Snow Survey at the Ancient Forest 27 January 2017

Transcription

1 Snow Survey at the Ancient Forest 27 January

2 Snow Survey 2

3 Tentative Agenda 3

4 Snow Survey Components Snow course for snow depth distribution. Snow core measurements for SWE. Snow pit for measurements and observations of snow temperature, snow grain sizes, layering and impurities. Meteorological data acquisition for interpretation of snowpack conditions. 4

5 Point measurements of snow depth Most simply, depth measurements of snow (snow accumulated on the ground) are made with a snow ruler or similar graduated rod that is pushed through the snow to the ground surface. Representative measurements by this method may be difficult to obtain in open areas since the snowcover undergoes drifting and may have embedded ice layers that limit penetration with a ruler. 5

6 Measurements of snow depth At each observing station a number of measurements are made and averaged. In remote regions, graduated snow stakes or aerial markers may be used. The snow depth at the stake or marker is observed from a distant point through binoculars or telescopes. However, rulers, stakes and aerial markers do not provide SWE information. 6

7 Sonic Ranger Automatic snow depth measure Determines the distance to a target by sending out ultrasonic pulses and listening for the returning echoes that are reflected from the target The time from transmission to return of an echo is used to obtain the distance measurement Air temperature correction required for variations in the speed of sound in air 7

8 Sonic Ranger January 20 th,

9 March 23 rd, 2012

10 March 20 th, 2013

11 Snow depth distribution Neumann et al. (2006) 11

12 Neumann et al. (2006) 12

13 April 28 th, 2011 May 10 th, 2011

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16 Snow Water Equivalent (SWE) The vertical depth of water that would be obtained by melting snow Snowfall measurement can be problematic Determining SWE from snowpack depth can be problematic Assuming mean density 100 kg m -3 (i.e. 10:1 ratio) Regional density variations (new snow: kg m -3 ) Densification over time Measuring snowpack SWE is the standard by weight of snowpack sample 16

17 Snow Pillows An antifreeze filled bladder of various shapes, sizes, and materials. Minimum size based on expected winter SWE Pressure inside the pillow changes in response to the weight of snow Fluid pressure changes are measured with a manometer or pressure transducer data can be transmitted remotely 17

18 Snow Pillow tana.edu/hydrology/i mages/img_1053.jpg 18

19 Advantages: A non-destructive sampling technique Snow Pillows An automatic measure of SWE in remote locations Identify snowfall and snowmelt events Can provide rough estimates of loss of SWE Disadvantages: A point SWE measurement site representativeness important Bridging may occur separation of pillow from overlaying snow under measurement of SWE Snow pillow is a barrier to heat and moisture fluxes between snowpack and ground 19

20 Snow Pillows B.C. Ministry of Environment River Forecast Centre Automated Snow Pillows (ASPs) and manual snow surveys view ASP SWE graphs (daily) download temperature, precipitation, and SWE data from ASP sites (near real-time) download manual snow survey data Historic data present Over 50 active ASP sites and almost 200 snow survey sites in the province 20

21 Snow Surveys Measure snow depth, density and SWE Snow course is the line of permanently marked sampling points Repeat measurements at regular intervals throughout season Location and frequency of snow survey depends on purpose: 1) as index of SWE for spring runoff prediction 2) absolute measure for hydrologic, agricultural, ecologic, transportation, recreational, and engineering functions Snow survey data are the ultimate base of comparison for other methods 21

22 Snow Surveys Considerations What are you measuring SWE for? Where to set up snow course? How long should the snow course be? How many sample points per course? SWE depth sampling ratio? When and how often to sample? What equipment to use? 22

23 Index of SWE: Snow Surveys Purpose Choose high accumulation area Show changes in SWE Represent basin characteristics Forest cover; aspect; elevation Consistent instrumentation and methodology Absolute estimate of SWE: Account for biases Instrument, method, site Account for variability in snowcover Erosional/depositional areas Stratify by landscape features 23

