A quasi-three-dimensional model for predicting rainfall-runoff processes in a forested catchment in Southern Finland
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
A quasi-three-dimensional model for predicting rainfall-runoff processes in a forested catchment in Southern Finland ; volume:4 ; number:1 ; year:2000 ; pages:65-78
Hydrology and earth system sciences ; 4, Heft 1 (2000), 65-78
- Urheber
-
Koivusalo, H.
Karvonen, T.
Lepistö, A.
- DOI
-
10.5194/hess-4-65-2000
- URN
-
urn:nbn:de:101:1-201712214117
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:34 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Koivusalo, H.
- Karvonen, T.
- Lepistö, A.
Ähnliche Objekte (12)
The PDM rainfall-runoff model
Rainfall-runoff modeling in arid areas
Deep learning for monthly rainfall-runoff modelling: a comparison with classical rainfall-runoff modelling across Australia
From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution
DEVELOPING A CELLULAR AUTOMATA MODEL FOR SIMULATING RAINFALL-RUNOFF PROCESS (CASE STUDY: BABOL CATCHMENT)
Rainfall-runoff processes in the Loess Plateau, China: Temporal dynamics of event rainfall-runoff characteristics and diagnostic analysis of runoff generation patterns
Towards a comprehensive physically-based rainfall-runoff model
CLASSIC: a semi-distributed rainfall-runoff modelling system
Deep learning rainfall–runoff predictions of extreme events
Regionalising rainfall–runoff modelling for predicting daily runoff in continental Australia
Comparative evaluation of conceptual and physical rainfall–runoff models
Regionalization of parameters of a conceptual rainfall-runoff model
The PDM rainfall-runoff model
Rainfall-runoff modeling in arid areas
Deep learning for monthly rainfall-runoff modelling: a comparison with classical rainfall-runoff modelling across Australia
From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution
DEVELOPING A CELLULAR AUTOMATA MODEL FOR SIMULATING RAINFALL-RUNOFF PROCESS (CASE STUDY: BABOL CATCHMENT)
Rainfall-runoff processes in the Loess Plateau, China: Temporal dynamics of event rainfall-runoff characteristics and diagnostic analysis of runoff generation patterns
Towards a comprehensive physically-based rainfall-runoff model
CLASSIC: a semi-distributed rainfall-runoff modelling system
Deep learning rainfall–runoff predictions of extreme events
Regionalising rainfall–runoff modelling for predicting daily runoff in continental Australia
Comparative evaluation of conceptual and physical rainfall–runoff models
Regionalization of parameters of a conceptual rainfall-runoff model
The PDM rainfall-runoff model
Rainfall-runoff modeling in arid areas
Deep learning for monthly rainfall-runoff modelling: a comparison with classical rainfall-runoff modelling across Australia
From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution
DEVELOPING A CELLULAR AUTOMATA MODEL FOR SIMULATING RAINFALL-RUNOFF PROCESS (CASE STUDY: BABOL CATCHMENT)
Rainfall-runoff processes in the Loess Plateau, China: Temporal dynamics of event rainfall-runoff characteristics and diagnostic analysis of runoff generation patterns
Towards a comprehensive physically-based rainfall-runoff model
CLASSIC: a semi-distributed rainfall-runoff modelling system
Deep learning rainfall–runoff predictions of extreme events
Regionalising rainfall–runoff modelling for predicting daily runoff in continental Australia
Comparative evaluation of conceptual and physical rainfall–runoff models