Andere Kunden interessierten sich auch für
![Perspectives on Environmental Management and Technology in Asian River Basins]( "Perspectives on Environmental Management and Technology in Asian River Basins")
Perspectives on Environmental Management and Technology in Asian River Basins41,99 €![Environmentally Devastated Areas in River Basins in Eastern Europe]( "Environmentally Devastated Areas in River Basins in Eastern Europe")
Environmentally Devastated Areas in River Basins in Eastern Europe39,99 €![Prediction of failure rate by artificial neural networks]( "Prediction of failure rate by artificial neural networks")
Prediction of failure rate by artificial neural networks51,99 €![Concrete and Masonry Movements]( "Concrete and Masonry Movements")
Concrete and Masonry Movements158,99 €![Spatio-Temporal Drought Characterization and Forecasting Using Indices and Artificial Neural Networks. A Case of the Upper Tana River Basin, Kenya]( "Spatio-Temporal Drought Characterization and Forecasting Using Indices and Artificial Neural Networks. A Case of the Upper Tana River Basin, Kenya")
Spatio-Temporal Drought Characterization and Forecasting Using Indices and Artificial Neural Networks. A Case of the Upper Tana River Basin, Kenya52,95 €![Hydrologic Modeling of Gauged and Ungauged Catchments]( "Hydrologic Modeling of Gauged and Ungauged Catchments")
Hydrologic Modeling of Gauged and Ungauged Catchments46,99 €![Parameterization of Hydrological model in ungauged catchments]( "Parameterization of Hydrological model in ungauged catchments")
Parameterization of Hydrological model in ungauged catchments33,99 €
The majority of the world's river basins remainungauged and, therefore, empirical techniques forpredicting floods and droughts cannot be applied. Analternative approach is to develop continuoussimulation models whose parameters pertain tophysical or hydrological properties of the riverbasins. However, difficulties related to scale,heterogeneity and complexity of real river basinshave made a priori estimation of such parametersimpossible: their estimation has always requiredcalibration using river flow data. Therefore,estimating hydrological model parameters in ungaugedriver basins is one of the greatest challengescurrently facing hydrologists. In this work, a novelmethod for classifying river basins according totheir physical properties is proposed. The studyfocuses on the surface flow component, applying themethodology to identify the best classifiers forsurface flow through river networks. This requiredsimulating river flow through a large number ofScottish river basins, developing a flow routingmodelling system that extracts river network detailfrom digital databases and numerically solves adistributed flow routing model.