USE OF TIME-LAPSE PHOTOGRAPHY TO ASSESS POTENTIAL INTERCEPTION IN ARIZONA PONDEROSA PINE1

ABSTRACT: The behavior of intercepted snow on a stand of uneven-aged ponderosa pine in east-central Arizona was evaluated with the use of a super 8-mm time lapse movie camera to determine the relative significance of snowfall interception in the water yield of this type forest. A snow load index was developed to estimate interception storage for two trees in the field of view for discrete time periods. The snow load index. photographs, and climatic data were combined to describe accumulation and to identify and rank according to relative magnitudes the basic processes of canopy snow removal. The rate of snow accumulation was nonlinear with initial storage being rapid. then slowing with time. Most of the intercepted snow eventually reached the snowpack on the ground by snowslide and wind erosion or by snowmelt and subsequent stemflow and drippmg of meltwater, and was therefore not considered a significant loss to the water budget on site. Some water apparently was disposed of by the evaporation of meltwater and sublimation of canopy snow, but these losses appeared to be comparatively minor.     

FOREST GROWTH IMPACT ON PEAK SNOW PACK MEASUREMENTS AT LONG TERM SNOW COURSES1

ABSTRACT: Snow course surveys in late winter provide stream‐flow forecasters with their best information for making water supply and flood forecasts for the subsequent spring and summer runoff period in mountainous regions of western North America. Snow survey data analyses are generally based on a 30‐year “normal” period. It is well documented that forest cover changes over time will affect snow accumulation on the ground within forests. This paper seeks to determine if forest cover changes over decades at long term snow courses decrease measured peak snow water equivalent (SWE) enough to affect runoff prediction. Annual peak SWE records were analyzed at four snow courses in two different forest types having at least 25 years of snowpack data to detect any decreases in SWE due to forest growth. No statistically significant decreases in annual peak SWE over time were found at any of these four snow courses. The wide range of annual winter precipitation and correspondingly highly variable peak snowpack accumulation, as well as many other weather and site variables, masked any minor trends in the data.     

iTree‐Hydro: Snow Hydrology Update For The Urban Forest Hydrology Model1

Yang, Yang, Theodore A. Endreny, and David J. Nowak, 2011. iTree‐Hydro: Snow Hydrology Update for the Urban Forest Hydrology Model. Journal of the American Water Resources Association (JAWRA) 47(6):1211–1218. DOI: 10.1111/j.1752‐1688.2011.00564.x Abstract: This article presents snow hydrology updates made to iTree‐Hydro, previously called the Urban Forest Effects—Hydrology model. iTree‐Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process‐based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate hydrology routines presented in this update to iTree‐Hydro include: (1) snow interception to simulate the capture of snow by the vegetation canopy, (2) snow unloading to simulate the release of snow triggered by wind, (3) snowmelt to simulate the solid to liquid phase change using a heat budget, and (4) snow sublimation to simulate the solid to gas phase via evaporation. Cold climate hydrology routines were tested with research‐grade snow accumulation and weather data for the winter of 1996‐1997 at Umpqua National Forest, Oregon. The Nash‐Sutcliffe efficiency for open area snow accumulation was 0.77 and the Nash‐Sutcliffe efficiency for under canopy was 0.91. The USDA Forest Service offers iTree‐Hydro for urban forest hydrology simulation through http://www.iTreetools.org .     

