Rainfall-runoff modelling in a catchment with a complex groundwater flow system: application of the Representative Elementary Watershed (REW) approach
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
Rainfall-runoff modelling in a catchment with a complex groundwater flow system: application of the Representative Elementary Watershed (REW) approach ; volume:9 ; number:3 ; year:2005 ; pages:243-261
Hydrology and earth system sciences ; 9, Heft 3 (2005), 243-261
- Creator
-
Zhang, G. P.
Savenije, H. H. G.
- DOI
-
10.5194/hess-9-243-2005
- URN
-
urn:nbn:de:101:1-201801068032
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:48 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Zhang, G. P.
- Savenije, H. H. G.
Other Objects (12)
The PDM rainfall-runoff model
Rainfall-runoff modeling in arid areas
Highly Resolved Rainfall-Runoff Simulation of Retrofitted Green Stormwater Infrastructure at the Micro-Watershed Scale
Regional climate models and bias correction methods for rainfall-runoff modeling in Katar watershed, Ethiopia
Deep learning for monthly rainfall-runoff modelling: a comparison with classical rainfall-runoff modelling across Australia
Regionalising rainfall–runoff modelling for predicting daily runoff in continental Australia
Rainfall-runoff processes in the Loess Plateau, China: Temporal dynamics of event rainfall-runoff characteristics and diagnostic analysis of runoff generation patterns
CLASSIC: a semi-distributed rainfall-runoff modelling system
Towards a comprehensive physically-based rainfall-runoff model
Deep learning rainfall–runoff predictions of extreme events
From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution
Comparative evaluation of conceptual and physical rainfall–runoff models
The PDM rainfall-runoff model
Rainfall-runoff modeling in arid areas
Highly Resolved Rainfall-Runoff Simulation of Retrofitted Green Stormwater Infrastructure at the Micro-Watershed Scale
Regional climate models and bias correction methods for rainfall-runoff modeling in Katar watershed, Ethiopia
Deep learning for monthly rainfall-runoff modelling: a comparison with classical rainfall-runoff modelling across Australia
Regionalising rainfall–runoff modelling for predicting daily runoff in continental Australia
Rainfall-runoff processes in the Loess Plateau, China: Temporal dynamics of event rainfall-runoff characteristics and diagnostic analysis of runoff generation patterns
CLASSIC: a semi-distributed rainfall-runoff modelling system
Towards a comprehensive physically-based rainfall-runoff model
Deep learning rainfall–runoff predictions of extreme events
From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution
Comparative evaluation of conceptual and physical rainfall–runoff models
The PDM rainfall-runoff model
Rainfall-runoff modeling in arid areas
Highly Resolved Rainfall-Runoff Simulation of Retrofitted Green Stormwater Infrastructure at the Micro-Watershed Scale
Regional climate models and bias correction methods for rainfall-runoff modeling in Katar watershed, Ethiopia
Deep learning for monthly rainfall-runoff modelling: a comparison with classical rainfall-runoff modelling across Australia
Regionalising rainfall–runoff modelling for predicting daily runoff in continental Australia
Rainfall-runoff processes in the Loess Plateau, China: Temporal dynamics of event rainfall-runoff characteristics and diagnostic analysis of runoff generation patterns
CLASSIC: a semi-distributed rainfall-runoff modelling system
Towards a comprehensive physically-based rainfall-runoff model
Deep learning rainfall–runoff predictions of extreme events
From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution