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.

scholarly journals Use of satellite-derived data for characterization of snow cover and simulation of snowmelt runoff through a distributed physically based model of runoff generation

2010 ◽  
Vol 14 (2) ◽  
pp. 339-350 ◽  
Author(s):  
L. S. Kuchment ◽  
P. Romanov ◽  
A. N. Gelfan ◽  
V. N. Demidov
Keyword(s):  
Snow Cover ◽  
Initial Conditions ◽  
Tree Cover ◽  
Special Focus ◽  
Snowmelt Runoff ◽  
Runoff Generation ◽  
Runoff Simulation ◽  
Physically Based Model ◽  
Physically Based ◽  
Derived Data

Abstract. A technique of using satellite-derived data for constructing continuous snow characteristics fields for distributed snowmelt runoff simulation is presented. The satellite-derived data and the available ground-based meteorological measurements are incorporated in a physically based snowpack model. The snowpack model describes temporal changes of the snow depth, density and water equivalent (SWE), accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The remote sensing data used in the model consist of products include the daily maps of snow covered area (SCA) and SWE derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites as well as available maps of land surface temperature, surface albedo, land cover classes and tree cover fraction. The model was first calibrated against available ground-based snow measurements and then applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The satellite-derived SWE data were used for assigning initial conditions and the SCA data were used for control of snow cover simulation. The simulated spatial distributions of snow characteristics were incorporated in a distributed physically based model of runoff generation to calculate snowmelt runoff hydrographs. The presented technique was applied to a study area of approximately 200 000 km2 including the Vyatka River basin with catchment area of 124 000 km2. The correspondence of simulated and observed hydrographs in the Vyatka River are considered as an indicator of the accuracy of constructed fields of snow characteristics and as a measure of effectiveness of utilizing satellite-derived SWE data for runoff simulation.

scholarly journals Changes in Andes snow cover from MODIS data, 2000–2016

2018 ◽  
Vol 12 (3) ◽  
pp. 1027-1046 ◽  
Author(s):  
Freddy A. Saavedra ◽  
Stephanie K. Kampf ◽  
Steven R. Fassnacht ◽  
Jason S. Sibold
Keyword(s):  
Snow Cover ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Significant Loss ◽  
Climate Indices ◽  
Climate Data ◽  
Large Area ◽  
Temperature And Precipitation ◽  
The Andes ◽  
Snow Cover Extent

Abstract. The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent). This analysis is conducted between 8 and 36∘ S due to high frequency of cloud (> 30 % of the time) south and north of this range. We ran Mann–Kendall and Theil–Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP = 20 %). We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) and University of Delaware datasets and climate indices as El Niño–Southern Oscillation (ENSO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO). Areas north of 29∘ S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2) with persistent snow cover between 29 and 36∘ S experienced a significant loss of snow cover (2–5 fewer days of snow year−1). Snow loss was more pronounced (62 % of the area with significant trends) on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10–30 m year−1 south of 29–30∘ S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31∘ S, whereas the SAM better predicted SP south of 31∘ S.

scholarly journals The Response of Areal Snow Cover to Climate Change in a Snowmelt—Runoff Model

1997 ◽  
Vol 25 ◽  
pp. 232-236 ◽  
Author(s):  
A. Rango
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Major Influence ◽  
Snowmelt Runoff ◽  
Snow Cover Extent ◽  
Physically Based ◽  
Depletion Rate ◽  
Snow Water ◽  
Runoff Model

The cryosphere is represented in some hydrological models by the arcal extent of snow cover, a variable that has been operationally available in recent years through remote sensing. In particular, the snowmelt runoff model (SRM) requires the remotely sensed snow-cover extent as a major input variable. The SRM is well-suited for simulating the hydrological response of a basin to hypothetical climate change because it is a non-calibrated model. In order to run the SRM in a climate-change mode, the response of the areal snow cover to a change in climate is critical, and must be calculated as a function of elevation, precipitation, temperature, and snow-water equivalent. For the snowmelt-runoff season, the effect of climate change on conditions in the winter months has a major influence. In a warmer climate, winter may experience more rain vs snow events, and more periods of winter snowmelt that reduce the snow water equivalent present in the basin at the beginning of spring snow melt. As a result, the spring snowmelt runoff under conditions of climate warming will be affected not only by different temperatures and precipitation, but also by a different snow cover with a changed depletion rate. A new radiation-based version of the SRM is under development that will also take changes in cloudiness and humidity into account, making climate-change studies of the cryosphere even more physically based.

