Context: The rice-wheat (RW) system, spanning 13.5 million hectares in South Asia, is crucial for food security and livelihoods. However, intensive conventional tillage-based practices have harmed soil and environmental health, decreased productivity trends and increased greenhouse gas emissions. Objective: This study aims to develop resilient, climate-smart cropping systems within the RW system, focusing on soil and crop productivity, economic viability, and reduced greenhouse gas (GHG) emissions. Methods: Over eight years, the study evaluated diverse parameters compared to farmer practices (FP) in seven scenarios (Sc), including one representing FP (Sc1) and six based on conservation agriculture (CA) principles. The study assessed system crop productivity, economic returns, soil quality (organic carbon; OC, nitrogen; N, phosphorus; P, potassium; K contents, bulk density; BD, soil aggregation, infiltration rates, microbial counts, and earthworm density), and GHG emissions. Results: CA-based scenarios (Sc2 to Sc7) showed improved soil quality, lower bulk density, enhanced soil aggregation, and increased infiltration rates compared to Sc1. In the 0–15 cm layer, surface soil organic carbon (OC) and C stock were 63.7 % and 49.6 % higher, respectively, in CA-based scenarios. Additionally, available N, P and K contents in the surface layer increased by 10.2 %, 28.6 %, and 21.8 % under CA-based scenarios. Adoption of CA in intensified maize-based scenarios (Sc4 and Sc5) led to the increased system and economic yields, higher soil quality index (SQI), reduced GHG emissions and increased C stock compared to Sc1. Implications: The study highlights that Conservation Agriculture (CA) practices and diversified crop rotations can address issues like falling crop productivity, reduced economic returns, soil degradation, and increasing environmental impacts in northwestern India's traditional rice-wheat system. However, widespread adoption requires government policies, including C credit payments and guaranteed markets with supportive pricing.
