Jia et al. (2026) Land–Water Allocation, Yield Stability, and Policy Trade-Offs Under Climate Change: A System Dynamics Analysis

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Systems
• Year: 2026
• Date: 2026-04-08
• Authors: XiaoJing Jia, Ruiqi Zhang
• DOI: 10.3390/systems14040412

Research Groups

Not explicitly specified in the provided paper text.

Short Summary

This study develops an integrated ML–SD–NSGA-II framework to optimize crop areas and irrigation depths, balancing profit, water productivity, and yield stability under climate change. Applied to a rice–wheat system, it demonstrates improved irrigation water productivity and reveals a scarcity-regime threshold where economic instruments become less effective under severe drought.

Objective

• To develop and apply an integrated Machine-learning–System-dynamics–Non-dominated-sorting-genetic-algorithm-II (ML–SD–NSGA-II) framework for multi-objective optimization of crop areas and irrigation depths, aiming to maximize profit and irrigation water productivity while minimizing yield deviation, considering long-horizon meteorological scenarios and policy instruments.

Study Configuration

• Spatial Scale: A rice–wheat irrigation system within the middle Yangtze River Basin.
• Temporal Scale: Daily climate sequences generated over a long horizon, with analysis of multi-year scenarios including normal and extreme drought conditions.

Methodology and Data

• Models used: Machine Learning (ML) for meteorological scenario generation, System Dynamics (SD) for simulating soil moisture, yield formation, basin-scale allocable water, and farm returns, and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) for multi-objective optimization.
• Data sources: Daily climate sequences generated by ML models. The SD model integrates data related to crop–water–economy feedback. Specific raw data sources (e.g., satellite, observation, reanalysis) are not detailed in the provided text.

Main Results

• Knee-point solutions achieved approximately 14% increase in irrigation water productivity, maintained near-baseline profits, and reduced yield deviation.
• Economic instruments like block tariffs primarily curb low-value water use during normal hydrological years.
• Under extreme drought conditions, physical water scarcity dominates, rendering economic tools less effective for buffering.
• The study identified a scarcity-regime threshold beyond which economic instruments become secondary to binding biophysical constraints.

Contributions

• Proposes an integrated decision framework that simultaneously optimizes cropping patterns and irrigation schedules, embedding yield robustness and policy instruments, which is a gap in existing literature.
• Provides a transparent framework for ex ante testing of tariff–subsidy packages to inform irrigation governance and adaptation strategies.
• Reveals the existence and implications of a scarcity-regime threshold, highlighting the limitations of economic instruments under severe biophysical water scarcity.

Funding

Not specified in the provided paper text.

Citation

@article{Jia2026LandWater,
  author = {Jia, XiaoJing and Zhang, Ruiqi},
  title = {Land–Water Allocation, Yield Stability, and Policy Trade-Offs Under Climate Change: A System Dynamics Analysis},
  journal = {Systems},
  year = {2026},
  doi = {10.3390/systems14040412},
  url = {https://doi.org/10.3390/systems14040412}
}