BER launches Environmental System Science Program. Visit our new website under construction!

U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


Using Remotely Sensed Data to Advance Streamflow Forecasts in Subarctic Watersheds
Published: May 21, 2019
Posted: October 22, 2019

MODIS fractional snow cover area improves streamflow modeling in undersampled regions of Alaska.

The Science
In the remote and understudied boreal forest of interior Alaska, scientists funded by the Next-Generation Ecosystem Experiments (NGEE)–Arctic project applied remotely sensed snow cover observations to improve snowmelt and streamflow forecasting in river basins with spatially and temporally sparse gaging networks.

he Impact
This paper highlights the challenges of modeling in subarctic environments through assimilating snow remote-sensing data with the discovery that assimilation improves streamflow forecasts in undermonitored systems. The implications of this work have great value for streamflow forecasting and indicate the utility of the remotely sensed fractional snow cover data in the subarctic. Additionally, their improvements to a widely used snow model increase robustness of the hydrological simulations, in support of the U.S. National Weather Service's move toward a physically based National Water Model.

Summary
This study seeks to integrate two different strains of the moderate resolution imaging spectroradiometer (MODIS) remotely sensed fractional snow cover area observations into the Alaska Pacific River Forecast Center’s modeling framework and analyze the results in four watersheds located near Fairbanks, Alaska. This analysis revealed that in well-instrumented systems, such as the Chena River basin, streamflow forecasts were unchanged by the data assimilation. However, for basins with poorly observed precipitation and streamflow, such as the Chatanika River, improving observations of fractional snow cover extent in the models led to a significantly better forecast of streamflow. Because Arctic systems are largely undermonitored, the Chatanika is representative of the challenge in understanding the hydrology of northern rivers, for which improvements in streamflow forecasting are badly needed to mitigate and plan for a changing north.

Contacts
BER Program Manager
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Terrestrial Ecosystem Science
daniel.stover@science.doe.gov

Principal Investigators
Katrina E. Bennett
Los Alamos National Laboratory, Earth and Environmental Sciences, Hydrologist and Team Leader
kbennett@lanl.gov

Jessica E. Cherry
Alaska Pacific River Forecast Center
jessica.cherry@noaa.gov

Funding
Alaska Climate Science Center, Natural Science and Engineering Research Council of Canada, GOES-R High Latitude Proving Ground award NA08OAR432075, and the Next-Generation Ecosystem Experiments (NGEE)–Arctic project of the Office of Biological and Environmental Research within the U.S. Department of Energy Office of Science.

Publications
Bennett, K. E., J. E. Cherry, B. Balk, and S. Lindsey. “Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska.” Hydrology and Earth System Sciences 23(5), 2439–59 (2019). [DOI:10.5194/hess-23-2439-2019]

Topic Areas:

  • Research Area: Terrestrial Ecosystem Science
  • Research Area: Next-Generation Ecosystem Experiments (NGEE)

Division: SC-33.1 Earth and Environmental Sciences Division, BER

 

BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

Mar 23, 2021
Molecular Connections from Plants to Fungi to Ants
Lipids transfer energy and serve as an inter-kingdom communication tool in leaf-cutter ants&rsqu [more...]

Mar 19, 2021
Microbes Use Ancient Metabolism to Cycle Phosphorus
Microbial cycling of phosphorus through reduction-oxidation reactions is older and more widespre [more...]

Feb 22, 2021
Warming Soil Means Stronger Microbe Networks
Soil warming leads to more complex, larger, and more connected networks of microbes in those soi [more...]

Jan 27, 2021
Labeling the Thale Cress Metabolites
New data pipeline identifies metabolites following heavy isotope labeling.

Analysis [more...]

Aug 31, 2020
Novel Bacterial Clade Reveals Origin of Form I Rubisco
Objectives

  • All plant biomass is sourced from the carbon-fixing enzyme Rub [more...]

List all highlights (possible long download time)