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Modelización hidrológica distribuida de crecidas en la región del Cévennes-Vivarais : impacto de incertidumbres ligadas a la estimación de la precipitación y a la parametrización del modelo

Abstract : It is known that having a precipitation observation system at high space - time resolution is crucial to obtain good results in rainfall - runoff modeling. Radar is a tool that offers quantitative precipitation estimates with very good resolution. When it is merged with a rain gauge network the advantages of both systems are achieved. However, radars estimates have different uncertainties than those obtained with the rain gauge. In the modeling process, uncertainty of precipitation interacts with uncertainty of the hydrological model. The objective of this work is: To study methods used to quantify the uncertainty in radar – raingauge merge precipitation estimation and uncertainty in hydrological modeling, in order to develop a methodology for the analysis of their individual contributions in the uncertainty of rainfall - runoff estimation.The work is divided in two parts, the first one evaluates: How the uncertainty of radar precipitation estimation can be quantified? To address the question, the geostatistical approach by Kriging with External Drift (KED) and Stochastic Generation of Precipitation was used, which allows to model the spatio - temporal structure of errors. The method was applied in the Cévennes - Vivarais region (France), where there is a very rich observation system. The second part explains: How can it be quantified the uncertainty of the hydrological simulation coming from the radar precipitation estimates and hydrological modeling process? In this point, the hydrological mesoscale computation tool was developed; it is distributed hydrological software in time continuous, within the basis of the Curve Number and the Unit Hydrograph. It was applied in 20 spatio-temporal resolutions ranging from 10 to 300 km2 and 1 to 6 hours in the Ardèche (~ 1971 km2) and the Gardon (1810 km2) basins. After a sensitivity analysis, the model was simplified with 4 parameters and the uncertainty of the chain of process was analyzed: 1) Precipitation estimation; 2) Hydrological modeling; and 3) Rainfall - runoff estimation, by using the coefficient of variation of the simulated flow.It has been shown that KED is a method that provides the standard deviation of the precipitation estimation, which can be transformed into a stochastic estimation of the local error. In the chain of processes: 1) Uncertainty in precipitation estimation increases with decreasing spatio-temporal scale, and its effect is attenuated by hydrological modeling, probably due by storage and transport properties of the basin; 2) The uncertainty of hydrological modeling depends on the simplification of hydrological processes and not on the surface of the basin; 3) Uncertainty in rainfall - runoff treatment is the result of the amplified combination of precipitation and hydrologic modeling uncertainties.
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Submitted on : Tuesday, February 13, 2018 - 11:08:06 AM
Last modification on : Friday, September 25, 2020 - 11:00:08 AM
Long-term archiving on: : Sunday, May 6, 2018 - 6:39:14 PM


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  • HAL Id : tel-01707871, version 1




Rafael Navas Nunez. Modelización hidrológica distribuida de crecidas en la región del Cévennes-Vivarais : impacto de incertidumbres ligadas a la estimación de la precipitación y a la parametrización del modelo. Hydrology. Université Grenoble Alpes, 2017. Español. ⟨NNT : 2017GREAU025⟩. ⟨tel-01707871⟩



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