Marmot Creek Research Basin Research Articles

Influence of forest canopy structure and wind flow on patterns of sub‐canopy snow accumulation in montane needleleaf forests

AbstractVegetation structure is considered one of the most important factors shaping the spatial variation of snow accumulation under forest canopies. However, fine scale relationships between canopy density, snow interception, wind redistribution and sub‐canopy accumulation are poorly understood and difficult to observe, and their influence governing stand‐scale snow distributions that determine snow covered area depletion during melt is largely unknown. In this study, fine‐scale observations of forest structure and sub‐canopy snow accumulation were analysed over two mid‐winter snowfalls to a sub‐alpine forest in Marmot Creek Research Basin, Canadian Rockies, Alberta, to identify the impact of snow‐canopy interactions on spatial patterns of sub‐canopy snow accumulation. High spatial resolution (5 and 25 cm) snow accumulation estimates and canopy structure metrics were calculated from the combination of repeated UAV‐lidar observations with snow and photographic surveys, utilizing novel resampling methods including voxel ray sampling of lidar (VoxRS) to improve metric robustness and reduce bias. Over 50% of the spatial variance in forest snow accumulation was found at length scales less than 2 m, supporting the role of local scale canopy structure in governing variation in subcanopy snow accumulation. Additionally, subcanopy snow accumulation showed significant angular spread in relationships with overhead canopy structure; the vertical asymmetry coinciding with local windflow directions during snowfall. Detailed angular analysis showed nontrivial snow‐vegetation relationships that likely reflect multiple snowfall‐vegetation processes, including unloading and entrainment of intercepted snowfall during wind gusts and funnelling of entrained particles by downwind vegetation. These fine‐scale findings suggest several emergent processes which may influence snow accumulation at the scale of forest stands, with novel considerations for representing snow water equivalent distributions under dense evergreen canopies under varying environmental and canopy conditions. Similar studies over a broad range of conditions and forests will help refine and generalize the effects observed here for further snow hydrology and forestry applications.

Diagnosis of future changes in hydrology for a Canadian Rockies headwater basin

Abstract. Climate change is anticipated to impact the hydrology of the Saskatchewan River, which originates in the Canadian Rockies mountain range. To better understand the climate change impacts in the mountain headwaters of this basin, a physically based hydrological model was developed for this basin using the Cold Regions Hydrological Modelling platform (CRHM) for Marmot Creek Research Basin (∼9.4 km2), located in the Front Ranges of the Canadian Rockies. Marmot Creek is composed of ecozones ranging from montane forests to alpine tundra and alpine exposed rock and includes both large and small clearcuts. The model included blowing and intercepted snow redistribution, sublimation, energy-balance snowmelt, slope and canopy effects on melt, Penman–Monteith evapotranspiration, infiltration to frozen and unfrozen soils, hillslope hydrology, streamflow routing, and groundwater components and was parameterised without calibration from streamflow. Near-surface outputs from the 4 km Weather Research and Forecasting (WRF) model were bias-corrected using the quantile delta mapping method with respect to meteorological data from five stations located from low-elevation montane forests to alpine ridgetops and running over October 2005–September 2013. The bias-corrected WRF outputs during a current period (2005–2013) and a future pseudo global warming period (PGW, 2091–2099) were used to drive model simulations to assess changes in Marmot Creek's hydrology. Under a “business-as-usual” forcing scenario, Representative Concentration Pathway 8.5 (RCP8.5) in PGW, the basin will warm up by 4.7 ∘C and receive 16 % more precipitation, which will lead to a 40 mm decline in seasonal peak snowpack, 84 mm decrease in snowmelt volume, 0.2 mm d−1 slower melt rate, and 49 d shorter snow-cover duration. The alpine snow season will be shortened by almost 1.5 months, but at some lower elevations there will be large decreases in peak snowpack (∼45 %) in addition to a shorter snow season. Declines in the peak snowpack will be much greater in clearcuts than under mature forest canopies. In alpine and treeline ecozones, blowing snow transport and sublimation will be suppressed by higher-threshold wind speeds for transport, in forest ecozones, sublimation losses from intercepted snow will decrease due to faster unloading and drip, and throughout the basin, evapotranspiration will increase due to a longer snow-free season and more rainfall. Runoff will begin earlier in all ecozones, but, as a result of variability in surface and subsurface hydrology, forested and alpine ecozones will generate the greatest runoff volumetric increases, ranging from 12 % to 25 %, whereas the treeline ecozone will have a small (2 %) decrease in runoff volume due to decreased melt volumes from smaller snowdrifts. The shift in timing in streamflow will be notable, with 236 % higher flows in spring months and 12 % lower flows in summer and 13 % higher flows in early fall. Overall, Marmot Creek's annual streamflow discharge will increase by 18 % with PGW, without a change in its streamflow generation efficiency, despite its basin shifting from primarily snowmelt runoff towards rainfall-dominated runoff generation.

