Joint calibration of a hydrological model and rating curve parameters for simulation of flash flood in urban areas

Abstract

Calibration process is usually time demanding and as much streamflow information as possible in rainfall-runoff models. Nevertheless, from a practical point of view, the available information is measurement of water level, which is essential to design rating curves. This manuscript proposes a set of joint calibration of hydrological model parameters with a range of rating curves, developed for the main channel of the catchment in a crowded urban area. As an alternative of free calibration, the simulations were carried out based on a list of proficient parameters. Four streamflow gauging stations were analysed and used to subdivide the basin. The hourly lumped rainfall-runoff model GR4H was applied to four critical flash flood events to create a rank of Nash-Sutcliffe efficiency criteria (NSE) applying the best set of parameters. The results indicated that the hydrological model errors were compensated by hydraulics errors and they presented an equifinality in the process. RESUMONos modelos chuva-vazão, a etapa de calibração geralmente exige tempo e grande quantidade de informação das vazões. No entanto, do ponto de vista prático, a informação usualmente disponível é o nível d'água medido, este, por sua vez, utilizado na construção das curvas-chave. Este artigo propõe uma calibração conjunta dos parâmetros de um modelo hidrológico com uma gama de curvas-chave, as quais foram desenvolvidas para o canal principal da bacia em estudo em uma área altamente ocupada e urbanizada. Como alternativa a uma calibração livre, as simulações foram realizadas com base em uma lista de parâmetros previamente testados. Quatro estações linimétricas foram analisadas e utilizadas para subdividir a área da bacia. O modelo concentrado horário de chuva-vazão GR4H foi utilizado com quatro eventos críticos de inundações bruscas com o intuito de criar uma classificação de critérios de eficiência de Nash-Sutcliffe aplicando o melhor conjunto de parâmetros. Os resultados indicam que os erros do modelo hidrológico foram compensados pelos erros hidráulicos e apresentaram uma equifinalidade no processo. Palavras-chave:Modelo chuva-vazão; Inundações bruscas; Curvas-chave; Hidrologia urbana; Modelagem hidrológica e ambiental. RBRH, Porto Alegre, v. 24, e24, 2019 Joint calibration of a hydrological model and rating curve parameters for simulation of flash flood in urban areas 2/15

Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins

“…The approach uses satellite data to infer both the discharge data used for model calibration and the reservoir operations included in the hydrological model. Unlike previous studies, our approach uses global sensitivity analysis to avoid the biases that could be introduced when co-calibrating the hydrological model and the rating curve used to reconstruct the discharge data (Lima et al, 2019). This fundamental step also helps us narrow down the uncertainty range for the parameterization of the rating curve in a more justified way.…”

“…1b) is to calibrate both models concurrently (e.g., Liu et al, 2015;Sun et al, 2018;Huang et al, 2020). Here, a potential pitfall is the fact that estimation errors in the hydraulic model (discharge estimation) may be compensated for by introducing parameter biases in the hydrological model, and vice versa (Lima et al, 2019). In other words, simultaneous calibration of the hydraulic and hydrological models may yield biased parameters, ultimately compromising the realism and reliability of the calibrated models.…”

Simulation of flood hydrographs in urban channels: a tool for urban planning

“…The combined use of hydrological and hydraulic models, together with the forecasting of meteorological systems, is a study aspect that has been widely applied in the analysis of extreme events in urban environments. [24][25][26] From the results and analysis of the flood studies, it is possible to reduce the damage caused by these events. Therefore, these analyses make it possible to forecast disasters and implement an alert system for the population, so that everyone is informed about the best way to act in the face of these events.…”