This study evaluates nitrogen (N) and phosphorus (P) pollution in the Ankara River Sub-basin, Türkiye, using the grey water footprint (GWF) approach. A Tier-1 GWF approach was applied, complemented by a sensitivity analysis to assess the influence of key parameters, including leaching–runoff fractions and water quality thresholds. The results should be interpreted as indicative rather than absolute values, as they depend on assumptions related to leaching fractions and background concentrations. By integrating data from agricultural diffuse sources and municipal wastewater treatment plants (WWTPs), the research identifies critical pollution hotspots and sectoral pressures on water resources, causing water quality degradation. The results reveal that P is the primary limiting pollutant governing GWF magnitudes across the sub-basin. The total GWF was estimated at 8294 million m³ yr⁻¹ in the sub-basin outlet. Approximately 10% and 31% of the basin-wide GWF were associated with fertilizer-based diffuse sources and WWTP1, respectively. The study demonstrates that regulatory compliance alone does not guarantee the protection of a river’s assimilative capacity. These results provide a basis for policy development, emphasizing the need to move beyond concentration-based regulations toward management frameworks that explicitly consider assimilative capacity and cumulative basin-scale impacts.

Agricultural irrigation is a critical component of global food security, accounting for a substantial share of both water use and energy demand while strongly influencing production costs and market stability under volatile energy conditions. This study evaluates grid-connected and off-grid solar water pumping systems for sugar beet irrigation using real case-study data from Konya, Türkiye. Unlike conventional approaches, this work incorporates irrigation method (sprinkler vs. drip) as a core variable, linking agronomic decisions to energy demand and system sizing. The analysis is based on high-resolution real-world data, including measured hourly solar generation, crop-specific irrigation schedules, and field-based water demand. Two hydraulic conditions were evaluated: low-head (LH-45 m) and high-head (HH-80 m). The results show that grid-connected PV systems provide the most economically viable solution across conditions. While small-scale systems remain marginally unprofitable, economic viability is achieved beyond moderate farm sizes, with payback periods decreasing to 7–8 years. Although higher groundwater depth increases energy demand, it also enhances economic performance through greater energy utilization and cost savings. In contrast, off-grid PV systems with battery storage remain economically unfeasible due to high capital costs. Overall, the findings highlight that irrigation strategy, hydraulic conditions, and system scale are key determinants of solar irrigation performance.

Agriculture consumes over 70% of global freshwater while generating substantial diffuse pollution that threatens water security and sustainable development objectives. The grey water footprint (GWF) concept quantifies the freshwater volume required to assimilate agricultural pollutants to acceptable environmental standards, providing a crucial metric for sustainable water resource management. This comprehensive review synthesizes current knowledge on agricultural GWF assessment, examining conceptual foundations, calculation methodologies, and practical applications across diverse farming systems. We analyze the evolution from simplified Tier-1 approaches to sophisticated process-based models incorporating hydrological dynamics, pollutant fate and transport, and ecosystem interactions. The review encompasses nitrogen and phosphorus from fertilizers, pesticide contamination, and livestock-derived pollutants, revealing substantial methodological challenges including data scarcity, temporal-spatial variability, and pollutant interaction effects. Comparative analysis of global case studies demonstrates order-of-magnitude differences in GWF estimates depending on calculation methods, regional conditions, and management practices. Advanced modeling frameworks integrating SWAT, HYDRUS, CROPWAT and machine learning algorithms show promise for improving accuracy and policy relevance, though standardization remains limited. Future developments should prioritize: (1) multi-pollutant interaction modeling under varying environmental conditions, (2) climate-adaptive GWF frameworks incorporating extreme weather scenarios, and (3) standardized global methodologies enabling cross-regional comparisons and policy integration. This review establishes GWF as an essential tool for achieving water-food-environment nexus sustainability, supporting evidence-based agricultural policy and contributing to SDG implementation at multiple scales.