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Comparison of River Daily Runoff Simulation Results using Time Series and IHACRES Rainfall-runoff Model

Rahsepar Tolouei, Talaye | 2013

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 44708 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Shamsaei, Abolfazl
  7. Abstract:
  8. Hydrologic models are the best tools to reduce hydrological uncertainties in rivers runoff estimation. Considering structure of model and calibration of parameters, there are several approaches to extend. In this study, we try to simulate daily river runoff by using two different approaches and then compare the results of them with each other. In first approach, IHACRES model is used to simulate rainfall- runoff, which is a conceptual model based on rainfall, runoff and evapotranspiration or temperature data. This model uses conceptual part to estimate effective rainfall and also it uses a transformation function to transform effective rainfall to output flow. This model works in daily time step and calculate surface runoff and base flow. One of the most famous methods of predicting daily river runoff is time series model. In second approach of this study, Box- Jenkins model is used to predict daily runoff by time series modeling. Since the data are daily and have seasonal pattern, mean and standard deviation factors of 13-year daily discharge data with 365-day period, will be estimated by utilization of furrier series. By using these factors, observed daily discharge data will be standardized and seasonal trend will be omitted. Then autoregressive integrated moving average model (ARIMA) will be fitted on standardized data, and the best model will be chosen by using Akaike information criterion (AIC) and considering minimum number of parameters; thus the prediction of daily runoff will be performed
  9. Keywords:
  10. Simulation ; Box-Jenkins Time Series ; Autoregressive Integrated Moving Average (ARIMA) ; IHACRES Model ; Correlation Coefficient ; Nash-Sutcliffe Efficiency

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