Improving the performance of rainfall-runoff models using the gene expression programming approach

Hassan Esmaeili-Gisavandani,Afshin Ashrafzadeh,Masoud Soori Damirchi Sofla,Morteza Lotfirad

doi:10.2166/wcc.2021.064

Abstract

Abstract In this study, five hydrological models, including the soil and water assessment tool (SWAT), identification of unit hydrograph and component flows from rainfall, evapotranspiration, and streamflow (IHACRES), Hydrologiska Byråns Vattenbalansavdelning (HBV), Australian water balance model (AWBM), and Soil Moisture Accounting (SMA), were used to simulate the flow of the Hablehroud River, north-central Iran. All the models were validated based on the root mean square error (RMSE), coefficient of determination (R2), Nash-Sutcliffe model efficiency coefficient (NS), and Kling-Gupta efficiency (KGE). It was found that SWAT, IHACRES, and HBV had satisfactory results in the calibration phase. However, only the SWAT model had good performance in the validation phase and outperformed the other models. It was also observed that peak flows were generally underestimated by the models. The sensitivity analysis results of the model parameters were also evaluated. A hybrid model was developed using gene expression programming (GEP). According to the error measures, the ensemble model had the best performance in both calibration (NS = 0.79) and validation (NS = 0.56). The GEP combination method can combine model outputs from less accurate individual models and produce a superior river flow estimate.

Highlights

Decision-making in water resources management, hydraulic structures, and flood control planning is of particular importance
The soil and water assessment tool (SWAT) was calibrated and validated based on monthly data
The genetic algorithm and Powell (GAP) method was used to calibrate the parameters of the Hydrologiska Byråns Vattenbalansavdelning (HBV) model (Pervin et al 2021)

Summary

Introduction

Decision-making in water resources management, hydraulic structures, and flood control planning is of particular importance. An acceptable estimate of runoff from rainfall is required. The results of rainfall-runoff models, divided into two categories of distributed and integrated, play an essential role in these decisions. The effective management of the existing water supplies is a matter of utmost concern, especially in countries where freshwater resources are limited and scarce. In many parts of Iran, rivers serve as resources or potential resources of domestic, industrial, and agricultural water. In these regions, simulating the temporal variations in the flow of rivers is an essential requisite for the effective and sustainable management of basins (Adib et al 2021a)

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Conclusion