Characterizing nutrient pollution in urban well water using hydrochemical, statistical, and remote sensing methods
摘要
In peri-urban areas where access to potable water is limited, groundwater from water table frequently constitutes the primary source of water, despite its susceptibility to contamination from human activity. The present study, conducted in Abomey-Calavi (Benin Republic), sought to identify the key factors influencing nitrogen and phosphorus pollution in well water. Thirty wells were sampled over three campaigns between June and December 2021. The analysis of nutrient concentrations was conducted, and a comparison was made with national and international drinking water standards. A multidimensional approach was adopted, combining multivariate statistical analyses (Principal Component Analysis and Hierarchical Cluster Analysis), nutrient pollution indices, and remote sensing data derived from Sentinel-2 imagery. Satellite data were processed to compute the Normalized Difference Built-Up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI) to characterise land-use, vegetation cover, and surface moisture around the sampled wells. Results revealed acidic conditions (pH: 3.15–5.81) and low mineralisation (272.86 µS/cm). More than 40% of the wells exhibited nitrate levels exceeding the 50 mg/L limit. Statistical analyses indicated that proximity to inadequate sanitation, human pressure, and seasonal variability significantly contributed to nutrient enrichment. Remote sensing results showed a positive correlation between NDBI and nitrate concentration (r = 0.39), while NDVI and NDWI exhibited inverse relationships, suggesting that urban expansion and reduced vegetation cover promote pollutant infiltration. Overall, the study underscores the need for integrated monitoring systems combining field data, statistical tools, and satellite indicators to assess and mitigate groundwater pollution in rapidly urbanising regions.