Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study
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 as...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2015-03-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | http://www.hydrol-earth-syst-sci.net/19/1469/2015/hess-19-1469-2015.pdf |
| _version_ | 1811204134609616896 |
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| author | P. Bauer-Gottwein I. H. Jensen R. Guzinski G. K. T. Bredtoft S. Hansen C. I. Michailovsky |
| author_facet | P. Bauer-Gottwein I. H. Jensen R. Guzinski G. K. T. Bredtoft S. Hansen C. I. Michailovsky |
| author_sort | P. Bauer-Gottwein |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T03:06:20Z |
| format | Article |
| id | doaj.art-7225ef63e5344350b8677c28bbbfcf69 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-04-12T03:06:20Z |
| publishDate | 2015-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-7225ef63e5344350b8677c28bbbfcf692022-12-22T03:50:29ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382015-03-011931469148510.5194/hess-19-1469-2015Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case studyP. Bauer-Gottwein0I. H. Jensen1R. Guzinski2G. K. T. Bredtoft3S. Hansen4C. I. Michailovsky5Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, DenmarkDepartment of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, DenmarkDHI GRAS, 2970 Hørsholm, DenmarkDepartment of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, DenmarkDepartment of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, DenmarkDepartment of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, DenmarkOperational 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.http://www.hydrol-earth-syst-sci.net/19/1469/2015/hess-19-1469-2015.pdf |
| spellingShingle | P. Bauer-Gottwein I. H. Jensen R. Guzinski G. K. T. Bredtoft S. Hansen C. I. Michailovsky Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study Hydrology and Earth System Sciences |
| title | Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study |
| title_full | Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study |
| title_fullStr | Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study |
| title_full_unstemmed | Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study |
| title_short | Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study |
| title_sort | operational river discharge forecasting in poorly gauged basins the kavango river basin case study |
| url | http://www.hydrol-earth-syst-sci.net/19/1469/2015/hess-19-1469-2015.pdf |
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