Assessment of streamflow simulation for a tropical forested catchment using dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) framework and Generalized Likelihood Uncertainty Estimation (GLUE)
Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal dri...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Published: |
Multidisciplinary Digital Publishing Institute
2021
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/96092/ |
| _version_ | 1848862293890170880 |
|---|---|
| author | Fadhliani Zulkafli, Zed Diyana Yusuf, Badronnisa Abu Bakar, Siti Nurhidayu |
| author_facet | Fadhliani Zulkafli, Zed Diyana Yusuf, Badronnisa Abu Bakar, Siti Nurhidayu |
| author_sort | Fadhliani |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1—considering the flexibility, modularity, and portability—and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e., the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. Thirty-two years’ continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatter plot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modeling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales. |
| first_indexed | 2025-11-15T13:14:44Z |
| format | Article |
| id | upm-96092 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T13:14:44Z |
| publishDate | 2021 |
| publisher | Multidisciplinary Digital Publishing Institute |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-960922023-02-24T03:11:37Z http://psasir.upm.edu.my/id/eprint/96092/ Assessment of streamflow simulation for a tropical forested catchment using dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) framework and Generalized Likelihood Uncertainty Estimation (GLUE) Fadhliani Zulkafli, Zed Diyana Yusuf, Badronnisa Abu Bakar, Siti Nurhidayu Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1—considering the flexibility, modularity, and portability—and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e., the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. Thirty-two years’ continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatter plot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modeling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales. Multidisciplinary Digital Publishing Institute 2021 Article PeerReviewed Fadhliani and Zulkafli, Zed Diyana and Yusuf, Badronnisa and Abu Bakar, Siti Nurhidayu (2021) Assessment of streamflow simulation for a tropical forested catchment using dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) framework and Generalized Likelihood Uncertainty Estimation (GLUE). Water, 13 (3). art. no. 317. pp. 1-16. ISSN 2073-4441 https://www.mdpi.com/2073-4441/13/3/317 10.3390/w13030317 |
| spellingShingle | Fadhliani Zulkafli, Zed Diyana Yusuf, Badronnisa Abu Bakar, Siti Nurhidayu Assessment of streamflow simulation for a tropical forested catchment using dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) framework and Generalized Likelihood Uncertainty Estimation (GLUE) |
| title | Assessment of streamflow simulation for a tropical forested catchment using dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) framework and Generalized Likelihood Uncertainty Estimation (GLUE) |
| title_full | Assessment of streamflow simulation for a tropical forested catchment using dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) framework and Generalized Likelihood Uncertainty Estimation (GLUE) |
| title_fullStr | Assessment of streamflow simulation for a tropical forested catchment using dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) framework and Generalized Likelihood Uncertainty Estimation (GLUE) |
| title_full_unstemmed | Assessment of streamflow simulation for a tropical forested catchment using dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) framework and Generalized Likelihood Uncertainty Estimation (GLUE) |
| title_short | Assessment of streamflow simulation for a tropical forested catchment using dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) framework and Generalized Likelihood Uncertainty Estimation (GLUE) |
| title_sort | assessment of streamflow simulation for a tropical forested catchment using dynamic topmodel—dynamic fluxes and connectivity for predictions of hydrology (decipher) framework and generalized likelihood uncertainty estimation (glue) |
| url | http://psasir.upm.edu.my/id/eprint/96092/ http://psasir.upm.edu.my/id/eprint/96092/ http://psasir.upm.edu.my/id/eprint/96092/ |