Title: Seasonal river discharge forecast in alpine catchments using snow map time series and support vector regression approach
Authors: CALLEGARI MattiaMAZZOLI PaoloDE GREGORIO LudovicaNOTARNICOLA ClaudiaPETITTA MarcelloPASOLLI LucaSEPPI RobertoPISTOCCHI Alberto
Publisher: IEEE
Publication Year: 2014
JRC N°: JRC88276
URI: http://ieeexplore.ieee.org/Xplore/defdeny.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Fstamp%2Fstamp.jsp%3Ftp%3D%26arnumber%3D6946379&denyReason=-134&arnumber=6946379&productsMatched=null&userType=inst
http://publications.jrc.ec.europa.eu/repository/handle/JRC88276
DOI: 10.1109/IGARSS.2014.6946379
Type: Articles in periodicals and books
Abstract: The prediction of monthly mean discharge is critical for water resources management. Statistical methods applied on discharge time series are traditionally used for predicting this kind of slow response hydrological events. With this paper we present a Support Vector Regression (SVR) system able to predict monthly mean discharge considering discharge and snow cover extent (250 meters resolution obtained by MODIS images) time series as input. Additional meteorological and climatic variables are also tested as inputs for the SVR. The prediction system has been evaluated on 14 catchments in South Tyrol (Northern Italy) showing improved prediction capacity compared with the expected value of the discharge, estimated as the average over the 10 years before the start of the simulation; the latter is an estimate used in common practice for water resources management in the study region. The percentage root mean square error (RMSE%) is reduced of 11% and 6% for a prediction lag of 1 and 3 months respectively.
JRC Directorate:Sustainable Resources

Files in This Item:
There are no files associated with this item.


Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.