Flood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model

2021 ◽  
Author(s):  
Gaurav Talukdar ◽  
Janaki Ballav Swain ◽  
Kanhu Charan Patra
Keyword(s):  
River Basin ◽  
Hazard Assessment ◽  
Hydraulic Model ◽  
Flood Inundation ◽  
Inundation Mapping ◽  
Flood Inundation Mapping

scholarly journals Machine-learning and HEC-RAS integrated models for flood inundation mapping in Baro River Basin, Ethiopia

2021 ◽  
Author(s):  
Habtamu Tamiru ◽  
Meseret Wagari
Keyword(s):  
Machine Learning ◽  
River Basin ◽  
Water Body ◽  
Hydrological Model ◽  
Daily Rainfall ◽  
Landsat 8 ◽  
Flood Inundation ◽  
Inundation Mapping ◽  
Flood Inundation Mapping ◽  
Daily Discharge

AbstractThis study presents an integrated machine-learning and HEC-RAS models for flood inundation mapping in Baro River Basin, Ethiopia. ANN and HEC-RAS models were integrated as a predictive hydrological and hydraulic model to generate runoff and the extent of flood, respectively. Daily rainfall and temperature data of 7-years (1999–2005), daily discharge (1999–2005) and 30 m × 30 m gridded Topographical Wetness Index (TWI) were used to train a predictive ANN hydrological model in RStudio. The predictive performance of the developed ANN hydrological model was evaluated in RStudio using Nash–Sutcliffe Efficiency (NSE) values of 0.86 and 0.88 during the training period (1999–2005) and testing period (2006–2008), respectively, with the corresponding observed daily discharge. The validated ANN predictive hydrological model was linked with HEC-RAS to generate the flood extent along the river course. The HEC-RAS model result was calibrated and validated using the water body delineated using Normal Difference Water Index (NDWI) from LANDSAT 8 imagery based on historical flood events of 2005 and 2008. It was found that about 96% of an agreement was made between the flood-prone areas generated in HEC-RAS and the water body delineated using NDWI. Therefore, it is logical to conclude that the integration of a machine-learning approach with the HEC-RAS model has improved the spatiotemporal uncertainties in traditional flood forecasting methods. This integrated model is powerful tool for flood inundation mapping to warn residents of this basin.

scholarly journals Machine learning and HEC-RAS integrated models for flood inundation mapping in Baro River Basin, Ethiopia

2021 ◽  
Author(s):  
Habtamu Tamiru
Keyword(s):  
Machine Learning ◽  
River Basin ◽  
Daily Rainfall ◽  
Simulation Models ◽  
Spatial And Temporal Variability ◽  
Flood Inundation ◽  
Rainfall Runoff ◽  
Ann Model ◽  
Inundation Mapping ◽  
Flood Inundation Mapping

This paper presents the integrated machine learning and HEC-RAS models for flood inundation mapping in Baro River Basin, Ethiopia. A predictive rainfall-runoff and spatially distributed river simulation models were developed using Artificial Neural Networks (ANNs) and HEC-RAS respectively. Daily rainfall and temperature data of 7-yrs and Topographical Wetness Index (TWI) with a spatial resolution of 50 x 50m were used to train the ANN in R studio. The integration of the spatial and temporal variability in this paper improved the accuracy of the predictive models integrated with ANN and HEC-RAS. The predictive ANN model was tested with the observed daily discharge of the same temporal resolution and the rainfall-runoff result obtained from the tested ANN model was used as input for the HEC-RAS. The flood event of 2005 was used to verify the accuracy of flood generated in the HEC-RAS model by implementing the Normal Difference Water Index (NDWI). The comparison was made between the flood inundation map generated by HEC-RAS and flood events of different periods based on coverage percentage areas and a good agreement was reached with 96 % overlapped areas. The performance of ANN and HEC-RAS models were evaluated with 0.86 and 0.88 values at the training and testing period respectively. Finally, it was concluded that the integration of a machine learning approach with the HEC-RAS model in developing a flood inundation mapping is an appropriate tool to warn residents in this river basin.

scholarly journals Flood Inundation Mapping along the Lower Reach of Kelani River Basin under the Impact of Climatic Change

2012 ◽  
Vol 45 (2) ◽  
pp. 23 ◽  
Author(s):  
M. M. G. T. De Silva ◽  
S. B. Weerakoon ◽  
Srikantha Herath ◽  
U. R. Ratnayake ◽  
Sarith Mahanama
Keyword(s):  
Climatic Change ◽  
River Basin ◽  
Flood Inundation ◽  
Lower Reach ◽  
Inundation Mapping ◽  
Flood Inundation Mapping ◽  
Kelani River ◽  
The Impact
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