Steven F. Daly

A Primer on Winter, Ice, and Fish: What Fisheries Biologists Should Know about Winter Ice Processes and Stream-Dwelling Fish

Abstract Stream-dwelling fish face highly-variable environmental conditions from fall to winter due to fluctuations in water temperatures, discharge, and ice conditions. We provide an in-depth description of the interactions between these complex environmental conditions and behaviors of stream-dwelling salmonids during winter. Fisheries managers should be aware of the conditions that fish confront during winter in order to make appropriate management decisions. Diverse habitats, including deep pools with low water velocities, coarse rock substrate, and abundant cover, as well as side channels and backwaters, aid in the survival of overwintering fish. The inflow of relatively warm groundwater into the water column can be an important factor affecting winter habitat. Considering the length of winter and the vulnerability of fish during winter, a broad understanding of winter ice process and their effects on stream dwelling fish can aid in the preservation and improvement of winter habitats.

Evolution and hydraulic resistance of anchor ice on gravel bed

This paper presents a laboratory study on anchor ice evolution and its hydraulic effect in channels with a gravel bed. The study revealed that anchor ice is initiated by frazil ice accumulation on bed gravel from half a gravel diameter below the crown level of the gravel. No in-situ ice growth within the frazil accumulation or downward growth towards the bed was observed. During the initial stage of growth anchor ice grew in the forms of tails, scales, or balls, depending on the flow velocity and Froude number. During the final stage of growth, when the gravel bed was covered by ice, the growth rate increased with the heat loss rate and Froude number, and inversely proportional to the flow depth. The overall hydraulic resistance of anchor ice was smaller for smaller bed gravel sizes and decreases with the increase in flow rate and flow depth. The rate of increase of the gross Mannings resistance coefficient decreases with the increase in Reynolds number. The bed/ice surface roughness first increases with anchor ice growth, then decreases to a minimum value after the initial stage of growth, when anchor ice grew out of the gravel bed.

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.

On the Nusselt number for frazil ice growth—a correction to ”Frazil evolution in channels“ by Lars Hammar and Hung-Tao Shen

The growth (melt) rate of frazil ice is governed by heat transfer away from (towards) the ice crystal, which can be represented by the Nusselt number. We discuss choices for the Nusselt number and turbulent length scale appropriate for frazil ice and note an inaccuracy in the study ”Frazil evolution in channels“ by Lars Hammar and Hung-Tao Shen, which has also led to potentially significant errors in several other papers. We correct this error and suggest an appropriate strategy for determining the Nusselt number applicable to frazil ice growth and melting.

Stability of floating and submerged blocks

The rotational stability of floating and submerged rectangular blocks is described. The limit of stability is reached when the underturning moment acting on the block is equal to the maximum hydrostatic righting moment. The hydrostatic righting moment is derived and a convenient expression for its maximum is presented in nondimensional form. A moment coefficient is defined that relates the underturning moment at the limit of stability to the moment produced by the product of the dynamic pressure of the flow and the plan area of the block. An exponential function of the ratio of block thickness to flow depth is postulated as a general expression for the moment coefficient. The parameters of this function are related to the block geometry by analyzing the existing experimental data. The limit of rotational stability for rectangular blocks can then be described in terms of a densimetric Froude number based on block thickness.

Application of neural networks to predict ice jam occurrence

Abstract Artificial neural networks show potential for modeling the behavior of complex nonlinear processes, such as those involved in the occurrence of breakup ice jams. Because breakup ice jams and related flooding occur suddenly, ice jam prediction methods are desirable to provide early warning and to allow rapid, effective ice jam mitigation. Unlike open-water flooding, however, an analytical description of all the complex physical processes involved is not available. As a result, breakup ice jam prediction models have historically been limited to classical empirical single-variable threshold-type analyses to statistical methods such as logistic regression and discriminant function analysis. A neural network is shown to improve the error rates of ice jam prediction at Oil City, PA. The neural network input vector is determined and the methods used to appropriately account for the relatively low occurrence of jams are addressed. The neural network prediction proves to be more accurate than the current method used at this site, with a false positive error rate of 5.9% and a false negative error rate of 7.4%.

Observed Ice Passage from Lake Huron Into the St. Clair River

Abstract Ice entering the St. Clair River from southern Lake Huron has caused large ice jams on the river, which have inundated large inhabited areas and delayed navigation. Study and forecasting of these ice jam events require that the ice passage from the lake into the river be described quantitatively. This paper analyzes data obtained from time-lapse photography of ice conditions at the entrance of the river at Lake Huron over six winters. For each day of record when ice was observed in Lake Huron or the river, the presence or absence of an ice arch and the daily average surface concentration of ice entering the river were noted. For the months of January through April, separate means, standard deviations, and distributions of the surface ice concentration were determined for periods when the ice arch was present or absent. The existence of the ice arch can be predicted by a simple indicator based on air temperature. The statistical distributions of ice concentration are strongly influenced by the presence or absence of the ice arch. The overall mean surface ice concentration was 9.5% with an arch present and 27.3% with no arch. Based on this finding, ice passage can be forecasted.

Development of an underwater frazil-ice detector

Abstract A new underwater frazil-ice detector developed at USACRREL is described. The detector can operate remotely and independently. It can automatically start de-icing procedures and alert operators to the presence of frazil. The detector operates by measuring the flow rate through a small intake screen upon which frazil ice can accumulate. The intake screen is, in effect, a miniature trash rack that will freeze up much sooner than the actual trash rack. The detector was tested in the laboratory and in the field with good results; it is economical and is built largely with off-the-shelf items.

Changes in the albedo of the Pegasus and Phoenix Runways, 2000–2017

Albedo is the ratio of total hemispherical reflected (upwelling) to incoming (downwelling) radiative flux (or irradiance) at a surface. For operations on the McMurdo Ice Shelf, Antarctica, albedo is a controlling factor. Impurities such as dust, soot, mineral, and other organic deposits on a snow or ice surface can dramatically lower albedo, increase solar energy absorption in the ice shelf, and significantly alter the energy balance, resulting in increased melting, snow density variations, and compromised structural integrity of the snow and ice matrix. The occurrence of such impurities at Pegasus Runway may have been a factor in its decline and replacement with the Phoenix Runway in the 2016–2017 field season. Therefore, the National Science Foundation (NSF) requested that the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) establish a longterm record of surface albedo at the Pegasus and Phoenix Runway sites. To accomplish this, data from the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) satellite was used. MODIS satellite data has a daily temporal resolution and a significant period of record (2000–present). Additionally, its narrowband surface reflectance may be used as a proxy for albedo. This report documents the results of these analyses. ERDC/CRREL TR-17-10 iii