Hydrological modelling of large river catchments has become a challenging task for water resources engineers due to its complexity in collecting and handling of both spatial and non-spatial data such as rainfall,gauge...Hydrological modelling of large river catchments has become a challenging task for water resources engineers due to its complexity in collecting and handling of both spatial and non-spatial data such as rainfall,gauge-discharge data,and topographic and hydraulic parameters.In this article,a flood forecast model is developed for the Godavari Basin,India through a distributed modelling approach using space inputs.The approach includes rainfall runoff modelling,hydrodynamic flow routing,calibration,and validation of the model with field discharge data.The study basin is divided into 128 subbasins to improve the model accuracy.Topographic and hydraulic parameters of each subbasin and channel are computed using the land use/land cover grid that is derived from the Indian Remote Sensing Satellite(IRS–P6) AWi FS sensor data(56 m resolution),Shuttled Radar Topographic Mission(SRTM) Digital Elevation Model(DEM),and the soil textural grid.The model is calibrated using the field hydrometeorological data of 2000 and validated with the data of 2001.The model was tested during the 2010 floods with real-time 3-hour interval hydrometeorological and daily evapotranspiration data.Accuracy in estimating the peak flood discharge and lag time was found to be very good.Flood forecast lead time is increased by 12 hours compared to conventional methods of forecasting.展开更多
文摘Hydrological modelling of large river catchments has become a challenging task for water resources engineers due to its complexity in collecting and handling of both spatial and non-spatial data such as rainfall,gauge-discharge data,and topographic and hydraulic parameters.In this article,a flood forecast model is developed for the Godavari Basin,India through a distributed modelling approach using space inputs.The approach includes rainfall runoff modelling,hydrodynamic flow routing,calibration,and validation of the model with field discharge data.The study basin is divided into 128 subbasins to improve the model accuracy.Topographic and hydraulic parameters of each subbasin and channel are computed using the land use/land cover grid that is derived from the Indian Remote Sensing Satellite(IRS–P6) AWi FS sensor data(56 m resolution),Shuttled Radar Topographic Mission(SRTM) Digital Elevation Model(DEM),and the soil textural grid.The model is calibrated using the field hydrometeorological data of 2000 and validated with the data of 2001.The model was tested during the 2010 floods with real-time 3-hour interval hydrometeorological and daily evapotranspiration data.Accuracy in estimating the peak flood discharge and lag time was found to be very good.Flood forecast lead time is increased by 12 hours compared to conventional methods of forecasting.
