Ice and Snow Cover of Continental Water Bodies from Simultaneous Radar Altimetry and Radiometry Observations

We show how the studies of ice and snow cover of continental water bodies can benefit from the synergy of more than 15 years-long simultaneous active (radar altimeter) and passive (radiometer) observations from radar altimetric satellites (TOPEX/Poseidon, Jason-1, ENVISAT and Geosat Follow-On) and how this approach can be complemented by SSM/I passive microwave data to improve spatial and temporal coverage. Five largest Eurasian continental water bodies—Caspian and Aral seas, Baikal, Ladoga and Onega lakes are selected as examples. First we provide an overview of ice regime and history of ice studies for these seas and lakes. Then a summary of the existing state of the art of ice discrimination methodology from altimetric observations and SSM/I is given. The drawbacks and benefits of each type of sensor and particularities of radiometric properties for each of the chosen water bodies are discussed. Influence of sensor footprint size, ice roughness and snow cover on satellite measurements is also addressed. A step-by-step ice discrimination approach based on a combined use of the data from the four altimetric missions and SSM/I is presented, as well as validation of this approach using in situ and independent satellite data in the visible range. The potential for measurement of snow depth on ice from passive microwave observations using both altimeters and SSM/I is addressed and a qualitative comparison of in situ snow depth observations and satellite-derived estimates is made.     

SNOW WETNESS ESTIMATES OF VEGETATED TERRAIN FROM SATELLITE PASSIVE MICROWAVE DATA

The Special Sensor Microwave/Imager (SSM/I) radiometer is a useful tool for monitoring snow wetness on a large scale because water content has a significant effect on the microwave emissions at the snowpack surface. To date, SSM/I snow wetness algorithms, based on statistical regression analysis, have been developed only for specific regions. Inadequate ground-based snow wetness measurements and the non-linearity between SSM/I brightness temperatures (T_Bs) and snow wetness over varied vegetation covered terrain has impeded the development of a general model. In this study, we used a previously developed linear relationship between snowpack surface wetness (% by volume) and concurrent air temperature (°C) to estimate the snow wetness at ground weather stations. The snow condition (snow free, dry, wet or refrozen snow) of each SSM/I pixel (a 37 × 29 km area at 37.0 GHz) was determined from ground-measured weather data and the T_B signature. SSM/I T_Bs of wet snow were then linked with the snow wetness estimates as an input/output relationship. A single-hidden-layer back-propagation (backprop) artificial neural network (ANN) was designed to learn the relationships. After training, the snow wetness values estimated by the ANN were compared with those derived by regression models. Results show that the ANN performed better than the existing regression models in estimating snow wetness from SSM/I data over terrain with different amounts of vegetation cover.     

Evaluating the utility of the EUMETSAT HSAF snow recognition product over mountainous areas of eastern Turkey

Abstract

Monitoring snow parameters (e.g. snow-cover area, snow water equivalent) is challenging work. Because of its natural physical properties, snow strongly affects the evolution of weather on a daily basis and climate on a longer time scale. In this paper, the snow recognition product generated from the MSG-SEVIRI images within the framework of the Hydrological Satellite Facility (HSAF) Project of EUMETSAT is presented. Validation of the snow recognition product H10 was done for the snow season (from 1 January to 31 March) of the water year 2009. The MOD10A1 and MOD10C2 snow products were also used in the validation studies. Ground truth of the products was obtained by using 1890 snow depth observations from 20 meteorological stations, which are mainly located in mountainous areas and are distributed across the eastern part of Turkey. The possibility of 37% cloud cover reduction was obtained by merging 15-min observations from MSG-SEVIRI as opposed to using only one daily observation from MODIS. The coarse spatial resolution of the H10 product gave higher commission errors compared to the MOD10A1 product. Snow depletion curves obtained from the HSAF snow recognition product were compared with those derived from the MODIS 8-day snow cover product. The preliminary results show that the HSAF snow recognition product, taking advantage of using high temporal frequency measurement with spectral information required for snow mapping, significantly improves the mapping of regional snow-cover extent over mountainous areas.

Citation Surer, S. and Akyurek, Z., 2012. Evaluating the utility of the EUMETSAT HSAF snow recognition product over mountainous areas of eastern Turkey. Hydrological Sciences Journal, 57 (8), 1–11.     

A new approach of dynamic monitoring of 5‐day snow cover extent and snow depth based on MODIS and AMSR‐E data from Northern Xinjiang region

Taking the Northern Xinjiang region as an example, we develop a snow depth model by using the Advanced Microwave Scanning Radiometer‐Earth Observing System (AMSR‐E) horizontal and vertical polarization brightness temperature difference data of 18 and 36 GHz bands and in situ snow depth measurements from 20 climatic stations during the snow seasons November–March) of 2002–2005. This article proposes a method to produce new 5‐day snow cover and snow depth images, using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products and AMSR‐E snow water equivalent and daily brightness temperature products. The results indicate that (1) the brightness temperature difference (Tb_18h–Tb_36h) provides the most accurate and precise prediction of snow depth; (2) the snow, land and overall classification accuracies of the new images are separately 89.2%, 77.7% and 87.2% and are much better than those of AMSR‐E or MODIS products (in all weather conditions) alone; (3) the snow classification accuracy increases as snow depth increases; and (4) snow accuracies for different land cover types vary as 88%, 92.3%, 79.7% and 80.1% for cropland, grassland, shrub, and urban and built‐up, respectively. We conclude that the new 5‐day snow cover–snow depth images can provide both accurate cloud‐free snow cover extent and the snow depth dynamics, which would lay a scientific basis for water management and prevention of snow‐related disasters in this dry and cold pastoral area. After validations of the algorithms over other regions with different snow and climate conditions, this method would also be used for monitoring snow cover and snow depth elsewhere in the world. Copyright © 2011 John Wiley & Sons, Ltd.     

Investigation of the relationship between optical auroral forms and HF radar E region backscatter

The SuperDARN HF radars have been employed in the past to investigate the spectral characteristics of coherent backscatter from L-shell aligned features in the auroral E region. The present study employs all-sky camera observations of the aurora from Husafell, Iceland, and the two SuperDARN radars located on Iceland, Þykkvibær and Stokkseyri, to determine the optical signature of such backscatter features. It is shown that, especially during quiet geomagnetic conditions, the backscatter region is closely associated with east-west aligned diffuse auroral features, and that the two move in tandem with each other. This association between optical and radar aurora has repercussions for the instability mechanisms responsible for generating the E region irregularities from which radars scatter. This is discussed and compared with previous studies investigating the relationship between optical and VHF radar aurora. In addition, although it is known that E region backscatter is commonly observed by SuperDARN radars, the present study demonstrates for the first time that multiple radars can observe the same feature to extend over at least 3 h of magnetic local time, allowing precipitation features to be mapped over large portions of the auroral zone.     

Snow Mass Quantification and Avalanche Victim Search by Ground Penetrating Radar

Ground penetrating radar (GPR) systems can be used in many applications of snow and ice research. The information from the GPR is used to identify and interpret layers, objects and different structures in the snow. A commercially available GPR system was further developed to work in the rough environment of snow and ice. The applied GPR is a 900 MHz system that easily reaches snow depths of up to 10 meters. The system was calibrated in the course of several manual snow depth measurements during each survey. The depth resolution depends on the snow type and is around ±0.1 m. The GPR system is carried alongside a line of interest and is triggered by an odometer wheel at regular adjustable steps. All equipment is mounted in a sledge and is pulled by a snowmobile over the snow surface. This setup allows for an efficient coverage of several kilometers of terrain profiles. The radar profiles give a real time two-dimensional impression of structures and objects and the interface between snow and the underlying ground. The actual radar profile is shown on a screen on the sledge allowing the immediate marking of objects and structures. During the past three years the instrument was successfully used for the study of snow distributions, for the detection of glacier crevasses under the snow cover, and for the search of avalanche victims in avalanche debris. The results show the capability of the instrument to detect persons and objects in the snow cover. In the future, this device may be a new tool for avalanche rescue operations. Today, the size and weight of the system prevents the accessing of very steep slopes and areas not accessible to snowmobiles. Further developments will decrease the size of the system and make it a valuable tool to quantify snow masses in avalanche release zones and run-out areas.     

Four-dimensional reflectivity data comparison between two ground-based radars: methodology and statistical analysis

Abstract

A methodology is proposed to compare radar reflectivity data obtained from two partially overlapping ground-based radars in order to explain relative differences in radar-rainfall products and establish sound merging procedures for multi-radar observing networks. To identify radar calibration differences, radar reflectivity is compared for well-matched radar sampling volumes viewing common meteorological targets. Temporal separation and three-dimensional matching of two different sampling volumes were considered based on the original polar coordinates of radar observation. Since the proposed method assumes radar beam propagation under standard atmospheric conditions, anomalous propagation cases were eliminated from the analysis. The reflectivity comparison results show systematic differences over time, but the variability of these differences is surprisingly large due to the sensitive nature of the radar reflectivity measurement.

Editor D. Koutsoyiannis/Z.W. Kundzewicz; Guest editor R.J. Moore

Citation Seo, B.-C., Krajewski, W.F., and Smith, J.A., 2013. Four-dimensional reflectivity data comparison between two ground-based radars: methodology and statistical analysis. Hydrological Sciences Journal, 59 (7), 1312–1326. http://dx.doi.org/10.1080/02626667.2013.839872     

Estimation de L'équivalent en Eau du Couvert Nival en Montagne Libanaise à Partir des Images RADARSAT-1/Estimation of Water Equivalent of the Snow Cover in Lebanese Mountains by Means of RADARSAT-1 Images

Abstract

The assessment of the spatial and temporal distribution of water resources in Mediterranean region is crucial for the better management of available resources. In Lebanon in particular, the snow is a crucial parameter for water supply. However, few research works were performed until now to study this potential resource because of difficulties inherent to the measurement of the water volume stored by snow. Remote sensing, and more specifically radar imaging, is the favourite tool for investigating the now water equivalent. This study aims to assess the potential of synthetic aperture radar (SAR) imaging for estimating the snow water equivalent in relation with eight experimental sites distributed over the high plateaus of the Lebanese mountains. With this purpose, an algorithm was tested, which links the backscattering coefficient to physical parameters of the snow and underlying soil, and which allows to assess the water equivalent from the backscattering ratios of a winter scene and a reference scene taken during a period with no snow. To this end, four RADARSAT images were acquired during winter 2001, concurrently to field observations. The model was developed in Quebec for regions with low relief, whereas relief has a decisive influence on the radar signal and on the geometry of images, in a context of high mountains. Consequently, radiometric and geometric corrections were compulsory in order to reduce distortions dues to topographical effects. The preliminary results corroborate the existence of a series of limitations to the application of the algorithm to the particular conditions of the Lebanese snow cover: heterogeneity, accelerated metamorphism and high content of liquid water.     

Sensitivity of the French Alps snow cover to the variation of climatic variables

In order to study the sensitivity of snow cover to changes in meteorological variables at a regional scale, a numerical snow model and an analysis system of the meteorological conditions adapted to relief were used. This approach has been successfully tested by comparing simulated and measured snow depth at 37 sites in the French Alps during a ten year data period. Then, the sensitivity of the snow cover to a variation in climatic conditions was tested by two different methods, which led to very similar results. To assess the impact of a particular “doubled CO₂” scenario, coherent perturbations were introduced in the input data of the snow model. It was found that although the impact would be very pronounced, it would also be extremely differentiated, dependent on the internal state of the snow cover. The most sensitive areas are the elevations below 2400 m, especially in the southern part of the French Alps.     

Broadband synthetic aperture borehole radar interferometry

Trials in mines have established that wideband VHF borehole radars (BHR), working in the 10–100-MHz band, can be used to probe the rockmass between boreholes over ranges from <5 m to as much as 150 m with submeter resolution. There is evidence that ore bodies reflect these radar signals both specularly and diffusely, much as the ground/air interface does when overflown by synthetic aperture radar (SAR). In both SAR and BHR, multiple flight lines, together with diffuse reflections admit the possibility of developing interferometric 3D images of the object. This paper examines the possibility of imaging buried objects in three dimensions by interferometrically combining broadband VHF borehole radar profiles shot in adjacent pairs of boreholes. Broadbanding in BHR has the advantage of releasing the image from 2nπ phase ambiguities, but practically, interferometric borehole radar (InBHR) needs high signal-to-noise ratios (SNR) to avoid noise capture. This means that 3D InBHR is limited to ranges in wavelengths which are less than the rock's attenuation factor Q. Interferometric methods are developed which are capable of mapping ore bodies and other structures in three dimensions. Tangent plane migration methods are developed here in order to reconstruct surfaces that lie in the near-field of sparse interferometric arrays.     

Impact of land-use changes on snow in a forested region with heavy snowfall in Hokkaido,Japan

Abstract

We simulated snow processes in a forested region with heavy snowfall in Japan, and evaluated both the regional-scale snow distribution and the potential impact of land-use changes on the snow cover and water balances over the entire domain. SnowModel reproduced the snow processes at open and forested sites, which were confirmed by snow water equivalent (SWE) measurements at two intensive observation sites and snow depth measurements at the Automated Meteorological Data Acquisition System sites. SnowModel also reproduced the observed snow distribution (from the MODIS snow cover data) over the simulation domain during thaw. The observed SWE was less at the forested site than at the open site. The SnowModel simulations showed that this difference was caused mainly by differences in sublimation. The type of land use changed the maximum SWE, onset and duration of snowmelt, and the daily snowmelt rate due to canopy snow interception.

Citation Suzuki, K., Kodama, Y., Nakai, T., Liston, G. E., Yamamoto, K., Ohata, T., Ishii, Y., Sumida, A., Hara, T. & Ohta, T. (2011) Impact of land-use changes in a forested region with heavy snowfall in Hokkaido, Japan. Hydrol. Sci. J. 56(3), 443–467.     

Factors controlling specific sediment yield in the upper Indus River basin,northern Pakistan

Estimates of sediment yield are essential in water resources analysis, modelling and engineering, in investigations of continental denudation rates, and in studies of drainage basin response to changes in climate and land use. The availability of high resolution, global environmental datasets offers an opportunity to examine the relationships between specific sediment yield (SY_sp) and drainage basin attributes in a geographical information system (GIS) environment. This study examines SY_sp at 14 long‐term gauging stations within the upper Indus River basin. Twenty‐nine environmental variables were derived from global datasets, the majority with a 1 × 1 km resolution. The SY_sp ranges from 194 to 1302 t km^?2 yr^?1 for sub‐basins ranging from 567 to 212 447 km². The high degree of scatter in SY_sp is greatly reduced when the stations are divided into three groups: upper, glacierized sub‐basins; lower, monsoon sub‐basins; and the main Indus River. Percentage snow/ice cover (LC_s) emerges as the single major land cover control for SY_sp in the high mountainous upper Indus River basin. A regression model with percentage snow/ice cover (LC_s) as the single independent variable explains 73·4% of the variance in SY_sp for the whole Indus basin. A combination of percentage snow/ice cover (LC_s), relief and climate variables explains 98·5% of the variance for the upper, glacierized sub‐basins. For the lower monsoon region, a regression model with only mean annual precipitation (P) explains 99·4% of the variance. Along the main Indus River, a regression model including just basin relief (R) explains 92·4% of the variance in SY_sp. Based on the R²_adj and P‐value statistics, the variables used are capable of explaining the majority of variance in the upper Indus River basin. Copyright © 2007 John Wiley & Sons, Ltd.     

Seasonal snow cover decreases young water fractions in high Alpine catchments

Estimation of young water fractions (F_yw), defined as the fraction of water in a stream younger than approximately 2–3 months, provides key information for water resource management in catchments where runoff is dominated by snowmelt. Knowing the average dependence of summer flow on winter precipitation is an essential context for comparing regional drought severity and provides the hydrological template for downstream water users and ecosystems. However, F_yw estimation based on seasonal signals of stable isotopes of oxygen and hydrogen has not yet explicitly addressed how to parsimoniously include the seasonal shift of water input from snow. Using experimental data from three high-elevation, Alpine catchments (one dominated by glacier and two by snow), we propose a framework to explicitly include the delays induced by snow storage into estimates of F_yw. Scrutinizing the key methodological choices when estimating F_yw from isotope data, we find that the methods used to construct precipitation input signals from sparse isotope samples can significantly impact F_yw. Given this sensitivity, our revised procedure estimates a distribution of F_yw values that incorporates a wide range of possible methodological choices and their uncertainties; it furthermore compares the commonly used amplitude ratio approach to a direct convolution approach, which circumvents the assumption that the isotopic signals have a sine curve shape, an assumption that is generally violated in snow-dominated environments. Our new estimates confirm that high-elevation Alpine catchments have low F_yw values, spanning from 8 to 11%. Such low values have previously been interpreted as the impact of seasonal snow storage alone, but our comparison of different F_yw estimation methods suggests that these low F_yw values result from a combination of both snow cover effects and longer storage in the subsurface. In contrast, in the highest elevation, glacier dominated catchment, F_yw is 3–4 times greater compared to the other two catchments, due to the lower storage and faster drainage processes. A future challenge, capturing spatio-temporal snowmelt isotope signals during winter baseflow and the snowmelt period, remains to improve constraints on the F_yw estimation technique.     

Mapping of Japanese areas susceptible to snow cover change

Abstract

Many of the Japanese regions subject to seasonal snow cover are characterized by low elevations and relatively high winter temperatures. A small change in winter temperatures could render many of these areas susceptible to snow cover change and consequently affect water resources management. This paper describes a climatological approach combined with an AGCM output to identify the regions and main river basins most sensitive to snow cover change in the case of climate change in Japan. It was found that a 1°C rise in temperature during the winter season could increase the snow-free area of Japan by 6%. The snow cover of Tohoku region and Mogami and Agano river basins was found to be the most sensitive to climate change. The AGCM output for a future scenario presents a reduction in total snowfall and an earlier peak in snowmelt for all regions.

Editor Z.W. Kundzewicz

Citation Chaffe, P.L.B, Takara, K, Yamashiki, Y, Apip, Luo, P., Silva, R.V., and Nakakita, E., 2013. Mapping of Japanese areas susceptible to snow cover change. Hydrological Sciences Journal, 58 (8), 1718–1728.     

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.     

Radar observations of ionospheric irregularities at Syowa Station, Antarctica: a brief overview

We briefly overview the radar observations that have been made for 30 years at Syowa Station, Antarctica for studying small-scale electron-density irregularities in the southern high-latitude E- and F-region ionosphere. Some observational results (i.e., long-term variations of radio aurora, Doppler spectra with narrow spectral widths and low Doppler velocities, and simultaneous observations of radar and optical auroras) from VHP radars capable of detecting 1.3- to 3-m scale irregularities are presented. A new 50-MHz radar system equipped with phased-antenna arrays began operation in February 1995 to observe two-dimensional behaviors of E-region irregularities. An HF radar experiment also began in February 1995 to explore decameter-scale E- and F-region irregularities in the auroral zone and polar cap. These two radars will contribute to a better understanding of the ionospheric irregularities and ionospheric physics at southern high latitudes.     

Temporal observations of a seasonal snowpack using upward‐looking GPR

An increase of the spatial and temporal resolution of snowpack measurements in Alpine or Arctic regions will improve the predictability of flood and avalanche hazards and increase the spatial validity of snowpack simulation models. In the winter season 2009, we installed a ground‐penetrating radar (GPR) system beneath the snowpack to measure snowpack conditions above the antennas. In comparison with modulated frequency systems, GPR systems consist of a much simpler technology, are commercially available and therefore are cheaper. The radar observed the temporal alternation of the snow height over more than 2·5 months. The presented data showed that with moved antennas, it is possible to record the snow height with an uncertainty of less than 8% in comparison with the probed snow depth. Three persistent melt crusts, which formed at the snow surface and were buried by further new snow events, were used as reflecting tracers to follow the snow cover evolution and to determine the strain rates of underlaying layers between adjacent measurements. The height in two‐way travel time of each layer changed over time, which is a cumulative effect of settlement and variation of wave speed in response to densification and liquid water content. The infiltration of liquid water with depth during melt processes was clearly observed during one event. All recorded reflections appeared in concordance with the physical principles (e.g. in phase structure), and one can assume that distinct density steps above a certain threshold result in reflections in the radargram. The accuracy of the used impulse radar system in determining the snow water equivalent is in good agreement with previous studies, which used continuous wave radar systems. The results of this pilot study encourage further investigations with radar measurements using the described test arrangement on a daily basis for continuous destruction‐free monitoring of the snow cover. Copyright © 2010 John Wiley & Sons, Ltd.     

Precipitation Observations with NSSL’s X-band Polarimetric Radar during the SNOW-V10 Campaign

In support of SNOW-V10, the National Oceanic Administration/National Severe Storms Laboratory (NOAA/NSSL) mobile dual-polarized X-band (NO-XP) radar was deployed to Birch Bay State Park in Birch Bay, Washington from 3 January 2010 to 17 March 2010. In addition to being made available in real time for Science and NOWcasting of the Olympic Weather for Vancouver 2010 (SNOW-V10) operations, NO-XP data are used here to demonstrate the capabilities of easily deployable, polarimetric X-band radar systems, especially for regions where mountainous terrain results in partial beam blockage. A rainfall estimator based on specific attenuation is shown to mitigate the effects of partial beam blockage and provide potential improvement in rainfall estimation. The ability of polarimetric X-band radar to accurately detect melting layer (ML) height is also shown. A 16 h comparison of radar reflectivity (Z), differential reflectivity (Z _DR), and correlation coefficient (ρ_hv) measurements from NO-XP with vertically pointing Micro Rain Radar observations indicates that the two instruments provide ML height evolution that exhibit consistent temporal trends. Since even slight changes in the ML height in regions of mountainous terrain might result in a change in precipitation type measured at the surface, this shows that horizontally extensive information on ML height fluctuations, such as provided by the NO-XP, is useful in determining short term changes in expected precipitation type. Finally, range-height indicator (RHI) scans of NO-XP Z, Z _DR, and ρ_hv fields from SNOW-V10 are used to demonstrate the ability of polarimetric radar to diagnose microphysical processes (both above and below the ML) that otherwise remain unseen by conventional radar. Near-surface enhancements in Z _DR are attributed to either differential sedimentation or the preferential evaporation of smaller drops. Immediately above the ML, regions of high Z, low Z _DR, and high ρ_hv are believed to be associated with convective turrets containing heavily aggregated or rimed snow that supply water/ice mass that later result in enhanced regions of precipitation near the surface. Higher up, horizontally extensive regions of enhanced Z _DR are attributed to rapid dendritic growth and the onset of snow aggregation, a feature that has been widely observed with both S band and C band radars.     

Remote sensing application to estimate the volume of water in the form of snow on Mount Lebanon / Application de la télédétection à l’estimation du volume d’eau sous forme de neige sur le Mont Liban

Abstract

Abstract At least one-quarter of the Lebanese terrain is covered by snow annually, thus contributing integrally to feeding surface and subsurface water resources. However, only limited estimates of snow cover have been carried out and applied locally. The use of remote sensing has enhanced significantly the delineation of snow cover over the mountains. Several satellite images and sensors are used in this respect. In this study, SPOT-4 (1-km resolution) satellite images are used. They have the capability to acquire consecutive images every 10 days, thus monitoring the dynamic change of snow and its maximum coverage could be achieved. This was applied to Mount Lebanon for the years 2001–2002. The areas covered by snow were delineated, and then manipulated with the slope angle and altitudes in order to classify five major zones of snowmelt potential. The field investigation was carried out in each zone by measuring depths and snow/water ratio. A volume of around 1100 × 10⁶ m³ of water was derived from snowmelt over the given period. This is equivalent to a precipitation rate of about 425 mm in the region, revealing the considerable portion of water that is derived from snowmelt.     

Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments

We examine the value of additional information in multiple objective calibration in terms of model performance and parameter uncertainty. We calibrate and validate a semi‐distributed conceptual catchment model for two 11‐year periods in 320 Austrian catchments and test three approaches of parameter calibration: (a) traditional single objective calibration (SINGLE) on daily runoff; (b) multiple objective calibration (MULTI) using daily runoff and snow cover data; (c) multiple objective calibration (APRIORI) that incorporates an a priori expert guess about the parameter distribution as additional information to runoff and snow cover data. Results indicate that the MULTI approach performs slightly poorer than the SINGLE approach in terms of runoff simulations, but significantly better in terms of snow cover simulations. The APRIORI approach is essentially as good as the SINGLE approach in terms of runoff simulations but is slightly poorer than the MULTI approach in terms of snow cover simulations. An analysis of the parameter uncertainty indicates that the MULTI approach significantly decreases the uncertainty of the model parameters related to snow processes but does not decrease the uncertainty of other model parameters as compared to the SINGLE case. The APRIORI approach tends to decrease the uncertainty of all model parameters as compared to the SINGLE case. Copyright © 2006 John Wiley & Sons, Ltd.