THE POTENTIAL FOR INCREASING STREAMFLOW FROM SIERRA NEVADA WATERSHEDS1

The Sierra Nevada produces over 50 percent of California's water. Improvement of water yields from the Sierra Nevada through watershed management has long been suggested as a means of augmenting the state's water supply. Vegetation and snowpack management can increase runoff from small watersheds by reducing losses due to evapotranspiration, snow interception by canopy, and snow evaporation. Small clearcuts or group selection cuts creating openings less than half a hectare, with the narrow dimension from south to north, appear to be ideal for both increasing and delaying water delivery in the red fir-lodgepole pine and mixed-conifer types of the Sierra west slope. Such openings can have up to 40 percent more snow-water equivalent than does uncut forest. However, the water yield increase drops to 1/2-2 percent of current yield for an entire management unit, due to the small number of openings that can be cut at one time, physical and management constraints, and multiple use/sustained yield guidelines. As a rough forecast, water production from National Forest land in the Sierra Nevada can probably be increased by about 1 percent (0.6 cm) under intensive forest watershed management. Given the state of reservoir storage and water use in California, delaying streamflow is perhaps the greatest contribution watershed management can make to meeting future water demands.     

Management Implications of Snowpack Sensitivity to Temperature and Atmospheric Moisture Changes in Yosemite National Park,CA

In order to investigate snowpack sensitivity to temperature increases and end‐member atmospheric moisture conditions, we applied a well‐constrained energy‐ and mass‐balance snow model across the full elevation range of seasonal snowpack using forcing data from recent wet and dry years. Humidity scenarios examined were constant relative humidity (high) and constant vapor pressure between storms (low). With minimum calibration, model results captured the observed magnitude and timing of snowmelt. April 1 snow water equivalent (SWE) losses of 38%, 73%, and 90% with temperature increases of 2, 4, and 6°C in a dry year centered on areas of greatest SWE accumulation. Each 2°C increment of warming also resulted in seasonal snowline moving upslope by 300 m. The zone of maximum melt was compressed upward 100–500 m with 6°C warming, with the range reflecting differences in basin hypsometry. Melt contribution by elevations below 2,000 m disappeared with 4°C warming. The constant‐relative‐humidity scenario resulted in 0–100 mm less snowpack in late spring vs. the constant‐vapor‐pressure scenario in a wet year, a difference driven by increased thermal radiation (+1.2 W/m²) and turbulent energy fluxes (+1.2 W/m²) to the snowpack for the constant‐relative‐humidity case. Loss of snowpack storage and potential increases in forest evapotranspiration due to warming will result in a substantial shift in forest water balance and present major challenges to land management in this mountainous region.     

GENERAL-CIRCULATION-MODEL SIMULATIONS OF FUTURE SNOWPACK IN THE WESTERN UNITED STATES1

ABSTRACT: April 1 snowpack accumulations measured at 311 snow courses in the western United States (U.S.) are grouped using a correlation-based cluster analysis. A conceptual snow accumulation and melt model and monthly temperature and precipitation for each cluster are used to estimate cluster-average April 1 snowpack. The conceptual snow model is subsequently used to estimate future snowpack by using changes in monthly temperature and precipitation simulated by the Canadian Centre for Climate Modeling and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HADLEY) general circulation models (GCMs). Results for the CCC model indicate that although winter precipitation is estimated to increase in the future, increases in temperatures will result in large decreases in April 1 snowpack for the entire western U.S. Results for the HADLEY model also indicate large decreases in April 1 snowpack for most of the western US, but the decreases are not as severe as those estimated using the CCC simulations. Although snowpack conditions are estimated to decrease for most areas of the western US, both GCMs estimate a general increase in winter precipitation toward the latter half of the next century. Thus, water quantity may be increased in the western US; however, the timing of runoff will be altered because precipitation will more frequently occur as rain rather than as snow.     

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.     

Observed Changes in Climate and Streamflow in the Upper Rio Grande Basin

Observed streamflow and climate data are used to test the hypothesis that climate change is already affecting Rio Grande streamflow volume derived from snowmelt runoff in ways consistent with model‐based projections of 21st‐Century streamflow. Annual and monthly changes in streamflow volume and surface climate variables on the Upper Rio Grande, near its headwaters in southern Colorado, are assessed for water years 1958–2015. Results indicate winter and spring season temperatures in the basin have increased significantly, April 1 snow water equivalent (SWE) has decreased by approximately 25%, and streamflow has declined slightly in the April–July snowmelt runoff season. Small increases in precipitation have reduced the impact of declining snowpack on trends in streamflow. Changes in the snowpack–runoff relationship are noticeable in hydrographs of mean monthly streamflow, but are most apparent in the changing ratios of precipitation (rain + snow, and SWE) to streamflow and in the declining fraction of runoff attributable to snowpack or winter precipitation. The observed changes provide observational confirmation for model projections of decreasing runoff attributable to snowpack, and demonstrate the decreasing utility of snowpack for predicting subsequent streamflow on a seasonal basis in the Upper Rio Grande Basin.     

Effect of Snow Cover Conditions on the Hydrologic Regime: Case Study in a Pluvial‐Nival Watershed,Japan1

Abstract: Hydrologic monitoring in a small forested and mountainous headwater basin in Niigata Prefecture has been undertaken since 2000. An important characteristic of the basin is that the hydrologic regime contains pluvial elements year‐round, including rain‐on‐snow, in addition to spring snowmelt. We evaluated the effect of different snow cover conditions on the hydrologic regime by analyzing observed data in conjunction with model simulations of the snowpack. A degree‐day snow model is presented and applied to the study basin to enable estimation of the basin average snow water equivalent using air temperature at three representative elevations. Analysis of hydrological time series data and master recession curves showed that flow during the snowmelt season was generated by a combination of ground water flow having a recession constant of 0.018/day and diurnal melt water flow having a recession constant of 0.015/hour. Daily flows during the winter/snowmelt season showed greater persistence than daily flows during the warm season. The seasonal water balance indicated that the ratio of runoff to precipitation during the cold season (December to May) was about 90% every year. Seasonal snowpack plays an important role in defining the hydrologic regime, with winter precipitation and snowmelt runoff contributing about 65% of the annual runoff. The timing of the snowmelt season, indicated by the date of occurrence of the first significant snowmelt event, was correlated with the occurrence of low flow events. Model simulations showed that basin average snow water equivalent reached a peak around mid‐February to mid‐March, although further validation of the model is required at high elevation sites.     

Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM1

Harshburger, Brian J., Karen S. Humes, Von P. Walden, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2010. Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM. Journal of the American Water Resources Association (JAWRA) 46(3):603-617. DOI: 10.1111/j.1752-1688.2010.00437.x Abstract: As demand for water continues to escalate in the western United States, so does the need for accurate streamflow forecasts. Here, we describe a methodology for generating short-to-medium range (1 to 15 days) streamflow forecasts using an enhanced version of the Snowmelt Runoff Model (SRM), snow-covered area data derived from MODIS products, data from Snow Telemetry stations, and meteorological forecasts. The methodology was tested on three mid-elevation, snowmelt-dominated basins ranging in size from 1,600 to 3,500 km². To optimize the model performance and aid in its operational implementation, two enhancements have been made to SRM: (1) the use of an antecedent temperature index method to track snowpack cold content, and (2) the use of both maximum and minimum critical temperatures to partition precipitation into rain, snow, or a mixture of rain and snow. The comparison of retrospective model simulations with observed streamflow shows that the enhancements significantly improve the model performance. Streamflow forecasts generated using the enhanced version of the model compare well with the observed streamflow for the earlier leadtimes; forecast performance diminishes with leadtime due to errors in the meteorological forecasts. The three basins modeled in this research are typical of many mid-elevation basins throughout the American West, thus there is potential for this methodology to be applied successfully to other mountainous basins.     

