Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator
Ensemble Streamflow Prediction (ESP) provides an efficient tool for seasonal hydrological forecasts. In this study, we propose a new modification of input data series for the ESP system used for the runoff volume prediction with a lead of one month. These series are not represented by short historic...
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Online Access: | https://doi.org/10.1016/j.jhydrol.2015.07.008 http://hdl.handle.net/11104/0247945 |
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ftczacademyscien:oai:asep.lib.cas.cz:CavUnEpca/0445334 2024-02-04T10:02:42+01:00 Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator Šípek, V. (Václav) Daňhelka, J. 2015 https://doi.org/10.1016/j.jhydrol.2015.07.008 http://hdl.handle.net/11104/0247945 eng eng doi:10.1016/j.jhydrol.2015.07.008 urn:pissn: 0022-1694 urn:eissn: 1879-2707 http://hdl.handle.net/11104/0247945 info:eu-repo/semantics/restrictedAccess seasonal forecasting ESP large-scale climate weather generator info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2015 ftczacademyscien https://doi.org/10.1016/j.jhydrol.2015.07.008 2024-01-09T17:31:58Z Ensemble Streamflow Prediction (ESP) provides an efficient tool for seasonal hydrological forecasts. In this study, we propose a new modification of input data series for the ESP system used for the runoff volume prediction with a lead of one month. These series are not represented by short historical weather datasets but by longer generated synthetic weather data series. Before their submission to the hydrological model, their number is restricted by relations among observed meteorological variables (average monthly precipitation and temperature) and large-scale climatic patterns and indices (e.g. North Atlantic Oscillation, sea level pressure values and two geopotential heights). This modification was tested over a four-year testing period using the river basin in central Europe. The LARS-WG weather generator proved to be a suitable tool for the extension of the historical weather records. The modified ESP approach proved to be more efficient in the majority of months compared both to the original ESP method and reference forecast (based on probability distribution of historical discharges). The improvement over traditional ESP was most obvious in the narrower forecast interval of the expected runoff volume. The inefficient forecasts of the modified ESP scheme (compared to traditional ESP) were conditioned by an insufficient restriction of input synthetic weather datasets by the climate forecast. Article in Journal/Newspaper North Atlantic North Atlantic oscillation The Czech Academy of Sciences: Publication Activity (ASEP) Journal of Hydrology 528 720 733 |
institution |
Open Polar |
collection |
The Czech Academy of Sciences: Publication Activity (ASEP) |
op_collection_id |
ftczacademyscien |
language |
English |
topic |
seasonal forecasting ESP large-scale climate weather generator |
spellingShingle |
seasonal forecasting ESP large-scale climate weather generator Šípek, V. (Václav) Daňhelka, J. Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator |
topic_facet |
seasonal forecasting ESP large-scale climate weather generator |
description |
Ensemble Streamflow Prediction (ESP) provides an efficient tool for seasonal hydrological forecasts. In this study, we propose a new modification of input data series for the ESP system used for the runoff volume prediction with a lead of one month. These series are not represented by short historical weather datasets but by longer generated synthetic weather data series. Before their submission to the hydrological model, their number is restricted by relations among observed meteorological variables (average monthly precipitation and temperature) and large-scale climatic patterns and indices (e.g. North Atlantic Oscillation, sea level pressure values and two geopotential heights). This modification was tested over a four-year testing period using the river basin in central Europe. The LARS-WG weather generator proved to be a suitable tool for the extension of the historical weather records. The modified ESP approach proved to be more efficient in the majority of months compared both to the original ESP method and reference forecast (based on probability distribution of historical discharges). The improvement over traditional ESP was most obvious in the narrower forecast interval of the expected runoff volume. The inefficient forecasts of the modified ESP scheme (compared to traditional ESP) were conditioned by an insufficient restriction of input synthetic weather datasets by the climate forecast. |
format |
Article in Journal/Newspaper |
author |
Šípek, V. (Václav) Daňhelka, J. |
author_facet |
Šípek, V. (Václav) Daňhelka, J. |
author_sort |
Šípek, V. (Václav) |
title |
Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator |
title_short |
Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator |
title_full |
Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator |
title_fullStr |
Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator |
title_full_unstemmed |
Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator |
title_sort |
modification of input datasets for the ensemble streamflow prediction based on large scale climatic indices and weather generator |
publishDate |
2015 |
url |
https://doi.org/10.1016/j.jhydrol.2015.07.008 http://hdl.handle.net/11104/0247945 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
doi:10.1016/j.jhydrol.2015.07.008 urn:pissn: 0022-1694 urn:eissn: 1879-2707 http://hdl.handle.net/11104/0247945 |
op_rights |
info:eu-repo/semantics/restrictedAccess |
op_doi |
https://doi.org/10.1016/j.jhydrol.2015.07.008 |
container_title |
Journal of Hydrology |
container_volume |
528 |
container_start_page |
720 |
op_container_end_page |
733 |
_version_ |
1789969597876666368 |