Detecting intercepted snow on mountain needleleaf forest canopies using satellite remote sensing

Snow interception in cold regions needleleaf forest canopies is a crucial process that controls local snow accumulation and redistribution over >20% of the Earth's land surface. Various ground-based methods exist to measure intercepted snow load, however all are based on single-tree measurements and are difficult to implement. No research has focussed on detecting large areal intercepted snow loads and no studies have assessed the use of satellite observations. In this study, four remote sensing indices (NDSI, NDVI, albedo, and land surface temperature (LST)) were retrieved from Landsat images to study their sensitivity to canopy intercepted snow and the possibility of using them to detect the presence of intercepted snow. The results indicate that presence of intercepted snow on canopy increased NDSI and albedo, but decreased NDVI. Intercepted snow presence also decreased the areal variability of NDSI and NDVI while increasing that of albedo. For these three indices, the differences between snow-free and snowcovered canopies were correlated to topography and forest canopy cover. Of these indices, NDSI changed the greatest. Intercepted snow noticeably decreased the LST difference between forest and open areas in springtime while the influence in wintertime was relatively smaller. An intercepted snow detection approach that uses both NDSI and NDVI to classify pixels into either snowcovered canopy or other (snow-free canopy and non-forest areas) is proposed here. A case study applying this approach compared remote sensing detection to simulations by the snow interception and sublimation model implemented in the Cold Regions Hydrological Modelling platform (CRHM). This used local meteorological observations from the pine, spruce and fir forest covered Marmot Creek Research Basin in the Canadian Rockies. The remote sensing detection of intercepted snow agreed well with CRHM simulations for continuous forests (83%) and less well for sparse forests (72%) and clearings with small trees (70%). Therefore, the approach is suitable for intercepted snow detection over continuous evergreen canopies. This technique provides a new capability for large-scale snow interception model validation and data assimilation to cold regions hydrological forecasting models.

Hydrometeorological data from Marmot Creek Research Basin, Canadian Rockies

Abstract. Meteorological, snow survey, streamflow, and groundwater data are presented from Marmot Creek Research Basin, Alberta, Canada. The basin is a 9.4 km2, alpine–montane forest headwater catchment of the Saskatchewan River basin that provides vital water supplies to the Prairie Provinces of Canada. It was heavily instrumented, experimented upon, and operated by several federal government agencies between 1962 and 1986, during which time its main and sub-basin streams were gauged, automated meteorological stations at multiple elevations were installed, groundwater observation wells were dug and automated, and frequent manual measurements of snow accumulation and ablation and other weather and water variables were made. Over this period, mature evergreen forests were harvested in two sub-basins, leaving large clear cuts in one basin and a “honeycomb” of small forest clearings in another basin. Whilst meteorological measurements and sub-basin streamflow discharge weirs in the basin were removed in the late 1980s, the federal government maintained the outlet streamflow discharge measurements and a nearby high-elevation meteorological station, and the Alberta provincial government maintained observation wells and a nearby fire weather station. Marmot Creek Research Basin was intensively re-instrumented with 12 automated meteorological stations, four sub-basin hydrometric sites, and seven snow survey transects starting in 2004 by the University of Saskatchewan Centre for Hydrology. The observations provide detailed information on meteorology, precipitation, soil moisture, snowpack, streamflow, and groundwater during the historical period from 1962 to 1987 and the modern period from 2005 to the present time. These data are ideal for monitoring climate change, developing hydrological process understanding, evaluating process algorithms and hydrological, cryospheric, or atmospheric models, and examining the response of basin hydrological cycling to changes in climate, extreme weather, and land cover through hydrological modelling and statistical analyses. The data presented are publicly available from Federated Research Data Repository (https://doi.org/10.20383/101.09, Fang et al., 2018).

