Blue water footprint and scarcity indicators in dairy cattle systems: a comparative study on water use

CONTEXT The intensification of dairy production systems has increased pressure on freshwater resources, making environmental sustainability a critical concern. Biophysical indicators such as the Blue Water Footprint (WFb), Blue Water Scarcity Index (BWSI), Available WAter REmaining (AWARE), and Water Stress Index (WSI) provide standardized tools to quantify consumptive water use and its impacts. Due to methodological differences, results from these indicators are not always comparable in terms of impact characterization. In Argentina, where dairy farming is a key economic activity, integrating such indicators is crucial to guide management practices and inform policy decisions aimed at sustainable resource use. To calculate WFb and determine the BWSI, water consumption during milking routines can be quantified using different methodologies. Global reference datasets from previous studies may be employed, although they often reflect diverse national contexts and production conditions, potentially introducing bias. Alternatively, in situ measurements—such as volumetric methods with stopwatches and flow meters—provide farm-level data that more accurately represent actual consumption. Data remains limited regarding the evaluation of differences between in situ measurements and global datasets in quantifying water scarcity footprints of dairy farming systems. Moreover, few studies have assessed how different water footprint methodologies affect the quantification of dairy farming water use under local conditions, highlighting the need for further research that could provide valuable insights for countries with similar climatic and production contexts. OBJECTIVE Evaluate and compare the blue water footprint (WFb) and water scarcity impacts of five representative dairy farms in Santa Fe, Argentina, using both global reference datasets and in situ measurements. METHODS Five representatives bovine milk production systems from the Province of Santa Fe, Argentina, were selected and analyzed. Surveys were conducted with two groups: dairy farm managers contributed insights into production management and practices, whereas dairy workers provided information on milking routines, feeding, and cleaning protocols Water consumption at each dairy establishment was quantified and expressed per unit of fat- and protein-corrected milk (FPCM), which served as the functional unit for the impact assessment. WFb was quantified through reference calculations and direct volumetric measurements during milking routines. Scarcity impacts were assessed using three indicators: Blue Water Scarcity Index (BWSI), Available WAter REmaining (AWARE), and Water Stress Index (WSI). Statistical analyses included comparative tests to identify differences among farms and methodologies. RESULTS AND CONCLUSIONS Case 3 showed the highest impacts across all indicators (WFb = 43.57 L·kg −1 FPCM; BWSI = 10.28 L·kg −1 FPCM; AWARE = 23.37 m 3 eq·kg −1 FPCM; WSI = 0.33 m 3 eq·kg −1 FPCM), reflecting inefficient water management. Case 5 presented the lowest BWSI (4.97 L·kg −1 FPCM), while Case 2 recorded the lowest AWARE (1.07 m 3 eq·kg −1 FPCM) and WSI (0.015 m 3 eq·kg −1 FPCM). Larger dairy farms demonstrated lower WFb per liter of milk, indicating scale-related efficiency. In situ measurements provided more accurate estimates than global datasets. The combined application of BWSI, AWARE, and WSI revealed variations in the ranking of cases according to impact, due to differences in system boundaries and the inclusion of indirect consumption. This demonstrates the importance of selecting the indicator based on the study's objective. SIGNIFICANCE This study provides an integrated perspective on water use within primary production systems and its implications for soil, directly linked to cattle feeding management practices. By applying environmental impact assessment tools, it highlights farm-level interactions and differences among production systems, offering the primary sector a complementary analysis that supports productivity optimization and long-term resilience. Furthermore, it underscores the importance of local empirical data for accurate water footprint assessments and demonstrates how the availability of primary data influences results. By comparing different methods, it reveals methodological differences among scarcity indicators and outlines a roadmap for selecting the most appropriate approach. Although grounded in the Argentine context, these insights are broadly applicable to dairy production worldwide, addressing common methodological challenges and decision-making processes across diverse environmental and production conditions.