Browsing by Author "Bárdossy, András ( Prof. Dr. rer. nat. Dr.-Ing. habil. )"

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Open Access
Robust parameter estimation in gauged and ungauged basins
(2010) Singh, Shailesh Kumar; Bárdossy, András ( Prof. Dr. rer. nat. Dr.-Ing. habil. )
Hydrological modeling has become a widely accepted theoretical tool for water resources engineering and management. Rainfall-runoff models are used both for short and medium time management (for example flood forecasting) and long-time design purposes. However, the application of hydrological models is limited due to several reasons. One important limitation is imposed by the availability of data and parameter estimation. Discharges are only measured at a few selected river cross sections, leading to a small number of catchments for which the runoff calculated from the models might be verified. Further, the high spatial and temporal variability of the meteorological input (such as precipitation, temperature or wind) cannot fully be captured by the usually small number of meteorological stations. Radar measurement of precipitation can provide more detailed space time information on precipitation but unfortunately the reliability of the data is at present still low. Other influencing factors such as soil properties also vary considerably in space and even to some extent in time (for example macropores in soils). These problems among others make models which are based on physical principles only infeasible for many practical applications. Models which to some extent use analogous concepts can partly smoothen out the effects of variability and thus can often be successfully used for practical purposes. The limitation of these models lies in the fact that some of their parameters are not directly related to physically measurable quantities. Therefore those have to be estimated from observations using calibration techniques. This research work was aimed at developing an efficient, practical and robust methodology for parameter estimation (calibration) for a reliable hydrological modeling at gauged and ungauged basin. The main focus of this research was to bring more insight into the process of parameter estimation techniques in hydrological modeling. The other objective of this research work was to develop a methodology that enables regional estimation of parameters of a conceptual continuous water balance model based on physical catchment descriptor, which includes the land use, soil type, stream network, elongation and topographic attributes of the catchment. It aims at improving the weakness inherent in the traditional two-step regionalization approach in estimating the relationship between the model parameters and the physical catchment descriptor. The specific objectives of the research were to answer some basic question as listed below: - How can we estimate hydrologically reliable parameters for modeling? - How do different objective functions map parameter space during calibration? - Can we calibrate a hydrological model using carefully selected critical events? - Can we improve prediction and model diagnosis by including dynamic variability in parameters? - How can we extend hydrologically reliable parameters from gauged to ungauged basins? In this research, several algorithms, for example, ROPE, SRWP, HOP, ICE, RDPE and SAV algorithm were developed to answer the basic questions mentioned above. These algorithms were very useful for the robust and reliable hydrological modeling in gauged and ungauged basins.