| Abstract: | ● Impacts of 30 cropping systems practiced on the North China Plain were evaluated. ● Trade-offs were assessed among productive, economic and environmental indicators. ● An evolutionary algorithm was used for multi-objective optimization. ● Conflict exists between productivity and profitability versus lower ground water decline. ● Six strategies were identified to jointly mitigate the trade-offs between objectives. Since the Green Revolution cropping systems have been progressively homogenized and intensified with increasing rates of inputs such as fertilizers, pesticides and water. This has resulted in higher crop productivity but also a high environmental burden due to increased pollution and water depletion. To identify opportunities for increasing the productivity and reducing the environmental impact of cropping systems, it is crucial to assess the associated trade-offs. The paper presents a model-based analysis of how 30 different crop rotations practiced in the North China Plain could be combined at the regional level to overcome trade-offs between indicators of economic, food security, and environmental performance. The model uses evolutionary multi-objective optimization to maximize revenues, livestock products, dietary and vitamin C yield, and to minimize the decline of the groundwater table. The modeling revealed substantial trade-offs between objectives of maximizing productivity and profitability versus minimizing ground water decline, and between production of livestock products and vitamin C yield. Six strategies each defining a specific combination of cropping systems and contributing to different extents to the various objectives were identified. Implementation of these six strategies could be used to find opportunities to mitigate the trade-offs between objectives. It was concluded that a holistic analysis of the potential of a diversity cropping systems at a regional level is needed to find integrative solutions for challenges due to conflicting objectives for food production, economic viability and environmental protection. |