Impact of antecedent conditions on simulations of a flood in a mountain headwater basin

A devastating flood struck Southern Alberta in late June 2013, with much of its streamflow generation in the Front Ranges of the Rocky Mountains, west of Calgary. To better understand streamflow generation processes and their sensitivity to initial conditions, a physically based hydrological model was developed using the Cold Regions Hydrological Modelling platform (CRHM) to simulate the flood for the Marmot Creek Research Basin (~9.4 km2). The modular model includes major cold and warm season hydrological processes including snow redistribution, sublimation, melt, runoff over frozen and unfrozen soils, evapotranspiration, subsurface runoff on hillslopes, groundwater recharge and discharge and streamflow routing. Uncalibrated simulations were conducted for eight hydrological years and generally matched streamflow observations well, with a NRMSD of 52%, small model bias (−3%) and a Nash–Sutcliffe efficiency (NSE) of 0.71. The model was then used to diagnose the responses of hydrological processes in 2013 flood from different ecozones in Marmot Creek: alpine, treeline, montane forest and large and small forest clearings to better understand spatial variations in the flood runoff generation mechanisms. To examine the sensitivity to antecedent conditions, ‘virtual’ flood simulations were conducted using a week (17 to 24 June 2013) of flood meteorology imposed on the meteorology of the same period in other years (2005 to 2012), or switched with the meteorology of one week in different months (May to July) of 2013. Sensitivity to changing precipitation and land cover was assessed by varying the precipitation amount during the flood and forest cover and soil storage capacity in forest ecozone. The results show that runoff efficiency increases rapidly with antecedent snowpack and soil moisture storage with the highest runoff response to rainfall from locations in the basin where there are recently melted or actively melting snowpacks and resulting high soil moisture or frozen soils. The impact of forest canopy on flooding is negligible, but flood peak doubles if forest canopy removal is accompanied by 50% reduction in water storage capacity in the basin. Copyright © 2016 John Wiley & Sons, Ltd.

Marmot Creek Experimental Watershed Study

The origins and results of the scientific experiments in Marmot Creek Experimental Watershed, now the Marmot Creek Research Basin, over more than 50 years are reviewed. Marmot Creek was established to better understand how forest manipulations could be used to manage streamflow hydrographs and was actively manipulated in the 1970s and 1980s. While small forest clearings were shown to increase snow accumulation consistently, the impacts on melt rates depended on clearing size, slope and aspect. As a result, clearing treatments whether through large cutblocks or small clearings had modest impacts on the hydrograph timing and variability and only local impacts on streamflow volume. Changes in climate are primarily manifested as warming which has substantially reduced snowpacks at low elevations. These climate changes have not been evident in hydrograph change and there is no trend to volumes or timing of streamflow over the last 50 years. Overall the basin shows remarkable resiliency to climate and land use change due to its wide range of elevations, slopes, snow environments and sub-surface storage. The basin has become a hydrological process observatory where multi-scale models are developed and evaluated for operation over larger areas. It has served an invaluable role for this and the scientific results from Marmot Creek have supported the development of global climate models and hydrological models that are now applied throughout the world.

Hydrological resilience of a Canadian Rockies headwaters basin subject to changing climate, extreme weather, and forest management

AbstractMarmot Creek Research Basin in the Canadian Rockies has been the site of intensive streamflow, groundwater, snow accumulation, precipitation, and air temperature observations at multiple elevations. The basin was instrumented in 1962, subjected to forestry experiments in the mid‐1970s, and experienced extreme flooding in 2013. Climate change, forest cover change, and recent extreme weather make the basin an ideal laboratory for studying hydrological resilience. Observations show increases in low elevation air temperature, multiple day and spring precipitation, interannual variability of precipitation, and high elevation groundwater levels. Observations also show decreases in peak seasonal snow accumulation and low elevation groundwater levels. Despite these substantial hydrometeorological and groundwater changes, streamflow volume, timing of peak, and magnitude of the peak are not changing. Streamflow volumes are also insensitive to forest cover changes and teleconnections. The June 2013 flood was unprecedented in the period of record, and the basin significantly moderated the hydrological response to the extreme precipitation; the 2013 storm precipitation depth was 65% greater than the next highest storm total over 51 years; however, the 2013 peak streamflow was only 32% greater than the next highest peak flow recorded. The hydrology of Marmot Creek Research Basin displays remarkable resilience to changing climate, extreme weather, and forest cover change. Copyright © 2015 John Wiley & Sons, Ltd.

