Time Series Modeling on Daily Streamflow in a Lack-Data Catchment

Abstract

Abstract The limited time series data for daily discharge to support the development and management of water resources in a catchment is a classic challenge in hydrology. Various methods, both empirically and conceptually based, have been developed to overcome this problem. This paper presents a time series modeling of daily discharge in relation to the scarcity of discharge data in Sausu Catchment, Central Sulawesi, Indonesia. The simulation has been assigned to the HEC-HMS Model with the input of daily rainfall data for the period 2018-2020 and potential evapotranspiration data. Before this stage is executed, optimization has been performed to determine 17 optimal parameters representing three methods in three sub-models with input data pairs ranfall-discharge in November 2017. Optimal parameters have been achieved at RMSE 10.3, with 2 parameters unchanged. The simulation results indicate that the daily flow of the Sausu River based on daily rainfall data for three years varies in the range of 8 m3/s to 160 m3/s. This trend of time series data flow tends to be associated with daily rainfall data as input.