Channel roughness is considered as the most sensitive parameter in development of hydraulic models for flood forecasting and flood inundation mapping. Hence, it is essential to calibrate the channel roughness coeffici...Channel roughness is considered as the most sensitive parameter in development of hydraulic models for flood forecasting and flood inundation mapping. Hence, it is essential to calibrate the channel roughness coefficient (Mannnig’s “n” value) for various river reaches through simulation of floods. In the present study it is attempted to calibrate and validate Mannnig’s “n” value using HEC-RAS for Mahanadi Riverin Odisha (India). For calibration of Mannnig’s “n” value, the floods for the years 2001 and 2003 have been considered. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year2006 inthe same river reach. The performance of the calibrated and validated HEC-RAS based model has been tested using Nash and Sutcliffe efficiency. It is concluded from the simulation study that optimum Mannnig’s “n” value that can be used effectively for Khairmal to Barmul reach of Mahanadi Riveris 0.029. It is also verified that the peak flood discharge and time to reach peak value computed using Mannnig’s “n” of 0.029 showed only an error of 5.42% as compared with the observed flood data of year 2006.展开更多
Given the challenges of re-creating complex bed load(BL)transport processes in rivers,models are preferred over gathering and examining field data.The highlight of the present research is to develop an approach to det...Given the challenges of re-creating complex bed load(BL)transport processes in rivers,models are preferred over gathering and examining field data.The highlight of the present research is to develop an approach to determine the ungauged bed load concentration(BLC_(u))utilizing the measured suspended sediment concentration(SSC)and hydraulic variables of the last four decades for the Mahanadi River Basin.This technique employs shear stress and SSC equations for turbulent open channel flow.Besides,the predicted BLC_(u)is correlated with SSC using a power relation to estimate BLC_(u)on the river and tributaries.Eventually,different BL functions(BLF)efficiency is assessed across stations.The model predicted BLC_(u)is comparable with the published data for sandy rivers and falls within±20%.Outliers in hydraulic and sedimentological statistics significantly influence estimating the BL fraction apart from higher relative ratios and catchment geology.The constants of power functions are physically linked to sediment transport configuration,mechanism,and inflow to the stream.The stream power-based BLF best predicts the BL transport,followed by shear stress and unit discharge approaches.The disparity in the estimation of BLC_(u)results from station-specific physical factors,sampling data dispersion,and associated uncertainties.展开更多
文摘Channel roughness is considered as the most sensitive parameter in development of hydraulic models for flood forecasting and flood inundation mapping. Hence, it is essential to calibrate the channel roughness coefficient (Mannnig’s “n” value) for various river reaches through simulation of floods. In the present study it is attempted to calibrate and validate Mannnig’s “n” value using HEC-RAS for Mahanadi Riverin Odisha (India). For calibration of Mannnig’s “n” value, the floods for the years 2001 and 2003 have been considered. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year2006 inthe same river reach. The performance of the calibrated and validated HEC-RAS based model has been tested using Nash and Sutcliffe efficiency. It is concluded from the simulation study that optimum Mannnig’s “n” value that can be used effectively for Khairmal to Barmul reach of Mahanadi Riveris 0.029. It is also verified that the peak flood discharge and time to reach peak value computed using Mannnig’s “n” of 0.029 showed only an error of 5.42% as compared with the observed flood data of year 2006.
基金Ministry of Water Resources,Government of India,No.28/1/2016-R&D/228–245。
文摘Given the challenges of re-creating complex bed load(BL)transport processes in rivers,models are preferred over gathering and examining field data.The highlight of the present research is to develop an approach to determine the ungauged bed load concentration(BLC_(u))utilizing the measured suspended sediment concentration(SSC)and hydraulic variables of the last four decades for the Mahanadi River Basin.This technique employs shear stress and SSC equations for turbulent open channel flow.Besides,the predicted BLC_(u)is correlated with SSC using a power relation to estimate BLC_(u)on the river and tributaries.Eventually,different BL functions(BLF)efficiency is assessed across stations.The model predicted BLC_(u)is comparable with the published data for sandy rivers and falls within±20%.Outliers in hydraulic and sedimentological statistics significantly influence estimating the BL fraction apart from higher relative ratios and catchment geology.The constants of power functions are physically linked to sediment transport configuration,mechanism,and inflow to the stream.The stream power-based BLF best predicts the BL transport,followed by shear stress and unit discharge approaches.The disparity in the estimation of BLC_(u)results from station-specific physical factors,sampling data dispersion,and associated uncertainties.
