Hydrological modelling of temporally-varying catchments: facets of change and the value of information |
| |
Authors: | A Efstratiadis I Nalbantis D Koutsoyiannis |
| |
Institution: | 1. School of Civil and Environmental Engineering, National Technical University of Athens, Zographou, Greeceandreas@itia.ntua.gr;3. School of Rural and Surveying Engineering, National Technical University of Athens, Zographou, Greece;4. School of Civil and Environmental Engineering, National Technical University of Athens, Zographou, Greece |
| |
Abstract: | AbstractRiver basins are by definition temporally-varying systems: changes are apparent at every temporal scale, in terms of changing meteorological inputs and catchment characteristics due to inherently uncertain natural processes and anthropogenic interventions. In an operational context, the ultimate goal of hydrological modelling is predicting responses of the basin under conditions that are similar or different to those observed in the past. Since water management studies require that anthropogenic effects are considered known and a long hypothetical period is simulated, the combined use of stochastic models, for generating the inputs, and deterministic models that also represent the human interventions in modified basins, is found to be a powerful approach for providing realistic and statistically consistent simulations (in terms of product moments and correlations, at multiple time scales, and long-term persistence). The proposed framework is investigated on the Ferson Creek basin (USA) that exhibits significantly growing urbanization during the last 30 years. Alternative deterministic modelling options include a lumped water balance model with one time-varying parameter and a semi-distributed scheme based on the concept of hydrological response units. Model inputs and errors are respectively represented through linear and nonlinear stochastic models. The resulting nonlinear stochastic framework maximizes the exploitation of the existing information by taking advantage of the calibration protocol used in this issue. |
| |
Keywords: | modified basins hydroclimatic variability model and parameter uncertainty statistical consistency Hurst-Kolmogorov dynamics hydrological response units error model stochastic simulation hybrid calibration nonlinear stochastic modelling |
|
|