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Title: Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska

Abstract

Remotely sensed snow cover observations give an opportunity to improve operational snow melt and stream flow forecasting in remote regions. This is particularly true in Alaska, where remote basins and a spatially and temporally sparse gaging network plague efforts to understand and forecast the hydrology of subarctic boreal basins and where climate change is leading to rapid shifts in basin function. In this study,the operational framework employed by the United States (US) National Weather Service, including the Alaska Pacific River Forecast Center, is adapted to integrate Moderate Resolution Imaging Spectroradiometer (MODIS) remotely sensed observations of fractional snow cover area (fSCA) to determine if these data improve streamflow forecasts in interior Alaska river basins. Two versions of MODIS fSCA are tested against a base case extent of snow cover derived by aerial depletion curves: the MODIS 10A1(MOD10A1) and the MODIS Snow Cover Area and Grain size (MODSCAG) product over the period 2000–2010. Observed runoff is compared to simulated runoff to calibrate both iterations of the model. MODIS-forced simulations haveimproved snow depletion timing compared with snow telemetry sites in the basins, with discernable increases in skill for the streamflow simulations.The MODSCAG fSCA version provides moderate increases in skill but is similar tomore » the MOD10A1 results. The basins with the largest improvement in streamflow simulations have the sparsest streamflow observations.Considering the numerous low-quality gages (discontinuous, short, or unreliable) and ungauged systems throughout the high-latitude regions of the globe, this result is valuable and indicates the utility of the MODIS fSCAdata in these regions. Additionally, while improvements in predicted discharge values are subtle, the snow model better represents the physical conditions of the snow pack and therefore provides more robust simulations,which are consistent with the US National Weather Service's move toward a physically based National Water Model. Physically based models may also be more capable of adapting to changing climates than statistical models corrected to past regimes. This work provides direction for both the Alaska Pacific River Forecast Center and other forecast centers across the US to implement remote-sensing observations within their operational framework, to refine the representation of snow, and to improve streamflow forecasting skill in basins with few or poor-quality observations.« less

Authors:
ORCiD logo [1];  [2];  [3];  [4]
  1. Univ. of Alaska, Fairbanks, AL (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Univ. of Alaska, Fairbanks, AL (United States); Alaska Pacific River Forecast Center, Anchorage, AL (United States)
  3. Deltares USA, Silver Spring, MD (United States)
  4. Alaska Pacific River Forecast Center, Anchorage, AL (United States)
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1525817
Report Number(s):
LA-UR-18-21603
Journal ID: ISSN 1607-7938
Grant/Contract Number:  
89233218CNA000001
Resource Type:
Accepted Manuscript
Journal Name:
Hydrology and Earth System Sciences (Online)
Additional Journal Information:
Journal Name: Hydrology and Earth System Sciences (Online); Journal Volume: 23; Journal Issue: 5; Journal ID: ISSN 1607-7938
Publisher:
European Geosciences Union (EGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Earth Sciences; remote sensing; snow cover; boreal forest; hydrology; Arctic

Citation Formats

Bennett, Katrina E., Cherry, Jessica E., Balk, Ben, and Lindsey, Scott. Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska. United States: N. p., 2019. Web. doi:10.5194/hess-23-2439-2019.
Bennett, Katrina E., Cherry, Jessica E., Balk, Ben, & Lindsey, Scott. Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska. United States. https://doi.org/10.5194/hess-23-2439-2019
Bennett, Katrina E., Cherry, Jessica E., Balk, Ben, and Lindsey, Scott. Tue . "Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska". United States. https://doi.org/10.5194/hess-23-2439-2019. https://www.osti.gov/servlets/purl/1525817.
@article{osti_1525817,
title = {Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska},
author = {Bennett, Katrina E. and Cherry, Jessica E. and Balk, Ben and Lindsey, Scott},
abstractNote = {Remotely sensed snow cover observations give an opportunity to improve operational snow melt and stream flow forecasting in remote regions. This is particularly true in Alaska, where remote basins and a spatially and temporally sparse gaging network plague efforts to understand and forecast the hydrology of subarctic boreal basins and where climate change is leading to rapid shifts in basin function. In this study,the operational framework employed by the United States (US) National Weather Service, including the Alaska Pacific River Forecast Center, is adapted to integrate Moderate Resolution Imaging Spectroradiometer (MODIS) remotely sensed observations of fractional snow cover area (fSCA) to determine if these data improve streamflow forecasts in interior Alaska river basins. Two versions of MODIS fSCA are tested against a base case extent of snow cover derived by aerial depletion curves: the MODIS 10A1(MOD10A1) and the MODIS Snow Cover Area and Grain size (MODSCAG) product over the period 2000–2010. Observed runoff is compared to simulated runoff to calibrate both iterations of the model. MODIS-forced simulations haveimproved snow depletion timing compared with snow telemetry sites in the basins, with discernable increases in skill for the streamflow simulations.The MODSCAG fSCA version provides moderate increases in skill but is similar to the MOD10A1 results. The basins with the largest improvement in streamflow simulations have the sparsest streamflow observations.Considering the numerous low-quality gages (discontinuous, short, or unreliable) and ungauged systems throughout the high-latitude regions of the globe, this result is valuable and indicates the utility of the MODIS fSCAdata in these regions. Additionally, while improvements in predicted discharge values are subtle, the snow model better represents the physical conditions of the snow pack and therefore provides more robust simulations,which are consistent with the US National Weather Service's move toward a physically based National Water Model. Physically based models may also be more capable of adapting to changing climates than statistical models corrected to past regimes. This work provides direction for both the Alaska Pacific River Forecast Center and other forecast centers across the US to implement remote-sensing observations within their operational framework, to refine the representation of snow, and to improve streamflow forecasting skill in basins with few or poor-quality observations.},
doi = {10.5194/hess-23-2439-2019},
journal = {Hydrology and Earth System Sciences (Online)},
number = 5,
volume = 23,
place = {United States},
year = {Tue May 21 00:00:00 EDT 2019},
month = {Tue May 21 00:00:00 EDT 2019}
}

