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RATIONALIZATION OF DISCHARGE DATA FLUCTUATIONS USING MINIMUM RESIDUALS MODEL OF MOVING AVERAGE METHODS IN CITARUM CASCADE RESERVOIRS
Muda Nasution E.I.a, Sabar A.a, Siti Salami I.R.a, Marganingrum D.b
a Doctoral Student, Faculty of Civil and Environmental Engineering, Institut Teknologi Bandung, Indonesia
b Geotechnology Research Center, Indonesian Institute of Sciences, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020. All rights reserved.Since 1981, a cascade of dams consisting of the Saguling, Cirata, and Jatiluhur reservoirs has been constructed along the Citarum River in order to fulfill demands for flood control, water supply, and electrical power generation, and this requires the implementation of an appropriate hydrological approach. The efficient operation of a water resource system requires an accurate water flow analysis that approximates the actual fact as closely as possible to minimize risks in decision-making. Discharge is a random and stochastic component in hydrology, influenced by rainfall variations with a maximum in the tropical wet season and a minimum in the dry season. Thus, discharge analysis requires a statistical approach especially minimum residuals. Values for average annual inflows has constructed through four different calculation techniques for the moving average method to rationalize the fluctuations in discharge data Citarum cascade reservoirs by reducing randomness in the data, with the eventual aim of obtaining more rational trend lines. An analysis of minimum residuals between the results of the calculation and those of model regressions has demonstrated that the cumulative moving average calculation technique provides the best fit among all the models with the smallest residual value, as shown in its lowest mean squared error values of 0.83, 2.04, and 1.77 for the three reservoirs.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Citarum cascade reservoirs,Discharge fluctuation,Minimum residual,Moving average[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.21660/2020.75.26880[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]