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contributor authorStéphane Lavallée
contributor authorFrançois P. Brissette
contributor authorRobert Leconte
contributor authorBruno Larouche
date accessioned2017-05-08T21:08:05Z
date available2017-05-08T21:08:05Z
date copyrightMarch 2006
date issued2006
identifier other%28asce%290733-9496%282006%29132%3A2%2871%29.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/39994
description abstractMany watersheds in Canada and in the northern United States see most of their precipitation in the form of snow. Many of these watersheds are the sites of important hydropower development projects. During snowmelt, watershed managers require information on snowpack depletion in order to optimize power production while minimizing flooding risk. In many cases, management techniques are based on simple correlations extracted from data collected in previous years or on inappropriate tools for data interpretation. Both of these factors can affect the reliability of forecasts and result in production losses or increased risk in downstream areas. This paper presents an approach to improve snowmelt forecasts. A simple distributed snowmelt model based on the degree-days approach is used to predict snowmelt based on weather forecasts. To improve forecasts, a feedback algorithm is presented that allows for real-time model adjustment using the integration of
publisherAmerican Society of Civil Engineers
titleMonitoring Snow-Cover Depletion by Coupling Satellite Imagery with a Distributed Snowmelt Model
typeJournal Paper
journal volume132
journal issue2
journal titleJournal of Water Resources Planning and Management
identifier doi10.1061/(ASCE)0733-9496(2006)132:2(71)
treeJournal of Water Resources Planning and Management:;2006:;Volume ( 132 ):;issue: 002
contenttypeFulltext


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