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.     

Applicability of isotopic hydrograph separation in a suburban basin during snowmelt

C. H. TAYLOR Methodological issues associated with isotopic hydrograph separations (IHSs) in built-up environments are explored using results from the 1990 spring melt in a suburban basin in Peterborough, Ontario, Canada. The hetrogeneous nature of suburban environments complicates the selection of appropriate isotopic signatures for event and pre-event waters. Near-stream groundwater δ¹⁸O sampled from wells was poorly mixed, such that the pre-event water signature was best characterized by δ¹⁸O in pre-melt baseflow or discharge from a headwater spring. The event water signature during snowmelt can be characterized using δ¹⁸O in the pre-melt snowpack, surface runoff samples or meltwater from lysimeters. However, the use of snowpack δ¹⁸O may be inappropriate in suburban basins where meltwater from thin snowcover may exhibit pronounced responses to δ¹⁸O in rainfall contributions. Intensive sampling of the spatial variability of runoff or meltwater δ¹⁸O may be required to characterize the average event water signature adequately. Rainfall δ¹⁸O provided an appropriate event water signal during a large rain on snow event, and differences between this IHS and one generated using an event water signature that included meltwater contributions from snow-covered surfaces were within the uncertainty attributable to the analytical error in δ¹⁸O values. Event water supplied 55-63% of the peak discharge and 48-58% of total runoff from the basin during the melt, which is consistent with the fraction of the basin that has been developed. These results contrast with IHSs conducted in forested basins that suggest that stormflow is dominated by pre-event water contributions.     

Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains,north‐west China

Snowmelt water is an important freshwater resource in the Altay Mountains in north‐west China; however, warming climate and rapid spring snowmelt can cause floods that endanger both public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature index model based on remote sensing coupled with high‐resolution meteorological data obtained from National Centers for Environmental Prediction (NCEP) reanalysis fields that were downscaled using the Weather Research Forecasting model and then bias corrected using a statistical downscaled model. Validation of the forcing data revealed that the high‐resolution meteorological fields derived from the downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of the temperature index model based on remote sensing were calibrated for spring 2014, and model performance was validated using Moderate Resolution Imaging Spectroradiometer snow cover and snow observations from spring 2012. The results show that the temperature index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash–Sutcliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt run‐off was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt run‐off accounts for 72% of spring run‐off and 21% of annual run‐off. Snowmelt is the main source of run‐off for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt run‐off predictions, so as to prevent snowmelt‐induced floods, and also provide a generalizable approach that can be applied to other remote locations where high‐density, long‐term observational data are lacking. Copyright © 2016 John Wiley & Sons, Ltd.     

Comparison of two snowmelt modelling approaches in the Dudh Koshi basin (eastern Himalayas,Nepal)

Abstract

The glaciers in the Nepalese Himalayas are retreating due to rising temperatures. Lack of data and information on Nepal’s cryosphere has impeded scientific studies and field investigations in the Nepalese Himalayas. Therefore, IRD France and Ev-K2 CNR Italy have conducted the PAPRIKA (CryosPheric responses to Anthropogenic PRessures in the HIndu Kush-Himalaya regions: impacts on water resources and society adaptation in Nepal) project in Nepal with the financial support of the French and Italian scientific agencies. This project aims to address the current and future evolution of the cryosphere in response to overall environmental changes in South Asia, and its consequences for water resources in Nepal. Thus, two hydrological models, the GR4J lumped precipitation–runoff model and the snowmelt runoff model (SRM), were used in the Dudh Koshi basin. The GR4J model has been successfully applied in different parts of Europe. To obtain better results in such a harsh and rugged topography, modifications needed to be made, particularly in the snow module. The runoff pattern is analysed herein both for past years and, in a sensitivity analysis, for possible future climatic conditions (i.e. precipitation and temperature) using the SRM and GR4J modelling approaches. The results reveal a significant contribution of snow- and glacier-melt to runoff, and the SRM model shows better performance in Nepalese catchments than the GR4J model.

