Sensitivity Analysis in Hydrological Modeling for the Gulf of México. (2016)

• Record Type: Journal Article
• Authors: Ibarra, Sara; Romero, Rabindranarth; Poulin, Annie; Glaus, Mathias; Cervantes, Eduardo; Bravo, José; Pérez, Ricardo; Castillo, Eduardo
• Is Part Of: Procedia engineering. Volume 154(2016)
• Page Start: 1152
• Page End: 1162
• Publication Date: 2016
• Subjects: Hydrological modeling -- sensitivity -- MCAT and floods; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2016.07.531
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: The progressive change in climatic conditions worldwide have caused an increase in the frequency and severity of extreme weather phenomena (EHP), an example is what happened in recent years (1990-2014) in southeastern Mexico, it has been affected by the presence of the EHP (floods and droughts), leaving substantial economic, social and environmental losses. An alternative to this problem is the use of hydrological simulation models for its possible operation at low cost, but these provide extrapolations or predictions that have some degree of uncertainty, which reduces the applicability and confidence in their results. Thus, the assessment of uncertainty in hydrologic modeling is important, especially when their results are used to support decision-making on the management of water resources. Therefore, the objective of this research is the evaluation of distributed hydrological modeling (HDM) to determine the sensitivity and uncertainty of the rainfall-runoff model using Monte Carlo tool toolbox (MCAT). The main conclusion of this work is the establishment of a strategy sensitivity analysis is needed to accelerate and optimize the calibration process, in the estimation of parameters and to understand the behavior of the model itself to the possible variation of the parameters more representative, which have an intrinsic error in its determination and define the dependencies of these parameters in the model solution.