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Titel |
A hydrometeorological forecasting approach for basins with complex flow regime |
VerfasserIn |
Akis Zarkadoulas, Konstantina Mantesi, Andreas Efstratiadis, Antonis Koussis, Aikaterini Mazi, Demetris Katsanos, Antonis Koukouvinos, Demetris Koutsoyiannis |
Konferenz |
EGU General Assembly 2015
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Medientyp |
Artikel
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Sprache |
Englisch
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 17 (2015) |
Datensatznummer |
250104484
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Publikation (Nr.) |
EGU/EGU2015-3904.pdf |
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Zusammenfassung |
The combined use of weather forecasting models and hydrological models in flood
risk estimations is an established technique, with several successful applications
worldwide. However, most known hydrometeorological forecasting systems have been
established in large rivers with perpetual flow. Experience from small- and medium-scale
basins, which are often affected by flash floods, is very limited. In this work we
investigate the perspectives of hydrometeorological forecasting, by emphasizing two
issues: (a) which modelling approach can credibly represent the complex dynamics
of basins with highly variable runoff (intermittent or ephemeral); and (b) which
transformation of point-precipitation forecasts provides the most reliable estimations of
spatially aggregated data, to be used as inputs to semi-distributed hydrological
models. Using as case studies the Sarantapotamos river basin, in Eastern Greece (145
km2), and the Nedontas river basin, in SW Peloponnese (120 km2), we demonstrate
the advantages of continuous simulation through the HYDROGEIOS model. This
employs conjunctive modelling of surface and groundwater flows and their interactions
(percolation, infiltration, underground losses), which are key processes in river
basins characterized by significantly variability of runoff. The model was calibrated
against hourly flow data at two and three hydrometric stations, respectively, for a
3-year period (2011-2014). Next we attempted to reproduce the most intense flood
events of that period, by substituting observed rainfall by forecast scenarios. In this
respect, we used consecutive point forecasts of a 6-hour lead time, provided by the
numerical weather prediction model WRF (Advanced Research version), dynamically
downscaled from the ~1°forecast of GSF–NCEP/NOAA successively first to
~18 km, then to ~6 km and ultimately at the horizontal grid resolution of 2x2
km2. We examined alternative spatial integration approaches, using as reference the
rainfall stations over the two basins. By combining consecutive rainfall forecasts at
the sub-basin scale (a kind of ensemble prediction), we run the model in forecast
mode to generate trajectories of flow predictions and associated uncertainty bounds. |
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