Aquaculture-planting system (APS) will enhance flood resilience and agricultural sustainability under global warming

Abstract

Climate change is intensifying extreme precipitation events and flooding, posing unprecedented challenges to agricultural sustainability. Here we evaluate a climate-adaptive agricultural innovation, the aquaculture-planting system implemented in China’s Jianghan Plain, by integrating multi-temporal Landsat imagery, long-term precipitation records, field-collected sediment samples, and socioeconomic statistics to assess its spatial-temporal expansion, flood resilience, ecological health, and economic performance. Over the past 30 years, this region has transformed 4,386 km² of flood-prone farmland into an integrated network of aquaculture zones that function as artificial wetlands, reaching a total area of 5,678 km² by 2023. Analysis of meteorological data reveals that extreme precipitation events now constitute 60 %-70 % of total summer rainfall in the region, up from 30 % in the 1960s. The aquaculture-planting system demonstrates remarkable flood resilience, with capacity to retain approximately 568 million cubic meters of floodwater. Moreover, the system yields significant economic benefits, generating combined net returns that significantly exceed traditional crop farming, with the aquaculture component alone yielding 63,000 CNY ha⁻¹ compared to traditional crop farming’s 25,200 CNY ha⁻¹. Sediment analysis shows that the system maintains ecological health through nutrient recycling while keeping heavy metal concentrations within safe limits. Our findings suggest that the aquaculture-planting system offers a viable model for flood-prone agricultural regions seeking to enhance climate resilience while promoting sustainable development.

Keywords

Climate change / Aquaculture / Circular economy / Climate adaptation pathways / Floods

CRediT authorship contribution statement

Ziwei Lin: Writing - original draft, Visualization, Formal analysis, Data curation. Tiezhu Shi: Validation, Methodology, Formal analysis, Data curation, Conceptualization. Chao Yang: Validation, Software, Methodology, Investigation. Wei Ma: Investigation, Data curation, Conceptualization.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported by the Hainan Provincial Technical Innovation Program for Provincial Research Institutes (KYYS-2019-12).

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geosus.2026.100436.

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