Multi-objective calibration and uncertainty analysis for the event-based modelling of flash floods

Muhammad Nabeel Usman, Jorge Leandro, Karl Broich, Markus Disse

Research output: Contribution to journalArticlepeer-review


This study investigates the best approach to calibrate an event-based conceptual Hydrologiska Byråns Vattenbalansavdelning (HBV) model, comparing different trials of single-objective, single-event multi-objective (SEMO), and multi-event-multi-objective (MEMO) model calibrations using root mean squared error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE), and Bias as objective functions. Model performance was validated for several peak events via 90% confidence interval (CI)-based output uncertainty quantification of relative error of discharges. Multi-objective optimization yielded more accurate and robust solutions compared to single-objective calibrations. Ensembles of Pareto solutions from the multi-objective calibrations better characterized the flood peaks within the uncertainty intervals. MEMO calibration exhibited lower uncertainties and better prediction of peak events versus SEMO calibration. Moreover, the MEMO_6D (six-dimensional) approach outperformed the SEMO_3D and MEMO_3D in capturing the larger peak events. This study suggests that the MEMO_6D is the best approach for predicting large flood events with lower model output uncertainties when the calibration is performed with a better combination of peak events.

Original languageEnglish
Pages (from-to)456-473
Number of pages18
JournalHydrological Sciences Journal
Issue number4
StatePublished - 2024


  • flash flood
  • HBV
  • hydrological peak events
  • multi-event multi-objective model calibration
  • uncertainty intervals


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