Estimating precipitation phase using a psychrometric energy balance method

AbstractPrecipitation phase is fundamental to a catchment's hydrological response to precipitation events. Phase is particularly variable over time and space in the Canadian Rockies where snowfall or rainfall can occur any month of the year. Phase is controlled by the microphysics of the falling hydrometeor, but microphysical calculations require detailed atmospheric information that is often lacking for hydrological analyses. In hydrology, there have been many methods developed to estimate phase, but most are regionally calibrated, and many depend on air temperature (Ta) and use daily time steps. Phase is not only related to Ta, but to other meteorological variables, and precipitation events are temporally dynamic, adding uncertainty to the use of daily indices to estimate phase. To better predict precipitation phase, the psychrometric energy balance of a falling hydrometeor was calculated and used to develop a method to estimate precipitation phase. High quality precipitation phase and meteorological data were observed at multiple elevations in a small Canadian Rockies catchment, Marmot Creek Research Basin, at 15‐min intervals over several years to develop and test the method. The results of the psychrometric energy balance method were compared to phase observations, to other methods over varying time scales and seasons and at varying elevations and topographic exposures. The results indicate that the psychrometric energy balance method performs much better than Ta index methods and that this improvement, and the accuracy of the psychrometric energy balance method, increases as the time step of calculation decreases. Copyright © 2013 John Wiley & Sons, Ltd.

Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

Abstract. One of the purposes of the Cold Regions Hydrological Modelling platform (CRHM) is to diagnose inadequacies in the understanding of the hydrological cycle and its simulation. A physically based hydrological model including a full suite of snow and cold regions hydrology processes as well as warm season, hillslope and groundwater hydrology was developed in CRHM for application in the Marmot Creek Research Basin (~ 9.4 km2), located in the Front Ranges of the Canadian Rocky Mountains. Parameters were selected from digital elevation model, forest, soil, and geological maps, and from the results of many cold regions hydrology studies in the region and elsewhere. Non-calibrated simulations were conducted for six hydrological years during the period 2005–2011 and were compared with detailed field observations of several hydrological cycle components. The results showed good model performance for snow accumulation and snowmelt compared to the field observations for four seasons during the period 2007–2011, with a small bias and normalised root mean square difference (NRMSD) ranging from 40 to 42% for the subalpine conifer forests and from 31 to 67% for the alpine tundra and treeline larch forest environments. Overestimation or underestimation of the peak SWE ranged from 1.6 to 29%. Simulations matched well with the observed unfrozen moisture fluctuation in the top soil layer at a lodgepole pine site during the period 2006–2011, with a NRMSD ranging from 17 to 39%, but with consistent overestimation of 7 to 34%. Evaluations of seasonal streamflow during the period 2006–2011 revealed that the model generally predicted well compared to observations at the basin scale, with a NRMSD of 60% and small model bias (1%), while at the sub-basin scale NRMSDs were larger, ranging from 72 to 76%, though overestimation or underestimation for the cumulative seasonal discharge was within 29%. Timing of discharge was better predicted at the Marmot Creek basin outlet, having a Nash–Sutcliffe efficiency (NSE) of 0.58 compared to the outlets of the sub-basins where NSE ranged from 0.2 to 0.28. The Pearson product-moment correlation coefficient of 0.15 and 0.17 for comparisons between the simulated groundwater storage and observed groundwater level fluctuation at two wells indicate weak but positive correlations. The model results are encouraging for uncalibrated prediction and indicate research priorities to improve simulations of snow accumulation at treeline, groundwater dynamics, and small-scale runoff generation processes in this environment. The study shows that improved hydrological cycle model prediction can be derived from improved hydrological understanding and therefore is a model that can be applied for prediction in ungauged basins.

Implications of mountain shading on calculating energy for snowmelt using unstructured triangular meshes

