ERM model analysis for adaptation to hydrological model errors

M. Baymani-Nezhad*, D. Han

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

313 Downloads (Pure)


Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.

Original languageEnglish
Pages (from-to)741–753
Number of pages13
JournalActa Geophysica
Issue number4
Early online date17 May 2018
Publication statusPublished - Aug 2018


  • Concentration time
  • Forecasting errors
  • Real-time model updating
  • Time to peak


Dive into the research topics of 'ERM model analysis for adaptation to hydrological model errors'. Together they form a unique fingerprint.

Cite this