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Lowell A. Rasmussen

Publications and source records attributed to Lowell A. Rasmussen.

17 recordsLinked to original sources
USGS2017

Using surface velocities to calculate ice thickness and bed topography: A case study at Columbia Glacier, Alaska, USA

Information about glacier volume and ice thickness distribution is essential for many glaciological applications, but direct measurements of ice thickness can be difficult and costly. We present a new method that calculates ice thickness via an estimate of ice flux. We solve the familiar continuity equation between adjacent flowlines, which decreases the computational time required compared to a solution on the whole grid. We test the method on Columbia Glacier, a large tidewater glacier in Alaska, USA, and compare calculated and measured ice thicknesses, with favorable results. This shows the potential of this method for estimating ice thickness distribution of glaciers for which only surface data are available. We find that both the mean thickness and volume of Columbia Glacier were approximately halved over the period 1957–2007, from 281m to 143 m, and from 294 km 3 to 134 km 3 , respectively. Using bedrock slope and considering how waves of thickness change propagate through the glacier, we conduct a brief analysis of the instability of Columbia Glacier, which leads us to conclude that the rapid portion of the retreat may be nearing an end.

Alaska↗
USGS2017

Calculation of a velocity distribution from particle trajectory end-points.

The longitudinal component of the velocity of a particle at or near a glacier surface is considered, its position as a function of time being termed its trajectory. Functional relationships are derived for obtaining the trajectory from the spatial distribution of velocity and for obtaining the velocity distribution from the trajectory. It is established that the trajectory end-points impose only an integral condition on the velocity distribution, and that no individual point on the velocity distribution can be determined if only the end-points are known. An example is given of a deduced velocity distribution that is consistent with (although not uniquely determined by) the end-points of several trajectories on the lower reach of Columbia Glacier, Alaska. It is shown that constructing a velocity distribution by assigning the average trajectory velocity to the trajectory mid-point can be subject to errors of several per cent for velocity distribution features that are typical of actual glaciers. The error in this method is determined, and closed-form expressions for the trajectory are obtained, for linear velocity distributions and for two classes of second-degree distributions. The class of functions is identified to which the velocity distribution must belong for this error to be zero.

Journal of Glaciology↗
USGS2010

Hydrology of the North Cascades region, Washington: 1. Runoff, precipitation, and storage characteristics

The time and space distributions of measured precipitation and measured runoff and of spring storage, which is approximately equal to the subsequent summer runoff of snowmelt and stored groundwater, have been analyzed for the North Cascades region of Washington. Neither precipitation nor runoff shows a consistent relationship with altitude, chiefly because of precipitation-shadowing effects in this region of high relief. The relationship between mean annual precipitation and altitude is improved considerably when a topographic mean altitude is used instead of the actual altitude of the weather station. However, the improvement is not sufficient to explain a number of discrepancies that still occur. Some of the scatter in a precipitation-altitude plot appears to be due to a deficient precipitation catch by high-altitude gages. When the dependence of runoff on precipitation was examined on an annual, seasonal, and monthly basis, it was found that only a few low-altitude gages correlated well with basin runoff. In several instances, annual (water year) runoff could be better predicted from winter precipitation than from annual precipitation. Precipitation and runoff were tested for changes with time and both appeared to have been increasing slightly but not at a statistically significant level. When the summer (May–September) fraction of the total annual runoff is plotted against mean basin altitude, a consistent, physically reasonable, mildly curvilinear relationship is revealed. On the basis of this relationship, by using several drainages with diverse area-altitude profiles the spring storage versus altitude distribution can be estimated for each basin. The area-altitude distribution is used instead of the mean altitude in this calculation because of the apparent nonlinear relationship between runoff and altitude.

Washington↗
USGS2010

Hydrology of the North Cascades region, Washington: 2. A proposed hydrometeorological streamflow prediction method