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Cited by: 11 works
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Figures / Tables:

Figure 1 Figure 1: Map of the five study basins with upper and lower divisions shown. Alaska SNOTEL sites are shown with numbered black triangles: (1) Fairbanks International Airport; (2) Little Chena Ridge; (3) Munson Ridge; (4) Mt. Ryan; (5) Monument Creek; (6) Teuchet Creek; (7) Upper Chena (Table 2).

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Works referenced in this record:

Evaluation of the MODIS snow cover fraction product: SATELLITE-BASED SNOW COVER FRACTION EVALUATION
journal, December 2012

  • Arsenault, Kristi R.; Houser, Paul R.; De Lannoy, Gabriëlle J. M.
  • Hydrological Processes, Vol. 28, Issue 3
  • DOI: 10.1002/hyp.9636

Recent Extreme Runoff Observations From Coastal Arctic Watersheds in Alaska
journal, November 2017

  • Stuefer, Svetlana L.; Arp, Christopher D.; Kane, Douglas L.
  • Water Resources Research, Vol. 53, Issue 11
  • DOI: 10.1002/2017WR020567

Reconstructing solid precipitation from snow depth measurements and a land surface model: RECONSTRUCTING SOLID PRECIPITATION
journal, September 2005

  • Cherry, Jessie Ellen; Tremblay, L. Bruno; Déry, Stephen J.
  • Water Resources Research, Vol. 41, Issue 9
  • DOI: 10.1029/2005WR003965

The Delft-FEWS flow forecasting system
journal, February 2013


Assimilation of snow covered area information into hydrologic and land-surface models
journal, August 2006


Transitions in Arctic ecosystems: Ecological implications of a changing hydrological regime: TERRESTRIAL AND FRESHWATER ECOSYSTEMS
journal, March 2016

  • Wrona, Frederick J.; Johansson, Margareta; Culp, Joseph M.
  • Journal of Geophysical Research: Biogeosciences, Vol. 121, Issue 3
  • DOI: 10.1002/2015JG003133

Water and life from snow: A trillion dollar science question: SNOW AND LIFE
journal, May 2017

  • Sturm, Matthew; Goldstein, Michael A.; Parr, Charles
  • Water Resources Research, Vol. 53, Issue 5
  • DOI: 10.1002/2017WR020840

Modeling the View Angle Dependence of Gap Fractions in Forest Canopies: Implications for Mapping Fractional Snow Cover Using Optical Remote Sensing
journal, October 2008

  • Liu, Jicheng; Woodcock, Curtis E.; Melloh, Rae A.
  • Journal of Hydrometeorology, Vol. 9, Issue 5
  • DOI: 10.1175/2008JHM866.1

Forward-Looking Assimilation of MODIS-Derived Snow-Covered Area into a Land Surface Model
journal, February 2009

  • Zaitchik, Benjamin F.; Rodell, Matthew
  • Journal of Hydrometeorology, Vol. 10, Issue 1
  • DOI: 10.1175/2008JHM1042.1

Estimating snow depletion curves for American River basins using distributed snow modeling
journal, February 2007


Calibration of a distributed snow model using MODIS snow covered area data
journal, June 2013


