AUTHOR=Muñoz-López Pablo , García-Lafuente Jesús , Nadal Irene , Sammartino Simone 

TITLE=Numerical modeling of the influence of tidal flats on estuaries: the case of the Guadalquivir estuary, SW of the Iberian Peninsula

JOURNAL=Frontiers in Marine Science

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2025.1608858

DOI=10.3389/fmars.2025.1608858

ISSN=2296-7745

ABSTRACT=IntroductionTidal flats play a crucial role in estuarine dynamics, yet their degradation due to human activities raises concerns about their ecological and hydrodynamic implications.MethodsThis study used a three-dimensional numerical model of the Guadalquivir estuary to simulate tidal flats with simplified geometries. A suite of configurations varying in location, depth, and inlet connectivity was tested to quantify impacts on water transport, tidal amplitude, and salinity gradients.ResultsThe most significant changes in the implementation of tidal flats, primarily local in nature, occur near them, extending asymmetrically a few kilometers along the estuary. Their presence increases water transport through the estuary mouth while reducing tidal amplitude (max. 10% decrease) and delaying tidal wave propagation by a few minutes, resembling the effect of increased bottom friction. Additionally, they act as reservoirs of saltier water, increasing time-averaged salinity and modifying horizontal salinity gradients, particularly upstream of their location. The most influential factors are tidal flat depth and proximity to the estuary mouth, with deeper and more seaward tidal flats producing more pronounced changes. The connection length of the tidal flats with the main channel also plays a crucial role in these dynamics, whereas their extent has a lesser influence overall. DiscussionThese findings imply that restoration design must prioritize bathymetry and site selection to balance ecological benefits and hydrodynamic alterations. Explicitly representing tidal flats (or equivalent friction) in operational models is critical for accurate forecasts and management decisions.