Interoperability and computational framework for simulating open channel hydraulics: application to sensitivity analysis and calibration of Gironde Estuary model

TL;DR

This paper introduces a new API for the TELEMAC-MASCARET system that enhances interoperability for hydro-environmental simulations, enabling advanced sensitivity analysis and calibration for complex water resource models like the Gironde Estuary.

Contribution

A novel distributed API for TELEMAC-MASCARET that facilitates interoperability, sensitivity analysis, and calibration in hydro-environmental modeling.

Findings

API enables rapid sensitivity analysis of model parameters.

API improves calibration efficiency through data assimilation.

Application to Gironde Estuary demonstrates practical benefits.

Abstract

Water resource management is of crucial societal and economic importance, requiring a strong capacity for anticipating environmental change. Progress in physical process knowledge, numerical methods and computational power, allows us to address hydro-environmental problems of growing complexity. Modeling of river and marine flows is no exception. With the increase in IT resources, environmental modeling is evolving to meet the challenges of complex real-world problems. This paper presents a new distributed Application Programming Interface (API) of the open source TELEMAC-MASCARET system to run hydro-environmental simulations with the help of the interoperability concept. Use of the API encourages and facilitates the combination of worldwide reference environmental libraries with the hydro-informatic system. Consequently, the objective of the paper is to promote the interoperability concept for studies dealing with such issues as uncertainty propagation, global sensitivity analysis, optimization, multi-physics or multi-dimensional coupling. To illustrate the capability of the API, an operational problem for improving the navigation capacity of the Gironde Estuary is presented. The API potential is demonstrated in a re-calibration context. The API is used for a multivariate sensitivity analysis to quickly reveal the most influential parameters which can then be optimally calibrated with the help of a data assimilation technique.