Sustainable Agricultural Residue Management in the Indo-Gangetic Plains for Cost-Effective Climate and Water Resilience

The efficient utilization of agricultural residues is essential to reduce waste and advance the transition to a low-carbon, resource-circular bioeconomy in any country. This study presents a multiobjective optimization framework for the spatial allocation and capacity design of biomass processing facilities, integrating the economic, logistical, and environmental trade-offs under climate-water resilience constraints. Using district-level residue availability and climate exposure-water stress indices (CEI-WSI), the model identifies 200 new facilities that can be established and integrates them with existing plants in Uttar Pradesh, India. The baseline model evaluates the current system comprising 46 facilities that process approximately 0.40 Mt · y –1 residues. The final optimized configuration links 36 source districts, 16 collection hubs, and 246 processing sites in the study regions, increasing residue utilization to 1.21 Mt · y –1 and reducing network vulnerability by 32% relative to the baseline. Despite higher total costs and emissions, emission intensity declines by 67% and the combined configuration achieves a 28% reduction in normalized flow centrality, indicating improved load distribution and enhanced structural resilience of the supply network. Although total system costs and emissions increase with higher residue input in the final optimized configuration, unit performance improves substantially, with lower processing costs per ton and reduced emissions intensity. Decentralizing the medium-scale biogas, biocoal, and biodiesel plants in low CEI-WSI districts enhances both spatial efficiency and adaptive capacity. Policy translation of these outcomes suggests that distributed infrastructure may improve emission intensity and network resilience under the modeled techno-economic and climate-water constraints, while practical deployment would require phased feasibility assessment and regional planning alignment to advance SDG 7 (Clean Energy), SDG 9 (Industry and Infrastructure), SDG 12 (Responsible Production), and SDG 13 (Climate Action). The framework offers a scalable, data-driven planning and decision-support approach for designing circular bioresource networks that align with economic feasibility in the emerging agrarian economies.