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Article

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)

by 1,2,*,†, 1,*,†, 1 and 3
1
Department of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia
2
Department of Civil Engineering, Faculty of Engineering, Universitas Malikussaleh, Aceh Utara 24355, Indonesia
3
Department of Forestry Science, Faculty of Forestry and Environment, Universiti Putra Malaysia, Serdang 43400, Malaysia
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Xuefeng Chu
Water 2021, 13(3), 317; https://doi.org/10.3390/w13030317
Received: 26 October 2020 / Revised: 18 December 2020 / Accepted: 21 December 2020 / Published: 28 January 2021
(This article belongs to the Special Issue Advanced Hydrologic Modeling in Watershed-Scale)
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. View Full-Text
Keywords: streamflow; dynamic TOPMODEL; DECIPHeR; GLUE analysis streamflow; dynamic TOPMODEL; DECIPHeR; GLUE analysis
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MDPI and ACS Style

Fadhliani; Zulkafli, Z.; Yusuf, B.; Nurhidayu, S. 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 2021, 13, 317. https://doi.org/10.3390/w13030317

AMA Style

Fadhliani, Zulkafli Z, Yusuf B, Nurhidayu S. 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. 2021; 13(3):317. https://doi.org/10.3390/w13030317

Chicago/Turabian Style

Fadhliani, Zed Zulkafli, Badronnisa Yusuf, and 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, no. 3: 317. https://doi.org/10.3390/w13030317

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