Senior Thesis in Environmental Earth Sciences: Winter/Spring 2021
Spatiotemporal Variation in Snowmelt Runoff Efficiency: Unmixing the Effect of Melt-Season Moisture Depth on Vegetation Water Consumption and Bedrock Evaporation Rates Using High-Resolution SWE Maps
Dartmouth College
With thanks to my advisors:
Carl Renshaw (professor, Department of Earth Sciences)
Evan Dethier (graduate researcher, Department of Earth Sciences)
Abstract
Accurate modeling of the melt-season runoff from alpine catchments is critical for forecasting yearly water availability in snow-dominated regions. Realtime runoff models often rely on an estimate of runoff efficiency, the ratio of streamflow to precipitation. In large mountain catchments, it is difficult to isolate the physical processes that cause annual variation in runoff efficiency because the drivers of runoff efficiency in such basins are spatially heterogeneous and vary over time. We leverage the high spatiotemporal resolution of seven years of distributed snow water equivalent (SWE) maps acquired by the NASA Airborne Snow Observatory (ASO) in the headwaters of the Tuolumne River (California, USA) to model melt-season runoff efficiency based on the spatial distribution of SWE into vegetation and bedrock eco-zones and the impact of total seasonal moisture on vegetation water consumption. We calibrate our seasonal runoff model using unimpaired reservoir inflow data measured at the catchment’s outlet point, achieving a mean seasonal error of 3%. We also use the remainder term in our runoff efficiency calculations to estimate evapotranspiration (ET) for both eco-zones. In the bedrock zone, results indicate a constant runoff ratio of 0.95, suggesting that almost all precipitation falling on bedrock is converted to streamflow. In the vegetation zone, results show that vegetation runoff efficiency varies from 0.42 to 0.68, with a positive correlation between runoff efficiency and total melt-season moisture even though vegetation water consumption increases during wetter years. We conclude that catchment-wide runoff efficiency is lower in relatively dry years despite the suppression of vegetation ET during droughts.
References
Bos, Rudi Van Den, Lucien Hoffmann, Jérôme Juilleret, Patrick Matgen, and Laurent Pfister (2006). Regional runoff prediction through aggregation of first-order hydrological process knowledge: A case study. Hydrological Sciences Journal 51, no. 6: 1021–38. https://doi.org/10.1623/hysj.51.6.1021.
California Department of Water Resources, DFM-Hydro-SMN (DWR). (2021). Meteorological Station Data and SNOTEL Data: DAN, SLI, TUM. 45-(daily)-PRECIPITATION, INCREMENTAL. 82-(daily)-SNOW, WATER CONTENT (REVISED). California Data Exchange Center (CDEC). Accessed 2021. https://cdec.water.ca.gov/dynamicapp/staMeta?station_id=DAN https://cdec.water.ca.gov/dynamicapp/staMeta?station_id=SLI https://cdec.water.ca.gov/dynamicapp/staMeta?station_id=TUM
Carroll, Rosemary W. H., Jeffrey S. Deems, Richard Niswonger, Rina Schumer, & Kenneth H. Williams. (2019). The importance of interflow to groundwater recharge in a snowmelt‐dominated headwater basin. Geophysical Research Letters 46, no. 11: 5899–5908. https://doi.org/10.1029/2019gl082447.
City of San Francisco. (2021). Meteorological Station Data: HEM. Station Metadata. California Data Exchange Center (CDEC). Accessed 2021. https://cdec.water.ca.gov/dynamicapp/staMeta?station_id=HEM
Conrad, O., Bechtel, B., Bock, M., Dietrich, H., Fischer, E., Gerlitz, L., Wehberg, J., Wichmann, V., & Bïchner, J. (2015). System for Automated Geoscientific Analyses (SAGA) v. 2.1.4, Geosci. Model Dev., 8, 1991-2007, doi:10.5194/gmd-8-1991-2015.
Freeman, G.T. (1991). Calculating catchment area with divergent flow based on a regular grid.
