نوع مقاله : مقاله پژوهشی
نویسندگان
گروه علوم و فناوریهای محیطی، دانشکده مهندسی انرژی و منابع پایدار، دانشگاه تهران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
In the arid and semi-arid climatic conditions of Iran, optimal water resource management is of paramount importance. Accurate prediction of river flow discharge serves as an effective strategy in this regard, playing a key role in dam operation planning. This study aimed to simulate flow discharge downstream of the Maijaran Dam in Mazandaran Province, using monthly discharge data from the Maijaran Dam hydrometric station spanning the period 2007 to 2022. Following preliminary analyses—including normality and stationarity tests—and decomposition of the data into deterministic and stochastic components, the stochastic part of the time series was selected for modeling. Various time series model structures were evaluated using the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF). Among the candidate models, the ARMA model was identified as the most suitable. Model orders were determined using ACF and PACF analyses, and model performance was assessed using the Akaike Information Criterion (AIC) and the coefficient of determination (R²). Results indicated that the ARMA(3,2) model, with an AIC value of 144.06 and R² of 0.79, outperformed other models and provided acceptable accuracy in flow discharge simulation. The findings demonstrate the high efficacy of stochastic ARMA models in simulation of hydrological time series in data-scarce regions, offering a reliable tool for supporting water resource management decisions.
کلیدواژهها [English]
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