Melted snow volume control in the snowmelt runoff model using a snow water equivalent statistically based model

Snowmelt is an important component of the river discharge in mountain environments. In the past 40 years, the snowmelt dynamics has been mostly evaluated using degree‐day‐based models like the snowmelt runoff model (SRM). This model has no control on the volume of the melting snow, even if SRM includes as data input the snow‐covered area. This lack explains why the application of SRM may lead to inaccurate snowmelt volume estimations, even if the discharge volumes are accurately reproduced. Here we introduce in SRM the control on the melted snow volume and consider it in the determination of SRM parameters. The total snow volume, accumulated at the end of winter season, is evaluated by a snow water equivalent statistically based model, SWE‐SEM, and used as an estimate of the melting snow during the summer season. The benefit derived from the introduction of the control on the melting snow volume was investigated in the Mallero basin (northern Italy) for the 2003 and 2004 snow melting seasons. The analysis compares the model's results adopting different parameter sets, both considering and ignoring the control on the melting snow volume. Copyright © 2011 John Wiley & Sons, Ltd.     

One‐year‐long runoff forecast by a single snowpack evaluation

A degree‐day‐based model is presented for a 1 year ahead runoff forecast, with 1 day time steps. The input information is a single snowpack evaluation collected at the beginning of the snowmelt season. The snow‐cover dynamics, the key information for long‐term snowmelt forecast, are described by the snow‐line dynamics, i.e. by the movements of the downhill snowpack limit. The snowmelt volume, estimated by the snow‐line dynamics, is the exogenous input of an autoregressive transformation model. The model is calibrated by a least‐squares procedure on the basis of observed daily runoff data and the corresponding measurements of the snowpack volume (one measurement per year). A real‐world case study on the Alto Tunuyan River basin (2380 km², Argentinean Andes) is presented. The 1 year ahead Alto Tunuyan River runoff patterns, computed for both calibration and validation periods, reveal high agreement with observed streamflows. Copyright © 2004 John Wiley & Sons, Ltd.     

Application of snowmelt runoff model for water resource management

Snow‐covered areas (SCAs) are the fundamental source of water for the hydrological cycle for some region. Accurate measurements of river discharge from snowmelt can help manage much needed water required for hydropower generation and irrigation purposes. This study aims to apply the snowmelt runoff model (SRM) in the Upper Indus basin by the Astore River in northern Pakistan for the years 2000 to 2006. The Shuttle Radar Topographic Mission (SRTM) data are used to generate the Digital Elevation Model (DEM) of the region. Various variables (snow cover depletion curves (SCDCs), temperature and precipitation) and parameters (degree‐day factor, recession coefficient, runoff coefficients, time lag, critical temperature and temperature lapse rate) are used as input in the SRM. However, snow cover data are direct and an important input to the SRM. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate the SCA. Normalized difference snow index (NDSI) algorithm is applied for snow cover mapping and to differentiate snow from other land features. Nash–Sutcliffe coefficient of determination (R²) and volume difference (D_V) are used for quality assessment of the SRM. The results of the current research show that for the study years (2000–2006), the average value of R² is 0·87 and average volume difference D_V is 1·18%. The correlation coefficient between measured and computed runoff is 0·95. The results of the study further show that a high level of accuracy can be achieved during the snowmelt season. The simulation results endorse that the SRM in conjunction with MODIS snow cover product is very useful for water resource management in the Astore River and can be used for runoff forecasts in the Indus River basin in northern Pakistan. Copyright © 2011 John Wiley & Sons, Ltd.     

Incorporating accumulated temperature and algorithm of snow cover calculation into the snowmelt runoff model

An accurate simulation of snowmelt runoff is of much importance in arid alpine regions. Data availability is usually an obstacle to use energy‐based snowmelt models for the snowmelt runoff simulation, and temperature‐based snowmelt models are more appealing in these regions. The snow runoff model is very popular nowadays, especially in the data sparse regions, because only temperature, precipitation and snow cover data are required for inputs to the model. However, this model uses average temperature as index, which cannot reflect the snowmelt simulation in the high altitude band. In this study, the snow runoff model is modified on the basis of accumulated active temperature. Snow cover calculation algorithm is added and is no longer needed as input but output. This makes the model able to simulate long‐time runoff and long‐time snow cover variation in every band. An examination of the improved model in the Manas River basin showed that the model is effective. It can reproduce the behaviour of the hydrology and can reflect the actual snow cover fluctuation. Copyright © 2012 John Wiley & Sons, Ltd.     

Hydrological sensitivity of a large Himalayan basin to climate change

The present study sets out to investigate the sensitivity of water availability to climate change for a large western Himalayan river (the Satluj River basin with an area of 22 275 km² and elevation range of 500 to 7000 m), which receives contributions from rain, snow and glacier melt runoff. About 65% of the basin area is covered with snow during winter, which reduces to about 11% after the ablation period. After having calibrated a conceptual hydrological model to provide accurate simulations of observed stream flow, the hydrological response of the basin was simulated using different climatic scenarios over a period of 9 years. Adopted plausible climate scenarios included three temperature scenarios (T + 1, T + 2, T + 3 °C) and four rainfall scenarios (P ? 10, P ? 5, P + 5 and P + 10%). The effect of climate change was studied on snowmelt and rainfall contribution runoff, and total stream flow. Under warmer climate, a typical feature of the study basin was found to be reduction in melt from the lower part of the basin owing to a reduction in snow covered area and shortening of the summer melting season, and, in contrast, an increase in the melt from the glacierized part owing to larger melt and an extended ablation period. Thus, on the basin scale, reduction in melt from the lower part was counteracted by the increase from melt from upper part of the basin, resulting in a decrease in the magnitude of change in annual melt runoff. The impact of climate change was found to be more prominent on seasonal rather than annual water availability. Reduction of water availability during the summer period, which contributes about 60% to the annual flow, may have severe implications on the water resources of the region, because demand of water for irrigation, hydropower and other usage is at its peak at this time. Copyright © 2004 John Wiley & Sons, Ltd.     

On the role of spatial resolution on snow estimates using a process‐based snow model across a range of climatology and elevation

Hydrological processes in mountainous settings depend on snow distribution, whose prediction accuracy is a function of model spatial scale. Although model accuracy is expected to improve with finer spatial resolution, an increase in resolution comes with modelling costs related to increased computational time and greater input data and parameter information. This computational and data collection expense is still a limiting factor for many large watersheds. Thus, this work's main objective is to question which physical processes lead to loss in model accuracy with regard to input spatial resolution under different climatic conditions and elevation ranges. To address this objective, a spatially distributed snow model, iSnobal, was run with inputs distributed at 50‐m—our benchmark for comparison—and 100‐m resolutions and with aggregated (averaged from the fine to the large resolution) inputs from the 50‐m model to 100‐, 250‐, 500‐, and 750‐m resolution for wet, average, and dry years over the Upper Boise River Basin (6,963 km²), which spans four elevation bands: rain dominated, rain–snow transition, and snow dominated below treeline and above treeline. Residuals, defined as differences between values quantified with high resolution (>50 m) models minus the benchmark model (50 m), of simulated snow‐covered area (SCA) and snow water equivalent (SWE) were generally slight in the aggregated scenarios. This was due to transferring the effects of topography on meteorological variables from the 50‐m model to the coarser scales through aggregation. Residuals in SCA and SWE in the distributed 100‐m simulation were greater than those of the aggregated 750 m. Topographic features such as slope and aspect were simplified, and their gradient was reduced due to coarsening the topography from the 50‐ to 100‐m resolution. Therefore, solar radiation was overestimated, and snow drifting was modified and caused substantial SCA and SWE underestimation in the distributed 100‐m model relative to the 50‐m model. Large residuals were observed in the wet year and at the highest elevation band when and where snow mass was large. These results support that model accuracy is substantially reduced with model scales coarser than 50 m.     

Development and application of a spatially‐distributed Arctic hydrological and thermal process model (ARHYTHM)

