Alegria, C.; Albuquerque, T. Remote Sensing for Water Quality Monitoring—A Case Study for the Marateca Reservoir, Portugal. Geosciences 2023, 13, 259, doi:10.3390/geosciences13090259.
Alegria, C.; Albuquerque, T. Remote Sensing for Water Quality Monitoring—A Case Study for the Marateca Reservoir, Portugal. Geosciences 2023, 13, 259, doi:10.3390/geosciences13090259.
Alegria, C.; Albuquerque, T. Remote Sensing for Water Quality Monitoring—A Case Study for the Marateca Reservoir, Portugal. Geosciences 2023, 13, 259, doi:10.3390/geosciences13090259.
Alegria, C.; Albuquerque, T. Remote Sensing for Water Quality Monitoring—A Case Study for the Marateca Reservoir, Portugal. Geosciences 2023, 13, 259, doi:10.3390/geosciences13090259.
Abstract
Continuous water resources monitoring is needed for sustainable urban water supply. Remote sensing techniques have proven useful for monitoring some water qualitative parameters with optical characteristics. The study area was the Marateca reservoir in central inland Portugal. The aims were the following: (1) to explore the water quality parameters at the monitoring points of the Marateca reservoir that may explain the event; (2) to validate optical water quality parameters with the monitoring points data; and (3) to model the reservoir water characteristics regarding its deepness, trophic state, and turbidity. The parameters total phosphorus, total nitrogen, and chlorophyll-a were used to compute a trophic level index. The Sentinel-2 imagery was used to compute spectral indices and bands image ratio; to obtain spectral signatures for the monitoring points, and to model water characteristics. The water parameters were above the recommended values at the reservoir entry point from the Ocreza River. The reservoir trophic level was Hypereutrophic and Eutrophic. The spectral signatures confirmed a Hypereutrophic pattern in the entry point. The Marateca reservoir’s water characteristics modeling forecasted problematic zones by contamination. The methodological approach developed can be easily applied to other reservoirs and is a key support tool for decision-makers.
Keywords
Trophic level index; spectral indices change; spectral signatures; Random Forest algorithm.
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