Persistence-based temporal filtering for MODIS snow products
journal, March 2016


Representing spatial variability of snow water equivalent in hydrologic and land-surface models: A review: REPRESENTING SPATIAL VARIABILITY OF SWE IN MODELS
journal, July 2011

  • Clark, Martyn P.; Hendrikx, Jordy; Slater, Andrew G.
  • Water Resources Research, Vol. 47, Issue 7
  • DOI: 10.1029/2011WR010745

Retrieval of subpixel snow covered area, grain size, and albedo from MODIS
journal, April 2009

  • Painter, Thomas H.; Rittger, Karl; McKenzie, Ceretha
  • Remote Sensing of Environment, Vol. 113, Issue 4
  • DOI: 10.1016/j.rse.2009.01.001

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism
journal, January 2017

  • Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis
  • Hydrology and Earth System Sciences, Vol. 21, Issue 7
  • DOI: 10.5194/hess-21-3427-2017

Processes and impacts of Arctic amplification: A research synthesis
journal, May 2011


Impact of snowfall measurement deficiencies on quantification of precipitation and its trends over Northern Eurasia
journal, March 2015


The effect of viewing geometry and topography on viewable gap fractions through forest canopies
journal, January 2004

  • Liu, Jicheng; Melloh, Rae A.; Woodcock, Curtis E.
  • Hydrological Processes, Vol. 18, Issue 18
  • DOI: 10.1002/hyp.5802

Ground-based testing of MODIS fractional snow cover in subalpine meadows and forests of the Sierra Nevada
journal, January 2013


MODIS snow-cover products
journal, November 2002

  • Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.
  • Remote Sensing of Environment, Vol. 83, Issue 1-2
  • DOI: 10.1016/S0034-4257(02)00095-0

Scaling snow observations from the point to the grid element: Implications for observation network design: UPSCALING SNOW OBSERVATIONS
journal, November 2005

  • Molotch, Noah P.; Bales, Roger C.
  • Water Resources Research, Vol. 41, Issue 11
  • DOI: 10.1029/2005WR004229

Use of Satellite Data for Streamflow and Reservoir Storage Forecasts in the Snake River Basin
journal, March 2006


A methodology for snow data assimilation in a land surface model
journal, January 2004


Time–space continuity of daily maps of fractional snow cover and albedo from MODIS
journal, November 2008


Characterizing parameter sensitivity and uncertainty for a snow model across hydroclimatic regimes
journal, January 2011


Trajectory of the Arctic as an integrated system
journal, December 2013

  • Hinzman, Larry D.; Deal, Clara J.; McGuire, A. David
  • Ecological Applications, Vol. 23, Issue 8
  • DOI: 10.1890/11-1498.1

Changes in vegetation in northern Alaska under scenarios of climate change, 2003–2100: implications for climate feedbacks
journal, June 2009

  • Euskirchen, E. S.; McGuire, A. D.; Chapin, F. S.
  • Ecological Applications, Vol. 19, Issue 4
  • DOI: 10.1890/08-0806.1

Evidence for intensification of the global water cycle: Review and synthesis
journal, March 2006


Assimilating satellite-based snow depth and snow cover products for improving snow predictions in Alaska
journal, April 2013


Arctic warming, increasing snow cover and widespread boreal winter cooling
journal, January 2012


Assimilating remotely sensed snow observations into a macroscale hydrology model
journal, June 2006


Analysis of the Arctic System for Freshwater Cycle Intensification: Observations and Expectations
journal, November 2010

  • Rawlins, Michael A.; Steele, Michael; Holland, Marika M.
  • Journal of Climate, Vol. 23, Issue 21
  • DOI: 10.1175/2010JCLI3421.1

Assessment of methods for mapping snow cover from MODIS
journal, January 2013


Diagnosing Present and Future Permafrost from Climate Models
journal, August 2013


Streamflow hydrology in the boreal region under the influences of climate and human interference
journal, November 2007

  • Woo, Ming-ko; Thorne, Robin; Szeto, Kit
  • Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 363, Issue 1501
  • DOI: 10.1098/rstb.2007.2197

Assimilation of MODIS Snow Cover Area Data in a Distributed Hydrological Model Using the Particle Filter
journal, November 2013

  • Thirel, Guillaume; Salamon, Peter; Burek, Peter
  • Remote Sensing, Vol. 5, Issue 11
  • DOI: 10.3390/rs5115825

Local spring warming drives earlier river-ice breakup in a large Arctic delta
journal, March 2014

  • Lesack, Lance F. W.; Marsh, Philip; Hicks, Faye E.
  • Geophysical Research Letters, Vol. 41, Issue 5
  • DOI: 10.1002/2013GL058761

