Modèles d'évolution du manteau nival et de la fonte des neiges

1989 ◽  
Vol 16 (3) ◽  
pp. 219-226
Author(s):  
Saâd Bennis ◽  
Paul-Édouard Brunelle
Keyword(s):  
Snow Cover ◽  
Key Words ◽  
Drainage Basin ◽  
Daily Temperature ◽  
Snow Pack ◽  
Snowmelt Runoff ◽  
Maximum Daily Temperature ◽  
Temperature And Precipitation ◽  
Simulation Results ◽  
Runoff Model

The predictive snowmelt runoff model (SRM), previously suggested by other authors, is reliable and easy to use. Furthermore, the only parameters required are temperature and precipitation, and density and thickness of the snow pack. The literature available indicates that simulation results with this model are generally satisfactory. However, data on the extent of the snow cover are not always available; this means that the snow pack must be calculated before the SRM can be used. Our purpose herein is to develop a model to evaluate the snowpack, which is to be used in conjunction with the SRM. The SRM was modified in that maximum daily temperature was used instead of the number of degrees-days. The snowmelt and snow cover models were calibrated and tested along the drainage basin of the Eaton River, a tributary of the Saint-François River in the province of Quebec. Key words: snowmelt, prediction, flooding. [Journal translation]

scholarly journals Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers

Geosciences ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 130
Author(s):  
Sebastian Rößler ◽  
Marius S. Witt ◽  
Jaakko Ikonen ◽  
Ian A. Brown ◽  
Andreas J. Dietz
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Air Temperature ◽  
Kendall Test ◽  
The Arctic ◽  
Boreal Winter ◽  
Snowmelt Runoff ◽  
River Catchment ◽  
Catchment Areas ◽  
Runoff Model

The boreal winter 2019/2020 was very irregular in Europe. While there was very little snow in Central Europe, the opposite was the case in northern Fenno-Scandia, particularly in the Arctic. The snow cover was more persistent here and its rapid melting led to flooding in many places. Since the last severe spring floods occurred in the region in 2018, this raises the question of whether more frequent occurrences can be expected in the future. To assess the variability of snowmelt related flooding we used snow cover maps (derived from the DLR’s Global SnowPack MODIS snow product) and freely available data on runoff, precipitation, and air temperature in eight unregulated river catchment areas. A trend analysis (Mann-Kendall test) was carried out to assess the development of the parameters, and the interdependencies of the parameters were examined with a correlation analysis. Finally, a simple snowmelt runoff model was tested for its applicability to this region. We noticed an extraordinary variability in the duration of snow cover. If this extends well into spring, rapid air temperature increases leads to enhanced thawing. According to the last flood years 2005, 2010, 2018, and 2020, we were able to differentiate between four synoptic flood types based on their special hydrometeorological and snow situation and simulate them with the snowmelt runoff model (SRM).

scholarly journals IMPACTS OF SNOWMELT AND CLIMATE CHANGE ON HIMALAYAN RIVERS: THE CASE OF DATA-SCARCE DUDHKOSHI RIVER IN EASTERN NEPAL

2021 ◽  
Vol 5 (12) ◽  
Author(s):  
Sudeep Pokhrel ◽  
Saraswati Thapa
Keyword(s):  
Maximum Temperature ◽  
Climate Projections ◽  
Snow Melt ◽  
Snow Hydrology ◽  
Statistical Downscaling Model ◽  
Snowmelt Runoff ◽  
Annual Average ◽  
Temperature And Precipitation ◽  
Increasing Trends ◽  
Runoff Model

Water from snow-melt is crucial to provide ecosystem services in downstream of the Himalayas. To study the fate of snow hydrology, an integrated modeling system has been developed coupling Statistical Downscaling Model (SDSM) outputs with Snowmelt Runoff Model (SRM) in the Dudhkoshi Basin, Nepal. The SRM model is well-calibrated in 2011 and validated in 2012 and 2014 using MODIS satellite data. The annual average observed and simulated discharges for the calibration year are 177.89 m3 /s and 181.47 m3 /s respectively. To assess future climate projections for the periods 2020s, 2050s, and 2080s, the SDSM model is used for downscaling precipitation, maximum temperature, and minimum temperature from the Canadian GCM model (CanESM2) under three different scenarios RCP2.6, RCP4.5 and RCP8.5. All considered scenarios are significant in predicting increasing trends of maximumminimum temperature and precipitation and the storehouse of freshwater in the mountains is expected to deplete rapidly if global warming continues.