A process‐based, spatially distributed hydrological model was developed to quantitatively simulate the energy and mass transfer processes and their interactions within arctic regions (arctic hydrological and thermal model, ARHYTHM). The model first determines the flow direction in each element, the channel drainage network and the drainage area based upon the digital elevation data. Then it simulates various physical processes: including snow ablation, subsurface flow, overland flow and channel flow routing, soil thawing and evapotranspiration. The kinematic wave method is used for conducting overland flow and channel flow routing. The subsurface flow is simulated using the Darcian approach. The energy balance scheme was the primary approach used in energy‐related process simulations (snowmelt and evapotranspiration), although there are options to model snowmelt by the degree‐day method and evapotranspiration by the Priestley–Taylor equation. This hydrological model simulates the dynamic interactions of each of these processes and can predict spatially distributed snowmelt, soil moisture and evapotranspiration over a watershed at each time step as well as discharge in any specified channel(s). The model was applied to Imnavait watershed (about 2·2 km²) and the Upper Kuparuk River basin (about 146 km²) in northern Alaska. Simulated results of spatially distributed soil moisture content, discharge at gauging stations, snowpack ablations curves and other results yield reasonable agreement, both spatially and temporally, with available data sets such as SAR imagery‐generated soil moisture data and field measurements of snowpack ablation, and discharge data at selected points. The initial timing of simulated discharge does not compare well with the measured data during snowmelt periods mainly because the effect of snow damming on runoff was not considered in the model. Results from the application of this model demonstrate that spatially distributed models have the potential for improving our understanding of hydrology for certain settings. Finally, a critical component that led to the performance of this modelling is the coupling of the mass and energy processes. Copyright © 2000 John Wiley & Sons, Ltd.     

Perturbation study of climate change impacts in a snow‐fed river basin

A physically based distributed hydrological model developed at the University of Yamanashi based on block‐wise use of TOPMODEL and the Muskingum–Cunge method (YHyM/BTOPMC), integrated with a simple degree‐day–based snow accumulation/melt sub‐model, was applied to evaluate hydrological responses under changing climatic conditions in the snow‐fed Kali Gandaki River Basin (KGRB) in Western Nepal. Rainy season precipitation (June to September) in the basin takes up about 80% of the annual precipitation, and dry season runoff is largely contributed by snowmelt. Climate change is likely to increase the probability of extreme events and problems related to water availability. Therefore, the study aimed to simulate runoff pattern under changing climatic conditions, which will be helpful in the management of water resources in the basin. Public domain global data were widely used in this study. The model was calibrated and validated with an acceptable degree of accuracy. The results predicted that the annual average discharge will increase by 2.4%, 3.7%, and 5.7% when temperature increases by 1, 2, and 3 °C compared with the reference scenario. Similarly, maximum, minimum, and seasonal discharges in the monsoon and pre‐monsoon seasons will also increase with rising temperature. Snowmelt runoff is found sensitive to temperature changes in the KGRB. Increasing temperature will cause a faster snowmelt, but precipitation will increase the snowpack and also shed a positive effect on the total annual and monsoonal discharge. For the combined scenarios of increasing temperature and precipitation, the annual average discharge will increase. In contrast, discharge during the increasing temperature and decreasing precipitation will tend to decrease. Copyright © 2012 John Wiley & Sons, Ltd.     

Soil partitioning and surface store controls on spring runoff from a boreal forest peatland basin in north‐central Manitoba,Canada

The mid‐ to high‐boreal forest in Canada occupies the discontinuous permafrost zone, and is often underlain by glaciolacustrine sediments mantled by a highly porous organic mat. The result is a poorly drained landscape dominated by wetlands. Frost‐table dynamics and surface storage conditions help to control runoff contributions from various landscape elements, hydrological linkages between these elements, and basin streamflow during spring snowmelt. Runoff components and pathways in a forested peatland basin were assessed during two spring snowmelts with contrasting input and basin conditions. Runoff from relatively intense melt (up to 16 mm day^?1) on slopes with limited soil thawing combined with large pre‐melt storage in surface depressions to produce high flows composed primarily of meltwater (78% of the 0·29 m³ s^?1 peak discharge) routed over wetland surfaces and through permeable upper peat layers. Melt intensity was less in the subsequent year (maximum of 10 mm day^?1) and active layer development was relatively greater (0·2 m deeper at the end of spring melt), resulting in less slope runoff. Coupling of reduced slope contributions with lower storage levels in basin wetlands led to relatively subdued streamflows dominated by older water (73% of the 0·09 m³ s^?1 peak discharge) routed through less‐permeable deeper peat layers and mineral soil. Interannual differences in runoff conditions provide important insight for the development of distributed hydrological models for boreal forest basins and into potential influences on biogeochemical cycling in this landscape under a warming climate. Copyright © 2001 John Wiley & Sons, Ltd.     