Spatial and temporal patterns in Arctic river ice breakup revealed by automated ice detection from MODIS imagery
journal, March 2016


Merging complementary remote sensing datasets in the context of snow water equivalent reconstruction
journal, March 2008

  • Durand, Michael; Molotch, Noah P.; Margulis, Steven A.
  • Remote Sensing of Environment, Vol. 112, Issue 3
  • DOI: 10.1016/j.rse.2007.08.010

Planning for climate change impacts on hydropower in the Far North
journal, January 2017

  • Cherry, Jessica E.; Knapp, Corrie; Trainor, Sarah
  • Hydrology and Earth System Sciences, Vol. 21, Issue 1
  • DOI: 10.5194/hess-21-133-2017

Overall distributed model intercomparison project results
journal, October 2004


Interpretation and topographic compensation of conifer canopy self-shadowing
journal, October 2008


An approach to using snow areal depletion curves inferred from MODIS and its application to land surface modelling in Alaska
journal, January 2005

  • Déry, Stephen J.; Salomonson, Vincent V.; Stieglitz, Marc
  • Hydrological Processes, Vol. 19, Issue 14
  • DOI: 10.1002/hyp.5784

Operational snow modeling: Addressing the challenges of an energy balance model for National Weather Service forecasts
journal, October 2008


Temperature index melt modelling in mountain areas
journal, November 2003


Analysis of Permafrost Thermal Dynamics and Response to Climate Change in the CMIP5 Earth System Models
journal, March 2013


Accuracy assessment of the MODIS snow products
journal, January 2007

  • Hall, Dorothy K.; Riggs, George A.
  • Hydrological Processes, Vol. 21, Issue 12
  • DOI: 10.1002/hyp.6715

Monitoring ice break-up on the Mackenzie River using MODIS data
journal, January 2016


Historical trends and extremes in boreal Alaska river basins
journal, August 2015


Evidence and Implications of Recent Climate Change in Northern Alaska and Other Arctic Regions
journal, October 2005


Evaluating snow models with varying process representations for hydrological applications
journal, April 2015

  • Magnusson, Jan; Wever, Nander; Essery, Richard
  • Water Resources Research, Vol. 51, Issue 4
  • DOI: 10.1002/2014WR016498

Arctic Freshwater Synthesis: Summary of key emerging issues: Arctic Freshwater Synthesis: Summary
journal, October 2015

  • Prowse, T.; Bring, A.; Mård, J.
  • Journal of Geophysical Research: Biogeosciences, Vol. 120, Issue 10
  • DOI: 10.1002/2015JG003128

The value of MODIS snow cover data in validating and calibrating conceptual hydrologic models
journal, September 2008


Development of the Pan-Arctic Snowfall Reconstruction: New Land-Based Solid Precipitation Estimates for 1940–99
journal, December 2007

  • Cherry, J. E.; Tremblay, L-B.; Stieglitz, M.
  • Journal of Hydrometeorology, Vol. 8, Issue 6
  • DOI: 10.1175/2007JHM765.1

Comparison of approaches for spatial interpolation of daily air temperature in a large region with complex topography and highly variable station density
journal, October 2006


Changes to freshwater systems affecting Arctic infrastructure and natural resources: CHANGES TO ARCTIC FRESHWATER SYSTEMS
journal, March 2016

  • Instanes, Arne; Kokorev, Vasily; Janowicz, Richard
  • Journal of Geophysical Research: Biogeosciences, Vol. 121, Issue 3
  • DOI: 10.1002/2015JG003125

The Global Land Data Assimilation System
journal, March 2004

  • Rodell, M.; Houser, P. R.; Jambor, U.
  • Bulletin of the American Meteorological Society, Vol. 85, Issue 3
  • DOI: 10.1175/BAMS-85-3-381

The value of satellite-derived snow cover images for calibrating a hydrological model in snow-dominated catchments in Central Asia
journal, March 2014

  • Duethmann, Doris; Peters, Juliane; Blume, Theresa
  • Water Resources Research, Vol. 50, Issue 3
  • DOI: 10.1002/2013WR014382

Improving runoff modelling using satellite-derived snow covered area?
journal, February 2007

  • Udnæs, Hans-Christian; Alfnes, Eli; Andreassen, Liss M.
  • Hydrology Research, Vol. 38, Issue 1
  • DOI: 10.2166/nh.2007.032

Accelerated dryland expansion regulates future variability in dryland gross primary production
journal, April 2020


The value of MODIS snow cover data in validating and calibrating conceptual hydrologic models
journal, September 2008


MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid
dataset, January 2015