OPTIMIZATION MODEL OF CIRATA RESERVOIR MANAGEMENT USING THE DISCRETE MARKOV, CONTINUOUS, AND ARIMA DISCHARGE FORECAST METHODS

The optimal management of the Citarum Cascade Reservoir has not yet been achieved even though there are guidelines for the management operation plan, which is indicated by the lack of water availability for the necessity of raw water and electricity operational. Optimal management of cascade reservo...

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Bibliographic Details
Main Author: Septiani Yogo Sri Waluyo, Dhita
Format: Theses
Language:Indonesia
Subjects:
Online Access:https://digilib.itb.ac.id/gdl/view/66195
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:The optimal management of the Citarum Cascade Reservoir has not yet been achieved even though there are guidelines for the management operation plan, which is indicated by the lack of water availability for the necessity of raw water and electricity operational. Optimal management of cascade reservoirs in an integrated manner is difficult due to complex operating procedures and high uncertainty of hydrological components. For this reason, it is necessary to conduct research on the optimal management of each reservoir by considering the discharge forecast model as input discharge (Qin). This research has the objective for optimizing the operational management of the Cirata Reservoir, so that all raw water needs are met without any water being wasted through the spillway. In addition, it is included how the analysis of regional rainfall, as well as conversion in land use in the Central Citarum Watershed. The discharge forecasting models used are continuous, discrete markov, and ARIMA models. Based on the results of the study, the annual rainfall in the Central Citarum Watershed is 2.194 mm/year, while the results of land use analysis indicate that there is a decrement of the runoff coefficient in the Central Citarum Watershed from 2011 to 2020. The mainstay of raw water allocation for downstream is 114.45 m3/s, with 87.98 m3/s for DMI needs and 26.47 m3/s for irrigation needs. The correlation coefficient between the inflow discharge of the Cirata Reservoir and the model discharge is 0.55 (Discrete Markov Class 3); 0.74 (Discrete Markov Class 5); 0.90 (Continuous QQPP); 0.87 (Continuous QPPP); and 0.68 (ARIMA (1,0,0)(1,0,1) and ARIMA (0,0,2)(1,0,1)). Optimization simulations were carried out for 24 scenarios with a combination of six discharge models and four guideline trajectory, in which the scenario using the QQPP continuous discharge model and the R5 continuous guideline trajectory was the best for optimal management of the Cirata Reservoir resulting a correlation coefficient between discharge of 0.90 and 0.86 for actual reservoir trajectory and guideline trajectory.