Environmental Systems Engineering for Agriculture–Water Systems under Climate Change: Emerging Pollutants, Digital Twins & Low-Carbon Co-Optimization

Environmental Systems Engineering is increasingly crucial in addressing the evolving challenges agriculture–water systems face amid intensifying climate extremes and mounting uncertainties. Current problems encompass the management of both point and non-point pollution sources, coping with pulse loading events, and the rise of emerging contaminants such as per- and polyfluoroalkyl substances (PFAS), microplastics, and antibiotic resistance genes. The complexity of these systems is compounded by multi-objective trade-offs across the water–energy–food–carbon (WEFC) nexus, necessitating solutions that balance environmental safeguards with operational flexibility. Recent studies have shown advancements in process integration, control at multiple scales (from unit to watershed), robust and adaptive optimization, and the use of digital twins integrated with real or high-fidelity data. Nevertheless, there remain significant knowledge gaps in scalable pollutant treatment, effective system coupling, coordinated control across sectors, and embedding resilience and sustainability within engineering frameworks. Ongoing debates persist regarding the best strategies for holistic system integration, comprehensive carbon accounting, and the full-scale implementation of emerging digital and data-driven methodologies.

This Research Topic aims to catalyze the development and demonstration of innovative engineering-centric approaches that can design, optimize, and manage agriculture–water systems under the pressing realities of climate change. Our key objective is to support cross-sectoral and multi-objective decision-making—balancing water quality, carbon emissions, energy use, and food production—through advanced modeling, robust process control, and the expanded use of digital twins. We invite research that tests hypotheses on the efficacy of integrated pollutant treatment, scalable solutions for emerging contaminants, and frameworks for WEFC co-optimization validated through real-world or high-fidelity data. Key questions also include: How can multi-level system coupling and cross-sector scheduling be optimized to minimize environmental and operational costs? What technological and methodological advances are necessary to ensure demonstration-scale robustness and sustainability?

This Research Topic focuses on integrative engineering solutions, model-based optimization, and system-scale validation for agriculture–water systems, while excluding studies limited to algorithmic or classification benchmarks absent of decision loop integration. To gather further insights in resilient, low-carbon, and digitally enabled agriculture–water systems, we welcome articles addressing, but not limited to, the following themes:
• Integrated modeling and control from process to watershed scale, including uncertainty propagation and robust/MPC strategies
• Innovative pollutant treatment and process integration, coupled with life-cycle and carbon-footprint assessment
• Engineering evaluation of blue–green infrastructure for performance, resilience, and multi-objective trade-offs
• Co-optimization strategies within the WEFC nexus, featuring joint reliability–cost–mitigation analysis and policy integration
• Digital twins for real-time monitoring, data assimilation, and closed-loop control, validated by real or high-fidelity datasets
• Uncertainty and sensitivity analysis to inform monitoring design and control adjustments
• Sustainable process trains: membrane/adsorption/catalysis with models for fouling, regeneration, and system consistency
• Demonstration and scale-up studies on techno-economics, reproducibility, and scenario-based robustness