AbstractIn many parts of the world, snowmelt energetics is dominated by solar irradiance. This is particularly the case in the Canadian Rocky Mountains, where clear skies dominate the winter and spring. In mountainous regions, solar irradiance at the snow surface is not only affected by solar angles, atmospheric transmittance, the slope and aspect of immediate topography but also by shadows from surrounding terrain. Accumulation of errors in estimating solar irradiation can lead to significant errors in calculating the timing and rate of snowmelt owing to the seasonal storage of internal energy in the snowpack. Gridded methods, which are often used to estimate solar irradiance in complex terrain, work best with high‐resolution digital elevation models (DEMs), such as those produced using Light Detection and Ranging. However, such methods also introduce errors caused by the rigid nature of the mesh as well as limiting the ability to represent basin characteristics. Unstructured triangular meshes are more efficient in their use of DEM data than fixed grids when producing solar irradiance information for spatially distributed snowmelt calculations, and they do not suffer from the artefact problems of a gridded DEM. This paper demonstrates the increased accuracy of using a horizon‐shading algorithm model with an unstructured mesh versus standard self‐shading algorithms. A systematic over‐prediction in irradiance is observed when only self‐shadows are considered. The modelled results are diagnosed by comparison to measurements of mountain shadows by time‐lapse digital cameras and solar irradiance by a network of radiometers in Marmot Creek Research Basin, Alberta, Canada. Results show that, depending on the depth and aspect of the snowpack of the Mount Allan cirque, 6.0 to 66.4% of the pre‐melt snowpack could be prematurely melted. On average at a basin scale, there was a 14.4‐mm SWE difference in equivalent melt energy between the two shading algorithms with maximum differences over 100% of the total annual snowfall. Copyright © 2012 John Wiley & Sons, Ltd.

Modelling longwave radiation to snow beneath forest canopies using hemispherical photography or linear regression

AbstractForest canopies reduce shortwave radiation and increase longwave radiation reaching the underlying surface, compared with open areas, and thus influence rates at which forest snowpacks melt. The sub‐canopy radiative environment can be highly heterogeneous, with temporal persistence depending on canopy structure and differing for shortwave and longwave fluxes, and this influences the rate at which snow‐free ground emerges during snowmelt. Arrays of radiometers have been used to measure spatial variability in forest radiation, but such instruments are expensive and require regular attention in snowy environments. Hemispherical photography allows rapid collection of canopy structure data, and many software packages have been developed for modelling transmission of shortwave radiation using hemispherical photographs, but modelling of longwave radiation has received much less attention. Results are used here from radiometers located beneath lodgepole pine stands of varying density at the Marmot Creek Research Basin in Alberta, Canada. A simple model using sky view calculated from hemispherical photographs to weight longwave emissions from the canopy, calculated using measured air temperature as a proxy for canopy temperature, and measured above‐canopy longwave radiation is found to give good estimates for spatial averages of sub‐canopy longwave radiation, although standard deviations are generally underestimated. If above‐canopy longwave radiation is parametrized as a function of air temperature and humidity rather than measured, good results are still obtained for daily and longer averages of sub‐canopy longwave radiation. A multiple linear regression model using measurements of above‐canopy shortwave radiation to estimate daytime canopy heating gives better results in comparison with individual radiometers. Copyright © 2008 John Wiley & Sons, Ltd.

Estimating sub‐canopy shortwave irradiance to melting snow on forested slopes

AbstractEstimates of shortwave irradiance energy beneath needle‐leaf forests over complex terrain are needed to drive energy balance snowmelt models and to evaluate the potential hydrological impacts of forest‐cover change in mountain regions. This paper outlines and evaluates a physically‐based model designed to estimate sub‐canopy shortwave irradiance to snowcover under needle‐leaf forest‐cover with respect to surface slope and azimuth. Transmission of above‐canopy irradiance was estimated using forest‐surveys and hemispherical photographs to determine the fractions of forest‐cover occupied by non‐transmitting trunks, partially‐transmitting crowns and fully‐transmitting gaps with respect to above‐canopy diffuse and direct beam shortwave irradiance. Simulations were conducted for continuous, uniform lodgepole pine forests on level site and a north facing slope and a discontinuous, non‐uniform forest on a southeast facing slope during snowmelt at the Marmot Creek Research Basin, Alberta, Canada. Mean observed daily transmissivity values of irradiance were 0·09 at the north‐facing forest, 0·21 at the level forest and 0·36 at the southeast‐facing forest. Modelled and observed results indicate that potential snowmelt energy from sub‐canopy shortwave irradiance is likely to exhibit the greatest variation with change in cloudiness and forest‐cover density under south‐facing forests and the least variation under north‐facing forests. Comparisons of simulations to observations indicate that the model can explain much of the difference in daily shortwave transmission amongst sites, performing relatively poorest at the north‐facing forest where fluxes were small and relatively best at the south‐east facing forest where fluxes were large. However, simulation errors in terms of absolute irradiance were greatest at the southeast‐facing forest, having a root mean square error (RMSE) 0·64 MJ m−2d−1 compared to 0·44 MJ m−2d−1 at the level forest and 0·27 MJ m−2d−1 at the north‐facing forest. Copyright © 2007 John Wiley & Sons, Ltd.