| 引用本文: | 霍 红,赵 轩,雷文文,等.典型干热河谷区干旱时空变化特征及驱动力分析[J].灌溉排水学报,2025,44(7):80-88. |
| HUO Hong,ZHAO Xuan,LEI Wenwen,et al.典型干热河谷区干旱时空变化特征及驱动力分析[J].灌溉排水学报,2025,44(7):80-88. |
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| 摘要: |
| 【目的】西南干热河谷是我国重要的生态功能区和典型的生态脆弱区。从时空尺度深入分析西南典型干热河谷区干旱变化趋势并探究其主要驱动因子，以期为区域干旱监测预警及防旱减灾提供参考依据。【方法】以云南金沙江-元江典型干热河谷区为研究区域，基于2001—2020年的地表温度（LST）和归一化植被指数（NDVI）构建温度植被干旱指数（TVDI），结合相应时段的年均气温、降水量、蒸散发、夜间灯光亮度等数据，通过分段线性回归模型、Mann-Kendall检验、Theil-Sen趋势分析、地理探测器、相关性分析等方法，从时空尺度系统分析典型干热河谷区干旱时空变化特征及驱动因子。【结果】年际尺度上，2001—2020年云南金沙江-元江干热河谷区干旱总体呈波动下降趋势，干旱状况于2018年发生突变，突变后干旱明显加剧；空间尺度上，研究区48.1%的区域表现出中度及重度干旱，其中金沙江流域的元谋、华坪、宾川、永仁等县以及元江流域沿岸仍是严重干旱发生的主要区域且有显著增强趋势，应考虑将这些区域作为干旱重点监测区和风险控制区；而研究区东北部和西北部区域干旱显著缓解。自然因素，特别是气温、海拔和蒸散发是影响研究区干旱状况的主要因子，人类活动影响则相对较弱。【结论】研究区2001—2020年整体表现为干旱缓解状态，干旱空间异质性较高，自然因素对干旱变化有重要作用。 |
| 关键词: 气候变化；干热河谷；干旱变化；驱动因素；灾害防控 |
| DOI：10.13522/j.cnki.ggps.2024322 |
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| Spatiotemporal variability of drought in representative dry-hot valley regions of Southwest China |
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HUO Hong, ZHAO Xuan, LEI Wenwen, SUN Changping
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1. College of Architecture and Civil Engineering, Kunming University, Kunming 650214, China;
2. Southwest Nonferrous Kunming Exploration Surveying and Designing (Institute) Inc., Kunming 650217, China;
3. Southwest Survey and Planning Institute of National Forestry and Grassland Administration, Kunming 650031, China
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| Abstract: |
| 【Objective】Extreme weather events like drought are expected to become more frequent in the context of climate change. Studying and understanding its spatiotemporal variation and the underlying drivers is critical to mitigating its detrimental impact. This paper analyzes drought trends and their influencing factors in a representative region in Southwest China.【Method】The study region is the Jinsha-Yuan River dry-hot valley in Yunnan Province. Using land surface temperature and the normalized difference vegetation index, we constructed a temperature vegetation dryness Index (TVDI). We then integrated natural and anthropogenic factors, including annual mean temperature, precipitation, evapotranspiration, and nighttime light intensity, and applied piecewise linear regression, the Mann-Kendall test, Theil-Sen slope estimation, GeoDetector, and correlation analysis to investigate the spatiotemporal changes in TVDI from 2001 to 2020 in the region.【Result】Temporally, TVDI exhibited a generally decreasing trend though with fluctuations. However, a significant shift occurred in 2018, after which drought became worse. Spatially, 48.1% of the area experienced moderate to severe drought, with Yuanmou, Huaping, Binchuan, and Yongren counties in the Jinsha River Basin and areas along the Yuan River identified as drought hotspots, which require priority monitoring and control. In contrast, there was less drought in Northeast and Northwest of the region. Temperature, altitude and evapotranspiration were the natural factors that affected drought variation the most, while human influence was relatively minor compared to natural factors. 【Conclusion】From 2001 to 2020, drought conditions across the study area generally improved, though with notable spatial heterogeneity. Natural environmental variables played a key role in shaping drought dynamics, underscoring their importance in regional drought risk assessment and management. |
| Key words: climate change; dry-hot valley; drought variation; driving factors; disaster prevention and control |