Estimating water consumption and factors affecting intake in grazing cattle

1994 ◽  
Vol 74 (3) ◽  
pp. 551-554 ◽  
Author(s):  
Shaukat Ali ◽  
L. A. Goonewardene ◽  
J. A. Basarab
Keyword(s):  
Relative Humidity ◽  
Key Words ◽  
Water Consumption ◽  
Important Determinant ◽  
Daily Temperature ◽  
Maximum Daily Temperature ◽  
Factors Affecting ◽  
Percentage Decrease ◽  
Grazing Cattle

Water consumption (WC) by 39.5 animal units (AU) of grazing cattle was studied at a central Alberta site in summer. Average WC AU−1 was estimated at 48.9 L d−1. WC increased by 0.68 L AU−1 (P < 0.01) for each percentage decrease in relative humidity, increased by 0.81 L AU−1 (P < 0.02) for each degree Celsius increase in maximum daily temperature, and increased by 0.15 L AU−1 (P < 0.06) as cattle grew and the season progressed. Relative humidity is shown to be an important determinant of WC in grazing cattle. Key words: Water consumption, animal unit, temperature, humidity, grazing cattle

Accuracy of Snowmelt Runoff Simulation

1981 ◽  
Vol 12 (4-5) ◽  
pp. 265-274 ◽  
Author(s):  
A. Rango ◽  
J. Martinec
Keyword(s):  
Snow Cover ◽  
Input Data ◽  
Snowmelt Runoff ◽  
Runoff Simulation ◽  
Simulation Accuracy ◽  
Temperature And Precipitation ◽  
Recession Coefficient ◽  
Snow Cover Extent ◽  
Mountainous Basin

Results of runoff simulations from various basins using a snowmelt runoff model were analyzed in order to predict the accuracy of simulations in future applications of the model. It was found that the model can be applied to nearly any mountainous basin where snowmelt runoff is an important factor if input data on temperature, precipitation, and snow cover are available. The simulation accuracy will depend on the quality of the input data as well as on the density of observations, size of the basin, care in determination of the recession coefficient, and amount of precipitation during snowmelt. Most accurate simulations will result when: 1) temperature and precipitation are recorded at the basin mean elevation; 2) snow cover observations are available once per week; 3) several climatic stations are available for large basins; and 4) a few years of runoff records exist for determination of the recession coefficient. Decreases in simulation accuracy will be expected as these optimum conditions are compromised, however, acceptable simulations will result with the following minimum conditions: 1) temperature and precipitation data are available in the general vicinity of the basin; and 2) snow cover observations are available 2-3 times during the snowmelt season. The availability of satellite observations of snow cover extent has permitted successful application of the model to large basins.

FACTORS INFLUENCING THE COMMERCIAL INCIDENCE OF DARK CUTTING BEEF

1989 ◽  
Vol 69 (3) ◽  
pp. 649-654 ◽  
Author(s):  
S. D. M. JONES ◽  
A. K. W. TONG
Keyword(s):  
Key Words ◽  
Daily Precipitation ◽  
Visual Assessment ◽  
Predisposing Factors ◽  
Daily Temperature ◽  
Carcass Weight ◽  
Temperature And Precipitation ◽  
Factors Influencing ◽  
Muscle Color ◽  
Beef Carcass

Data collected on 170 534 head of Saskatchewan cattle slaughtered over a period of 12 consecutive months were used to evaluate the importance of some factors influencing the incidence of dark cutting (DC) beef (Canada B2 grade based on a visual assessment of muscle color and texture). The variables examined included carcass weight, gender of animal, daily temperature and precipitation, month of slaughter, distance from farm to abattoir, mixing of loads during transportation and slaughter plant. DC beef compared to normal beef was associated with a slightly warmer daily temperature (5.4 vs. 4.8 °C), a lighter carcass weight (283 vs. 286 kg), but was not influenced by daily precipitation. The incidence of DC beef increased as distance between farm and slaughter plant increased (0.78–0.98%), and was higher in loads of cattle that were mixed during transportation than in those loads that originated from the same farm (1.11 vs. 0.79%). Steers recorded a higher frequency of DC beef than heifers (0.99 vs. 0.77%). There were large differences in the frequency of DC beef among slaughter plants after adjustment of the data for the effects of other variables (gender, mixing, trucking distance). Of the six slaughter plants in this study, the frequency of DC beef ranged from 0.27–1.79%. Month of shipment had a significant effect on the incidence of DB beef, with March and April recording the highest frequencies (1.54 and 1.24%), and December the lowest (0.45%). It was concluded that the mixing of loads and the slaughter plant were the two most important predisposing factors for DC beef. Key words: Beef, carcass, stress, dark cutting