Climatic control on river discharge simulations,Zackenberg River drainage basin,northeast Greenland

A spatially distributed, physically based, hydrologic modeling system (MIKE SHE) was applied to quantify intra‐ and inter‐annual discharge from the snow and glacierized Zackenberg River drainage basin (512 km²; 20% glacier cover) in northeast Greenland. Evolution of snow accumulation, distribution by wind‐blown snow, blowing‐snow sublimation, and snow and ice surface melt were simulated by a spatially distributed, physically based, snow‐evolution modelling system (SnowModel) and used as input to MIKE SHE. Discharge simulations were performed for three periods 1997–2001 (calibration period), 2001–2005 (validation period), and 2071–2100 (scenario period). The combination of SnowModel and MIKE SHE shows promising results; the timing and magnitude of simulated discharge were generally in accordance with observations (R² = 0·58); however, discrepancies between simulated and observed discharge hydrographs do occur (maximum daily difference up to 44·6 m³ s^?1 and up to 9% difference between observed and simulated cumulative discharge). The model does not perform well when a sudden outburst of glacial dammed water occurs, like the 2005 extreme flood event. The modelling study showed that soil processes related to yearly change in active layer depth and glacial processes (such as changes in yearly glacier area, seasonal changes in the internal glacier drainage system, and the sudden release of glacial bulk water storage) need to be determined, for example, from field studies and incorporated in the models before basin runoff can be quantified more precisely. The SnowModel and MIKE SHE model only include first‐order effects of climate change. For the period 2071–2100, future IPCC A2 and B2 climate scenarios based on the HIRHAM regional climate model and HadCM3 atmosphere–ocean general circulation model simulations indicated a mean annual Zackenberg runoff about 1·5 orders of magnitude greater (around 650 mmWE year^?1) than from today 1997–2005 (around 430 mmWE year^?1), mainly based on changes in negative glacier net mass balance. Copyright © 2007 John Wiley & Sons, Ltd.     

Spatially distributed hydrotope‐based modelling of evapotranspiration and runoff in mountainous basins

River basins in mountainous regions are characterized by strong variations in topography, vegetation, soils, climatic conditions and snow cover conditions, and all are strongly related to altitude. The high spatial variation needs to be considered when modelling hydrological processes in such catchments. A complex hydrological model, with a great potential to account for spatial variability, was developed and applied for the hourly simulation of evapotranspiration, soil moisture, water balance and the runoff components for the period 1993 and 1994 in 12 subcatchments of the alpine/pre‐alpine basin of the River Thur (area 1703 km²). The basin is located in the north‐east of the Swiss part of the Rhine Basin and has an elevation range from 350 to 2500 m a.s.l. A considerable part of the Thur Basin is high mountain area, some of it above the tree‐line and a great part of the basin is snow covered during the winter season. In the distributed hydrological model, the 12 sub‐basins of the Thur catchment were spatially subdivided into sub‐areas (hydrologically similar response units—HRUs or hydrotopes) using a GIS. Within the HRUs a hydrologically similar behaviour was assumed. Spatial interpolations of the meteorological input variables wereemployed for each altitudinal zone. The structure of the model components for snow accumulation and melt, interception, soil water storage and uptake by evapotranspiration, runoff generation and flow routing are briefly outlined. The results of the simulated potential evapotranspiration reflect the dominant role of altitudinal change in radiation and albedo of exposure, followed by the influence of slope. The actual evapotranspiration shows, in comparison with the potential evapotranspiration, a greater variability in the lower and medium altitudinal zones and a smaller variability in the upper elevation zones, which was associated with limitations of available moisture in soil and surface depression storages as well as with the evaporative demand of the local vegetation. The higher altitudinal dependency and variability of runoff results from the strong increase in precipitation and the decrease in evaporation with increased altitude. An increasing influence of snow cover on runoff as well as evapotranspiration with altitude is obvious. The computed actual evapotranspiration and runoff were evaluated against the observed values of a weighting lysimeter and against runoff hydrographs. Copyright © 1999 John Wiley & Sons, Ltd.     