Editor D. Koutsoyiannis; Associate editor D. Gerten     

Impact of climate change on runoff in the upper part of the Euphrates basin

Abstract

Among the processes most affected by global warming are the hydrological cycle and water resources. Regions where the majority of runoff consists of snowmelt are very sensitive to climate change. It is significant to express the relationship between climate change and snow hydrology and it is imperative to perform climate change impact studies on snow hydrology at global and regional scales. Climate change impacts on the mountainous Upper Euphrates Basin were investigated in this paper. First, historical data trend analysis of significant hydro-meteorological data is presented. Available future climate data are then explained, and, finally, future climate data are used in hydrological models, which are calibrated and validated using historical hydro-meteorological data, and future streamflow is projected for the period 2070–2100. The hydrological model outcomes indicate substantial runoff decreases in summer and spring season runoff, which will have significant consequences on water sectors in the Euphrates Basin.

Citation Yilmaz, A.G. & Imteaz, M.A. (2011) Impact of climate change on runoff in the upper part of the Euphrates basin. Hydrol. Sci. J. 56(7), 1265–1279.     

Application of a distributed blowing snow model to the Arctic

Transportation, sublimation and accumulation of snow dominate snow cover development in the Arctic and produce episodic high evaporative fluxes. Unfortunately, blowing snow processes are not presently incorporated in any hydrological or meteorological models. To demonstrate the application of simple algorithms that represent blowing snow processes, monthly snow accumulation, relocation and sublimation fluxes were calculated and applied in a spatially distributed manner to a 68-km² catchment in the low Arctic of north-western Canada. The model uses a Landsat-derived vegetation classification and a digital elevation model to segregate the basin into snow ‘sources’ and ‘sinks’. The model then relocates snow from sources to sinks and calculates in-transit sublimation loss. The resulting annual snow accumulation in specific landscape types was compared with the result of intensive surveys of snow depth and density. On an annual basis, 28% of annual snowfall sublimated from tundra surfaces whilst 18% was transported to sink areas. Annual blowing snow transport to sink areas amounted to an additional 16% of annual snowfall to shrub–tundra and an additional 182% to drifts. For the catchment, 19·5% of annual snowfall sublimated from blowing snow, 5·8% was transported into the catchment and 86·5% accumulated on the ground. The model overestimated snow accumulation in the catchment by 6%. The application demonstrates that winter precipitation alone is insufficient to calculate snow accumulation and that blowing snow processes and landscape patterns govern the spatial distribution and total accumulation of snow water equivalent over the winter. These processes can be modelled by relatively simple algorithms, and, when distributed by landscape type over the catchment, produce reasonable estimates of snow accumulation and loss in wind-swept regions. © 1997 John Wiley & Sons, Ltd.     

Long‐term change of seasonal snow cover and its effects on river runoff in the Tarim River basin,northwestern China

Spatio‐temporal variation of snow depth in the Tarim River basin has been studied by the empirical orthogonal function (EOF) based on the data collected by special sensor microwave/imager (SSM/I) and scanning multichannel microwave radiometer (SMMR) during the period from 1979 to 2005. The long‐term trend of snow depth and runoff was presented using the Mann‐Kendall non‐parametric test, and the effects of the variations of snow depth and climatic factors on runoff were analysed and discussed by means of the regression analysis. The results suggested that the snow depth variation on the entire basin was characterised by four patterns: all consistency, north–south contrast, north‐middle‐south contrast and complex. The first pattern accounting 39·13% of the total variance was dominant. The entire basin was mainly affected by one large‐scale weather system. However, the spatial and temporal differences also existed among the different regions in the basin. The significant snow depth changes occurred mainly in the Aksu River basin with the below‐normal snow depth anomalies in the 1980s and the above‐normal snow depth anomalies in the 1990s. The long‐term trend of snow depth was significant in the northwestern, western and southern parts of the basin, whereas the long‐term trend of runoff was significant in the northwestern and northeastern parts. The regression analysis revealed that the runoff of the rivers replenished by snow melt water and rainfall was related primarily to the summer precipitation, followed by the summer temperature or the maximum snow depth in the cold season. Our results suggest that snow is not the principal factor that contributes to the runoff increase in headstreams, although there was a slow increase in snow depth. It is the climatic factors that are responsible for the steady and continuous water increase in the headstreams. Copyright © 2009 John Wiley & Sons, Ltd.     

Estimation of mass and energy balance of glaciers using a distributed energy balance model over the Chandra river basin (Western Himalaya)

The ongoing glacier shrinking in the Himalayan region causes a significant threat to freshwater sustainability and associated future runoff. However, data on the spatial climatic contribution of glacier retreat is scanty in this region. To investigate the spatially distributed glacier surface energy and mass fluxes, a two-dimensional mass balance model was developed and applied to the selected glaciers of the Chandra basin, in the Upper Indus Basin, Western Himalaya. This model is driven by the remote sensing data and meteorological variables measured in the vicinity of the Chandra basin for six hydrological years (October 2013 to September 2019). The modelled variables were calibrated/validated with the in-situ observation from the Himansh station in the Chandra basin. We have derived air temperature (T_a ) spatially using the multivariate statistical approach, which indicates a relative error of 0.02–0.05°C with the observed data. Additionally, the relative error between the modelled and observed radiation fluxes was <10.0 W m⁻². Our study revealed that the Chandra basin glaciers have been losing its mass with a mean annual mass balance of −0.59 ± 0.12 m w.e. a⁻¹ for the six hydrological years. Results illustrated that the mean surface melt rate of the selected glaciers ranged from −5.1 to −2.5 m w.e. a⁻¹ that lies between 4500 and 5000 m a.s.l. The study revealed that the net radiation (R_N) contributes ~75% in total energy (F_M ) during the melt season while sensible heat (H_S) , latent heat (H_l) , and ground heat (H_G) fluxes shared 15%, 8%, and 2%, respectively. Sensitivity analysis of the energy balance components suggested that the mass balance is highly sensitive to albedo and surface radiations in the study area. Overall, the proposed model performed well for glacier-wide energy and mass balance estimation and confirms the utility of remote sensing data, which may help in reducing data scarcity in the upper reaches of the Himalayan region.     

Use of the recession characteristics of snowmelt hydrographs in the assessment of snow water storage in a basin

For a better management of water resources, the information on water stored in a basin in the form of snow is of immense use. Changes in the snow water storage with time influence the recession characteristics of the hydrographs. Recession is found to be slower in a basin when it contains higher snow water storage and becomes faster as the volume of stored water reduces. In other words, the recession coefficient is not constant throughout the melt season, it changes with time. In the present study, the possibility of assessing snow water storage at any time during the melt season using recession coefficients is examined. The hydrograph analyses have been made for the Glatzbach watershed in the Hohe Tauern region of the Austrian Alps. For this purpose, a relationship between snow water storage and the recession coefficients is developed. This study suggests a simple and useful approach to assess the snow water storage in a basin at any time during the snowmelt season. The information on the snow water storage of a basin can be obtained using a readily derived single parameter, the recession coefficient. The results are based on limited data, but they are sufficient to illustrate how the changes in snow water storage control the recession characteristics of the hydrographs. These investigations set the pace for further research in this area. Copyright © 2000 John Wiley & Sons, Ltd.     

