Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study

Peter Bauer-Gottwein, Iris Hedegaard Jensen, R. Guzinski, G. K. T. Bredtoft, S. Hansen, Claire Irene B. Michailovsky, Claire Irene B. Michailovsky

    Research output: Contribution to journalJournal articleResearchpeer-review

    377 Downloads (Pure)

    Abstract

    Operational probabilistic forecasts of river discharge are essential for effective water resources management. Many studies have addressed this topic using different approaches ranging from purely statistical black-box approaches to physically based and distributed modeling schemes employing data assimilation techniques. However, few studies have attempted to develop operational probabilistic forecasting approaches for large and poorly gauged river basins. The objective of this study is to develop open-source software tools to support hydrologic forecasting and integrated water resources management in Africa. We present an operational probabilistic forecasting approach which uses public-domain climate forcing data and a hydrologic-hydrodynamic model which is entirely based on open-source software. Data assimilation techniques are used to inform the forecasts with the latest available observations. Forecasts are produced in real time for lead times of 0-7 days. The operational probabilistic forecasts are evaluated using a selection of performance statistics and indicators and the performance is compared to persistence and climatology benchmarks. The forecasting system delivers useful forecasts for the Kavango River, which are reliable and sharp. Results indicate that the value of the forecasts is greatest for intermediate lead times between 4 and 7 days.
    Original languageEnglish
    JournalHydrology and Earth System Sciences
    Volume19
    Issue number3
    Pages (from-to)1469-1485
    Number of pages17
    ISSN1027-5606
    DOIs
    Publication statusPublished - 2015

    Fingerprint

    Dive into the research topics of 'Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study'. Together they form a unique fingerprint.

    Cite this