Performance of conceptual and black-box models in flood warning systems. Issue 1 (31st December 2016)

• Record Type: Journal Article
• Authors: Banihabib, Mohammad Ebrahim
• Editors: Revelli, Roberto
• Is Part Of: Cogent engineering. Volume 3:Issue 1(2016)
• Publication Date: 2016-12-31
• Subjects: flash floods -- ANN -- HEC-HMS -- flood forecasting -- flood warning system -- lead-time -- black-box -- conceptual rainfall–runoff; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2015.1127798
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: Flood forecasting is a core of flood forecasting and flood warning system which can be implemented by both conceptual rainfall–runoff (CRR) model and black-box rainfall–runoff (BBRR) model. Dynamic artificial neural network (DANN) as an innovative BBRR model and HEC-HMS as a traditional CRR model were used for flood forecasting. The aim of this paper is to compare the efficiency of HEC-HMS and DANN for the determination of flood warning lead-time (FWLT) in a steep urbanized watershed. A framework is proposed to compare the performance of the models based on four criteria: type and quantity of required input data by each model, flood simulation performance, FWLT and expected lead-time (ELT). Finally, the results show that FWLT and ELT were estimated longer by DANN than by HEC-HMS model. In brief, because of less required data by BBRR model and its longer ELT, future research should be focused on better verification of it.