Snowmelt runoff forecast using satellite data in high mountainous Italian Alps

A. Narayana Swamy; Pietro Alessandro Brivio

doi:10.1117/12.227180

24 November 1995 Snowmelt runoff forecast using satellite data in high mountainous Italian Alps

A. Narayana Swamy, Pietro Alessandro Brivio

Proceedings Volume 2585, Remote Sensing for Agriculture, Forestry, and Natural Resources; (1995) https://doi.org/10.1117/12.227180
Event: Satellite Remote Sensing II, 1995, Paris, France

Abstract

The seasonal changes of snow cover are delineated during the snowmelt period of a hydrological year by digital image processing of Landsat-4 and 5 Multispectral Scanner System (MSS) and Thematic Mapper (TM) data. The study area is the upper part of the Cordevole river basin located in the eastern part of the Italian Alps. Digital elevation model, slope and hill shading maps are generated and used in the study. Satellite images are classified into snow, mixed snow, and aper using a supervised maximum likelihood algorithm and estimated separately for three elevation zones of the catchment. The satellite derived information is integrated with meteorological and hydrological data in a snowmelt runoff model using pre-determined values of degree day factors, snow and rain runoff coefficients, and recession coefficient. The model performance evaluation indicated 0.94, 0.89, and +4.6 for correlation coefficient (r), Nash Sutcliffe coefficient (R²) and percentage volume deviation (D_v), respectively. The results are in good agreement when compared to those published for the World Meteorological Organization test basins. The relative advantages and disadvantages of using remote sensing data from various satellites for snowmelt runoff forecast are discussed.

Citation Download Citation

A. Narayana Swamy and Pietro Alessandro Brivio "Snowmelt runoff forecast using satellite data in high mountainous Italian Alps", Proc. SPIE 2585, Remote Sensing for Agriculture, Forestry, and Natural Resources, (24 November 1995); https://doi.org/10.1117/12.227180

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KEYWORDS

Satellites

Earth observing sensors

Snow cover

Landsat

Atmospheric modeling

Satellite imaging

Meteorology

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