Modelling runoff using optical satellite remote sensing data in a high mountainous alpine catchment of Italy

Development of hydrological models for seasonal and real-time runoff forecast in rivers of high alpine catchments is useful for management of water resources. The conceptual models for this purpose are based on a temperature index and/or energy budget and can be either lumped or distributed over the catchment area. Remote sensing satellite data are most useful to acquire near real-time geophysical parameters in order to input to the distributed forecasting models. In the present study, integration of optical satellite remote sensing-derived information was made with ground meteorological and hydrological data, and predetermined catchment morphological parameters, to study the feasibility of application of a distributed temperature index snowmelt runoff model to one of the high mountainous catchments in the Italian Alps, known as Cordevole River Basin. Five sets of Landsat Multispectral Scanning System (MSS) and Thematic Mapper (TM) computer-compatible tapes (CCTs) were processed using digital image processing techniques in order to evaluate the snow cover variation quantitatively. Digital elevation model, slope and aspect parameters were developed and used during satellite data processing. The satellite scenes were classified as snow, snow under transition and snow free areas. A second-order polynomial fit has been attempted to approximate the snow depletion and to estimate daily snow cover areal extent for three elevation zones of the catchment separately. Model performance evaluation based on correlation coefficient, Nash–Sutcliffe coefficient and percentage volume deviation indicated very good simulation between measured and computed discharges for the entire snowmelt period. The use of average temperature values computed from the maximum and minimum temperatures into the model was studied and a suitable algorithm was proposed. © 1997 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.     

Estimating source regions for snowmelt runoff in a Rocky Mountain basin: tests of a data‐based conceptual modeling approach

In many mountain basins, river discharge measurements are located far away from runoff source areas. This study tests whether a basic snowmelt runoff conceptual model can be used to estimate relative contributions of different elevation zones to basin‐scale discharge in the Cache la Poudre, a snowmelt‐dominated Rocky Mountain river. Model tests evaluate scenarios that vary model configuration, input variables, and parameter values to determine how these factors affect discharge simulation and the distribution of runoff generation with elevation. Results show that the model simulates basin discharge well (NSCE and R >0.90) when input precipitation and temperature are distributed with different lapse rates, with a rain‐snow threshold parameter between 0 and 3.3 °C, and with a melt rate parameter between 2 and 4 mm °C^?1 d^?1 because these variables and parameters can have compensating interactions with each other and with the runoff coefficient parameter. Only the hydrograph recession parameter can be uniquely defined with this model structure. These non‐unique model scenarios with different configurations, input variables, and parameter values all indicate that the majority of basin discharge comes from elevations above 2900 m, or less than 25% of the basin total area, with a steep increase in runoff generation above 2600 m. However, the simulations produce unrealistically low runoff ratios for elevations above 3000 m, highlighting the need for additional measurements of snow and discharge at under‐sampled elevations to evaluate the accuracy of simulated snow and runoff patterns. Copyright © 2013 John Wiley & Sons, Ltd.     

Application of semi‐distributed hydrological model for basin level water balance of the Ken basin of Central India

In the present study, a semi‐distributed hydrological model soil and water assessment tool (SWAT) has been employed for the Ken basin of Central India to predict the water balance. The entire basin was divided into ten sub basins comprising 107 hydrological response units on the basis of unique slope, soil and land cover classes using SWAT model. Sensitivity analysis of SWAT model was performed to examine the critical input variables of the study area. For Ken basin, curve number, available water capacity, soil depth, soil evaporation compensation factor and threshold depth of water in the shallow aquifer (GWQ_MN) were found to be the most sensitive parameters. Yearly and monthly calibration (1985–1996) and validation (1997–2009) were performed using the observed discharge data of the Banda site in the Ken basin. Performance evaluation of the model was carried out using coefficient of determination, Nash–Sutcliffe efficiency, root mean square error‐observations standard deviation ratio, percent bias and index of agreement criterion. It was found that SWAT model can be successfully applied for hydrological evaluation of the Ken basin, India. The water balance analysis was carried out to evaluate water balance of the Ken basin for 25 years (1985–2009). The water balance exhibited that the average annual rainfall in the Ken basin is about 1132 mm. In this, about 23% flows out as surface run‐off, 4% as groundwater flow and about 73% as evapotranspiration. Copyright © 2013 John Wiley & Sons, Ltd.     

