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  • Stage Frequency Analysis from Snowmelt Runoff near Utqiaġvik, Alaska

    Abstract: For the village of Utqiaġvik, located at the North Slope of Alaska, a stone-armored revetment along the coastline is proposed to reduce coastal erosion. The inner drainage capacity of the revetment must be sufficient to handle seasonal runoff from snowmelt. For this effort, we investigated the snowmelt runoff and the hydraulic impact at the watershed outlet using numerical snow and hydraulic modeling of the study area. We validated the snow model results by comparing simulated snow water equivalent (SWE) values to field measurements. Additionally, the snow model was validated using satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) snow-covered area (SCA) products and time-lapse camera imagery during snowmelt. Our results indicate that the simulated SWE and snowmelt dates agree closely with measured values. The timing of modeled runoff onset was less accurate due to natural processes that delay snowmelt runoff such as snow dams and refreeze. The effect of the uncertainty from both runoff timing and volume was addressed with a Monte Carlo simulation of stage-frequency curves for the lagoons that receive snowmelt runoff. These stage-frequency curves can be used directly in the design of outlet, drainage or discharge structures for the proposed revetment.
  • Initial Data Collection from a Fiber-Optic-Based Dam Seepage Monitoring and Detection System

    Abstract: Visual inspection is the most used method to detect seepage at dams. Early detection can be difficult with this method, and use of appropriate real time monitoring could significantly increase the chances of recognizing possible failure. Seepages can be identified by analyzing changes in water and soil temperature. Optical fiber placed at the embankment’s downstream toe has been proven to be an efficient means of detecting real time changes at short intervals over several kilometers. This study aims to demonstrate how temperatures measured using fiber optic distributed sensing can be used to monitor seepage at Moose Creek Dam, North Pole, Alaska. The fiber optic cable portion of the monitoring system is installed along a section of the embankment where sand boils have occurred. Though no flood event occurred during this monitoring period, routine pumping tests of nearby relief wells resulted in an increase of soil and water temperature (up to 13°C) along a 100 m section where sand boils were detected during the 2014 flood events. Measurements during a flood event are expected to provide a quantitative assessment of seepage and its rate.
  • Summary of Ground-Based Snow Measurements for the Northeastern United States

    ABSTRACT: Snow is an important resource for both communities and ecosystems of the Northeastern United States. Both flood risk management and water supply forecasts for major municipalities, including New York City, depend on the collection of snowpack information. Therefore, the purpose of this study is to summarize all of the snowpack data from ground-based networks currently available in the Northeast. The collection of snow-depth and snow water equivalent information extends back several decades, and there are over 2,200 active sites across the region. Sites are distributed across the entire range of elevations in the region. The number of locations collecting snow information has increased substantially in the last 20 years, primarily from the expansion of the CoCoRaHS (Community Collaborative Rain, Hail, and Snow) network. Our summary of regional snow measurement locations provides a foundation for future studies and analysis, including a template for other regions of the United States.