Thermomechanical Response of Reactive Gas to Rapid Transient, Spatially Distributed Energy Addition: An Asymptotic Formulation

2012 ◽  
Author(s):  
David Kassoy ◽  
Keith Wojciechowski
Keyword(s):  
Distributed Energy ◽  
Thermomechanical Response ◽  
Spatially Distributed ◽  
Energy Addition ◽  
Asymptotic Formulation ◽  
Reactive Gas

A spatially distributed energy balance snowmelt model for application in mountain basins

1999 ◽  
Vol 13 (12-13) ◽  
pp. 1935-1959 ◽  
Author(s):  
Danny Marks ◽  
James Domingo ◽  
Dave Susong ◽  
Tim Link ◽  
David Garen
Keyword(s):  
Energy Balance ◽  
Distributed Energy ◽  
Spatially Distributed ◽  
Mountain Basins ◽  
Snowmelt Model

scholarly journals Hydrological modelling of glacierized catchments focussing on the validation of simulated snow patterns – applications within the flood forecasting system of the Tyrolean river Inn

2010 ◽  
Vol 27 ◽  
pp. 99-109 ◽  
Author(s):  
J. Schöber ◽  
S. Achleitner ◽  
R. Kirnbauer ◽  
F. Schöberl ◽  
H. Schönlaub
Keyword(s):  
Flood Forecasting ◽  
Parameter Setting ◽  
Operational Mode ◽  
Distributed Energy ◽  
Remotely Sensed Data ◽  
Spatially Distributed ◽  
First Results ◽  
Forecasting System ◽  
Energy Balance Approach ◽  
Flood Flow

Abstract. The catchment of the river Inn is located in the Swiss and Austrian Alps. In the frame of the flood forecasting system "HoPI" (Hochwasserprognose für den Tiroler Inn), the Austrian part of the river Inn and its tributaries are covered within a hybrid numerical model. The runoff from the glacierized headwaters of the south-western Inn tributaries is calculated using the Snow- and Icemelt Model "SES" which utilizes a spatially-distributed energy balance approach; within SES, the accumulation and melting processes for snow, firn, and ice are considered. It is of great importance that such a type of model is used in the simulation of alpine areas since in these regions stream flow is influenced by the accumulation and melt of snow and ice and snow-free glaciers have also the potential to increase or even induce flood flow. For a prototype of the forecast system, SES was calibrated using the snow depletion of a glacier, but later, following the first results during the operational mode, the model was recalibrated and validated using remotely-sensed data covering all 13 glacierized catchments. Using the final snow-parameter setting, a simulation run of 15 hydrological years without any state corrections achieved overall agreements between observed and simulated snow cover ranging from 68% to 88% for all individual catchments. Runoff was calibrated and validated using the data from three different gauges. A parameter set, including both validated snow and runoff parameters, was applied for the modelling of a fourth gauged catchment and also achieved accurate results. This final unique parameterization was transferred to the remaining, ungauged watersheds.

scholarly journals Mass Balance of Austre Grønfjordbreen, Svalbard, 2006–2020, Estimated by Glaciological, Geodetic and Modeling Aproaches

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 78
Author(s):  
Nelly Elagina ◽  
Stanislav Kutuzov ◽  
Ekaterina Rets ◽  
Andrei Smirnov ◽  
Robert Chernov ◽  
...  
Keyword(s):  
Mass Balance ◽  
Glacier Mass Balance ◽  
Distributed Energy ◽  
Climatic Fluctuations ◽  
Temperature Index ◽  
Index Model ◽  
Spatially Distributed ◽  
Calculated Mass ◽  
Geodetic Mass Balance ◽  
West Spitsbergen

Glacier mass balance measurements, reconstructions and modeling are the precondition for assessing glacier sensitivity to regional climatic fluctuations. This paper presents new glaciological and geodetic mass balance data of Austre Grønfjordbreen located in the western part of Nordenskiöld Land in Central Spitsbergen. The average annual mass balance from 2014 to 2019 was −1.59 m w.e. The geodetic mass balance from 2008 to 2017 was −1.34 m w.e. The mass balance was also reconstructed by the temperature-index model from 2006 to 2020 and by spatially-distributed energy-balance models for 2011–2015 and 2019. We found a cumulative mass balance of −21.62 m w.e. over 2006–2020. The calculated mass-balance sensitivity to temperature was −1.04 m w.e. °C−1, which corresponds to the highest glacier mass balance sensitivity among Svalbard glaciers. Sensitivity to precipitation change was 0.10 m w.e. for a 10% increase in precipitation throughout the balance year. Comparing the results of the current study with other glacier mass balance assessments in Svalbard, we found that Austre Grønfjordbreen loses mass most rapidly due to its location, which is mostly influenced by the warm West Spitsbergen Current, small area and low elevation range.

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