Under pressure: estuarine suspended sediment dynamics in response to hydrodynamic forcings and extreme events
Juliana Tavora Bertazo Pereira is a PhD student in the Department of Water Resources. Promotors are prof.dr. D. van der Wal and dr.ir. S. Salama from the Faculty ITC.
Coastal and estuarine regions, hosting a significant fraction of the world's population, are economically and ecologically important. However, these regions are also vulnerable to climate change and extreme events that may increase in frequency and severity in the next few decades. Such events, including severe windstorms and extreme river discharge, can significantly impact the hydrodynamics of estuaries and sediment variability with consequences for water quality and the functioning of ecosystems. Extreme events also drive changes in the bottom morphology of estuaries through the re-distribution of sediments, including the erosion of intertidal mudflats or silting. Beyond bottom morphological changes, hotspots of suspended sediment, like turbid surface features in the form of turbid plumes, may be observed as markers of the occurrence of extreme events.
This thesis studied sediment dynamics in response to prevailing 'normal' conditions and extreme events in contrasting estuarine systems: Patos Lagoon in Brazil, Western Scheldt Estuary in the Netherlands, and Gironde Estuary in France. Patos Lagoon estuary is a microtidal system characteristically dominated by winds and river discharge. Western Scheldt estuary is a mesotidal to macrotidal system dominated by both winds and tides. Lastly, the Gironde Estuary is a macrotidal estuary highly affected by both tides and river discharge. In common, these systems have intense turbid waters and relative vulnerability to extreme river discharge and windstorms. Thus, they are ideal laboratories for investigating different aspects of sediment responses to hydrodynamics and extreme events.
Moreover, in the context of increasing frequency of extreme events, it is crucial to understand and address the pressures on estuarine and coastal environments to support effective management and conservation strategies. This requires re-evaluating traditional methods to provide approaches adapted for spatial monitoring of suspended sediment dynamics in extreme conditions, including developing new algorithms and frameworks while optimizing data usage. This thesis aims to answer the following questions:
- Where are the hotspots of suspended sediment, and how do they vary in time and space? What factors contribute to their spatial and temporal variability? How do different tools detect these hotspots?
- How do river discharge and winds affect the spatial patterns of suspended sediments in estuarine and coastal waters under ‘normal’ and extreme conditions? How do we apply low-frequency data?
- What are the main forcing mechanisms and their compound effects on suspended sediment variability? Do extreme events modify the contribution of these forcing mechanisms to sediment variability?
In this study, an algorithm (PLUMES) was developed to monitor hotspots of suspended sediment (such as turbid plumes) using satellite imagery. The PLUMES algorithm has demonstrated advantages over traditional approaches by adapting to various hydrological and meteorological conditions without requiring extensive manual recalibration while also capturing low turbidity plumes.
Further, an approach integrating long-term satellite observations with field measurements of oceanographic parameters has provided a spatial and temporal overview of the effects of winds, river discharge, and suspended sediment variability in estuaries. The findings underscore the importance of high-frequency data from autonomous instruments at fixed stations in estuarine and coastal systems, particularly under extreme conditions. However, implementing and maintaining such instruments at a representative spatial distribution may pose economic challenges in many coastal systems, especially in low-to-middle-income countries. In light of this, the thesis proposed using synoptic low-frequency satellite-based data to aid in identifying strategic locations for the installation of high-frequency turbidity sensors.
Lastly, a machine-learning framework was proposed to maximize the use of the synoptic low-frequency satellite remote sensing and high-frequency data such as numerical modeling outputs. This framework quantifies pixel-by-pixel the interplay of forcing mechanisms influencing suspended sediment variability in a spatially explicit context. In this case, the role of tides, river discharge, and winds was quantified. Using high-frequency data, the role of forcing mechanisms can also be quantified under extreme events, for which the role of tides was found to increase under extreme river discharge and windbursts. The proposed machine learning framework is a generic practical tool that can monitor the relative impact of forcing mechanisms on sediment variability in estuaries, especially under extreme events. The findings highlight the potential of synoptic high-frequency data over low-frequency data in providing insights and aiding in effective decision-making on extreme events.
The techniques developed in this thesis hold potential for a wide range of estuarine and coastal settings, as they were designed for generic applications. The results of this study, therefore, could influence the design and implementation of future coastal and estuarine management strategies. This is particularly important in the context of maximizing suspended sediment monitoring in a varied range of meteorological and hydrodynamic settings.