scholarly journals Sensitivity of snowmelt runoff modelling to the level of cloud coverage for snow cover extent from daily MODIS product collection 6

2021 ◽  
Vol 36 ◽  
pp. 100835
Author(s):  
Wahidullah Hussainzada ◽  
Han Soo Lee ◽  
Bhanage Vinayak ◽  
Ghulam Farooq Khpalwak
Keyword(s):  
Snow Cover ◽  
Snowmelt Runoff ◽  
Cloud Coverage ◽  
Snow Cover Extent

scholarly journals Changes in Andes Mountains snow cover from MODIS data 2000–2014

2017 ◽  
Author(s):  
Freddy A. Saavedra ◽  
Stephanie K. Kampt ◽  
Steven R. Fassnacht ◽  
Jason S. Sibold
Keyword(s):  
Snow Cover ◽  
Significant Loss ◽  
Andes Mountains ◽  
Climate Indices ◽  
Climate Data ◽  
Large Area ◽  
Temperature And Precipitation ◽  
The Andes ◽  
Snow Cover Extent ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The Andes Mountains span a length of 7,000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000–2014 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent) limited between 8 °S and 36 °S due high frequency of cloud (>30 % of the time) south and north of this range. We ran Mann-Kendall and Theil-Sens analyses to identify significant areas of change in SP and snow line (the line at lower elevation which SP=20%). We evaluated whether these trends in the context of temperature and precipitation (University of Delaware dataset) and climate indices (ENSO, SAM, PDO). North of 29 °S has limited snow cover, and few trends in snow persistence were detected. A large area (70,515 km2) with persistent snow cover between 29–36 °S experienced a significant loss of snow cover (2–5 fewer days of snow year−1). Snow loss was more pronounced (62 %) on the east side of the Andes. We also found a significant increase in the elevation of 10–30 m year−1 south of 29–30 °S. Decreasing SP correlates with decreasing precipitation, increasing temperature, and climate indices and it varies with latitude and elevation. ENSO indices better predicted SP conditions north of 31 °S, and the SAM better predicted SP south of 31 °S.

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 The response of areal snow cover to climate change in a snowmelt–runoff model

1997 ◽  
Vol 25 ◽  
pp. 232-236
Author(s):  
A. Rango
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Major Influence ◽  
Snowmelt Runoff ◽  
Snow Cover Extent ◽  
Physically Based ◽  
Snow Water ◽  
Runoff Model ◽  
Spring Snowmelt

The cryosphere is represented in some hydrological models by the areal extent of snow cover, a variable that has been operationally available in recent years through remote sensing. In particular, the snowmelt–runoff model (SRM) requires the remotely sensed snow-cover extent as a major input variable. The SRM is well-suited for simulating the hydrological response of a basin to hypothetical climate change because it is a non-calibrated model. In order to run the SRM in a climate-change mode, the response of the areal snow cover to a change in climate is critical, and must be calculated as a function of elevation, precipitation, temperature, and snow-water equivalent. For the snowmelt-runoff season, the effect of climate change on conditions in the winter months has a major influence. In a warmer climate, winter may experience more rain vs snow events, and more periods of winter snowmelt that reduce the snow water equivalent present in the basin at the beginning of spring snowmelt. As a result, the spring snowmelt runoff under conditions of climate warming will be affected not only by different temperatures and precipitation, but also by a different snow cover with a changed depletion rate. A new radiation-based version of the SRM is under development that will also take changes in cloudiness and humidity into account, making climate-change studies of the cryosphere even more physically based.

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]

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