Complementary Information for Reducing Parameter Uncertainty in Distributed Rainfall-Runoff Modeling (original) (raw)
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Abstract Conceptual mathematical models are a useful tool for rainfallrunoff modelling of a basin. The calibration of such models has attracted the attention of a number of hydrologists since unique and optimal parameters are difficult to obtain. The calibration of a conceptual model is discussed through a simple conceptual model whose parameters are determined using a search technique.
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Assessment of rainfall-runoff model structures for regionalisation purposes
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The calibration process would ideally be able to define a single well-identified optimum parameter set. However, this is difficult in practice, as there are many combinations of parameter values that may give similar objective function values, as indeed may different model structures. Beven (1993) defined this problem as equifinality, arising from overparameterisation of models, data limitations and structural faults in the model. If parameters cannot be uniquely identified, then they cannot be deterministically linked to ...
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Identification of distributed precipitation–runoff models for hourly runoff simulation based on transfer of full parameters (FP) and partial parameters (PP) are lacking for boreal mid-Norway. We evaluated storage–discharge relationships based model (Kirchmod), the Basic-Grid-Model (BGM) and a simplified Hydrologiska Byråns Vattenbalansavdelning (HBV) model for multi-basins (26 catchments). A regional calibration objective function, which uses all streamflow records in the region, was used to optimize local calibration parameters for each catchment and regional parameters yielding maximum regional weighted average (MRWA) performance measures (PM). Based on regional median Nash–Sutcliffe efficiency (NSE) and NSEln (for log-transformed series) for the calibration and validation periods, the Kirchmod model performed better than the others. Parsimony of the Kirchmod model provided less parameter uncertainty for the FP case but did not guarantee parameter identifiability. Tradeoffs betwee...
Water Resources Management
Conceptual lumped rainfall-runoff models are frequently used for various environmental problems. To put them into practice, both the model calibration method and data series of the area-averaged precipitation and air temperature are needed. In the case when data from more than one measurement station are available, first the catchment-averaged meteorological data series are usually obtained by some method, and then they are used for calibration of a lumped rainfall-runoff model. However, various optimization methods could easily be applied to simultaneously calibrate both the aggregation weights attributed to various meteorological stations to obtain a lumped meteorological data series and the rainfall-runoff model parameters. This increases the problem dimensionality but allows the optimization procedure to choose the data that are most important for the rainfall-runoff process in a particular catchment, without a priori assumptions. We test the idea using two conceptual models, HB...