Snow cover and runoff modelling in a high mountain catchment with scarce data: effects of temperature and precipitation parameters

Snowmelt is an important source of runoff in high mountain catchments. Snowmelt modelling for alpine regions remains challenging with scarce gauges. This study simulates the snowmelt in the Karuxung River catchment in the south Tibetan Plateau using an altitude zone based temperature‐index model, calibrates the snow cover area and runoff simulation during 2003–2005 and validates the model performance via snow cover area and runoff simulation in 2006. In the snowmelt and runoff modelling, temperature and precipitation are the two most important inputs. Relevant parameters, such as critical snow fall temperature, temperature lapse rate and precipitation gradient, determine the form and amount of precipitation and distribution of temperature and precipitation in hydrological modelling of the sparsely gauged catchment. Sensitivity analyses show that accurate estimation of these parameters would greatly help in improving the snowmelt simulation accuracy, better describing the snow‐hydrological behaviours and dealing with the data scarcity at higher elevations. Specifically, correlation between the critical snow fall temperature and relative humidity and seasonal patterns of both the temperature lapse rate and the precipitation gradient should be considered in the modelling studies when precipitation form is not logged and meteorological observations are only available at low elevation. More accurate simulation of runoff involving snowmelt, glacier melt and rainfall runoff will improve our understanding of hydrological processes and help assess runoff impacts from a changing climate in high mountain catchments. Copyright © 2013 John Wiley & Sons, Ltd.     

Application and evaluation of a snowmelt runoff model in the Tamor River basin,Eastern Himalaya using a Markov Chain Monte Carlo (MCMC) data assimilation approach

Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree‐day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash–Sutcliffe metric ~0.84, annual volume bias < 3%). The Markov Chain Monte Carlo approach constrains the parameters to which the model is most sensitive (e.g. lapse rate and recession coefficient) and maximizes model fit and performance. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall compared with simulations using observed station precipitation. The average snowmelt contribution to total runoff in the Tamor River basin for the 2002–2006 period is estimated to be 29.7 ± 2.9% (which includes 4.2 ± 0.9% from snowfall that promptly melts), whereas 70.3 ± 2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000–5500 m range contributes the most to basin runoff, averaging 56.9 ± 3.6% of all snowmelt input and 28.9 ± 1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree‐day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds. Copyright © 2013 John Wiley & Sons, Ltd.     

Role of temporal resolution of meteorological inputs for process‐based snow modelling

Accurate snow accumulation and melt simulations are crucial for understanding and predicting hydrological dynamics in mountainous settings. As snow models require temporally varying meteorological inputs, time resolution of these inputs is likely to play an important role on the model accuracy. Because meteorological data at a fine temporal resolution (~1 hr) are generally not available in many snow‐dominated settings, it is important to evaluate the role of meteorological inputs temporal resolution on the performance of process‐based snow models. The objective of this work is to assess the loss in model accuracy with temporal resolution of meteorological inputs, for a range of climatic conditions and topographic elevations. To this end, a process‐based snow model was run using 1‐, 3‐, and 6‐hourly inputs for wet, average, and dry years over Boise River Basin (6,963 km²), which spans rain dominated (≤1,400 m), rain–snow transition (>1,400 and ≤1,900 m), snow dominated below tree line (>1,900 and ≤2,400 m), and above tree line (>2,400 m) elevations. The results show that sensitivity of the model accuracy to the inputs time step generally decreases with increasing elevation from rain dominated to snow dominated above tree line. Using longer than hourly inputs causes substantial underestimation of snow cover area (SCA) and snow water equivalent (SWE) in rain‐dominated and rain–snow transition elevations, due to the precipitation phase mischaracterization. In snow‐dominated elevations, the melt rate is underestimated due to errors in estimation of net snow cover energy input. In addition, the errors in SCA and SWE estimates generally decrease toward years with low snow mass, that is, dry years. The results indicate significant increases in errors in estimates of SCA and SWE as the temporal resolution of meteorological inputs becomes coarser than an hour. However, use of 3‐hourly inputs can provide accurate estimates at snow‐dominated elevations. The study underscores the need to record meteorological variables at an hourly time step for accurate process‐based snow modelling.     

