Fully Stochastic Distributed Methodology for Multivariate Flood Frequency Analysis

Flores Montoya, Isabel and Sordo Ward, Álvaro Francisco and Mediero Orduña, Luis Jesús and Garrote de Marcos, Luis (2016). Fully Stochastic Distributed Methodology for Multivariate Flood Frequency Analysis. "Water", v. 8 (n. 6); p. 225. ISSN 2073-4441. https://doi.org/10.3390/w8060225.


Title: Fully Stochastic Distributed Methodology for Multivariate Flood Frequency Analysis
  • Flores Montoya, Isabel
  • Sordo Ward, Álvaro Francisco
  • Mediero Orduña, Luis Jesús
  • Garrote de Marcos, Luis
Item Type: Article
Título de Revista/Publicación: Water
Date: 27 May 2016
ISSN: 2073-4441
Volume: 8
Freetext Keywords: Derived Flood Frequency Curve, Stochastic Rainfall Model, Distributed, Event-Based, Rainfall–Runoff Model, Probabilistic, Initial Soil Moisture
Faculty: E.T.S.I. Caminos, Canales y Puertos (UPM)
Department: Ingeniería Civil: Hidráulica y Energética [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (5MB) | Preview


An adequate estimation of the extreme behavior of basin response is essential both for designing river structures and for evaluating their risk. The aim of this paper is to develop a new methodology to generate extreme hydrograph series of thousands of years using an event-based model. To this end, a spatial-temporal synthetic rainfall generator (RainSimV3) is combined with a distributed physically-based rainfall?runoff event-based model (RIBS). The use of an event-based model allows simulating longer hydrograph series with less computational and data requirements but need to characterize the initial basis state, which depends on the initial basin moisture distribution. To overcome this problem, this paper proposed a probabilistic calibration simulation approach, which considers the initial state and the model parameters as random variables characterized by a probability distribution though a Monte Carlo simulation. This approach is compared with two other approaches, the deterministic and the semi-deterministic approaches. Both approaches use a unique initial state. The deterministic approach also uses a unique value of the model parameters while the semi-deterministic approach obtains these values from its probability distribution through a Monte Carlo simulation, considering the basin variability. This methodology has been applied to the Corbès and Générargues basins, in the Southeast of France. The results show that the probabilistic approach offers the best fit. That means that the proposed methodology can be successfully used to characterize the extreme behavior of the basin considering the basin variability and overcoming the basin initial state problem.

Funding Projects

Government of SpainCGL2011-22868UnspecifiedUnspecifiedModelación físicamente basada para la caracterización extremal de la respuesta hidrológica de una cuenca bajo enfoque probabilístico. Aplición a la seguridad de presas.
FP7283568DRIHMCentro Internazionale in Monitoraggio Ambientale - Fondazione CIMADistributed Research Infrastructure for Hydro-Meteorology

More information

Item ID: 51370
DC Identifier: https://oa.upm.es/51370/
OAI Identifier: oai:oa.upm.es:51370
DOI: 10.3390/w8060225
Official URL: http://www.mdpi.com/2073-4441/8/6/225
Deposited by: Memoria Investigacion
Deposited on: 26 Jun 2018 18:10
Last Modified: 25 Mar 2019 16:02
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM