DIGITAL TECHNOLOGY TO CALCULATE WATER FOOTPRINTS FOR DIFFERENT AGRICULTURAL PRODUCTS

Abstract: Agricultural production is inextricably linked with freshwater consumption, rendering quantitative, reliable water-footprint assessments essential for sustainable environmental resource management. This research proposes a robust digital technology-based framework for systematically calculating, validating, organizing, and visualizing the water footprints of diverse agricultural commodities. The proposed digital workflow integrates field data collection, structured product-level digital records, component-wise water-footprint computation engines, automated validation rules, and interactive reporting dashboards. Green (rainwater), blue (surface and groundwater), and grey (pollutant dilution volume) water footprint components are quantified separately and combined to yield precise product-level water footprint indicators (m³/ton). Digital record management drastically improves data traceability by preserving raw data sources, mathematical calculation methods, model version parameters, timestamps, and data quality flags. Operating within a design-oriented engineering framework, this study defines the architectural layers, database schema attributes, sequential data workflows, and a target performance evaluation matrix. The resulting framework provides a transparent foundation for multi-crop comparison, policy reporting, and future integration with Internet of Things (IoT) field sensors, remote sensing, artificial intelligence, and smart agriculture decision-support ecosystems.

Keywords: Water footprint assessment, Digital agriculture, Green-blue-grey water, Data traceability, Precision farming, Smart agriculture, Quality validation, IoT integration.