Application of models with different types of modelling methodologies for river flow forecasting
In the present study, a conceptual watershed model, a distributed watershed model, and an artificial neural network (ANN) have been applied to river flow forecasting in the Kalu River upper catchment in Sri Lanka. The Xinanjiang watershed model has been used as a conceptual watershed model and the S...
| Autores principales: | , , |
|---|---|
| Formato: | Conference Paper |
| Lenguaje: | Inglés |
| Publicado: |
2003
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/38476 |
| _version_ | 1855535872560070656 |
|---|---|
| author | Hapuarachchi, H.A.P. Zhijia, L. Flügel, Wolfgang-Albert |
| author_browse | Flügel, Wolfgang-Albert Hapuarachchi, H.A.P. Zhijia, L. |
| author_facet | Hapuarachchi, H.A.P. Zhijia, L. Flügel, Wolfgang-Albert |
| author_sort | Hapuarachchi, H.A.P. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | In the present study, a conceptual watershed model, a distributed watershed model, and an artificial neural network (ANN) have been applied to river flow forecasting in the Kalu River upper catchment in Sri Lanka. The Xinanjiang watershed model has been used as a conceptual watershed model and the SWAT model (Neitsch, 2000) has been used with spatial data as a distributed model. Two types of ANN architectures, namely multi-layer perceptron network (MLP) and radial basis function network (RBF) have been implemented as "black box" type modelling methodology. Based on the application results, it seems that the conceptual watershed model could perform slightly better than the distributed model and the ANN for this watershed. It was clearly noted that the performance of distributed models strictly depends on the quality of input data (Arnold et al., 1998) whereas the performance of conceptual models depends on the calibration (Duan et al., 1992, 1993). |
| format | Conference Paper |
| id | CGSpace38476 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2003 |
| publishDateRange | 2003 |
| publishDateSort | 2003 |
| record_format | dspace |
| spelling | CGSpace384762026-01-12T13:05:34Z Application of models with different types of modelling methodologies for river flow forecasting Hapuarachchi, H.A.P. Zhijia, L. Flügel, Wolfgang-Albert rivers flow forecasting watersheds catchment areas models networks In the present study, a conceptual watershed model, a distributed watershed model, and an artificial neural network (ANN) have been applied to river flow forecasting in the Kalu River upper catchment in Sri Lanka. The Xinanjiang watershed model has been used as a conceptual watershed model and the SWAT model (Neitsch, 2000) has been used with spatial data as a distributed model. Two types of ANN architectures, namely multi-layer perceptron network (MLP) and radial basis function network (RBF) have been implemented as "black box" type modelling methodology. Based on the application results, it seems that the conceptual watershed model could perform slightly better than the distributed model and the ANN for this watershed. It was clearly noted that the performance of distributed models strictly depends on the quality of input data (Arnold et al., 1998) whereas the performance of conceptual models depends on the calibration (Duan et al., 1992, 1993). 2003 2014-06-13T11:42:11Z 2014-06-13T11:42:11Z Conference Paper https://hdl.handle.net/10568/38476 en Limited Access Hapuarachchi, H. A. P.; Zhijia, L.; Flügel, Wolfgang-Albert . 2003. Application of models with different types of modelling methodologies for river flow forecasting. Tachikawa, Y.; Vieux, B. E.; Georgakakos, K. P.; Nakakita, E. (Eds.). Weather Radar Information and Distributed Hydrological Modelling: proceedings of Symposium HS03 held during IUGG2003 at Sapporo, Japan, 30 June-11 July 2003. Wallingford, UK: International Association of Hydrological Sciences (IAHS) pp.218-226. (IAHS Publication 282) |
| spellingShingle | rivers flow forecasting watersheds catchment areas models networks Hapuarachchi, H.A.P. Zhijia, L. Flügel, Wolfgang-Albert Application of models with different types of modelling methodologies for river flow forecasting |
| title | Application of models with different types of modelling methodologies for river flow forecasting |
| title_full | Application of models with different types of modelling methodologies for river flow forecasting |
| title_fullStr | Application of models with different types of modelling methodologies for river flow forecasting |
| title_full_unstemmed | Application of models with different types of modelling methodologies for river flow forecasting |
| title_short | Application of models with different types of modelling methodologies for river flow forecasting |
| title_sort | application of models with different types of modelling methodologies for river flow forecasting |
| topic | rivers flow forecasting watersheds catchment areas models networks |
| url | https://hdl.handle.net/10568/38476 |
| work_keys_str_mv | AT hapuarachchihap applicationofmodelswithdifferenttypesofmodellingmethodologiesforriverflowforecasting AT zhijial applicationofmodelswithdifferenttypesofmodellingmethodologiesforriverflowforecasting AT flugelwolfgangalbert applicationofmodelswithdifferenttypesofmodellingmethodologiesforriverflowforecasting |