Geographical Information System–driven intelligent surface water quality assessment for enhanced drinking and irrigation purposes in Brahmani River, Odisha (India)

Abstract

River basins in Odisha suffer from serious anthropogenic interventions that degrade water quality, including runoff from agriculture, municipal wastewater, and industrial discharges. The Brahmani River, an essential source of water for industrial, agricultural, and drinking uses, is especially affected by overuse of fertilizer and pesticides. Ensuring health and cleanliness in cities and communities requires constant monitoring and management of drinking water sources. This study evaluates the river’s water quality for drinking and agricultural applications and identifies key factors influencing its deterioration. Water samples were collected from 12 locations during pre-monsoon (PRM) and post-monsoon (POM) seasons (2017–2021) and analyzed for physicochemical parameters against World Health Organization (WHO) standards. For quality assessment, values of analyzed parameters of the surface water samples were compared with the WHO water quality standards. The findings show that the majority of the samples are fit for drinking and irrigation, with the main cations arranged as Ca²⁺ > Na⁺ > Mg²⁺ > K⁺ and anions as HCO₃⁻ > Cl⁻ > SO₄²⁻ > CO₃²⁻, respectively. The analytical results indicate slightly alkaline nature of the surface water in the study area. Strong correlations among ions (HCO₃⁻, Ca²⁺, Mg²⁺, Cl⁻, SO₄²⁻) suggest influences from natural processes (weathering, erosion) and anthropogenic activities. Seasonal variations assessed using Water Quality Index (WQI) and Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) method indicate that water quality ranges from good to poor in PRM and good to marginal in POM seasons. The metrics and the criteria differ significantly, indicating that remedial action is necessary to enhance the quality of the water at these locations. Irrigation suitability indices (SAR, MH, %Na, PI, RSC, KI, ESP) further confirm the water’s acceptability for agricultural use. The irrigation suitability of agriculture-dominated basin was assessed using Empirical Bayesian Kriging (EBK) modeling, achieving high accuracy with an RMSS error and an MS error. Spatial maps generated using Geographical Information System (GIS) software, along with Gibbs plots, Piper diagrams, and Wilcox diagrams, help delineate agricultural zones and highlight the dominant geochemical processes. The study concludes that both anthropogenic (sewage discharge, waste dumping) and geogenic (evaporation, mineral dissolution) factors significantly affect water quality. The findings highlight the effectiveness of EBK for sustainable irrigation and agriculture. To preserve this critical resource, measures such as reducing sewage outflows, managing stormwater discharge, and preventing solid waste disposal are essential. The purpose of this study is to pinpoint areas with low water quality and offer workable solutions to the nation’s water resources management agency in order to enhance the drinking water supply or attain sustainable water resources. Findings revealed greater water stress in upstream areas compared to downstream regions, offering valuable insights for drinking, irrigation management, and drought-resistant crop planning.

Graphical abstract