scholarly journals ESTIMATION OF SNOW DEPLETION CURVE FOR GANGOTRI BASIN USING MULTI-SOURCE REMOTE SENSING DATA

2021 ◽  
Vol V-3-2021 ◽  
pp. 197-202
Author(s):  
P. Verma ◽  
S. K. Ghosh ◽  
R. Ramsankaran
Keyword(s):  
Snow Cover ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Snowmelt Runoff ◽  
Multiple Sources ◽  
Snow Cover Area ◽  
Depletion Curve ◽  
Normalized Difference Snow Index ◽  
Runoff Model ◽  
Key Parameter

Abstract. Snow Depletion Curve derived from satellite images is a key parameter in Snowmelt Runoff Model. The fixed temporal resolution of a satellite and presence of cloud cover in Himalayas restricts accuracy of generated SDC. This study presents an effective approach of reducing temporal interval between two consecutive dates by integrating normalized Snow Cover Area estimated from multiple sources of satellite data. SCA is extracted by using Normalized Difference Snow Index for six snowmelt seasons from 2013 to 2018 for Gangotri basin situated in Indian Himalayas. This work also explores potential of recently launched Sentinel-3A for estimating SCA. Normalized SCA is utilized to eliminate the effect of difference in spatial resolution of various satellites. The result develops an important linear relation between SDC and time with a decrease in snow cover of 0.005/day that may be further refined by increasing the number of snowmelt seasons. This relationship may help scientific community in understanding hydrological response of glaciers to climate change.

A comparison of MODIS and NOHRSC snow-cover products for simulating streamflow using the Snowmelt Runoff Model

2005 ◽  
Vol 19 (15) ◽  
pp. 2951-2972 ◽  
Author(s):  
Songweon Lee ◽  
Andrew G. Klein ◽  
Thomas M. Over
Keyword(s):  
Snow Cover ◽  
Snowmelt Runoff ◽  
Runoff Model

scholarly journals Hydrological Data-Model Work in Greenland

1984 ◽  
Vol 15 (1) ◽  
pp. 39-56 ◽  
Author(s):  
Th. Thomsen ◽  
G.H. Jørgensen
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Drainage Basin ◽  
Model Simulation ◽  
Drainage Basins ◽  
Hydrological Data ◽  
Heating And Cooling ◽  
Temperature And Precipitation ◽  
Runoff Model ◽  
Ablation Model

The hydrological studies of the Greenland technical Organization in Greenland are being followed up at Copenhagen by hydrological data work as well as hydrological model-simulation. The hydrological regions vary greatly in Greenland, depending on whether the drainage basin is influenced by ablation runoff. To describe a runoff time series from these areas, a hydrological model calibration is made, followed by a simulation. In drainage basins influenced by rain and snow only, a slightly modified version of the precipitation runoff model (NAM) is applied. The parameter transfer for the determination of model input is found by intensive data analysis work here between Nuuk and Kangerluarsunnguup Tasersua (KANG) for temperature and precipitation along with detailed investigations in the basin. This is to ensure that a too short calibration period in connection with the adaption of a hydrological model to the basin data is balanced in the manner that these adapt the hydrological model, and not vice versa. In drainage basins also influenced by ablation runoff it is not possible to use a traditional precipitation runoff model but a hydrological ablation model has been developed in cooperation with The Geological Survey of Greenland. The hydrological ablation model describes the transfer of the temperature after heating and cooling factors as well as snow mobility on the ice, melting density criteria, refreezing etc. The model has been applied to the hydrological basin of Paakitsup Akuliarusersua (PAKI) at Ilulissat where 90% of the drainage basin is covered by the Ice cap. Data evaluation work prior to hydrological model calibration thus allows for a higher degree of simulation reliability.

