The influence of ground- and lidar-derived forest structure metrics on snow accumulation and ablation in disturbed forests

The current mountain pine beetle infestation in British Columbia's lodgepole pine forests has raised concerns about potential impacts on water resources. Changes in forest structure resulting from defoliation, windthrow, and salvage harvesting may increase snow accumulation and ablation (i.e., spring runoff and flooding risk) below the forest canopy be- cause of reduced snow interception and higher levels of radiation reaching the surface. Quantifying these effects requires a better understanding of the link between forest structure and snow processes. Light detection and ranging (lidar) is an in- novative technology capable of estimating forest structure metrics in a detailed, three-dimensional approach not easily ob- tained from manual measurements. While a number of previous studies have shown that increased snow accumulation and ablation occur as forest cover decreases, the potential improvement of these relationships based on lidar metrics has not been quantified. We investigated the correlation between lidar-derived and ground-based traditional canopy metrics with snow accumulation and ablation indicators, demonstrating that a lidar-derived forest cover parameter was the strongest pre- dictor of peak snow accumulation (r 2 = 0.70, p < 0.001) and maximum snow ablation rate (r 2 = 0.59, p < 0.01). Improving our ability to quantify changes in forest structure in extensive areas will assist in developing more robust models of water- shed processes.

[1]  W. Cohen,et al.  Lidar Remote Sensing for Ecosystem Studies , 2002 .

[2]  Joanne C. White,et al.  The role of LiDAR in sustainable forest management , 2008 .

[3]  Michael A. Wulder,et al.  Surveying mountain pine beetle damage of forests: A review of remote sensing opportunities , 2006 .

[4]  Kenneth N. Brooks,et al.  Hydrology and the Management of Watersheds , 1991 .

[5]  R. Winkler,et al.  Measured differences in snow accumulation and melt among clearcut, juvenile, and mature forests in southern British Columbia , 2005 .

[6]  D. J. Mulla,et al.  Hydrology and the Management of Watersheds, 3rd ed. , 2003 .

[7]  R. G. Mitchell,et al.  Fall Rate of Lodgepole Pine Killed by the Mountain Pine Beetle in Central Oregon , 1998 .

[8]  John W. Pomeroy,et al.  Prediction of seasonal snow accumulation in cold climate forests , 2002 .

[9]  Nicholas C. Coops,et al.  Forest canopy effects on snow accumulation and ablation: an integrative review of empirical results. , 2010 .

[10]  Patrick Teti,et al.  Effects of overstory mortality on snow accumulation and ablation , 2008 .

[11]  R. Hudson.  Snowpack recovery in regenerating coastal British Columbia clearcuts , 2000 .

[12]  R. Moore,et al.  Variability in snow accumulation patterns within forest stands on the interior plateau of British Columbia, Canada , 2006 .

[13]  S. Reutebuch,et al.  Estimating forest canopy fuel parameters using LIDAR data , 2005 .

[14]  D. R. Stevenson,et al.  Managing snow accumulation and melt under leafless aspen to enhance watershed value , 1971 .

[15]  E. Næsset.  Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data , 2002 .

[16]  Rodney J. Keenan,et al.  Planted forests and water in perspective , 2007 .

[17]  Sarah Boon,et al.  Snow ablation energy balance in a dead forest stand , 2009 .

[18]  Nicholas C. Coops,et al.  Evaluating error associated with lidar-derived DEM interpolation , 2009, Comput. Geosci..

[19]  Dennis P. Lettenmaier,et al.  Application of a GIS-based distributed hydrology model for prediction of forest harvest effects on peak stream flow in the Pacific Northwest , 1998 .

[20]  Laura Chasmer,et al.  Towards a universal lidar canopy height indicator , 2006 .

[21]  Y. Alila,et al.  Effects of pine beetle infestations and treatments on hydrology and geomorphology: integrating stand-level data and knowledge into mesoscale watershed functions. , 2009 .

[22]  R. Davis,et al.  Snow ablation modelling in a mature aspen stand of the boreal forest , 1998 .

[23]  Younes Alila,et al.  The influence of forest and topography on snow accumulation and melt at the watershed-scale , 2007 .

[24]  Petteri Packalen,et al.  Airborne laser scanning-based prediction of coarse woody debris volumes in a conservation area , 2008 .

