1. A Simple and Inexpensive Method to Measure Snow Water Equivalent: Updates, Developments, and How the Data is Being Used Andrea Holz Hydrologist North Central River Forecast Center James LaRosa Hydrology Program Manager National Weather Service Marquette, MI

2. Changes To The Snow Tube Design: > The new design (left) does not have teeth cut into the flared end of the pipe. Not sure why, but I have found this allows more snow to get into the pipe. Does the snow escape out the side in between the teeth? Does the snow get stuck where the pipe constricts?

3. How The Data Stacks Up: The difference in the data in the middle of the chart is likely due to ice formation in the snowpack. Snow can get caught up in the bottle-neck area, and to combat this, observers have been instructed to use the other end of the pipe and apply a correction factor. > For the most part, the data collected by the Adirondack and muffler pipe were similar. A high bias could be argued for the muffler pipe as snow often fell out of the Adirondack tube, especially at low snow depths.

4. Expansion Of The Empire: > The network of weekly SWE observers has grown to 24, most of which are water treatment plant operators. Although a handful of spotters, cooperative observers, and others with an interest in snowmelt runoff were recently added after outreach activities. Additional SWE data is obtained from more than 50 NOHRSC Gamma Flight lines, and 26 supplemental locations within the Menominee River Basin. However, this data is not collected on a weekly basis.

5. Weekly Maps Of The Data: > A typical weekly map of SWE data shows the areas of concern, and point data taken by the volunteer observers. A larger scale and more colors are needed, plus the National Weather Service logo. Feedback from users, including County Emergency Managers, Michigan Department of Environmental Quality, engineering firms, and the users themselves has been very positive.

6. Other Local Uses For The Data: > After the flooding of the Dead River due to a levee failure in May 2003, there was a lot of concern as to how much water would be flowing into the Dead River Storage Basin. Local users placed a map of the watershed boundary on the SWE map, giving them a general idea of how much water could potentially flow into the system.

7. SWE Observations Used in NWSRFS NCRFC has capability to look at point data and compare observed data with model simulated Mean Areal SWE. NCRFC has capability to look at point data and compare observed data with model simulated Mean Areal SWE. NCRFC can list observed SWE data in the SNOW-17 Output for closer comparison. NCRFC can list observed SWE data in the SNOW-17 Output for closer comparison. If more than one SWE observation is available in the basin, a WEIGH-TS operation can be used to create a Mean Areal SWE. If more than one SWE observation is available in the basin, a WEIGH-TS operation can be used to create a Mean Areal SWE. Important for river forecasters to remember the observation is at one point in the basin. Important for river forecasters to remember the observation is at one point in the basin. Observed SWE is useful when looking at accumulation and ablation trends. Observed SWE is useful when looking at accumulation and ablation trends. NCRFC uses NOHRSC model output as a Mean Areal SWE comparison tool. NCRFC uses NOHRSC model output as a Mean Areal SWE comparison tool.

8. Compare SWE graphically

9. SNOW-17 Output Listing Watton SD & SWE Observations

10. NOHRSC Web Graphic

11. NCRFC Use of Observations Weekly SWE observations aid in setting up SWE values for melt Weekly SWE observations aid in setting up SWE values for melt Weekly SWE observations aid in monitoring accumulation and ablation trends Weekly SWE observations aid in monitoring accumulation and ablation trends SWE observations aid NOHRSC in assimilating their model, which is used daily at NCRFC SWE observations aid NOHRSC in assimilating their model, which is used daily at NCRFC More observation points = more confidence in snow model = more consistent snow melt river forecasts More observation points = more confidence in snow model = more consistent snow melt river forecasts