Glacier Contribution to Streamflow A Simple Energy Balance

Glacier Contribution to Streamflow A Simple Energy Balance, Global Scale Investigation Neil Schaner and Dennis. P. Lettenmaier University of Washington Department of Civil and Environmental Engineering Box 352700, Seattle, WA 98195 The importance of mountain glaciers as reservoirs of water is well known (Hock, 2005). At a time of increased concern regarding the remaining lifespan of mountainous glaciers, it has become important to quantify glacier contribution to streamflow. A simple energy balance model is used to estimate the fractional contribution glaciers make to total runoff. The model is applied to large spatial and temporal scales in an attempt to determine the upper bound of glacier contribution. The model underestimates glacier contribution in comparison to other, published values and in comparison to USGS Benchmark glacier drainage basin discharge records. However, the model overestimates the loss of mass for the same Benchmark glaciers. Despite uncertainties in the specific quantity of melt water, the model serves to highlight areas of importance to water resources at a time of climatic uncertainty. The calculated glacier melt contributions were compared to published results. The methods used by the authors of Xu, et al. to separate snowmelt from glacier melt are unclear. Source Jain MODELING METHOD AND INPUTS Glacier melt calculations were conducted across a quarter degree gridcell domain for the entire globe. Temporally, calculations were based on a year of average months. The large spatial and temporal resolutions were chosen to simplify assumptions for global determination of glacier contribution. The general total net radiation equation is often a sum of net shortwave, net longwave, sensible, latent, and advected radiation components. Compared to the other components, advected energy is small and is thus ignored. Further, over larger time scales sensible and latent heat fluxes tend to cancel each other out, leading to their discount. Total net radiation is thus taken as the incoming shortwave radiation minus the albedo dependent reflection plus the net longwave radiation. Qnet = [SWdown * (1 – α)] + LWnet Due to high temporal and spatial variability, glacier albedo is difficult to determine. Published values range from 0. 2 to 0. 5, leading to the choice of a fixed value of 0. 4 (Brock, et al. , 2000, Cottom, 2009, Paul and Haeberli, 2008). Total depth of melt is equal to the product of net radiation and elapsed time divided by the product of latent heat and water density. Melt = (Qnet * Δt ) / (HL * ρw) This total potential glacier melt water value was then compared to a total runoff value on a per gridcell basis to give a fraction of glacier melt runoff contribution. From the melt information a global, quarterdegree grid was produced with values of glacier melt contribution to total runoff. This grid was used to weight the values of a flow accumulation grid derived from a digital elevation model (DEM). Shortwave and longwave radiation data are taken from the International Satellite Cloud Climatology Project (ISCCP). Mean monthly values from the complete data record, July 1983 to December 2004, were used in all calculations. To determine the upper bound of glacier contribution to runoff, the months of greatest net radiation were used for calculations. Glacier areas were derived from the Global Land Ice Measurements from Space (GLIMS) database. To compare the calculated glacier melt values to total runoff, global runoff values were taken from one of Jenny Adam’s global Variable Infiltration Capacity (VIC) model runs. To track the flow of glacier melt water, the Global Land One-kilometer Base Elevation Project (GLOBE), a product of the National Oceanic and Atmospheric Administration, was used to provide elevation data. COMPARISON TO PUBLISHED VALUES GLACIER MELT SIGNATURE ABSTRACT The accumulated signature of all glacier melt runoff may be seen in the above figure as red lines, overlain on a Digital Elevation Model (DEM) for reference. The image is a combination of the months of largest potential melt for the northern hemisphere (June) and the southern hemisphere (December). CONTRIBUTING DRAINAGE BASINS FOR GLACIER MELT THRESHOLDS Area/River Deoprayag, India Time Period June Referenced Glacier Contribution (%) Calculated Glacier Contribution (%) 20* 6 Singh Bhakra Dam, and Jain India Avg. Annual 28. 7* 3 Tarim Basin, China Avg. Annual 40. 2 5 Junggar Basin, Avg. China Annual 13. 5 2 Qaidam Basin, Avg. Xu, et al. China Annual 12. 5 1 Hexi Corridor, Avg. China Annual 13. 8 5 Qinghai Lake, Avg. China Annual 0. 4 0. 2 * Referenced Glacier Melt Contribution values are stated to include ephemeral snowmelt. COMPARISON TO BENCHMARK GLACIERS As a further means of comparison, the melt model was applied to two Alaskan United States Geological Survey (USGS) Benchmark glaciers, Gulkana and Wolverine. Gulkana glacier is 19. 6 km 2 in area and rests in a drainage basin covering 31. 6 km 2. Wolverine glacier is similar in size at 16. 8 km 2 and lies in a 24. 6 km 2 drainage basin. A stream gauge is located near the terminus of each glacier. Using the discharge from the stream gauges it is possible to compare the amount of glacier melt water discharge created by the melt model with a physical record. Mean monthly stream discharge values were taken from the same time period as the ISCCP radiation data. By removing the contribution of non-glaciated land, the amount of discharge contributed by the glaciated area was determined. Mass balance is also recorded at each glacier, leading to the comparison of average annual mass balance values. Glacier Contribution Threshold and Population Estimate 50% 46. 5 million 25% 6. 2 million 5% 0. 44 million Glacier The drainage basins were created using flow direction calculated from the DEM to highlight the upstream areas of each farthest downstream 5%, 25%, and 50% contribution. Using the drainage basins and a population density map from 2005 it is possible to estimate the number of people relying on glacier melt water. Population estimates do not account for reservoirs that may be filled with glacier melt water. REFERENCES Brock, Ben W. , Ian C. Willis, Martin J. Sharp, 2000. Measurement and parameterization of albedo variations at Haut Glacier d’Arolla, Switzerland. Journal of Glaciology, 46, 675 -688. Cottom, Brandon, 2009. Driving Forces Behind Himalayan Glacial Melt. Summer Institute in Earth Science. Accessed January 19, 2010 from <http: //www. gest. umbc. edu/student_opp/2009_sies_reports/BCottom. pdf>. Hock, Regine, 2005. Glacier melt: a review of processes and their modeling. Processes in Physical Geography, 29, 362 -391. Jain, C. K. , 2002. A hydro-chemical study of a mountainous watershed: the Ganga, India. Water Research, 36, 1262 -1274. Paul, Frank and Wilfred Haeberli, 2008. Spatial variability of glacier elevation changes in the Swiss Alps obtained from two digital elevation models. Geophysical Research Letters, 35, doi: 10. 1029/2008 GL 034718. Singh, P. and S. K. Jain, 2002. Snow and glacier melt in the Satluj River at Bhakra Dam in the western Himalayan region. Water Research, 47, 93 -106. Xu, Baiqing, Tandong Yao, and Ninglian Wang. Observed Glacier Melting and Black Soot Deposition in the Third Pole. Presentation given at Workshop on “Ice, Snow and Water: Impacts of Climate Change on California and Himalayan Asia, ” La Jolla, CA, May 4 -6, 2009. Gulkana Wolverine Recorded Discharge (acre-ft) 381, 200 622, 100 Calculated Discharge (acre-ft) 356, 700 429, 000 0. 935 0. 689 0. 602 0. 535 1. 346 2. 240 Calculated / Recorded Average Annual Mass Balance (m) Calculated Average Annual Mass Balance (m)