This story highlights a remote sensing project using data collections from the Hubbard Brook Experimental Forest. To read more about HBEF datasets, visit our Datasets page. Check back regularly to learn about new projects.
Passive Microwave Detection of Snowmelt and Runoff

 

  Contact Info:
  Jennifer Jacobs
Department of Civil Engineering
University of New Hampshire
Durham, NH
Carrie Vuyovich
University of New Hampshire Durham, NH
  Date Prepared: May 2013

Snow melt provides the dominant hydrologic signal for many watersheds across the globe. Spring melt is a major transition period that is demarked by significant changes in the land and aquatic ecosystems. Lakes, streams, wetlands and vernal pools that depend on melt water are sensitive not only to the timing and magnitude of winter precipitation delivery, but also to how that melt controls later summer and fall baseflow conditions. Spring snow melt also influences soil moisture. Snowmelt is also a primary source of water in many mountainous regions of the world, and has a far-reaching influence on areas that rely upon melt water to fill streams and reservoirs and replenish aquifers.

In developing countries and very remote regions, snow data are rarely available and assessing a snowpack’s volume of water can be especially difficult. Even in well instrumented regions, the observational network is not able to capture the significant spatial heterogeneity of snow. Remote sensing data offer the capability to monitor snowpack and snowmelt runoff. Remote sensing data show abrupt transitions when the water content of snow increases, indicating onset of snowmelt and potential for flooding. This project uses current and historical microwave measurements gathered via satellite to predict when and where flooding caused by snowmelt will occur nationwide.

This study encompasses sites across the northern United States as well as East Asia. The Hubbard Brook Experimental Forest in New Hampshire is the focus area for understanding how the microwave signal behaves in a forested landscape. The research is leveraging the long-term HBEF snow observations to link to the nearly daily 30-yr record of satellite microwave observations as well as making new measurements to capture the variability of snow water and snow density in time and space. Ultimately, this research has wide potential value to detecting hazards, managing water resources, and understanding climate sensitive ecosystem processes. The project also has value for short-term forecasting needs by the operational community as well as for climate studies to detect trends in rain on snow events frequency and snowpack melt onset and duration.

 
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References

Comerford DP, Schaberg PG, Templer PH, Socci AM, Campbell JL, Wallin KF 2012 Influence of experimental snow removal on root and canopy physiology of sugar maple trees in a northern hardwood forest. Oecologia DOI 10.1007/s00442-012-2393-x

Fitzhugh RD, Driscoll CT, Groffman PM, Tierney GL, Fahey TJ, Hardy JP 2001 Effects of soil freezing disturbance on soil solution nitrogen, phosphorus, and carbon chemistry in a northern hardwood ecosystem. Biogeochemistry 56:215-238

Fitzhugh RD, Driscoll CT, Groffman PM, Tierney GL, Fahey TJ, Hardy JP 2003 Soil freezing and the acid-base chemistry of soil solutions in a northern hardwood forest. Soil Science Society of America Journal 67:1897-1908

Groffman PM, Driscoll CT, Fahey TJ, Hardy JP, Fitzhugh RD, Tierney GL 2001 Colder soils in a warmer world: A snow manipulation study in a northern hardwood forest ecosystem. Biogeochemistry 56:135-150

Templer PH, Schiller AF, Fuller NW, Socci AM, Campbell JL, Drake JE, Kunz TH. 2012 Impact of a reduced winter snowpack on litter athropod abundance and diversity in a northern hardwood forest ecosystem. Biology and Fertility of Soils 48: 413-424

Tierney GL, Fahey TJ, Groffman PM, Hardy JP, Fitzhugh,RD, Driscoll CT 2001 Soil freezing alters fine root dynamics in a northern hardwood forest. Biogeochemistry 56:175-190

Yanai R, Fisk M, Fahey T, Cleavitt N, Park B 2008) Identifying roots of northern hardwood species: patterns with diameter and depth. Canadian Journal of Forest Resources 38:2862-2869