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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
parameters that could be derived from remote sensing 
information. 
There has to be a correspondence between the resolution in 
space of the distributed system type model and the resolution of 
the input data. 
Runoff streaming from snowmelt can be estimated with 
snowmelt runoff model (SRM). The SRM (Martinec at all, 
1994) model can simulate and forecast daily stream flow in 
mountain basins where snowmelt is majored component of the 
water balance. The required model input consists of periodic 
snow cover areas estimated from satellite (LANDSAT-TM, 
SPOT, NOAA-AVHRR) or from air photos, daily temperature 
and precipitation. 
The snow cover data are used to construct the snow cover 
depletion curves for different zones in the basin. 
Certain model parameters relevant for snowmelt runoff can be 
estimated on the basis of the land use/land cover classification 
and vegetation index, derived from multispectral data. 
The forecasting, of the watershed flow generated by liquid 
g 8 y 
precipitation and snowmelt is expressed by a general relation of 
the following form: 
Vinow T Vip) EN (1) 
where: Vsnow - water volume stored in the snowpack ; 
Vyp- Water volume generated by liquid precipitation; 
a - water flow coefficient; 
V4 - total water volume measured on the river at the 
watershed outlet. 
The error that determines the accuracy of the total flow in a 
watershed (£y1) is done by: 
EVT Eu + (Evsiow Vanow i £vpp V pp) / (V mov 3 Vir) (2) 
The averaged accuracy of the water volume stored in the 
snowpack is about 90 - 93 %. The averaged accuracy of the 
water flow coefficient and of the water volume generated by the 
liquid precipitations may be considered in the range 70 - 80% 
(taking into account the averaged accuracy of the 
meteorological forecasting). 
The improvement of reservoir exploitation depends on the 
accuracy of the hydro-meteorological forecastings and of the 
decision efficiency that can be taken on that basis. 
The study of the relation between the accuracy, decision 
efficiency and anticipation forecasting time is useful to 
establish the optimal zone of the forecasting methods. The 
spatial forecastings based on remotely sensed information are 
located near the central zone of the optimization curve. So, it is 
highly recommended for the improvement of the reservoir 
exploitation, the use of spatial forecasting method. 
267 
CONCLUSIONS 
Snow melting and the occurrence of the flow resulted from the 
snow mass accumulated during winter-spring period is one of 
the important phases of the hydrological cycle within the basins 
of the Carpathian rivers. 
Remote sensing data play a rapidly increasing role in the field 
of snow hydrology. One of the great advantages of remote 
sensing data in hydrology consists in the area information 
instead of the usual point data. The cost of collecting and using 
remotely sensed data could be very high, so the use of this data 
should be carefully evaluated. The cost of collecting adequate 
ground-station data could be even higher, so the trade-offs 
between the two data types need to be examined. 
The possibility of merging satellite imagery in the GIS allows 
the use of updating spatial information for land cover, land use 
and also for the evaluation of the snow cover characteristics. 
A combined remote sensing data base consisting of satellite, 
aircraft data and digital terrain information derived from DEM 
proved to be well suited in determining snowcover area extend, 
snowline, melting zones and water volume stored in the 
snowpack on different Carpathian basins of Romania. 
REFERENCES 
Martinec, J., Rango, A. and Roberts, R., 1994. Snowmelt runoff 
model (SRM). User’s manual, Geographica Bernesia University 
of Bern, 29 p. 
Schultz, G. A. and Barrett, E.C., 1989. Advances in remote 
sensing for hydrology and water resources management. 
Technical documents in hydrology, UNESCO, Paris. 
Stancalie, G., 1991. Remote sensing monitoring of snowpack 
dynamics in view of estimating the snowcover water resources 
in drainage basins of hydroelectric power interest. IUGG-XX 
General Assembly, Congress Report, Wien.