A two-stage sensitivity analysis for parameter identification and calibration of a physically-based distributed model in a river basin

Hydrological models demand large numbers of input parameters, which are to be optimally identified for better simulation of various hydrological processes. Identifying the most relevant parameters and their values using efficient sensitivity analysis methods helps to better understand model performance. In this study, the physically-based distributed model SHETRAN is used for hydrological simulation on the Netravathi River Basin in south India and the most important parameters are identified using the Morris screening method. Further, the influence of a particular model parameter on streamflow is quantified using local sensitivity analysis and optimal parameters are obtained for calibration of the SHETRAN model. The results demonstrate the capability of two-stage sensitivity analysis, combining qualitative and quantitative methods in the initial screening-out of insignificant model parameters, identifying parameter interactions and quantifying the contribution of each model parameter to the streamflow. The results of the sensitivity analysis simplified the calibration procedure of SHETRAN for the study area.     

A framework for quantifying the impacts of climate change and human activities on hydrological drought in a semiarid basin of Northern China

Climate change and human activities are two major driving forces affecting the hydrologic cycle, which further influence the stationarity of the hydrologic regime. Hydrological drought is a substantial negative deviation from the normal hydrologic conditions affected by these two phenomena. In this study, we propose a framework for quantifying the effects of climate change and human activities on hydrological drought. First, trend analysis and change‐point test are performed to determine variations of hydrological variables. After that, the fixed runoff threshold level method (TLM) and the standardized runoff index (SRI) are used to verify whether the traditional assessment methods for hydrological drought are applicable in a changing environment. Finally, two improved drought assessment methods, the variable TLM and the SRI based on parameter transplantation are employed to quantify the impacts of climate change and human activities on hydrological drought based on the reconstructed natural runoff series obtained using the variable infiltration capacity hydrologic model. The results of a case study on the typical semiarid Laohahe basin in North China show that the stationarity of the hydrological processes in the basin is destroyed by human activities (an obvious change‐point for runoff series is identified in 1979). The traditional hydrological drought assessment methods can no longer be applied to the period of 1980–2015. In contrast, the proposed separation framework is able to quantify the contributions of climate change and human activities to hydrological drought during the above period. Their ranges of contributions to hydrological drought calculated by the variable TLM method are 20.6–41.2% and 58.8–79.4%, and the results determined by the SRI based on parameter transplantation method are 15.3–45.3% and 54.7–84.7%, respectively. It is concluded that human activities have a dominant effect on hydrological drought in the study region. The novelty of the study is twofold. First, the proposed method is demonstrated to be efficient in quantifying the effects of climate change and human activities on hydrological drought. Second, the findings of this study can be used for hydrological drought assessment and water resource management in water‐stressed regions under nonstationary conditions.     

Coupling of a simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

Snow and frozen soil prevail in cold regions worldwide, and the integration of these processes is crucial in hydrological models. In this study, a combined model was developed by fully coupling a simultaneous heat and water model with a geomorphologically based distributed hydrological model. The combined model simulates vertical and lateral water transfer as well as vertical heat fluxes and is capable of representing the effects of frozen soil and snowmelt on hydrological processes in cold regions. This model was evaluated by using in situ observations in the Binggou watershed, an experimental watershed for cold region hydrology of the Watershed Allied Telemetry Experimental Research Project. Results showed that the model was able to predict soil freezing and thawing, unfrozen soil water content, and snow depth reasonably well. The simulated hydrograph was in good agreement with the in situ observation. The Nash–Sutcliffe coefficient of daily discharge was 0.744 for the entire simulation period, 0.472 from April to June, and 0.711 from June to November. This model can improve our understanding of hydrological processes in cold regions and assess the impacts of global warming on hydrological cycles and water resources. Copyright © 2012 John Wiley & Sons, Ltd.     

Simulation of spatially-distributed copper pollution in a large river basin using the ECOMAG-HM model

The semi-distributed physically-based model ECOMAG-HM was developed to simulate cycling of heavy metals in large river basins: on the surface, and in soil, groundwater and river water. The model was applied to study the spatial distribution and temporal dynamics of copper concentrations in watercourses of the Nizhnekamskoe Reservoir watershed in Russia. This watershed is characterized by high background concentrations of heavy metals due to wide occurrence of ore deposits and considerable concentrations of ore-parent elements in rocks. The model was found to adequately reproduce the spatial variation of the mean annual copper concentrations at different monitoring points of the river network. The mean annual specific copper washoff, with the surface and subsurface components of river runoff, and the total copper washoff from the watershed into the river network were calculated and mapped. The contributions of natural and anthropogenic factors to river water pollution by copper were evaluated.     

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.     

Operational snow modeling: Addressing the challenges of an energy balance model for National Weather Service forecasts

Prediction of snowmelt has become a critical issue in much of the western United States given the increasing demand for water supply, changing snow cover patterns, and the subsequent requirement of optimal reservoir operation. The increasing importance of hydrologic predictions necessitates that traditional forecasting systems be re-evaluated periodically to assure continued evolution of the operational systems given scientific advancements in hydrology. The National Weather Service (NWS) SNOW17, a conceptually based model used for operational prediction of snowmelt, has been relatively unchanged for decades. In this study, the Snow–Atmosphere–Soil Transfer (SAST) model, which employs the energy balance method, is evaluated against the SNOW17 for the simulation of seasonal snowpack (both accumulation and melt) and basin discharge. We investigate model performance over a 13-year period using data from two basins within the Reynolds Creek Experimental Watershed located in southwestern Idaho. Both models are coupled to the NWS runoff model [SACramento Soil Moisture Accounting model (SACSMA)] to simulate basin streamflow. Results indicate that while in many years simulated snowpack and streamflow are similar between the two modeling systems, the SAST more often overestimates SWE during the spring due to a lack of mid-winter melt in the model. The SAST also had more rapid spring melt rates than the SNOW17, leading to larger errors in the timing and amount of discharge on average. In general, the simpler SNOW17 performed consistently well, and in several years, better than, the SAST model. Input requirements and related uncertainties, and to a lesser extent calibration, are likely to be primary factors affecting the implementation of an energy balance model in operational streamflow prediction.     

Response of snow processes to climate change: spatial variability in a small basin in the Spanish Pyrenees

In this study, the Cold Regions Hydrological Modelling platform was used to create an alpine snow model including wind redistribution of snow and energy balance snowmelt to simulate the snowpack over the period 1996–2009 in a small (33 ha) snow‐dominated basin in the Spanish Pyrenees. The basin was divided into three hydrological response units (HRUs), based on contrasting physiographic and aerodynamic characteristics. A sensitivity analysis was conducted to calculate the snow water equivalent regime for various combinations of temperature and precipitation that differed from observed conditions. The results show that there was large inter‐annual variability in the snowpack in this region of the Pyrenees because of its marked sensitivity to climatic conditions. Although the basin is small and quite homogeneous, snowpack seasonality and inter‐annual evolution of the snowpack varied in each HRU. Snow accumulation change in relation to temperature change was approximately 20% for every 1 °C, and the duration of the snowpack was reduced by 20–30 days per °C. Melting rates decreased with increased temperature, and wind redistribution of snow was higher with decreased temperature. The magnitude and sign of changes in precipitation may markedly affect the response of the snowpack to changes in temperature. There was a non‐linear response of snow to individual and combined changes in temperature and precipitation, with respect to both the magnitude and sign of the change. This was a consequence of the complex interactions among climate, topography and blowing snow in the study basin. Copyright © 2012 John Wiley & Sons, Ltd.