Spatial Distribution Analysis of Groundwater Quality Parameters in the East Region of Burkina Faso Using GIS Techniques

Groundwater quality assessment is critical for achieving Sustainable Development Goal 6 (SDG-6), which aims to ensure the availability and sustainable management of water and sanitation for all. In Burkina Faso, groundwater is a vital natural resource supporting socio-economic development, particularly in arid and semi-arid regions where water scarcity and quality are significant challenges. Climatic conditions in the country made of a long, hot and dry season followed by a short rainy period, result in considerable variability in water availability. Rapid population growth exacerbates these challenges by increasing water demand in both urban and rural areas; therefore, putting additional pressure on the already limited water resources. Moreover, the expansion of mining and agricultural activities further stresses these resources with contaminations from use of hazardous substances and over-extraction. The use of fertilizers and pesticides contributes to pollution, posing serious risks to human health and local ecosystems. Given the strategic importance of groundwater for Burkina Faso development amidst these growing challenges, a comprehensive understanding of groundwater quality is essential. This study focuses on the Eastern Region of Burkina Faso and aims to analyze the spatial distribution of physicochemical parameters related to groundwater quality in order to support sustainable water resource management and public health initiatives. Water samples from 42 sites were collected and analyzed for parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS), and concentrations of calcium, magnesium, sodium, potassium, chloride, sulfate, bicarbonate, and nitrate. The data were processed using the Inverse Distance Weighted (IDW) interpolation method in ArcGIS 10.8 to produce spatial maps of these parameters. A Water Quality Index (WQI) was calculated to classify groundwater quality as "Excellent" (WQI < 50), "Good" (50 ≤ WQI ≤ 100), or "Poor" (WQI > 100). The results revealed significant spatial variability in groundwater quality with concentrations sometimes exceeding WHO-standards. Specifically, 38.10% of the analyzed samples exceeded the standard for nitrates while 28.57% of the samples show turbidity above recommended thresholds. TDS levels vary considerably, reaching maximum values of 1,336 mg/L and electrical conductivity values reached 1,336 µS/cm. These results demonstrate marked heterogeneity in water quality parameters across the region. The generated maps could serve as valuable tool for decision-makers to enable identification of areas requiring particular attention for groundwater quality management.