Severe Snowmelt Runoff in North-East England and Its Implications.

ARCHER, DR

doi:10.1680/iicep.1981.1755

Cited by 6 publications

(10 citation statements)

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“…No snow-course measurements have yet been made in the basin but the best-fit W Q values of 450 mm (1979) and 350 mm (1980) are not incompatible with an annual precipitation in excess of 1500 mm which falls mainly as snow from December to March. The discrepancy between water-balance and snow line estimates may be due to the rather low snow density assumed by Jackson (Archer, 1981).…”

Section: Snowmelt Computationmentioning

confidence: 95%

“…Although snowmelt does not dominate seasonal river regimes anywhere in Britain, many Scottish rivers show a secondary maximum of runoff in April when precipitation is least; and the combination of snowmelt and rainfall has been responsible for major floods in many rivers rising in upland Britain, for example in 1947Britain, for example in , 1963Britain, for example in , and 1982. Despite this, very little attention has been paid to snow hydrology in Britain until recently (Johnson & Archer, 1972;Johnson 1975;Archer 1981;Morris 1982). This paper describes features of snowmelt runoff from the basin of the River Feshie in the eastern Highlands of Scotland, and demonstrates that daily snowmelt discharges can be simulated well by a model requiring only widely-available meteorological data.…”

Section: Introductionmentioning

confidence: 99%

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Magnitude and modelling of snowmelt runoff in the Cairngorm mountains, Scotland

Ferguson

1984

Hydrological Sciences Journal

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Streamflow in the River Feshie (106 km 2 ) shows persistent diurnal oscillations from March to June when runoff augmented by snowmelt greatly exceeds precipitation. Diurnal amplitude and maximum daily runoff are comparable to a similar-sized Swiss glacier basin. Daily discharges in the springs of 1979 and 1980 are successfully simulated from daily air temperatures and precipitation using a lumped degree-day model based on Martinec's model but with endogenous snowpack shrinkage at a rate proportional to melting. A best fit of R = 0.88 was achieved over 53 days in the unusually snowy season of 1979. The biggest errors are in simulating runoff from precipitation for which only lumped data are available. Best-fit parameter values are physically reasonable and only two parameters , describing the initial snowpack, need vary from year to year.

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Section: Snowmelt Computationmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Magnitude and modelling of snowmelt runoff in the Cairngorm mountains, Scotland

Ferguson

1984

Hydrological Sciences Journal

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“…About 75% of the runo in the Colorado River originates from snowmelt in key basins that represent only 13% of the contributing land area (US Department of Interior, 1970). It was estimated that 50% of the annual runo from a representative basin in Sweden occurs during the spring snowmelt¯ood in May (Bergstrom, 1979). Water derived from snowmelt is being used for generation of hydropower, irrigation, domestic and industrial water supply.…”

Section: Introductionmentioning

confidence: 99%

“…Empirical laws were derived to determine the snowmelt from temperature data, like the degree±day method (Kuz'min, 1972). With the increased availability of computers a number of snowmelt models appeared, the most popular of which are multiregression models (Archer, 1981) and conceptual models based on temperature index and/or energy budget (Anderson, 1973;Komarov et al, 1975;Charbonneau et al, 1977;Quick and Pipers, 1977;Leavesley, 1978;Bergstrom, 1979;Tanghborn, 1980). The conceptual model tries to simulate the energy exchange between the air, snow cover and bottom ground, and compute day-to-day river¯ows taking advantage of the daily measurements of temperature and solar radiation.…”

Section: Introductionmentioning

confidence: 99%

Modelling runoff using optical satellite remote sensing data in a high mountainous alpine catchment of Italy

Swamy

Brivio

1997

Hydrol. Process.

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Development of hydrological models for seasonal and real-time runo forecast in rivers of high alpine catchments is useful for management of water resources. The conceptual models for this purpose are based on a temperature index and/ or energy budget and can be either lumped or distributed over the catchment area. Remote sensing satellite data are most useful to acquire near real-time geophysical parameters in order to input to the distributed forecasting models. In the present study, integration of optical satellite remote sensing-derived information was made with ground meteorological and hydrological data, and predetermined catchment morphological parameters, to study the feasibility of application of a distributed temperature index snowmelt runo model to one of the high mountainous catchments in the Italian Alps, known as Cordevole River Basin. Five sets of Landsat Multispectral Scanning System (MSS) and Thematic Mapper (TM) computer-compatible tapes (CCTs) were processed using digital image processing techniques in order to evaluate the snow cover variation quantitatively. Digital elevation model, slope and aspect parameters were developed and used during satellite data processing. The satellite scenes were classi®ed as snow, snow under transition and snow free areas. A second-order polynomial ®t has been attempted to approximate the snow depletion and to estimate daily snow cover areal extent for three elevation zones of the catchment separately. Model performance evaluation based on correlation coecient, Nash±Sutclie coecient and percentage volume deviation indicated very good simulation between measured and computed discharges for the entire snowmelt period. The use of average temperature values computed from the maximum and minimum temperatures into the model was studied and a suitable algorithm was proposed.

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“…More recently Archer (1981) has calculated very efficient snowmelt processes in northern England; the implication is that whilst 'greenhouse winters' in Britain seem destined to be milder, if a substantial snow accumulates from a prolonged spell of continental climatic conditions, i.e., the winter equivalent of those causing drought in summer, very high rates of melt may result once 'normal' mild, wet conditions return.…”

Section: Introductionmentioning

confidence: 99%