Risk evaluation of low temperature disaster in greenhouses based on GIS spatial analysis under climate change: a case study in Hebei province, China

To improve the scientific planning of crop cultivation regions, enhance crop quality, mitigate meteorological disaster risks, and optimize the utilization of climatic resources, this study analyzed temperature data from 141 national meteorological stations covering the period from 1975 to 2022 in Hebei, China. Additionally, the future climate projection data under different emission scenarios (SSP2-4.5 and SSP5-8.5) derived from the BCC-CSM2-MR model of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were also analyzed. Seven types of greenhouses with varying heat-retaining capacities were selected as representative facilities. The low-temperature disaster index (LTDI), based on the assurance rate method, and the low-temperature risk index (LTRI), calculated using an equal-weight method, were employed to evaluate the risk of low-temperature disasters in facility agriculture. Furthermore, GIS-based spatial analysis was utilized to delineate low-temperature disaster risk regions, enabling a comprehensive evaluation of the low-temperature disaster risks across different regions of Hebei during the winter months. The results indicate that the climate probability and occurrence frequency of low temperatures (LTDI ≤−8 °C and ≤−10 °C) are high, exceeding 0.8 in most regions of Hebei. In regions with plastic greenhouses, southern Hebei is categorized as a low-risk region, whereas other regions face moderate to high risks. Single-layer plastic greenhouses are unsuitable for winter agriculture, while insulated plastic greenhouses are feasible in southern Hebei. In regions with solar greenhouses, the Zhangjiakou and Chengde districts are identified as extremely severe risk regions. Under the two climate change scenarios (SSP2-4.5 and SSP5-8.5), the low-temperature disaster risk for facility agriculture in Hebei exhibits an overall decreasing trend, though with notable regional variability. These findings provide valuable theoretical guidance for meteorological disaster prediction, risk reduction, and future mitigation strategies. They also inform the strategic planning of facility agriculture in Hebei, tailored to regional conditions.