Computers and Geosciences, 17:413-22
Funk, Chris, Pete Peterson, Martin Landsfeld, Diego Pedreros, James Verdin, Shraddhanand Shukla, Gregory Husak, James Rowland, Laura Harrison, Andrew Hoell, & Joel Michaelsen. (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific Data 2, 150066. doi:10.1038/sdata.2015.66 2015.
GDAL/OGR contributors (2021). GDAL/OGR Geospatial Data Abstraction software Library. Open Source Geospatial Foundation. https://gdal.org
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment.
Graham, C. (2018). ASO in the Tuolumne River Basin: Forecasting streamflow using basin wide SWE estimates. PowerPoint document. Yosemite Hydroclimate Meeting. https://www.cafiresci.org/events-webinars-source/category/yosemite-hydroclimate-meeting-2018
Hedrick, Andrew R., Danny Marks, Scott Havens, Mark Robertson, Micah Johnson, Micah Sandusky, Hans‐Peter Marshall, Patrick R. Kormos, Kat J. Bormann, & Thomas H. Painter. (2018). Direct insertion of NASA Airborne Snow Observatory‐derived snow depth time series into the iSNOBAL energy balance snow model. Water Resources Research 54, no. 10: 8045–63. https://doi.org/10.1029/2018wr023190.
Henn, B., Painter, T. H., Bormann, K. J., McGurk, B., Flint, A. L., Flint, L. E., White, V., & Lundquist, J. D. (2018). High-elevation evapotranspiration estimates during drought: Using streamflow and NASA Airborne Snow Observatory SWE observations to close the upper Tuolumne River Basin water balance. Water Resources Research, 54(2), 746–766. https://doi.org/10.1002/2017WR020473
Hood, E., Williams, M., & Cline, D. (1999). Sublimation from a seasonal snowpack at a continental, mid-latitude alpine site. Hydrological Processes, 13(12–13), 1781–1797. https://doi.org/https://doi.org/10.1002/(SICI)1099-1085(199909)13:12/13<1781::AID-HYP860>3.0.CO;2-C
Hunsaker, C. T., Whitaker, T. W., & Bales, R. C. (2012). Snowmelt runoff and water yield along elevation and temperature gradients in California’s southern Sierra Nevada. JAWRA Journal of the American Water Resources Association, 48(4), 667–678. https://doi.org/10.1111/j.1752-1688.2012.00641.x
Keeler-Wolf, T., P. E. Moore, E. T. Reyes, J. M. Menke, D. N. Johnson & D. L. Karavidas. (2012). Yosemite National Park vegetation classification and mapping project report. Natural Resource Technical Report NPS/YOSE/NRTR—2012/598. National Park Service, Fort Collins, Colorado.
Leydecker, A., & Melack, J. M. (2000). Estimating evaporation in seasonally snow-covered catchments in the Sierra Nevada, California. Journal of Hydrology, 236(1–2), 121–138. https://doi.org/10.1016/S0022-1694(00)00290-0
Martinec, Jaroslav, Albert Rango, & Ralph Roberts. (2008). Snowmelt Runoff Model (SRM) User’s Manual. Edited by Enrique Gomez-Landesa and Max P Bleiweiss. Special Report 100. Version 1.11ed. Vol. Special Report 100. WinSRM. Las Cruces, NM: New Mexico State University College of Agriculture and Home Economics Agricultural Experiment Station.
References, cont.
McGurk, B. (2021). Unimpaired Hetch Hetchy Reservoir inflow data, water years 1970-2020. Available by request to McGurck Hydrologic. Orinda, California USA.
Merz, Bruno, & Erich J. Plate. (1997). An Analysis of the Effects of Spatial Variability of Soil and Soil Moisture on Runoff. Water Resources Research 33, no. 12: 2909–22. https://doi.org/10.1029/97wr02204.