scholarly journals Climate Change Scenarios and Effects on Snow-Melt Runoff

2020 ◽  
Vol 6 (9) ◽  
pp. 1715-1725 ◽  
Author(s):  
Safieh Javadinejad ◽  
Rebwar Dara ◽  
Forough Jafary
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Annual Runoff ◽  
Hydrologic Model ◽  
Climate Change Scenarios ◽  
Snow Melt ◽  
Snowmelt Runoff ◽  
Rcp Scenarios ◽  
Temperature And Precipitation ◽  
Spring Runoff

Climate change is an important environmental issue, as progression of melting glaciers and snow cover is sensitive to climate alteration. The aim of this research was to model climate alterations forecasts, and to assess potential changes in snow cover and snow-melt runoff under the different climate change scenarios in the case study of the Zayandeh-rud River Basin. Three cluster models for climate change (NorESM1-M, IPSL-CM5A-LR and CSIRO-MK3.6.0) were applied under RCP 8.5, 4.5 and 2.6 scenarios, to examine climate influences on precipitation and temperature in the basin. Temperature and precipitation were determined for all three scenarios for four periods of 2021-2030, 2031-2040, 2041-2050 and 2051-2060. MODIS (MOD10A1) was also applied to examine snow cover using temperature and precipitation data. The relationship between snow-covered area, temperature and precipitation was used to forecast future snow cover. For modeling future snow melt runoff, a hydrologic model of SRM was used including input data of precipitation, temperature and snow cover. The results indicated that all three RCP scenarios lead to an increase in temperature, and reduction in precipitation and snow cover. Investigation in snowmelt runoff throughout the observation period (November 1970 to May 2006) showed that most of annual runoff is derived from snow melting. Maximum snowmelt runoff is generated in winter. The share of melt water in the autumn and spring runoff is estimated at 35 and 53%, respectively. The results of this study can assist water manager in making better decisions for future water supply.

scholarly journals Application of the Snowmelt Runoff Model in the Salang River Basin, Afghanistan Using MODIS Satellite Data

2016 ◽  
Vol 9 (1) ◽  
pp. 109-118
Author(s):  
Hedayatullah Arian ◽  
Rijan B. Kayastha ◽  
Bikas C. Bhattarai ◽  
Ahuti Shresta ◽  
Hafizullah Rasouli ◽  
...  
Keyword(s):  
River Basin ◽  
River Flow ◽  
Snowmelt Runoff ◽  
Annual Average ◽  
Temperature And Precipitation ◽  
Promising Tool ◽  
Daily Discharge ◽  
Input Variables ◽  
The Impact ◽  
Runoff Model

This study is carried out on the Salang River basin, which is located at the northern part of the Kabul River basin, and in the south facing slope of the Hindu Kush Mountains. The basin drains through the Salang River, which is one of the tributaries of the Panjshir River. The basin covers an area of 485.9km2 with a minimum elevation of 1653 m a.s.l. and a maximum elevation of 4770 m a.s.l. The Salang River sustains a substantial flow of water in summer months due to the melting of snow. In this study, we estimate daily discharge of Salang River from 2009 to 2011 using the Snowmelt Runoff Model (SRM, Version 1.12, 2009), originally developed by J. Martinec in 1975. The model uses daily observed precipitation, air temperature and snow cover data as input variables from which discharge is computed. The model is calibrated for the year 2009 and validated for 2010 and 2011. The observed and calculated annual average discharges for the calibration year 2009 are 11.57m3s-1 and 10.73m3s-1, respectively. Similarly, the observed and calculated annual average discharges for the validation year 2010 are 11.55m3s-1 and 10.07m3s-1, respectively and for 2011, the discharges are 9.05 m3s-1 and 9.6m3s-1, respectively. The model is also tested by changing temperature and precipitation for the year 2009. With an increase of 1°C in temperature and 10% in precipitation, the increases in discharge for winter, summer and annually are 21.8%, 13.5% and 14.8%, respectively. With an increase of 2°C in temperature and 20% in precipitation, the increases are 48.5%, 43.3% and 44.1%, respectively. The results obtained suggest that the SRM can be used as a promising tool to estimate the river discharge of the snow fed mountainous river basins of Afghanistan and to study the impact of climate change on river flow pattern of such basins.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.109-118

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