Performance of conceptual and black-box models in flood warning systems
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 we...
Main Author: | Mohammad Ebrahim Banihabib |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2016-12-01
|
Series: | Cogent Engineering |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/23311916.2015.1127798 |
Similar Items
-
Evaluation of a weather forecasting model and HEC-HMS for flood forecasting: case study of Talesh catchment
by: Mohammad Reza Goodarzi, et al.
Published: (2024-01-01) -
Application of Machine Learning and Process-Based Models for Rainfall-Runoff Simulation in DuPage River Basin, Illinois
by: Amrit Bhusal, et al.
Published: (2022-06-01) -
MIDAS: A New Integrated Flood Early Warning System for the Miño River
by: Diego Fernández-Nóvoa, et al.
Published: (2020-08-01) -
Simulation of hydrograph of flood with hydrological model HEC-HMS and prediction of return period in Kermanshah Ravansar Basin
by: zahra rahimzadeh, et al.
Published: (2018-12-01) -
Integration of Satellite Precipitation Data and Deep Learning for Improving Flash Flood Simulation in a Poor-Gauged Mountainous Catchment
by: Xuan Tang, et al.
Published: (2021-12-01)