Browsing by Author "Hassan, Zulkarnain"

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    Streamflow optimization using statistical downscaling and analytical probabilistic models under
    (Universiti Teknologi Malaysia, 2016) Hassan, Zulkarnain
    The global climate change phenomenon has significant effects on the water resources management and river-reservoir system. A reliable projected future streamflow that would enter a river-reservoir system as inflow is essential for planning a sustainable water development project. The current and future climate change scenarios were studied and the impact of climate change on frequency distribution of flow was assessed using the Analytical Probabilistic Model (APM) and the Hydrologic Engineering Center-Hydrologic Modeling System (Hec-HMS). The APM as a rainfall-runoff model incorporated with the climate response were investigated. The General Circulation Models (GCMs) were applied to project the current and future rainfall. Further, the GCMs output was downscaled into temporal scale by using the Statistical DownScaling Model (SDSM). The Bartlett-Lewis Rectangular Pulses (BLRP) was employed to disaggregate the rainfall. The Nelder- Mead Simplex (NMS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO) were tested for efficiency in optimization. A hybrid optimization method known as Artificial Bee Colony Simplex (ABCS) was introduced to investigate on the efficiency and robustness. This framework of methods had been deployed in the two selected rural catchments namely Kurau and the Tasoh located in the northern of Peninsular Malaysia. The future rainfall duration in the Kurau River catchment had been projected by the SDSM and the BLRP models appeared to increase up to 1.29 hours. The magnitude of future rainfall duration for Tasoh River catchment had been shortened by 3.18 hours, as compared to the current rainfall duration. As a result, the future rainfall amount showed an increase for both catchments with up to 22 mm, as compared to the observed rainfall duration. The APM model illustrated higher reliability and resilience compared to the Hec-HMS model, with the ability to perform similarly during the model development. The model also was able to reasonably adapt with the response of the climate scenarios. The result confirmed that the APM model projected a significant increase up to 5.78 times of future peak flow at 100-year return period for both Kurau and Tasoh catchments. A hybrid optimization, namely ABCS was developed to optimize the BLRP parameters apparently to be more robust and efficient during the calibration and the validation performances. The proposed flow optimization using statistical downscaling and analytical probabilistic approach were successfully tested in the framework of climate change and could be implemented for sustainable water development