Work

Data Integration for Investigating Drivers ofWater Quality Variability in the Banja Reservoir Watershed

Year: 2023

Type: article

Abstract: It is increasingly important to know the water quality of a reservoir, given the prospect of an environment poor in water reserves, which are based on intense and short-lived precipitation events. In this work, vegetation indices (NDVI, EVI) and bio-physical parameters of the vegetation (LAI, FC), meteorological variables, and hydrological data are considered as possible drivers of the spatial and temporal variability of water quality (WQ) of the Banja reservoir (Albania). Sentinel-2 and Landsat 8/9 images are analyzed to derive WQ parameters and vegetation properties, while the HYPE model provides hydrological variables. Timeseries of the considered variables are examined using graphical and statistical methods and correlations among the variables are computed for a five-year period (2016–2022). The added-value of integrating earth observation derived data is demonstrated in the analysis of specific time periods or precipitation events. Significant positive correlations are found between water turbidity and hydrological parameters such as river discharge or runoff (0.55 and 0.40, respectively), while negative correlations are found between water turbidity and vegetation descriptors (􀀀0.48 to 􀀀0.56). The possibility of having easy-to-use tools (e.g., web portal) for the analysis of multi-source data in an interactive way, facilitates the planning of hydroelectric plants management operations.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.7763070