River flow forecasting would normally bring benefits to water resource management and
planning, as well as flood damage mitigation with regards to infrastructure failure, residential
disturbance, environmental destruction, water resources and livelihood interruption caused by
floods. The objective of this paper is to examine the potential of using gene expression
programming (GEP) in developing reliable river flow forecasting models. GEP is an
evolutionary modeling approach, which has a flexible structure for developing powerful nonlinear
input-output relationships. In the present study, GEP is used to develop a river flow
forecasting model for Chaiyaphum catchment using rainfall measurements and the most
recent observed river flows as inputs to the model. The results of the study show GEP can be
used a powerful tool for developing river flow forecasting model.
Key words: River Flow Forecasting, rainfall-runoff modeling,
River flow forecasting would normally bring benefits to water resource management andplanning, as well as flood damage mitigation with regards to infrastructure failure, residentialdisturbance, environmental destruction, water resources and livelihood interruption caused byfloods. The objective of this paper is to examine the potential of using gene expressionprogramming (GEP) in developing reliable river flow forecasting models. GEP is anevolutionary modeling approach, which has a flexible structure for developing powerful nonlinearinput-output relationships. In the present study, GEP is used to develop a river flowforecasting model for Chaiyaphum catchment using rainfall measurements and the mostrecent observed river flows as inputs to the model. The results of the study show GEP can beused a powerful tool for developing river flow forecasting model.Key words: River Flow Forecasting, rainfall-runoff modeling,
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