Modeling Snowmelt Runoff under Climate Change Scenarios Using MODIS-Based Snow Cover Products

2012 ◽  
pp. 213-249
Author(s):  
Russell J. Qualls ◽  
Ayodeji Arogundade
2020 ◽  
Vol 6 (9) ◽  
pp. 1715-1725 ◽  
Author(s):  
Safieh Javadinejad ◽  
Rebwar Dara ◽  
Forough Jafary

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.


mSphere ◽  
2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Sarahi L. Garcia ◽  
Anna J. Szekely ◽  
Christoffer Bergvall ◽  
Martha Schattenhofer ◽  
Sari Peura

ABSTRACT Climate change scenarios anticipate decreased spring snow cover in boreal and subarctic regions. Forest lakes are abundant in these regions and substantial contributors of methane emissions. To investigate the effect of reduced snow cover, we experimentally removed snow from an anoxic frozen lake. We observed that the removal of snow increased light penetration through the ice, increasing water temperature and modifying microbial composition in the different depths. Chlorophyll a and b concentrations increased in the upper water column, suggesting activation of algal primary producers. At the same time, Chlorobiaceae, one of the key photosynthetic bacterial families in anoxic lakes, shifted to lower depths. Moreover, a decrease in the relative abundance of methanotrophs within the bacterial family Methylococcaceae was detected, concurrent with an increase in methane concentration in the water column. These results indicate that decreased snow cover impacts both primary production and methane production and/or consumption, which may ultimately lead to increased methane emissions after spring ice off. IMPORTANCE Small lakes are an important source of greenhouse gases in the boreal zone. These lakes are severely impacted by the winter season, when ice and snow cover obstruct gas exchange between the lake and the atmosphere and diminish light availability in the water column. Currently, climate change is resulting in reduced spring snow cover. A short-term removal of the snow from the ice stimulated algal primary producers and subsequently heterotrophic bacteria. Concurrently, the relative abundance of methanotrophic bacteria decreased and methane concentrations increased. Our results increase the general knowledge of microbial life under ice and, specifically, the understanding of the potential impact of climate change on boreal lakes.


2011 ◽  
Vol 11 (6) ◽  
pp. 1769-1785 ◽  
Author(s):  
B. Groppelli ◽  
A. Soncini ◽  
D. Bocchiola ◽  
R. Rosso

Abstract. We investigate future (2045–2054) hydrological cycle of the snow fed Oglio (≈1800 km2) Alpine watershed in Northern Italy. A Stochastic Space Random Cascade (SSRC) approach is used to downscale future precipitation from three general circulation models, GCMs (PCM, CCSM3, and HadCM3) available within the IPCC's data base and chosen for this purpose based upon previous studies. We then downscale temperature output from the GCMs to obtain temperature fields for the area. We also consider a projected scenario based upon trends locally observed in former studies, LOC scenario. Then, we feed the downscaled fields to a minimal hydrological model to build future hydrological scenarios. We provide projected flow duration curves and selected flow descriptors, giving indication of expected modified (against control run for 1990–1999) regime of low flows and droughts and flood hazard, and thus evaluate modified peak floods regime through indexed flood. We then assess the degree of uncertainty, or spread, of the projected water resources scenarios by feeding the hydrological model with ensembles projections consistent with our deterministic (GCMs + LOC) scenarios, and we evaluate the significance of the projected flow variables against those observed in the control run. The climate scenarios from the adopted GCMs differ greatly from one another with respect to projected precipitation amount and temperature regimes, and so do the projected hydrological scenarios. A relatively good agreement is found upon prospective shrinkage and shorter duration of the seasonal snow cover due to increased temperature patterns, and upon prospective increase of hydrological losses, i.e. evapotranspiration, for the same reason. However, precipitation patterns are less consistent, because HadCM3 and PCM models project noticeably increased precipitation for 2045–2054, whereas CCSM3 provides decreased precipitation patterns therein. The LOC scenario instead displays unchanged precipitation. The ensemble simulations indicate that several projected flow variables under the considered scenarios are significantly different from their control run counterparts, and also that snow cover seems to significantly decrease in duration and depth. The proposed hydrological scenarios eventually provide a what-if analysis, giving a broad view of the possible expected impacts of climate change within the Italian Alps, necessary to trigger the discussion about future adaptation strategies.


1997 ◽  
Vol 28 (4-5) ◽  
pp. 273-282 ◽  
Author(s):  
C-Y Xu ◽  
Sven Halldin

Within the next few decades, changes in global temperature and precipitation patterns may appear, especially at high latitudes. A simple monthly water-balance model of the NOPEX basins was developed and used for the purposes of investigating the effects on water availability of changes in climate. Eleven case study catchments were used together with a number of climate change scenarios. The effects of climate change on average annual runoff depended on the ratio of average annual runoff to average annual precipitation, with the greatest sensitivity in the catchments with lowest runoff coefficients. A 20% increase in annual precipitation resulted in an increase in annual runoff ranging from 31% to 51%. The greatest changes in monthly runoff were in winter (from December to March) whereas the smallest changes were found in summer. The time of the highest spring flow changed from April to March. An increase in temperature by 4°C greatly shortened the time of snow cover and the snow accumulation period. The maximum amount of snow during these short winters diminished by 50% for the NOPEX area even with an assumed increase of total precipitation by 20%.


Water ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 3535
Author(s):  
Elmer Calizaya ◽  
Abel Mejía ◽  
Elgar Barboza ◽  
Fredy Calizaya ◽  
Fernando Corroto ◽  
...  

Effects of climate change have led to a reduction in precipitation and an increase in temperature across several areas of the world. This has resulted in a sharp decline of glaciers and an increase in surface runoff in watersheds due to snowmelt. This situation requires a better understanding to improve the management of water resources in settled areas downstream of glaciers. In this study, the snowmelt runoff model (SRM) was applied in combination with snow-covered area information (SCA), precipitation, and temperature climatic data to model snowmelt runoff in the Santa River sub-basin (Peru). The procedure consisted of calibrating and validating the SRM model for 2005–2009 using the SRTM digital elevation model (DEM), observed temperature, precipitation and SAC data. Then, the SRM was applied to project future runoff in the sub-basin under the climate change scenarios RCP 4.5 and RCP 8.5. SRM patterns show consistent results; runoff decreases in the summer months and increases the rest of the year. The runoff projection under climate change scenarios shows a substantial increase from January to May, reporting the highest increases in March and April, and the lowest records from June to August. The SRM demonstrated consistent projections for the simulation of historical flows in tropical Andean glaciers.


1997 ◽  
Vol 25 ◽  
pp. 232-236 ◽  
Author(s):  
A. Rango

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.


2014 ◽  
Vol 8 (5) ◽  
pp. 1673-1697 ◽  
Author(s):  
H. Castebrunet ◽  
N. Eckert ◽  
G. Giraud ◽  
Y. Durand ◽  
S. Morin

Abstract. Projecting changes in snow cover due to climate warming is important for many societal issues, including the adaptation of avalanche risk mitigation strategies. Efficient modelling of future snow cover requires high resolution to properly resolve the topography. Here, we introduce results obtained through statistical downscaling techniques allowing simulations of future snowpack conditions including mechanical stability estimates for the mid and late 21st century in the French Alps under three climate change scenarios. Refined statistical descriptions of snowpack characteristics are provided in comparison to a 1960–1990 reference period, including latitudinal, altitudinal and seasonal gradients. These results are then used to feed a statistical model relating avalanche activity to snow and meteorological conditions, so as to produce the first projection on annual/seasonal timescales of future natural avalanche activity based on past observations. The resulting statistical indicators are fundamental for the mountain economy in terms of anticipation of changes. Whereas precipitation is expected to remain quite stationary, temperature increase interacting with topography will constrain the evolution of snow-related variables on all considered spatio-temporal scales and will, in particular, lead to a reduction of the dry snowpack and an increase of the wet snowpack. Overall, compared to the reference period, changes are strong for the end of the 21st century, but already significant for the mid century. Changes in winter are less important than in spring, but wet-snow conditions are projected to appear at high elevations earlier in the season. At the same altitude, the southern French Alps will not be significantly more affected than the northern French Alps, which means that the snowpack will be preserved for longer in the southern massifs which are higher on average. Regarding avalanche activity, a general decrease in mean (20–30%) and interannual variability is projected. These changes are relatively strong compared to changes in snow and meteorological variables. The decrease is amplified in spring and at low altitude. In contrast, an increase in avalanche activity is expected in winter at high altitude because of conditions favourable to wet-snow avalanches earlier in the season. Comparison with the outputs of the deterministic avalanche hazard model MEPRA (Modèle Expert d'aide à la Prévision du Risque d'Avalanche) shows generally consistent results but suggests that, even if the frequency of winters with high avalanche activity is clearly projected to decrease, the decreasing trend may be less strong and smooth than suggested by the statistical analysis based on changes in snowpack characteristics and their links to avalanches observations in the past. This important point for risk assessment pleads for further work focusing on shorter timescales. Finally, the small differences between different climate change scenarios show the robustness of the predicted avalanche activity changes.


1997 ◽  
Vol 25 ◽  
pp. 232-236
Author(s):  
A. Rango

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.


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