基于地理探测器的鄂尔多斯干旱时空变化驱动因素分析

doi:10.13866/j.azr.2024.12.01

干旱区研究 ›› 2024, Vol. 41 ›› Issue (12): 1981-1991.doi: 10.13866/j.azr.2024.12.01 cstr: 32277.14.AZR.20241201

基于地理探测器的鄂尔多斯干旱时空变化驱动因素分析

王思楠¹(), 吴英杰¹(), 王宏宙², 黎明扬³, 王飞⁴, 张雯颖⁴, 马小茗⁵, 于向前¹

1.水利部牧区水利科学研究所，内蒙古呼和浩特 010020
2.北京师范大学国家安全与应急管理学院，广东珠海 519087
3.山东省水利科学研究院，山东济南 250014
4.内蒙古水利事业发展中心，内蒙古呼和浩特 010020
5.内蒙古自治区水利科学研究院，内蒙古呼和浩特 010010

收稿日期:2024-05-21 修回日期:2024-09-13 出版日期:2024-12-15 发布日期:2024-12-20
通讯作者: 吴英杰. E-mail: 508188330@qq.com
作者简介:王思楠（1993-），男，博士，工程师，主要从事大范围干旱监测模拟研究. E-mail: nmgnydx2016@163.com
基金资助:
内蒙古自治区自然科学青年基金(2023QN05003);鄂尔多斯市科技计划项目(2022YY018);内蒙古自治区重点研发和成果转化计划(2022YFHH0100);国家自然科学基金(42072291);2022年度自治区本级引进高层次人才科研支持

Spatial and temporal drivers of drought analysis using the geodetector in Ordos

WANG Sinan¹(), WU Yingjie¹(), WANG Hongzhou², LI Mingyang³, WANG Fei⁴, ZHANG Wenying⁴, MA Xiaoming⁵, YU Xiangqian¹

1. Institute of Water Resources of Pastoral Area Ministry of Water Resources, Hohhot 010020, Inner Mongolia, China
2. School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, Guangdong, China
3. Water Resources Research Institute of Shandong Province, Jinan 250014, Shandong, China
4. Inner Mongolia Water Conservancy Development Center, Hohhot 010020, Inner Mongolia, China
5. Water Resources Research Institute of Inner Mongolia Autonomous Region, Hohhot 010010, Inner Mongolia, China

Received:2024-05-21 Revised:2024-09-13 Published:2024-12-15 Online:2024-12-20

摘要/Abstract

摘要：

干旱是鄂尔多斯市最严重的自然灾害之一，频发的干旱加剧土地荒漠化进程、导致草场植被退化。因此，研究该地区干旱对科学防旱抗旱、沙漠化治理与生态建设具有重要意义。基于干旱严重程度指数（Drought Severity Index，DSI），探究干旱的时空动态、变化趋势并利用地理探测器模型分析DSI空间分异性的驱动因子。结果表明：（1）鄂尔多斯蒸散发（Evapotranspiration，ET）和归一化植被指数（Normalized Difference Vegetation Index，NDVI）均呈显著增加趋势（P<0.05），增加速率依次为：4.291 mm·a^-1和0.004 a^-1。（2） DSI年际变化整体也呈显著上升趋势，趋势变化速率为0.089。ET和NDVI呈现出西南低、东北高的空间格局，潜在蒸散发（Potential Evapotranspiration，PET）呈现出西南高、东北低的空间格局，而DSI呈现西部干旱东部湿润的分布特征。（3） DSI的空间分异主要受气温、降水、土地利用类型、土壤类型和高程（Digital Elevation Model，DEM）等5个因子影响，是鄂尔多斯干旱的主要驱动因素；在多因子交互作用下，气温和DEM、降水和DEM、日照时数和DEM、相对湿度与DEM共同驱动干旱，其中降水（0.156）∩DEM（0.248）对干旱发生的影响力最强，q达到0.389。该研究结果可为鄂尔多斯生态环境保护和抗旱管理措施制定提供科学依据。

关键词: 鄂尔多斯, DSI干旱指数, 地理探测器, 时空变化, 驱动因素

Abstract:

Drought is a significant natural disaster in Ordos, exacerbating desertification and degrading grassland vegetation. Therefore, studying drought in this region is crucial for effective drought prevention, desertification control, and ecological restoration. In this study, we explored the spatiotemporal dynamics and trends of drought and analyzed the driving factors behind the spatial differentiation of DSI using a geographic detector model. The results show that evapotranspiration (ET) and the normalized difference vegetation index (NDVI) in the Ordos exhibit a significant increasing trend (P<0.05), with rates of 4.291 mm·a^-1 for ET and 0.004 a^-1 for NDVI. