International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
For the purpose of obtaining the information concerning the 
area of the snow cover one has employed the binarization of the 
ratio between the signals in the NIR and visible on the basis of 
a threshold obtain by means of data from test areas. The method 
allows of minimizing the effect of shades. 
The surveillance of the dynamics of the snow cover is done by 
the depletion curves of the snow-covered areals. These curves 
vary function of the type of the watershed and climatic 
conditions, their shape being dependent upon the 
physiographical characteristics and the altitudinal range. The 
latter can enhances the accumulation differences and those 
noticed in the rates of melting in various areas of the basin. 
With most applications one has employed the modified 
depletion curves where the area covered with snow is expressed 
in degree-days accumulated, starting from a balanced 
temperature. The advantages one may derive from using these 
curves reside in that they can be extrapolated on the basis of the 
maximum forecasted temperature values. 
For the Carpathian basins four principal types of snow cover 
depletion curves where established (figure 4): 
- the A type corresponds to increasing snowmelt depletion rate; 
- the B type is characteristic to a slower melting rate in some 
sectors of the basins, mainly because of the snow accumulation 
arised during the melting season; 
- the C type characterizes a faster melting during the first 
period, followed by more reduced accumulations in some areas; 
- the D type is representative for a basin which can be divided 
in two areas of different characteristics: one area within reduced 
accumulation and/or faster melting rate and the other with a 
more important accumulation and/or reduced melting rate. 
* 
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Areal water equivalent / 
Maximum areal water equivalent 
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30 
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Snow free area (%) 
Figure 4. Areal snowcover depletion curves characteristics 
for the Carpathian basins 
The water amount in the snow cover is calculated from data 
concerning the depth and density of snow as well as the area it 
covers. 
The determination of the water content of the snow in the 
mountain watersheds is affected by errors occurring during the 
data acquisition and processing stages. 
The accuracy in determining the areal data obtained from 
images depends upon: 
- the spatial resolution of the sensors and geometric correction 
level ; 
- tonal contrast of images; 
- existing interference objects (clouds, shadows, relief); 
- temporal frequency of available images. 
When snow cover areas are determines indirectly by snow 
cover depletion curves extrapolation, based on forecasted 
temperatures, the accuracy also depends on the errors related 
with the temperature forecasting. 
Snow physical parameters vary with elevation and land vegetal 
cover and the accuracy of their measurement values involves 
the representativity of ground stations network. 
The accuracy in estimating the water resources in the snow by 
the presented method is in the range 5 - 15 %. 
6. DETECTING SNOWPACK CONDITION FROM 
VISIBLE NEAR-IR SATELLITE CHANNELS 
Use of near-IR data in conjunction with reflected visible 
radiation allows detection of early melting stages of snow and 
ice. Under normal conditions snow and ice are highly reflective 
(80-9096) in both the visible and near-IR channels. But under 
melting conditions near-IR radiation is absorbed, whereas 
visible radiation is strongly reflected. 
Comparison of simultaneous visible and near-IR imageries from 
LANDSAT-TM or NOAA-AVHRR satellite provides a method 
for monitoring snow melting that can be applied to runoff 
prediction. 
Where deeper accumulations persist the snow albedo apparently 
remains relatively high during the melting period. The depth of 
the snow is an important factor which controls the albedo of 
plain and hill regions, whereas the metamorphic processes may 
play a secondary role. The study of spatial variability of snow 
albedo may be achieved utilizing airborne and satellite 
imageries. 
7. SNOWMELT RUNOFF MODELLING AND 
FORECAST BASED ON REMOTE SENSING 
INFORMATION 
The advent of remote sensing data caused some confusion 
among the hydrologists since the information obtained by 
remotely sensed data could not be used directly in many of the 
existing models (Schultz & Barrett, 1989). The reason for this 
was the fact that: 
- the input data consist in electromagnetic information instead 
of hydro-meteorological data; 
- the resolution in time and space is sometimes higher or lower 
than necessary due to the available sensors. 
We have to clearly distinguish between the estimation of model 
parameters on the basis of remote sensing data and the 
estimation of model input with the aid of the remote sensing 
information. 
If we deal with physically based distributed system 
hydrological models, many model parameters characteristics 
depend on the parameters of the hydrological systems such the 
catchment/river characteristics. Some of these characteristics 
may be derived from the image-data (vegetal cover, land use, 
morphometric parameters). 
Also model input data can be estimated from the remote sensing 
data. For the computation of snowmelt, the snow cover area, the 
reflected radiation (albedo) and temperatures are relevant 
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