...
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Estimating how glacial melt impacts lakes in the Rwenzori Mountains of Uganda Map Area

Ben Hudson- GE 132 ABSTRACT

Glaciers in the Rwenzori Mountains of Uganda have received relatively little study and are predicted to disappear within 20 years. Inconsistent monitoring of glaciers provides difficulties in estimating glacial volume and runoff, however within these constraints this map estimates glacial volume and runoff’ s impact on the water budget of the lakes. It was found that glacial melt does not play a major role in monthly and yearly runoff. -Glaciers in Africa are disappearing at an alarming rate -These glaciers are not well understood- especially their contribution to the overall hydrology of the watersheds they inhabit -Understanding glacial dynamics is important to help prepare

Mt. Speke

Lake Speke

Ice Volume Loss in the Rwenzori Mountains by Lake Catchment Speke Lake Catchment

Bukuju Lake Catchment

Upper Kitandara Catchment

40000000

35000000

30000000

25000000

Volume (cubic meters)

20000000

15000000

10000000

5000000

0 1906

Mt. Speke from Mt. Stanley (Rwenzori.com)

1955

1990

Year

QUESTIONS

Mt. Stanley

- Are glaciers an important source of water for the lakes? - Where should paleo-climatologists take lake sediment cores to get a good glacial signal? Upper Kitandara Lake Monthly Water Dynamics Speke Lake Monthly Water Dynamics Speke Runoff Volume Speke Catchment Glacial Melt 1990-1955

Upper Kitandara Runoff Volume Upper Kitandara Catchment Glacial Melt 1990-1955

Speke Catchment Glacial Melt 1955-1906

Upper Kitandara Catchment Glacial Melt 1955-1906

800000

215000

700000

165000

600000

500000

Water Volume (cubic meters)

300000

65000

200000

100000

be r

be r

De ce m

No ve m

O ct ob er

be r

t Se pt em

Au gu s

Ju ly

Ju ne

ay M

Ap ril

M

Fe br ua ry

Ja nu a

De ce m

Month

Bujuku Lake Monthly Water Dynamics

Runoff Per Month by Lake Speke Runoff Volume

ar ch

0

ry

be r

be r No ve m

O ct ob er

be r

t

Month

Se pt em

Au gu s

Ju ly

Ju ne

ay M

Ap ril

M

Ja nu a

-35000

ar ch

15000

ry

Lake Bujuku

400000

Fe br ua ry

Water Volume (cubic meters)

115000

Bujuku Runoff Volume Upper Kitandara Runoff Volume

Low Kitandara Runoff Volume

Bujuku Runoff Volume Bujuku Catchment Glacial Melt 1990-1955

Bujuku Catchment Glacial Melt 1955-1906

1200000

1200000

1000000

1000000

800000

800000

Mt. Baker

600000

Water Volume (cubic meters)

Runoff (cubic meters)

600000

400000

200000

400000

200000

De ce m

be r

be r No ve m

O ct ob er

Se pt em

be r

t Au gu s

Ju ly

14

Ju ne

12

M

10

Ap ril

8 Month

ar ch

6

M

4

ry

2

Ja nu a

0

Fe br ua ry

0

ay

0

Mt. Speke

BACKGROUND Despite being the third highest glacierized mountains in Africa (Kaser and Osmaston, 2002) and reaching over 5000 meters at their highest point the Rwenzori Mountains are Mt. oneStanley of the last refuges of glaciers on the continent. Located near the equator, (0º 10" to 0º 30" Mt. Baker N, 29º 50" to 30º 00" E) the horizontal extent of glaciers in the Rwenzori Mountains has decreased from 2.01 ± 0.56 km2 in 1987 to 0.96 ± 0.34 km2 in 2003. (Taylor et al. 2006)

Upper Kitandara Lake

CONCLUSIONS Catchment

Glacial Extent

Estimated Ice Thickness (Meters)

Elevation (Meters)

Lower Kitandara Lake

Lake Bujuku

1906

Lake Speke

1955

High : 390.151642

High : 5100.907227

Lower Kitandara

1990

Low : 17.409210

Low : 3315.673096

Upper Kitandara 0

0.25

0.5

1

1.5

2

Kilometers 2.5

«

The lakes studied in the Rwenzori Mountains are largely dominated by precipitation, not glacial melt. For communities that depend on the waters that flow out of the Rwenzori Mountains this is largely good news- the glacial reservoirs that are predicted to disappear within 20 years (Taylor 2006) in fact are not large sources of runoff for the lakes. For paleoclimatologists looking for lakes with strong glacial signals the search continues.

ESTIMATING ICE THICKNESS

METHODS: LAKES

The 2-D extent of the glaciers in 1906, 1955, and 1990 was determined previously (Moelg 2003)

Using GPS points linked to depth measurements TINs were created to estimate the volume of each lake. A image of the TIN of Lake Bujuku is at right. METHODS: HYDROLOGY

A formula that links ice thickness to the slope of the glacial surface was used (Kaser & Osmaston 2002).

Catchment areas were calculated using the Hydrology Toolbox. Monthly runoff was calculated where Monthly runoff = monthly precipitation values * the area of the catchment * the empirically determined runoff coefficient

H = t / [? *g *f *sin ( a/ 57.296) ]

Lake Volume (m3)

Where H is the thickness of ice, t is the basal shear stress on the glacier bed, ? is the density of ice, g is acceleration due to gravity, f is a form factor related to the hydraulic radius, and a is the angle of inclination of glacial surface in radians. Alpha is divided by a factor converting radians (default in ArcMap) to degrees. Below variables were held constant: t = 97000 Pa ? = 910 kg m-3

g = 9.8 m s-2 f = .69

Lake Speke Lake Bujuku Upper Kitandara Lower Kitandara

305684.51 709013.83 225363.53 137526.49

residence time (years) 0.261431126 0.133250045 0.058084162 0.031378661

Lake Bujuku in photo at right and image of TIN above right. Calculations of Lake volume and residence time of water are in the table at left. Residence time assumes lake is at steady state.

THANKS

Step 1: The digital elevation model (with hillshade for emphasis)

Step 2: Using raster calculator to create a raster of slope (above) from the DEM

Step Three: Use the slope raster as a in formula at left to calculate ice thickness

-Lynn Carlson, Gillian Galford, and Wilfrid Rodriguez for all the GIS help -Jim Russell for the project idea, data, and guidance -Georg Kaser and Thomas Moelg for the digital base maps of the Rwenzori Mountains