Mooney, H., Hillier, R., & Billings, W. (1965). Transpiration rates of alpine plants in the Sierra Nevada of California. The American Midland Naturalist, 74(2), 374-386. doi:10.2307/2423268
Ogden, Fred L., Trey D. Crouch, Robert F. Stallard, & Jefferson S. Hall. (2013). Effect of land cover and use on dry season river runoff, runoff efficiency, and peak storm runoff in the seasonal tropics of central Panama. Water Resources Research 49, no. 12: 8443–62. https://doi.org/10.1002/2013wr013956.
Painter, T., Berisford, D., Boardman, J., Bormann, K., Deems, J., Gehrke, F., Hedrick, A., Joyce, M., Laidlaw, R., Marks, D., Mattmann, C., Mcgurk, B., Ramirez, P., Richardson, M., Skiles, S.M., Seidel, F., & A. Winstral. (2016). The Airborne Snow Observatory: Fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo. Remote Sensing of Environment. DOI: 10.1016/j.rse.2016.06.018
Painter, T., et al. (2019). ASO L4 Lidar Snow Water Equivalent 50m UTM Grid, Version 1. Tuolumne Basin. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/M4TUH28NHL4Z. Accessed 2021.
Painter, T. H., K. J. Bormann, et al. (2020). ASO L4 Lidar Point Cloud Digital Terrain Model 3m UTM Grid, Version 1. Tuolumne Basin. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/2EHMWG4IT76O. Accessed 2021
Phillips, R. W., C. Spence, & J. W. Pomeroy. (2011). Connectivity and Runoff Dynamics in Heterogeneous Basins. Hydrological Processes, April 19, 2011. https://doi.org/10.1002/hyp.8123.
QGIS.org (2021). QGIS Geographic Information System. QGIS Association. http://www.qgis.org
Quinn, P.F., Beven, K.J., Chevallier, P., & Planchon, O. (1991). The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models. Hydrological Processes, 5:59-79
Rango, A., & J. Martinec. (1981). Accuracy of Snowmelt Runoff Simulation. Hydrology Research 12, no. 4-5: 265–74. https://doi.org/10.2166/nh.1981.0021.
Roche, J. W., Ma, Q., Rungee, J., & Bales, R. C. (2020). Evapotranspiration mapping for forest management in California’s Sierra Nevada. Frontiers in Forests and Global Change, 3, 69. https://doi.org/10.3389/ffgc.2020.00069
Safeeq, M., & Hunsaker, C. T. (2016). Characterizing runoff and water yield for headwater catchments in the southern Sierra Nevada. JAWRA Journal of the American Water Resources Association, 52(6), 1327–1346. https://doi.org/10.1111/1752-1688.12457
Saksa, P. C., Conklin, M. H., Tague, C. L., & Bales, R. C. (2020). Hydrologic response of Sierra Nevada mixed-conifer headwater catchments to vegetation treatments and wildfire in a warming climate. Frontiers in Forests and Global Change, 3, 539429. https://doi.org/10.3389/ffgc.2020.539429
San Joaquin River Restoration Program (SJRRP). (2011). Program Environmental Impact Statement/Report: Appendix H Modeling (Draft). San Joaquin River Restoration Program. https://www.usbr.gov/mp/nepa/includes/documentShow.php?Doc_ID=7557
United States Department of Agriculture, Natural Resources Conservation Service (USDA/NRCS). (2007). Soil survey of Yosemite National Park, California. Accessible online at: http://soils.usda.gov/surve/printed_survey/
United States Geological Survey (USGS). (2014). Landsat 8 Level-1 GeoTIFF Data Product. https://earthexplorer.usgs.gov/scene/metadata/full/5e83d0b656b77cf3/LC80420342014239LGN01/
Williams, A. Park, Edward R. Cook, Jason E. Smerdon, Benjamin I. Cook, John T. Abatzoglou, Kasey Bolles, Seung H. Baek, Andrew M. Badger, & Ben Livneh. (2020). Large Contribution from Anthropogenic Warming to an Emerging North American Megadrought.” Science 368, no. 6488: 314–18. https://doi.org/10.1126/science.aaz9600.
Wolfram Research, Inc., (2020). Mathematica, Version 12.2, Champaign, IL.