Risk assessment and climate adaptation research for agricultural cultivation and water resource systems within rural green production models
- 1School of Water Resources and Hydropower Engineering, North China Electric Power University
- 2Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences
Abstract
In the context of global climate change, analyzing the evolution patterns of climate and extreme hydrological events in rural watersheds, and evaluating the adaptability of green agricultural production methods, are crucial for building climate-resilient agricultural systems. Taking the Chen Village Green Agriculture Demonstration Zone in Jiangsu Province as the research object, this study integrates historical observations and multi-scenario reanalysis data to systematically reveal the spatiotemporal evolution characteristics of regional climate and extreme precipitation during the historical period of 1961–2021 and the future period of 2030–2060. Furthermore, by coupling crop growth with meteorological and soil hydrological processes, this study innovatively constructs an Agricultural Production Hydro-Climatic Suitability Index (P) and an Agricultural Water Resource Risk Index (R), quantitatively identifying risk thresholds and response potentials of regional agricultural production under multiple scenarios. The results indicate that: (1) A significant warming trend is observed for the future period of 2030–2060, while precipitation and extreme precipitation changes show clear scenario dependence; under SSP585, reduced precipitation and declining available water resources become more prominent. (2) The constructed suitability index P shows a significant positive correlation with crop yield (r = 0.9), demonstrating good representational accuracy. Under climate pressure, P values in all future scenarios decrease significantly compared to the historical mean (0.43), revealing the strong inhibitory effect of climate change on agricultural production. (3) The Agricultural Water Resource Risk Index (R) shows pronounced scenario differentiation: under the Conventional farming scenario, the historical mean R value is 0.89, while future R values increase to 0.99, 1.03, 1.52, and 6.86 under SSP126, SSP245, SSP370, and SSP585, respectively. Under medium- and low-emission scenarios, the risk is mainly associated with precipitation-related extremes, whereas under high-emission scenarios, drought-related risk increases due to sharply reduced available water resources and intensified irrigation deficits. (4) The Green agriculture scenario demonstrates significant regulatory potential, effectively reducing the annual average irrigation water demand by 10.6–27.4% and mitigating climate risks.
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BibTeX
@article{ding2026risk,
title = {{Risk assessment and climate adaptation research for agricultural cultivation and water resource systems within rural green production models}},
author = {Junwei Ding and Yi Wang and Yule Liu and Chenglin Cao and Wen Chen},
journal = {Scientific Reports},
year = {2026},
month = jul,
doi = {10.1038/s41598-026-63081-2},
url = {https://doi.org/10.1038/s41598-026-63081-2},
note = {CC BY},
}
RIS
TY - JOUR
TI - Risk assessment and climate adaptation research for agricultural cultivation and water resource systems within rural green production models
AU - Junwei Ding
AU - Yi Wang
AU - Yule Liu
AU - Chenglin Cao
AU - Wen Chen
PY - 2026
DA - 2026/07/01
JO - Scientific Reports
DO - 10.1038/s41598-026-63081-2
UR - https://doi.org/10.1038/s41598-026-63081-2
AB - In the context of global climate change, analyzing the evolution patterns of climate and extreme hydrological events in rural watersheds, and evaluating the adaptability of green agricultural production methods, are crucial for building climate-resilient agricultural systems. Taking the Chen Village Green Agriculture Demonstration Zone in Jiangsu Province as the research object, this study integrates historical observations and multi-scenario reanalysis data to systematically reveal the spatiotemporal evolution characteristics of regional climate and extreme precipitation during the historical period of 1961–2021 and the future period of 2030–2060. Furthermore, by coupling crop growth with meteorological and soil hydrological processes, this study innovatively constructs an Agricultural Production Hydro-Climatic Suitability Index (P) and an Agricultural Water Resource Risk Index (R), quantitatively identifying risk thresholds and response potentials of regional agricultural production under multiple scenarios. The results indicate that: (1) A significant warming trend is observed for the future period of 2030–2060, while precipitation and extreme precipitation changes show clear scenario dependence; under SSP585, reduced precipitation and declining available water resources become more prominent. (2) The constructed suitability index P shows a significant positive correlation with crop yield (r = 0.9), demonstrating good representational accuracy. Under climate pressure, P values in all future scenarios decrease significantly compared to the historical mean (0.43), revealing the strong inhibitory effect of climate change on agricultural production. (3) The Agricultural Water Resource Risk Index (R) shows pronounced scenario differentiation: under the Conventional farming scenario, the historical mean R value is 0.89, while future R values increase to 0.99, 1.03, 1.52, and 6.86 under SSP126, SSP245, SSP370, and SSP585, respectively. Under medium- and low-emission scenarios, the risk is mainly associated with precipitation-related extremes, whereas under high-emission scenarios, drought-related risk increases due to sharply reduced available water resources and intensified irrigation deficits. (4) The Green agriculture scenario demonstrates significant regulatory potential, effectively reducing the annual average irrigation water demand by 10.6–27.4% and mitigating climate risks.
SN - 2045-2322
ER -