Flowrate Forecasting and Ecohydrodynamic Insights from the Eşen Stream (Southwestern Türkiye): Time Series Perspectives
: Accurate flowrate forecasting is vital for sustainable water management, supporting flood control, drought mitigation, hydropower optimization, and agricultural planning. This study analyzes daily discharge data from the E ş en Stream in southwestern Türkiye for 2017 to 2022, provided by the General Directorate of State Hydraulic Works. Three statistical approaches were applied: Autoregressive Integrated Moving Average, Trigonometric Box-Cox ARMA Trend Seasonal, and Multiple Linear Regression with lagged predictors. A Box-Cox transformation was used to stabilize variance, and model performance was evaluated with Akaike Information Criterion, Bayesian Information Criterion, Root Mean Square Error, and the coefficient of determination. Results showed that Autoregressive Integrated Moving Average captured short term dependencies, Trigonometric Box-Cox ARMA Trend Seasonal achieved the highest predictive accuracy with strong seasonal patterns, and Multiple Linear Regression offered a simple framework for operational forecasts. All models indicated a declining discharge trend toward 2030. The findings demonstrate the value of complementary approaches for practical water management and contribute to understanding ecohydrodynamic processes at the freshwater-marine interface.