24 Accessibility Snow Surveys Site Selection Representativeness of terrain/land cover Choose slightly sloping terrain Avoid steep slopes Avoid areas with land use disturbances i.e. logging, mining, construction Avoid microsite irregularities at sample points i.e. stumps, logs, ponding areas Avoid areas with snow removal activity 24

25 Snow Surveys Site Selection Snowmelt for testing melt models North and south aspect Radiation differences Open and forest cover Radiation differences Similar location, slope, elevation Same weather, vegetation Access 25

26 Longer in complex terrain Snow Surveys Course Length More samples in complex terrain Snow course can zig-zag Oversample initially Length and sample density adjusted based on selected precision level Fewer SWE than depth measurements possible Density shows least variability Calculate SWE at depth measurement points 26

27 Snow Surveys Course Length cont. Cumulative coefficient of variation (C.V.) standard deviation mean Measure of variability independent of scale C.V. = Plot cumulative C.V. against length of course How many samples before C.V. levels off? 27

28 Snow Surveys Equipment Graduated snow tube with cutter Various materials, cutter configurations, and sizes Larger diameter tubes for shallow snowpacks Graduations on outside to measure snow depth Slots in tube to view snow core Spring balance measures SWE directly Federal (formerly Mt. Rose) snow sampler 28

29 B.C. Snow Survey Sampling Guide Snow Surveys Methods recast/snow_surveys_manual.pdf 29

30 Snow Surveys Methods Weigh and record empty tube SWE. 2. Push tube straight into snow pack to ground. 3. Push and twist into ground to obtain soil plug. 30

31 Snow Surveys Methods Weigh and record empty tube SWE. 2. Push tube straight into snow pack to ground. 3. Push and twist into ground to obtain soil plug. 4. Record snow depth from outside of tube. 5. Carefully pull tube straight out of snowpack. 6. Check for soil plug. 31

32 Snow Surveys Methods Weigh and record empty tube SWE. 2. Push tube straight into snow pack to ground. 3. Push and twist into ground to obtain soil plug. 4. Record snow depth from outside of tube. 5. Carefully pull tube straight out of snow pack. 6. Check for soil plug. 7. Remove soil plug and estimate depth of soil in tube. 32

33 Snow Surveys Methods Weigh and record empty tube SWE. 2. Push tube straight into snow pack to ground. 3. Push and twist into ground to obtain soil plug. 4. Record snow depth from outside of tube. 5. Carefully pull tube straight out of snow pack. 6. Check for soil plug. 7. Remove soil plug and estimate depth of soil in tube. 8. Weigh and record filled tube SWE. *If hit obstruction during sampling or if no soil plug obtained re-take snow sample. 33

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35 Snow Surveys Methods rinse & repeat Give tube a good shake or tap it against toe of boot to get out snow core Don t hit tube or cutter end against anything hard because it is easy to damage Check that no snow remains in tube between samples No significant snow in tube 35

36 Snow Surveys Tips Weighing empty tube before each sample is at your discretion Dependent on snow conditions; tube-clearing skill; level of accuracy desired Bring small, slotted screwdriver and old knife to remove soil plug, or tricky snow core, from tube Bring many pairs of gloves, grippy palms are a good idea Waterproof paper and pencil for data recording 36

37 Site NF GPS Date Apr 27, U Aspect S Slope 16.1% Start Time 13:20 End Time 14:15 Weather Sampler Kara Recorder Audrey N-S Distance (m) 7 E-W Distance (m) Overcast, light drizzle Point Line Direction Depth w/ Soil Soil Plug SWE Empty SWE Full NOTES 1 1 5: : : : in nasty tree well 37

38 Site GPS Aspect Slope Date Start Time End Time Weather Sampler Recorder N-S Distance (m) E-W Distance (m) Point Line Direction Depth w/ Soil Soil Plug SWE Empty SWE Full NOTES

