Improving hydrological forecasting using multi-source remote sensing data together with in situ measurements

Juha-Petri Kärnä, Markus Huttunen, Sari Metsämäki, Bertel Vehviläinen, Victor Podsechin, Jouni Pulliainen, Juha Lemmetyinen, Timo Kuitunen, Yrjö Rauste, Robin Berglund

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Abstract

    This paper describes the development of information systems and techniques for improving hydrological forecasting by applying satellite observations, weather radars, and in situ measurements from automatic monitoring stations. In the methodology developed and demonstrated, the observation data are accompanied with a detailed soil and land cover information. The information system is concerned with the following physical characteristics relevant to river discharges and flooding: snow water equivalent (SWE), cumulative amount of precipitation, fraction of snow covered area during the melting period (FSC), soil moisture, and soil frost. Feasibility of the multi-source information system is demonstrated in a pilot experiment for Finnish Lapland, using the hydrological forecasting system of the Finnish Environment Institute (SYKE) as an example of a typical operational distributed model
    Original languageEnglish
    Title of host publicationProceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages1749-1752
    ISBN (Electronic)978-1-4244-9566-5
    ISBN (Print)978-1-4244-9565-8
    DOIs
    Publication statusPublished - 2010
    MoE publication typeA4 Article in a conference publication
    EventInternational Geoscience and Remote Sensing Symposium, IGARSS 2010 - Honolulu, Hawaii, United States
    Duration: 25 Jul 201030 Jul 2010

    Conference

    ConferenceInternational Geoscience and Remote Sensing Symposium, IGARSS 2010
    Abbreviated titleIGARSS 2010
    Country/TerritoryUnited States
    CityHonolulu, Hawaii
    Period25/07/1030/07/10

    Keywords

    • Snow, hydrology
    • floods
    • multi-source data

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