HYPE (Hydrological Predictions for the Environment) model was applied for simulation of discharge and streamwater inorganic nitrogen (IN) concentration in two different meso scale catchments of the German lower mountain range, the Selke (463 km2) and Weida catchments (99 km2). DREAM(ZS) (DiffeRential Evolution Adaptive Metropolis algorithm) was combined with the HYPE model to implement parameter calibration and uncertainty analysis. Results showed that IN concentration and daily IN load had a proportional relationship with discharge, indicating that IN leaching is mainly controlled by runoff. The HYPE model was proved to be capable of capturing dynamics and balances of water and IN load with a Nash-Sutcliffe coefficient above 0.83. Multi-site calibration improved model performances at internal sites and decreased parameter posterior uncertainty ranges as well as prediction uncertainty. Compared with calibration using bi-weekly measurements, nitrogen-process parameters calibrated using daily averages of nitrate-N concentration observations produced better and more robust IN modelling performance, narrower posterior parameter uncertainty ranges and IN prediction uncertainty.
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Dr.Sanyuan Jiang,05.2014-Currently,Assistant Professor in Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences.01.2010-04.2014, PhD student at Department Aquatic Ecosystem Analysis,Helmholtz Centre for Environmental Research (UFZ),Germany
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -HYPE (Hydrological Predictions for the Environment) model was applied for simulation of discharge and streamwater inorganic nitrogen (IN) concentration in two different meso scale catchments of the German lower mountain range, the Selke (463 km2) and Weida catchments (99 km2). DREAM(ZS) (DiffeRential Evolution Adaptive Metropolis algorithm) was combined with the HYPE model to implement parameter calibration and uncertainty analysis. Results showed that IN concentration and daily IN load had a proportional relationship with discharge, indicating that IN leaching is mainly controlled by runoff. The HYPE model was proved to be capable of capturing dynamics and balances of water and IN load with a Nash-Sutcliffe coefficient above 0.83. Multi-site calibration improved model performances at internal sites and decreased parameter posterior uncertainty ranges as well as prediction uncertainty. Compared with calibration using bi-weekly measurements, nitrogen-process parameters calibrated using daily averages of nitrate-N concentration observations produced better and more robust IN modelling performance, narrower posterior parameter uncertainty ranges and IN prediction uncertainty. 168 pp. Englisch. N° de réf. du vendeur 9783838150031
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jiang SanyuanDr.Sanyuan Jiang,05.2014-Currently,Assistant Professor in Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences.01.2010-04.2014, PhD student at Department Aquatic Ecosystem Analysis,Helmholtz Centre f. N° de réf. du vendeur 13010686
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - HYPE (Hydrological Predictions for the Environment) model was applied for simulation of discharge and streamwater inorganic nitrogen (IN) concentration in two different meso scale catchments of the German lower mountain range, the Selke (463 km2) and Weida catchments (99 km2). DREAM(ZS) (DiffeRential Evolution Adaptive Metropolis algorithm) was combined with the HYPE model to implement parameter calibration and uncertainty analysis. Results showed that IN concentration and daily IN load had a proportional relationship with discharge, indicating that IN leaching is mainly controlled by runoff. The HYPE model was proved to be capable of capturing dynamics and balances of water and IN load with a Nash-Sutcliffe coefficient above 0.83. Multi-site calibration improved model performances at internal sites and decreased parameter posterior uncertainty ranges as well as prediction uncertainty. Compared with calibration using bi-weekly measurements, nitrogen-process parameters calibrated using daily averages of nitrate-N concentration observations produced better and more robust IN modelling performance, narrower posterior parameter uncertainty ranges and IN prediction uncertainty. N° de réf. du vendeur 9783838150031
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Hydrological water quality modelling of nested meso scale catchments | Sanyuan Jiang | Taschenbuch | 168 S. | Englisch | 2016 | Südwestdeutscher Verlag für Hochschulschriften | EAN 9783838150031 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 104900476
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -HYPE (Hydrological Predictions for the Environment) model was applied for simulation of discharge and streamwater inorganic nitrogen (IN) concentration in two different meso scale catchments of the German lower mountain range, the Selke (463 km2) and Weida catchments (99 km2). DREAM(ZS) (DiffeRential Evolution Adaptive Metropolis algorithm) was combined with the HYPE model to implement parameter calibration and uncertainty analysis. Results showed that IN concentration and daily IN load had a proportional relationship with discharge, indicating that IN leaching is mainly controlled by runoff. The HYPE model was proved to be capable of capturing dynamics and balances of water and IN load with a Nash-Sutcliffe coefficient above 0.83. Multi-site calibration improved model performances at internal sites and decreased parameter posterior uncertainty ranges as well as prediction uncertainty. Compared with calibration using bi-weekly measurements, nitrogen-process parameters calibrated using daily averages of nitrate-N concentration observations produced better and more robust IN modelling performance, narrower posterior parameter uncertainty ranges and IN prediction uncertainty.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 168 pp. Englisch. N° de réf. du vendeur 9783838150031
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