39 Snow Surveys Issues Different samplers for different conditions Federal generally regarded as best all-around Generally overestimate SWE Design of cutting point forces more snow inside tube Ice layers Losing water from the tube during melt Gaining extra snow Through slots with twisting in deep snowpack Dull cutter Shrubs, branches, vegetation beneath the snow Air pockets Check length of core 80% snow depth; consistent density between samples Freezing of snow in the tube Particularly when air temp > 0 o C, snow temp < 0 o C 39

40 Measurement Errors The number and quality of data, as well as their statistical nature, impose limitations on the information that can be usually deduced; in fact, all measurements are inaccurate to some degree. The observer s procedures, the instruments and their maintenance, data transmission and transcription, may each contribute individually or collectively to errors in the published values. 40

41 Measurement Errors Errors may be random, such as mistakes in transcribing numbers, or systematic, such as a bias introduced by an observer or an instrument. Random errors often cluster around mean values and are generally both positive and negative so that normal or Gaussian statistics apply. Some obvious errors can be easily explained and corrected; others must be rejected if they lack a sound physical explanation, but should not be discarded, since later evidence may provide 41 an explanation.

42 Measurement Errors Errors that fall within reasonable limits of possibility are the most insidious since they are virtually impossible to detect. A mean value of several measurements is a better estimate of the true value, provided systematic errors are negligible. Similarly, the average of a time series may give a superior measure of its true (normal) value. 42

43 Measurement Errors Systematic errors may either be constant or proportional to a variable s magnitude or appear only under specific environmental conditions, e.g., when snow is wet and adhesive rather than dry and easily transported by the wind. Such errors are minor in data for indices, but are serious in data required for quantitative values. Adjustment factors can be determined to compensate for exposure bias but are somewhat subjective and cannot be freely transposed to other seasons or sites. 43

44 Measurement Errors Most snow courses are established to aid in predicting runoff volumes and peaks. Their data measurements are used as indices so that the measured values need not be representative of a large area. Preferably they indicate snowcover amounts over areas that contribute substantially to runoff. 44

45 Measurement Errors A simple comparison with values in the same general area will often indicate the extent to which exposures are comparable. Major differences should be explainable in terms of elevation, land form, vegetation, or other climatic or physical features. Snowfall and snowcover data are highly amenable to statistical analyses and probabilistic statistical association. 45

46 Measurement Errors Peculiarities of the data must always be kept in mind (e.g., the data must be examined critically for the occurrence of zero values and for the frequency distribution most appropriate for analysis). The choice of the most suitable theoretical distribution to be fitted depends on each dataset; for instance the incomplete gamma function is used to represent many snowfall and snowcover variables. 46

47 Measurement Errors The distribution of a single variable can frequently be expressed in a linear form such that: X(F) = X + s k(f) Where X(F) is the expected value of the variable whose probability of not being exceeded is F, X is the estimated mean of the population, s is the estimated standard deviation, and k(f) is the frequency factor which is chosen to correspond to a given probability level, F, and whose magnitude depends on the frequency distribution and sample size. 47

48 Sources of sampling errors Riming of meteorological instruments Loss of power Incorrect wiring or programming of the instrument Malfunctioning or deteriorating instrument Tampering or involuntary displacement Others?? 48

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50 Final Preparation Checklist Review agenda and be fully prepared for an on-time departure at the bus loop at 10:30 a.m. on Friday, January 27 th, Prepare all personal gear, pack a lunch/water Read and bring all documents related to the fieldtrip and components of the snow survey. Submit the fieldwork critical data form to Stephen. Please express any concerns to Stephen prior to or during the snow survey. 50

51 Teams Team Alpha Team Beta 1) Hadleigh 2)? 3)? 4)? 1) Taras 2)? 3)? 4)? 51

52 Weather Forecast 52

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54 Snow survey data Please digitize all snow survey data including snow depth, SWE and snow pit measurements Include all relevant metadata and notes from your snow survey (e.g. GPS coordinates and weather conditions) Send all the data (preferably in an Excel spreadsheet) to Stephen for upload on website Acquire meteorological data for 1 September 2016 to 27 January 2017 and begin QA/QC 54