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Snowmelt Runoff (snowmelt + runoff)
Selected AbstractsAN ORGANIZED SIGNAL IN SNOWMELT RUNOFF OVER THE WESTERN UNITED STATES,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 2 2000D. H. Peterson ABSTRACT: Daily-to-weekly discharge during the snowmelt season is highly correlated among river basins in the upper elevations of the central and southern Sierra Nevada (Carson, Walker, Tuolumne, Merced, San Joaquin, Kings, and Kern Rivers). In many cases, the upper Sierra Nevada watershed operates in a single mode (with varying catchment amplitudes). In some years, with appropriate lags, this mode extends to distant mountains. A reason for this coherence is the broad scale nature of synoptic features in atmospheric circulation, which provide anomalous insolation and temperature forcing that span a large region, sometimes the entire western U.S. These correlations may fall off dramatically, however, in dry years when the snowpack is spatially patchy. [source] Effects of the El Niño,southern oscillation on temperature, precipitation, snow water equivalent and resulting streamflow in the Upper Rio Grande river basinHYDROLOGICAL PROCESSES, Issue 6 2004Songweon Lee Abstract Snowmelt runoff dominates streamflow in the Upper Rio Grande (URG) basin of New Mexico and Colorado. Annual variations in streamflow timing and volume at most stations in the region are strongly influenced by the El Niño,southern oscillation (ENSO) through its modulation of the seasonal cycles of temperature and precipitation, and hence on snow accumulation and melting. After removing long-term trends over the study period (water years 1952,99), the dependence of monthly temperature, precipitation, snow water equivalent (SWE) at snowcourse stations, and streamflow throughout the URG on ENSO was investigated using composite analyses of the detrended residuals and through dependence of the residuals on the Climate Prediction Center southern oscillation index during the preceding summer and fall. The climate of La Niña years was found to differ significantly from either El Niño or neutral years. Moreover, significant climatological ENSO-related effects are confined to certain months, predominantly at the beginning and end of the winter season. In particular, March of La Niña years is significantly warmer and drier than during either El Niño or neutral years, and November of El Niño years is significantly colder and wetter. Differences in temperature and precipitation lead to significant differences in SWE and streamflow in the URG between the three ENSO phases. Copyright © 2004 John Wiley & Sons, Ltd. [source] Snow density variations: consequences for ground-penetrating radarHYDROLOGICAL PROCESSES, Issue 7 2006A. Lundberg Abstract Reliable hydrological forecasts of snowmelt runoff are of major importance for many areas. Ground-penetrating radar (GPR) measurements are used to assess snowpack water equivalent for planning of hydropower production in northern Sweden. The travel time of the radar pulse through the snow cover is recorded and converted to snow water equivalent (SWE) using a constant snowpack mean density from the drainage basin studied. In this paper we improve the method to estimate SWE by introducing a depth-dependent snowpack density. We used 6 years measurements of peak snow depth and snowpack mean density at 11 locations in the Swedish mountains. The original method systematically overestimates the SWE at shallow depths (+25% for 0·5 m) and underestimates the SWE at large depths (,35% for 2·0 m). A large improvement was obtained by introducing a depth,density relation based on average conditions for several years, whereas refining this by using separate relations for individual years yielded a smaller improvement. The SWE estimates were substantially improved for thick snow covers, reducing the average error from 162 ± 23 mm to 53 ± 10 mm for depth range 1·2,2·0 m. Consequently, the introduction of a depth-dependent snow density yields substantial improvements of the accuracy in SWE values calculated from GPR data. Copyright © 2005 John Wiley & Sons, Ltd. [source] Application of fuzzy logic to forecast seasonal runoffHYDROLOGICAL PROCESSES, Issue 18 2003C. Mahabir Abstract Each spring in Alberta, Canada, the potential snowmelt runoff is forecast for several basins to assess the water supply situation. Water managers need this forecast to plan water allocations for the following summer season. The Lodge Creek and Middle Creek basins, located in southeastern Alberta, are two basins that require this type of late winter forecast of potential spring runoff. Historically, the forecast has been based upon a combination of regression equations. These results are then interpreted by a forecaster and are modified based on the forecaster's heuristic knowledge of the basin. Unfortunately, this approach has had limited success in the past, in terms of the accuracy of these forecasts, and consequently an alternative methodology is needed. In this study, the applicability of fuzzy logic modelling techniques for forecasting water supply was investigated. Fuzzy logic has been applied successfully in several fields where the relationship between cause and effect (variable and results) are vague. Fuzzy variables were used to organize knowledge that is expressed ,linguistically' into a formal analysis. For example, ,high snowpack', ,average snowpack' and ,low snowpack' became variables. By applying fuzzy logic, a water supply forecast was created that classified potential runoff into three forecast zones: ,low', ,average' and ,high'. Spring runoff forecasts from the fuzzy expert systems were found to be considerably more reliable than the regression models in forecasting the appropriate runoff zone, especially in terms of identifying low or average runoff years. Based on the modelling results in these two basins, it is concluded that fuzzy logic has a promising potential for providing reliable water supply forecasts. Copyright © 2003 John Wiley & Sons, Ltd. [source] Soil frost effects on soil water and runoff dynamics along a boreal transect: 2.HYDROLOGICAL PROCESSES, Issue 6 2001Simulations Abstract A physically based SVAT-model was tested with soil and snow physical measurements, as well as runoff data from an 8600 m2 catchment in northern Sweden in order to quantify the influence of soil frost on spring snowmelt runoff in a moderately sloped, boreal forest. The model was run as an array of connected profiles cascading to the brook. For three winter seasons (1995,98) it was able to predict the onset and total accumulation of the runoff with satisfactory accuracy. Surface runoff was identified as only a minor fraction of the total runoff occurring during short periods in connection with ice blocking of the water-conducting pores. Little surface runoff, though, does not mean that soil frost is unimportant for spring runoff. Simulations without frost routines systematically underestimated the total accumulated runoff. The possibility of major frost effects appearing in response to specific combinations of weather conditions were also tested. Different scenarios of critical initial conditions for the winter, e.g. high water saturation and delayed snow accumulation leading to an increased frost penetration, were tested. These showed that under special circumstances there is potential for increased spring runoff due to soil frost. Copyright © 2001 John Wiley & Sons, Ltd. [source] | ||||||||||