PhD Defence Behnaz Arabi

optical remote sensing of water quality in the wadden sea

Behnaz Arabi is a PhD student in the department of Water Resources. Her supervisor is W. Verhoef from the faculty of Geo-Information Science and Earth Observation.

Deterioration of estuarine and coastal water quality has become a worldwide issue of substantial concern as anthropogenetic actions increase and climate change tends to cause main changes to the hydrological cycle. The acquisition of water quality information using radiometric measurements of the water’s optical properties has developed quickly in recent years. Developments in algorithms and results improvement, sensor technology and reliability, and data availability have led to established practices in remotely-sensed observations with potential implications to water resources management. Using remotely sensed observations have played a significant role to develop satellite-derived products for providing vital information on most important water quality variables such as Chlorophyll-a (Chla), Suspended Particulate Matter (SPM), and Coloured Dissolved Organic Matter (CDOM) with the required accuracies for management organizations. This study investigates how these water quality variables can be estimated from remote sensing observations by means of a quantitative approach in complex coastal areas. This is important with respect to the Sustainable Development Goals (SDGs) to better understand the capability of the state of art of remote sensing technology to monitor long-term spatio-temporal variation of water quality in estuarine and coastal waters as a consequence of climate change, global warming, pollution and population increase, transportation changes and human activities.

The thesis presents how remote sensing techniques and observations can be employed to accurately retrieve water quality variables in complex coastal waters at both the water surface and Top Of Atmosphere (TOA) levels in the frame of proposing and evaluating the latest remote sensing methods and techniques established based on radiative transfer modeling, advanced retrieval methods, developed algorithms and optimal instruments and sensors.

This dissertation is composed of six chapters: Chapter 1 is introductory and describes the optical remote sensing of water quality, the challenges and requirements to apply the remote sensing techniques in the coastal waters, the importance of the study area and the proposed methods and algorithms in this study. Chapter 2 deals with application and validation of a new and developed radiative transfer hydro-optical model (i.e., the 2SeaColor model) to accurately retrieving water quality variables at water surface level under various Solar Zenith Angles (SZAs) and water turbidity conditions by using in-situ hyperspectral measurements. Chapter 3 deals with application and validation of a proposed radiative transfer atmospheric-hydro-optical model (i.e., the coupled 2SeaColor- MODerate resolution atmospheric TRANsmission (MODTRAN) model) to simultaneously retrieve water quality variables and atmospheric properties (i.e., visibility and aerosol type) at TOA level by using MEdium Resolution Imaging Spectrometer (MERIS) images. Chapter 4 deals with 15-years water quality monitoring in complex coastal waters of the Dutch Wadden Sea by using time series of diurnal in-situ hyperspectral measurements and multi-sensor satellite images of MERIS, Sentinel-2 Multispectral Instrument (MSI) and Sentinel-3 Ocean and Land Colour Instrument (OLCI) images. Chapter 5 deals with the problem of the sea-bottom effect in the shallow coastal waters and develops a refined hydro-optical model (i.e., the Water-Sea Bottom (WSB) model) to evaluate the sea-bottom effect on remote sensing observations in these areas. Further analysis and investigations in this chapter lead to proposing a new near-infrared bottom effect index (i.e., the NIBEI) to distinguish optically shallow waters from optically deep waters. Chapter 6 discusses the main objectives of this dissertation and explains how these objectives are achieved and provide research recommendations for future studies.