Integrating IHACRES with a data-driven model to investigate the possibility of improving monthly flow estimates Parisa Fattahi, Afshin Ashrafzadeh * , Nader Pirmoradian and Majid Vazifedoust Department of Water Engineering, Faculty of Agricultural Sciences, University of Guilan, 41996-13776, Khalij-e-Fars Blvd., Rasht, Iran *Corresponding author. E-mail: ashrafzadeh@guilan.ac.ir AA, 0000-0002-9417-6431; NP, 0000-0002-2311-5703; MV, 0000-0002-0962-2813 ABSTRACT Estimating the outflow of basins is a critical step in surface water resources planning and management, especially in basins that lack reliable long-term observed data of streamflow. Hydrological models, which can simulate the process of rainfall-runoff, can be used to obtain reliable estimates of streamflow from precipitation data and the physical characteristics of basins. The focus of the present study was to estimate the outflow of 19 sub-basins located in Guilan Province, northern Iran. To achieve this, hybrid models were developed by integrating the IHACRES (identification of unit hydrograph and component flows from rainfall, evapotranspiration, and streamflow) hydrological model with the intel- ligent-based GMDH (group method of data handling) model. The IHACRES model was calibrated using monthly ground-based precipitation and temperature data as well as satellite-based precipitation data. The lowest and highest Nash-Sutcliffe coefficient (NS) for the IHACRES models were, respectively, 0.14 and 0.68 in the calibration phase and 0.11 and 0.73 in the validation phase. It was also observed that using satellite-based precipitation data reduces NS by 10–75% in the 19 sub-basins under study. After calibrating and validating the IHACRES models, the hybrid models were developed by integrating IHACRES and GMDH models. The lowest and highest NS for the hybrid models were, respectively, 0.23 and 0.81 in the calibration phase and 0.11 and 0.81 in the validation phase. It was observed that, on average, inte- grating IHACRES and GMDH increases the NS by 44.1% in the calibration phase and 37.0% in the validation phase in comparison with the IHACRES model. According to the NS, the hybrid model had ‘acceptable’ performance in six sub-basins in which the IHCRES model had ‘unac- ceptable’ performance. It was observed that integrating the IHACRES model with a data-driven model (the GMDH model) can generally improve the simulation results in all sub-basins under study. Key words: conceptual model, hybrid model, satellite precipitation data HIGHLIGHTS • The IHACRES model was calibrated in 19 sub-basins located in Northern Iran. • The GMDH model was used to improve the performance of the IHACRES model. • Hybrid conceptual data-based models were developed by integrating IHACRES and GMDH. 1. INTRODUCTION Accurately measured data and reliable estimates of basin yield are one of the most critical tools in water resources manage- ment. However, many basins in Iran lack suitable long-term data on runoff due to various limitations (Salehpoor Laghani et al. 2018). Rainfall-runoff models have always attracted the interest of hydrologists because they are a tool that can be used to simulate basin behavior in response to precipitation to obtain reliable estimates of basin output. In recent decades, various models with different perspectives in simulating the rainfall-runoff process have been developed. IHACRES (identification of unit hydrograph and component flows from rainfall, evapotranspiration, and streamflow) is one of the rainfall-runoff conceptual models developed to minimize the need for input data. It comprises two in series mod- ules: the non-linear loss module and the linear unit hydrograph module. The model inputs (precipitation and temperature) are first converted into effective precipitation by the nonlinear module, and then the linear module produces the runoff flowing out of the basin. Many studies have been carried out worldwide using this model and have reported its acceptable perform- ance. Goodarzi et al. (2013) studied the performance of the soil and water assessment tool (SWAT), simple hydrology This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/). © 2021 The Authors Water Supply Vol 00 No 0, 1 doi: 10.2166/ws.2021.267 Corrected Proof Downloaded from http://iwaponline.com/ws/article-pdf/doi/10.2166/ws.2021.267/931160/ws2021267.pdf by guest on 07 September 2021