Carrie M. Vuyovich

Comparison of passive microwave and modeled estimates of total watershed SWE in the continental United States

In the U.S., a dedicated system of snow measurement stations and snowpack modeling products is available to estimate the snow water equivalent (SWE) throughout the winter season. In other regions of the world that depend on snowmelt for water resources, snow data can be scarce, and these regions are vulnerable to drought or flood conditions. Even in the U.S., water resource management is hampered by limited snow data in certain regions, as evident by the 2011 Missouri Basin flooding due in large part to the significant Plains snowpack. Satellite data could potentially provide important information in under-sampled areas. This study compared the daily AMSR-E and SSM/I SWE products over nine winter seasons to spatially distributed, modeled output SNODAS summed over 2100 watersheds in the conterminous U.S. Results show large areas where the passive microwave retrievals are highly correlated to the SNODAS data, particularly in the northern Great Plains and southern Rocky Mountain regions. However, the passive microwave SWE is significantly lower than SNODAS in heavily forested areas, and regions that typically receive a deep snowpack. The best correlations are associated with basins in which maximum annual SWE is less than 200 mm, and forest fraction is less than 20%. Even in many watersheds with poor correlations between the passive microwave data and SNODAS maximum annual SWE values, the overall pattern of accumulation and ablation did show good agreement and therefore may provide useful hydrologic information on melt timing and season length.

Remote Sensing of Drivers of Spring Snowmelt Flooding in the North Central U.S.

Spring snowmelt poses an annual flood risk in nonmountainous regions, such as the northern Great Plains of North America. However, ground observations are often not sufficient to characterize the spatiotemporal variation of drivers of snowmelt floods for operational flood forecasting purposes. Remote sensing platforms are well suited to nonmountainous, low vegetation areas, and can add value by providing estimates of hydrological states important for flood prediction. In this chapter, we review the use of remote sensing observations, primarily from passive microwave instruments, to constrain drivers of spring snowmelt floods, with a special focus on the Red River of the North basin in the north central United States. While many factors affect snowmelt flooding, snow water equivalent (SWE) and fall soil moisture play a significant role in determining flood severity in the region. Methods to estimate SWE and soil moisture are summarized, and past remote sensing research conducted in the region is reviewed. Considerations for incorporation of remote sensing estimates into the operational flood forecasting workflow and models are also discussed, using the NOAA National Weather Service (NWS) North Central River Forecast Center (NCRFC) as an example.

Benefit Analysis of Ice Control Structures in Oil City, Pennsylvania

AbstractIn designing flood control projects, engineers must show that the proposed project provides a flood damage reduction benefit in economic terms. For ice control structures, however, cost ben...

Intercomparison of snow water equivalent observations in the Northern Great Plains

University of New Hampshire, 105 Main Street, Durham, NH 03824, USA U.S. Army Corps of Engineers, Cold Regions Research and Engineering Laboratory, 72 Lyme Road, Hanover, NH 03755, USA National Weather Service Office of Water Prediction—Minnesota, 1735 Lake Drive West, Chanhassen, MN 55317, USA Correspondence Samuel E. Tuttle, University of New Hampshire, 105 Main Street, Durham, NH 03824, USA. Email: stuttle@mtholyoke.edu Present Address Samuel E. Tuttles present address is Mount Holyoke College, 50 College Street, South Hadley, MA 01075, USA.

Assessing the Effectiveness of an Ice Control Structure

The effectiveness of riverine flood damage reduction projects is assessed through the use of rainfall-runoff models for the open-water case. However, since no analytical model exists to describe the effects of complex hydrological and meteorological conditions that lead to ice jams, no similar method exists to assess the benefits of an ice control structure. In 1981, the New England Division of the U.S. Army Corps of Engineers completed an ice control structure (ICS) located about 0.5 miles upstream from the center of Lancaster, NH. In recent years, the ICS has fallen into disrepair and much of the impoundment area has filled with gravel, reducing its frazil ice storage ice capacity. The structures current condition, combined with operation and maintenance safety issues and concerns about fish passage have prompted the town to pursue the option of its removal. This paper reports the results of a study is to determine, within the budget constraints and based on existing data, whether the ICS has had any impact in reducing ice-affected floods in Lancaster, NH.