On the basis of a linear relationship between winter (October-April) precipitation and annual runoff from a drainage basin (Rasmussen and Tangborn, 1976) a physically reasonable model for predicting summer (May-September) streamflow from drainages in the North Cascades region was developed. This hydrometeorological prediction method relates streamflow for a season beginning on the day of prediction to the storage (including snow, ice, soil moisture, and groundwater) on that day. The spring storage is inferred from an input-output relationship based on the principle of conservation of mass: spring storage equals winter precipitation on the basin less winter runoff from the basin and less winter evapotranspiration, which is presumed to be small. The method of prediction is based on data only from the years previous to the one for which the prediction is made, and the system is revised each year as data for the previous year become available. To improve the basin storage estimate made in late winter or early spring, a short-season runoff prediction is made. The errors resulting from this short-term prediction are used to revise the storage estimate and improve the later prediction. This considerably improves the accuracy of the later prediction, especially for periods early in the summer runoff season. The optimum length for the test period appears to be generally less than a month for east side basins and between 1 and 2 months for those on the west side of the Cascade Range. The time distribution of the total summer runoff can be predicted when this test season is used so that on May 1 monthly streamflow for the May-September season can be predicted. It was found that summer precipitation and the time of minimum storage are two error sources that were amenable to analysis. For streamflow predictions in seasons beginning in early spring the deviation of the subsequent summer precipitation from a long-period average will contribute up to 53% of the prediction error. This contribution decreases to nearly zero during the summer and then rises slightly for late summer predictions. The reason for the smaller than expected effect of summer precipitation is thought to be due to the compensating effect of increased evaporative losses and increased infiltration when precipitation is greater than normal during the summer months. The error caused by the beginning winter month (assumed to be October in this study) not coinciding with the time of minimum storage was examined; it appears that October may be the best average beginning winter month for most drainages but that a more detailed study is needed. The optimum beginning of the winter season appears to vary from August to October when individual years are examined. These results demonstrate that standard precipitation and runoff measurements in the North Cascades region are adequate for constructing a predictive hydrologic model. This model can be used to make streamflow predictions that compare favorably with current multiple regression methods based on mountain snow surveys. This method has the added advantages of predicting the space and time distributions of storage and summer runoff.

Washington↗
USGS1985

Short-term velocity measurements at Columbia Glacier, Alaska: August-September 1984

Ice velocity data are presented for the lower reach of Columbia Glacier, Alaska. The data span a 29 day period and contain 1,072 angle sightings from two survey stations to 22 markers placed on the ice surface, and 1,621 laser measurements of the distance to one of those markers (number 11) from another station. These short-interval observations were made to investigate the dynamics of the glacier and to provide input to models for estimation of future retreat and iceberg discharge. The mean ice velocity (at marker number 11) was approximately 9 m/day and ranged from 8 to < 15 m/day. The data set includes a well defined 2-day, 50% velocity increase and a clear pattern of velocity fluctuations of about 5% with approximately diurnal and semiurnal periods. (Author 's abstract)

Alaska↗
USGS1982

Quadratic spline subroutine package

A continuous piecewise quadratic function with continuous first derivative is devised for approximating a single-valued, but unknown, function represented by a set of discrete points. The quadratic is proposed as a treatment intermediate between using the angular (but reliable, easily constructed and manipulated) piecewise linear function and using the smoother (but occasionally erratic) cubic spline. Neither iteration nor the solution of a system of simultaneous equations is necessary to determining the coefficients. Several properties of the quadratic function are given. A set of five short FORTRAN subroutines is provided for generating the coefficients (QSC), finding function value and derivatives (QSY), integrating (QSI), finding extrema (QSE), and computing arc length and the curvature-squared integral (QSK). (USGS)

Water-Resources Investigations Report↗
USGS1977

Application of a hydrometeorological model to the south-central Sierra Nevada of California

A hydrometeorological streamflow-prediction model (HM model) developed for the North Cascades of Washington has been tested in the south-central Sierra Nevada of California. Twenty-four drainages ranging in mean altitude from 770 to 3,160 metres, including several of the major ones such as those of the Kern, Kings, and Merced Rivers, were examined. Eight U.S. National Oceanic and Atmospheric Administration precipitation stations were evaluated. Of these, three proved to be of significant value for nearly all the drainages used. Results are given for predictions on February 1, March 1, and April 1 of monthly runoff of five major drainages for the April-September season. Also demonstrated is the April 1 prediction of a daily hydrograph for the April-September season for 2 diverse years. The altitude distribution of storage and runoff, both observed and predicted, is determined by using several drainages with different area-altitude profiles. Results of this calculation for two drainages show that, on the average, approximately 50 percent of the April-July runoff originates above 2,800 m. The influence of subsequent precipitation on prediction accuracy is determined by relating prediction error and actual precipitation occurring after the prediction day. Results for three basins show that about 75 percent of the error of a January-September prediction on January 1 is due to precipitation occurring during the prediction season. Comparisons of prediction accuracy are made for five major drainages: the Kern River near Kernville; the Kings River below North Fork, near Trimmer (inflow to Pine Flat Dam); the Kings River at Piedra; the Merced River at Pohono Bridge, near Yosemite; and the Merced River below Merced Falls Dam, near Snelling. The accuracy of the HM model appears to be about 24 percent higher than existing operational methods in predicting the April-July runoff on April 1.

California↗