Water quality monitoring in coastal areas and estuaries poses significant challenges due to the intricate interplay of hydrodynamic, chemical, and biological processes, regardless of the chosen monitoring methods. In this study, we analyzed the applicability of different monitoring sources using in situ data, uncrewed-aerial-vehicle (UAV)-mounted hyperspectral sensing, and Sentinel-2-based multispectral imagery. In the first part of the study, we evaluated the applicability of existing empirical algorithms for water quality (WQ) parameter retrieval using hyperspectral, simulated multispectral, and satellite multispectral datasets and in situ measurements. In particular, we focused on three optically active WQ parameters: chlorophyll a ($Chl,a$), turbidity (TUR), and colored dissolved organic matter (CDOM) in oligotrophic coastal waters. We observed that most existing algorithms performed poorly when applied to different reflectance datasets, similar to previous findings in small and optically complex water bodies. Hence, we proposed a novel set of locally based empirical algorithms tailored for determining water quality parameters, which constituted the second part of our study. The newly developed regression-based algorithms utilized all possible combinations of spectral bands derived from UAV-generated hyperspectral data and exhibited coefficients of determination exceeding 0.9 for the three considered WQ parameters. The presented two-part approach was demonstrated in the semi-enclosed area of Kaštela Bay and the Jadro River estuary in the Central Eastern Adriatic Sea. This study introduces a promising and efficient screening method for UAV-based water quality monitoring in coastal areas worldwide. Such an approach may support decision-making processes related to coastal management and ultimately contribute to the conservation of coastal water ecosystems.

There are multiple factors affecting the behavior of water properties in an estuary, including the hydraulic properties of rivers and corresponding receiving water bodies, along with the potential solutes brought by rivers. Although there are various numerical models and analytical approaches to solving particular or holistic problems in estuaries, measurements are inevitably required. In this study, we developed an innovative low-cost probe based on the Arduino platform as an alternative to more expensive measuring systems. Our device is designed to measure position, temperature, and electrical conductivity in multiple realizations, and it consists of a floating container equipped with the following components: an Arduino Mega development board, a power management module, an SD card logging module, a Bluetooth module, a temperature measuring module, a global positioning satellite (GPS) position module, and a newly developed module for measuring electrical conductivity (EC). We emphasize that all used tools are open-source and greatly supported by the worldwide community. We tested our probe during a field campaign conducted at the estuary of River Jadro near Split (Croatia). Nine probes were released at the river mouth and their position, temperature, and EC were monitored and recorded during the experiment, which ended when the probes stopped, due to the river plume attenuation. The same experiment was repeated three times. All of the probes recorded consistent temperature data, while the EC data show more variable behavior, due to the higher sensitivity of the corresponding sensor. This was expected as a part of the natural process in the estuary. The measured data were additionally used to parameterize an analytical model for mean flow velocity and salinity as a proxy concentration. This showed a good match between the experimental results and the theoretical framework. This work, although focused on water surface applications in the near field zone of an estuary, should be considered as a promising step toward the development of innovative and affordable measurement devices.

Rivers represent an essential pathway for waterborne transport, and therefore estuaries are critical coastal areas for a pollution hazard that might lead to eutrophication and general water quality deterioration. When addressing these problems, the decision makers and coastal managers often need additional skills and specialists, so they engage consultants in developing models and providing potential solutions. Different stakeholders’ interests present a challenge in the implementation process of proposed solutions. Nevertheless, if the relevant institutions were presented with a screening tool, enabling them with a certain level of solution ownership, potentially more involvement would occur. There are numerous intertwined physical processes present in the estuary ecosystem, including river discharge, tidal forces, wind-induced stress and water density variations. This research utilizes an analytical model based on ensemble averaging and near-field approximation of the advective-diffusion equation for the case of continuous, steady, conservative solute transport in a stratified, river-dominated estuary. Such an approach significantly reduces the costs and time needed to obtain enough measured data required for common statistical analysis or the need for a more complex numerical model. The developed methodology is implemented into a simple software named CPoRT (Coastal Pollution Risk Tool) within a recently conducted research project funded by European Social Fund.