ESTIMATED RUNOFF FROM MAN-MADE SNOW1

ABSTRACT: The consumptive loss from man-made snowmaking at six Colorado ski areas is calculated. The focus of the procedures in this investigation is on the consumptive loss that occurs to man-made snow particles during the period they reside on or in the snowpack until spring snowmelt (termed the watershed loss). Calculated watershed losses under a variety of precipitation and temperature conditions at six ski areas varied from 7 to 33 percent. These calculations were made using the calibrated Subalpine Water Balance Simulation Model (Leaf and Brink, 1973a, 1973b). The watershed loss of 7 to 33 percent indicates the range of likely watershed losses that can be expected at Colorado ski areas. A previous paper by the authors (Eisel et al., 1988) provided estimates of the mean consumptive loss during the snowmaking process (termed initial loss) for conditions existing at Colorado ski areas to be 6 percent of water applied. Therefore, based on the mean initial loss, the total consumptive loss from man-made snowmaking under conditions found at Colorado ski areas could be expected to range from 13 to 37 percent. These results demonstrate the range of total consumptive losses that could be expected in various years and for various watershed conditions. These total percentage losses cannot be extrapolated directly to other specific sites because the total consumptive loss is dependent on temperature during actual snowmaking, temperature and precipitation throughout the winter at the specific ski area, and watershed conditions at the ski area. Consumptive losses to man-made snow for a specific ski area should be estimated using the handbook procedures developed especially for this purpose (Colorado Ski Country USA, 1986b).     

A COMPARISON OF GEOSTATISTICAL METHODOLOGIES USED TO ESTIMATE SNOW WATER EQUIVALENT1

ABSTRACT: The need to monitor and forecast water resources accurately, particularly in the western United States, is becoming increasingly critical as the demand for water continues to escalate. Consequently, the National Weather Service (NWS) has developed a geostatistical model that is used to obtain areal estimates of snow water equivalent (the thtal water content in all phases of the snowpack), a major source of water in the West. The areal snow water equivalent estimates are used to update the hydrologic simulation models maintained by the NWS and designed to produce extended streamflow forecasts for river systems throughout the United States. An alternative geostatistical technique has been proposed to estimate snow water equivalent. In this research, we describe the two methodologies and compare the accuracy of the estimates produced by each technique. We illustrate their application and compare their estimation accuracy using snow data collected in the North Fork Clearwater River basin in Idaho.     

Spatiotemporal Variability of Snow Depletion Curves Derived from SNODAS for the Conterminous United States, 2004‐2013

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental‐scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental‐extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1‐km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed‐scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed‐scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national‐scale categorization of snowmelt processes.     

THE POTENTIAL FOR WATER YIELD AUGMENTATION FROM FOREST MANAGEMENT IN THE ROCKY MOUNTAIN REGION1

With the exception of the Sierra-Cascade mountain ranges, the Rocky Mountain chain is the only portion of the western United States that consistently yields more than 3 cm of flow annually. Ten to 15 percent of the land mass in the region produces the majority of the total flow. This paper addresses the opportunities for increasing flow through forest manipulation, and summarizes the research base that has yielded the current “state of the art” understanding of how snow pack and vegetation management can influence water yield. The optimal harvest design appears to consist of small openings, irregularly shaped, and about 3 to 8 tree heights in width parallel to the wind.     

Trends in Raindrop Kinetic Energy with Modeled Climate Warming in the Lake Tahoe Basin

Two means by which climate change may increase surface soil erosion in mountainous terrain are: (1) increasing the frequency of extreme rainfall events and (2) decreasing the duration of snow cover on bare soil. We used output from four general circulation models (GCMs) and two greenhouse gas trajectories to produce a suite of hydrologic variables at a daily time‐step for historic and projected 21st Century conditions. We statistically disaggregated the daily rainfall to hourly, using hourly rainfall from a network of nine weather stations in the Tahoe Basin, and filtered out rain falling on a snowpack. We applied published equations to convert hourly intensity to raindrop kinetic energy (KE) for each day and grid cell in the Basin, averaged across grid cells, and created time series of total annual and maximum annual hourly kinetic energy (TKE and MKE) on snow‐free ground. Using the Generalized Extreme Value distribution, we calculated the significance of long‐term trends in KE on snow‐free ground, and estimated energy levels for return periods of 2, 20, and 100 years. We then detrended the snowpack data and compared the resulting trends in KE with the trends resulting from changes in both rainfall energy and snowpack under two GCMs. Principal findings include (1) upward trends in MKE, (2) stronger upward trends in TKE; and (3) an effect of increasing rainfall intensities on KE in some cases, and a strong effect of reduced snowpack in all cases examined.     

Trends in Western U.S. Snowpack and Related Upper Colorado River Basin Streamflow1

Miller, W. Paul and Thomas C. Piechota, 2011. Trends in Western U.S. Snowpack and Related Upper Colorado River Basin Streamflow. Journal of the American Water Resources Association (JAWRA) 47(6):1197–1210. DOI: 10.1111/j.1752‐1688.2011.00565.x Abstract: Water resource managers in the Western United States (U.S.) are currently faced with the challenge of adapting to unprecedented drought and uncertain impacts of climate change. Recent research has indicated increasing regional temperature and changes to precipitation and streamflow characteristics throughout the Western U.S. As such, there is increased uncertainty in hydroclimatological forecasts, which impact reservoir operations and water availability throughout the Western U.S., particularly in the Colorado River Basin. Previous research by the authors hypothesized a change in the character of precipitation (i.e., the frequency and amount of rainfall and snowfall events) throughout the Colorado River Basin. In the current study, 398 snowpack telemetry stations were investigated for trends in cumulative precipitation, snow water equivalent, and precipitation events. Observations of snow water equivalent characteristics were compared to observations in streamflow characteristics. Results indicate that the timing of the last day of the snow season corresponds well to the volume of runoff observed over the traditional peak flow season (April through July); conversely, the timing of the first day of the snow season does not correspond well to the volume of runoff observed over the peak flow season. This is significant to water resource managers and river forecasters, as snowpack characteristics may be indicative of a productive or unproductive runoff season.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

SNOW: NATURE'S RESERVOIR1

ABSTRACT: Snow, one of Nature's greatest reservoirs, supplies most of the usable water in the Western United States. Reliable predictions of the quantity and timing of the release of this water are used in making management decisions involving irrigation, stock water and municipal water supplies, hydro-power generation, recreation, navigation, and pollution control Practically oriented research is vital for the proper development and management of this resource. In southwestern Idaho, the Northwest Watershed Research Center, ARS, USDA, is conducting intensive investigations for assessing snow Volumes, snow water content, and snow-melt over a watershed. Application of these research findings will result in better development and management of the water stored as snow in Nature's reservoir.     

ENERGY BALANCE OF A CORN RESIDUE-COVERED FIELD DURING SNOWMELT1

ABSTRACT: Transport of agricultural chemicals in runoff and recharge waters from snowmelt and soil thawing may represent a significant event in terms of annual contaminant loadings in temperate regions. Improved understanding of the melt dynamics of shallow snowpacks is necessary to fully assess the implications for water quality. The objective of this study was to measure the energy balance components of a corn (Zea mays L.) stubble field during the melting of its snowcover. Net radiation (Rn), soil (G), sensible (H), and latent (Q) heat fluxes were measured in a field near Ames, Iowa, during the winter of 1994–1995. Energy consumed by melting including change in energy storage of the snowpack was determined as the residual of the measured energy balance. There was continuous snowcover at the field site for 71 days (maximum depth = 222 mm) followed by an open period of 11 days before additional snowfall and a second melt period. The net radiation and snow melt/energy storage change (5) terms dominated the energy balance during both measurement intervals. Peak daily sensible and latent heat fluxes were below 100 W m^?2 on all days except the last day of the second melt period. There was good agreement between predicted and measured values of H and Q during the melting of an aged snow layer but poorer agreement during the melt of fresh snow. Both snowpacks melted rapidly and coincident changes in soil moisture storage were observed. Improved estimates of Q and H, especially for partially open surfaces, will require better characterization of the surface aerodynamic properties and spatially-representative surface temperature measurements.