Assessment of rainfall-runoff time series data using transfer function modelling with exogenous variable
by Homa Jalaeian Taghadomi; Xixi Wang; Mujde Erten-Unal; Turaj Vazifedan
International Journal of Hydrology Science and Technology (IJHST), Vol. 14, No. 1, 2022

Abstract: This study assesses the rainfall-runoff time series data using a transform function approach. Modelling rainfall-runoff data is crucial in the hydrology and water resource management. However, the characteristics of serial and cross-correlation between runoff and rainfall sequences have not been discussed widely in the literature. This study evaluates the performance of the transfer function method in modelling monthly rainfall-runoff data in the Blackwater River watershed located in coastal Virginia. Maximum likelihood estimation was employed for estimating the model's parameters. Different performance evaluation criteria (AIC, AICC, BIC, RMSE and MASE) were employed for model selection. The adequacy of the final transfer function model was evaluated by Dickey-Fuller, KPSS, Ljung-Box. Moreover, the performance of the final model was compared with the simplest time series models to justify the complexity of the model. This study is the first achievement of the hydrological response to precipitation and temperature over the Blackwater River watershed.

Online publication date: Thu, 30-Jun-2022

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