A temperature‐precipitation‐based model of thirty‐year mean snowpack accumulation and melt in Oregon,USA

High‐resolution, spatially extensive climate grids can be useful in regional hydrologic applications. However, in regions where precipitation is dominated by snow, snowmelt models are often used to account for timing and magnitude of water delivery. We developed an empirical, nonlinear model to estimate 30‐year means of monthly snowpack and snowmelt throughout Oregon. Precipitation and temperature for the period 1971–2000, derived from 400‐m resolution PRISM data, and potential evapotranspiration (estimated from temperature and day length) drive the model. The model was calibrated using mean monthly data from 45 SNOTEL sites and accurately estimated snowpack at 25 validation sites: R² = 0·76, Nash‐Sutcliffe Efficiency (NSE) = 0·80. Calibrating it with data from all 70 SNOTEL sites gave somewhat better results (R² = 0·84, NSE = 0·85). We separately applied the model to SNOTEL stations located < 200 and ≥ 200 km from the Oregon coast, since they have different climatic conditions. The model performed equally well for both areas. We used the model to modify moisture surplus (precipitation minus potential evapotranspiration) to account for snowpack accumulation and snowmelt. The resulting values accurately reflect the shape and magnitude of runoff at a snow‐dominated basin, with low winter values and a June peak. Our findings suggest that the model is robust with respect to different climatic conditions, and that it can be used to estimate potential runoff in snow‐dominated basins. The model may allow high‐resolution, regional hydrologic comparisons to be made across basins that are differentially affected by snowpack, and may prove useful for investigating regional hydrologic response to climate change. Published in 2011 by John Wiley & Sons, Ltd.     

Quantitative evaluation of different hydrological modelling approaches in a partly glacierized Swiss watershed

Mountain water resources management often requires hydrological models that need to handle both snow and ice melt. In this study, we compared two different model types for a partly glacierized watershed in central Switzerland: (1) an energy‐balance model primarily designed for snow simulations; and (2) a temperature‐index model developed for glacier simulations. The models were forced with data extrapolated from long‐term measurement records to mimic the typical input data situation for climate change assessments. By using different methods to distribute precipitation, we also assessed how various snow cover patterns influenced the modelled runoff. The energy‐balance model provided accurate discharge estimations during periods dominated by snow melt, but dropped in performance during the glacier ablation season. The glacier melt rates were sensitive to the modelled snow cover patterns and to the parameterization of turbulent heat fluxes. In contrast, the temperature‐index model poorly reproduced snow melt runoff, but provided accurate discharge estimations during the periods dominated by glacier ablation, almost independently of the method used to distribute precipitation. Apparently, the calibration of this model compensated for the inaccurate precipitation input with biased parameters. Our results show that accurate estimates of snow cover patterns are needed either to correctly constrain the melt parameters of the temperature‐index model or to ensure appropriate glacier surface albedos required by the energy‐balance model. Thus, particularly when only distant meteorological stations are available, carefully selected input data and efficient extrapolation methods of meteorological variables improve the reliability of runoff simulations in high alpine watersheds. Copyright © 2011 John Wiley & Sons, Ltd.     

Snowmelt characteristics in a pristine mountain catchment of the Jalovecký Creek,Slovakia, over the last three decades

The Jalovecký Creek catchment, Slovakia (area 22.2 km², mean elevation 1500 m a.s.l.), is likely the last big valley complex in the Carpathian Mountains, in which the hydrological cycle is still governed by natural processes. Hydrological research is conducted there since the end of the 1980s. The overall mission of the research is to increase the knowledge about the hydrological cycle in the highest part of the Carpathians. The research agenda, briefly introduced in the first part of this article, is focused on water balance, snow accumulation and melt and runoff formation. Recent analysis of precipitation, discharge, snow cover and isotopic data from period 1989–2018 indicates that hydrological cycle has become more dynamic since 2014. Although several indicators suggest that it could be related to the cold part of the year, direct links with snow storage and the contribution of snowmelt water to catchment runoff were not confirmed. The second part of the article is therefore focused on an analysis of daily cycles in streamflow in March to June 1988–2018 to obtain a deeper insight into the snowmelt process. We describe characteristics of the cycles and examine their variability over the study period. The results indicate that less snow at the lowest elevations (800–1150 m a.s.l.) since 2009 could have influenced the cessation of the cycles in June since 2010. The possible role of the decreased amount of snow at the lowest elevations in changes in runoff characteristics is also suggested by an increase in time lags between maximum discharges during the events and maximum air temperatures preceding discharge maxima measured near the catchment outlet (at 750 m a.s.l.) in spring 2018 compared to springs with a similar number of streamflow cycles in the years 1988, 2000 and 2009. Wavelet analysis did not indicate changes in global power spectra in hourly discharge and air temperature data.     