[25]  S. Rood,et al.  Declining summer flows of Rocky Mountain rivers: Changing seasonal hydrology and probable impacts on floodplain forests , 2008 .

[26]  S. Halldin,et al.  Snow interception evaporation. Review of measurementtechniques, processes, and models , 2001 .

[27]  N. Coops,et al.  Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests , 2003 .

[28]  R. Sibson,et al.  A brief description of natural neighbor interpolation , 1981 .

[29]  Mingguang Xu,et al.  Foliage biomass distribution of loblolly pine as affected by tree dominance, crown size, and stand characteristics , 1998 .

[30]  M. Carver,et al.  Using indicators to assess hydrologic risk. , 2000 .

[31]  T. R. Dell,et al.  Quantifying Diameter Distributions with the Weibull Function , 1973 .

[32]  I. Creed,et al.  Advances in Canadian forest hydrology, 1999–2003 , 2005 .

[33]  John W. Pomeroy,et al.  Measurements and modelling of snow interception in the boreal forest , 1998 .

[34]  E. Næsset,et al.  Weibull and percentile models for lidar-based estimation of basal area distribution , 2005 .

[35]  Robert L. Hendrick,et al.  Application of Environmental Analysis to Watershed Snowmelt , 1971 .

[36]  Martyn P. Clark,et al.  DECLINING MOUNTAIN SNOWPACK IN WESTERN NORTH AMERICA , 2005 .

[37]  John W. Pomeroy,et al.  Coupled Modelling of Forest Snow Interception and Sublimation , 1998 .

[38]  A. D. Gordon,et al.  Interpreting multivariate data , 1982 .

[39]  Klaus I. Itten,et al.  Assessment of the influence of flying altitude and scan angle on biophysical vegetation products derived from airborne laser scanning , 2008 .

[40]  R. Pike,et al.  Hydrologic effects of mountain pine beetle in the interior pine forests of British Columbia: Key questions and current knowledge , 2006 .

[41]  J. Buttle,et al.  Impacts of clearcut harvesting on snow accumulation and melt in a northern hardwood forest , 2002 .

[42]  W. Kurz,et al.  Mountain pine beetle and forest carbon feedback to climate change , 2008, Nature.

[43]  Nicholas C. Coops,et al.  Assessing differences in tree and stand structure following beetle infestation using lidar data , 2009 .

[44]  R. Essery,et al.  Sublimation of Snow from Coniferous Forests in a Climate Model , 2003 .

[45]  Nicholas C. Coops,et al.  A new low-cost, stand-alone sensor system for snow monitoring. , 2010 .

[46]  E. Næsset.  Effects of different sensors, flying altitudes, and pulse repetition frequencies on forest canopy metrics and biophysical stand properties derived from small-footprint airborne laser data , 2009 .

[47]  E. Næsset.  Practical large-scale forest stand inventory using a small-footprint airborne scanning laser , 2004 .

[48]  M. Sambridge,et al.  Geophysical parametrization and interpolation of irregular data using natural neighbours , 1995 .

[49]  R. Swanson,et al.  Snow Distribution Patterns in Clearings and Adjacent Forest , 1986 .

[50]  S. Reutebuch,et al.  Light detection and ranging (LIDAR): an emerging tool for multiple resource inventory. , 2005 .

[51]  Svein Solberg,et al.  Assessment of defoliation during a pine sawfly outbreak: Calibration of airborne laser scanning data with hemispherical photography , 2007 .

[52]  R. D’eon.  Snow depth as a function of canopy cover and other site attributes in a forested ungulate winter range in southeast British Columbia , 2004, Journal of Ecosystems and Management.

[53]  H. W. Anderson,et al.  Effects of logging and brush removal on snow water runoff. , 1960 .

[54]  M. Flood,et al.  LiDAR remote sensing of forest structure , 2003 .

[55]  M. Eisenbies,et al.  Forest operations, extreme flooding events, and considerations for hydrologic modeling in the Appalachians--A review , 2007 .

[56]  S. Magnussen,et al.  Derivations of stand heights from airborne laser scanner data with canopy-based quantile estimators , 1998 .

[57]  D. Marks,et al.  Radiative transfer modeling of a coniferous canopy characterized by airborne remote sensing , 2008 .