Title: Assessment of rainfall-runoff time series data using transfer function modelling with exogenous variable

Authors: Homa Jalaeian Taghadomi; Xixi Wang; Mujde Erten-Unal; Turaj Vazifedan

Addresses: Department of Civil and Environmental Engineering, Old Dominion University, Norfolk, VA, USA ' Department of Civil and Environmental Engineering, Old Dominion University, Norfolk, VA, USA ' Department of Civil and Environmental Engineering, Old Dominion University, Norfolk, VA, USA ' Division of Biostatistics and Innovation in Research, Department of Paediatrics, Eastern Virginia Medial School, Norfolk, VA, USA

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.

Keywords: rainfall; runoff; temperature; transfer function model; exogenous variable; ARIMAX; seasonal; Dickey-Fuller; KPSS; Ljung-Box; Blackwater River.

DOI: 10.1504/IJHST.2022.123640

International Journal of Hydrology Science and Technology, 2022 Vol.14 No.1, pp.47 - 62

Received: 30 Aug 2019
Accepted: 18 Sep 2020
Published online: 30 Jun 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article