Hydrological response to timber harvest in northern Idaho: implications for channel scour and persistence of salmonids

The potential for forest harvest to increase snowmelt rates in maritime snow climates is well recognized. However, questions still exist about the magnitude of peak flow increases in basins larger than 10 km² and the geomorphic and biological consequences of these changes. In this study, we used observations from two nearly adjacent small basins (13 and 30 km²) in the Coeur d'Alene River basin, one with recent, relatively extensive, timber harvest, and the other with little disturbance in the last 50 years to explore changes in peak flows due to timber harvest and their potential effects on fish. Peak discharge was computed for a specific rain‐on‐snow event using a series of physical models that linked predicted values of snowmelt input to a runoff‐routing model. Predictions indicate that timber harvest caused a 25% increase in the peak flow of the modelled event and increased the frequency of events of this magnitude from a 9‐year recurrence interval to a 3·6‐year event. These changes in hydrologic regime, with larger discharges at shorter recurrence intervals, are predicted to increase the depth and frequency of streambed scour, causing up to 15% added mortality of bull trout (Salvelinus confluentus) embryos. Mortality from increased scour, although not catastrophic, may have contributed to the extirpation of this species from the Coeur d'Alene basin, given the widespread timber harvest that occurred in this region. Copyright © 2008 John Wiley & Sons, Ltd.     

Snow in Lebanon: a preliminary study of snow cover over Mount Lebanon and a simple snowmelt model / Etude préliminaire du couvert neigeux et modèle de fonte des neige pour le Mont Liban

Abstract

The physical properties of snow, including apparent density, snow cover distribution and snowmelt in the Nahr El Kelb basin (Mount Lebanon), were studied in order to design a simple empirical snowmelt model. In February 2001, snow covered an area of 1600 km² on Mount Lebanon, representing a water equivalent of 1.1 x 10⁹ m³. The snow surface area was calculated by combining TM5 images with a digital elevation model, and field observations made every three days, from 1400 to 2300 m altitude. The depletion of snow cover was measured from the end of December 2000 to the end of June 2001. The snowmelt was measured from surface depletion on a degree-day basis. A simple model relating the daily snowmelt to the product of wind speed and average positive daily air temperature, is presented and discussed. For Mount Lebanon, this model gave a better approximation of snowmelt than a simple degree-day model.     

Understanding the hydrological system dynamics of a glaciated alpine catchment in the Himalayan region using the J2000 hydrological model

This paper provides the results of hydrological modelling in a mesoscale glaciated alpine catchment of the Himalayan region. In the context of global climate change, the hydrological regime of an alpine mountain is likely to be affected, which might produce serious implications for downstream water availability. The main objective of this study was to understand the hydrological system dynamics of a glaciated catchment, the Dudh Kosi River basin, in Nepal, using the J2000 hydrological model and thereby understand how the rise in air temperature will affect the hydrological processes. The model is able to reproduce the overall hydrological dynamics quite well with an efficiency result of Nash–Sutcliffe (0.85), logarithm Nash–Sutcliffe (0.93) and coefficient of determination (0.85) for the study period. The average contribution from glacier areas to total streamflow is estimated to be 17%, and snowmelt (other than from glacier areas) accounts for another 17%. This indicates the significance of the snow and glacier runoff in the Himalayan region. The hypothetical rise in temperature scenarios at a rate of +2 and +4 °C indicated that the snowmelt process might be largely affected. An increase in snowmelt volume is noted during the premonsoon period, whereas the contribution during the monsoon season is significantly decreased. This occurs mainly because the rise in temperature will shift the snowline up to areas of higher altitude and thereby reduce the snow storage capacity of the basin. This indicates that the region is particularly vulnerable to global climate change and the associated risk of decreasing water availability to downstream areas. Under the assumed warming scenarios, it is likely that in the future, the river might shift from a ‘melt‐dominated river’ to a ‘rain‐dominated river’. The J2000 model should be considered a promising tool to better understand the hydrological dynamics in alpine mountain catchments of the Himalayan region. This understanding will be quite useful for further analysis of ‘what‐if scenarios’ in the context of global climate and land‐use changes and ultimately for sustainable Integrated Water Resources Management in the Himalayan region. Copyright © 2012 John Wiley & Sons, Ltd.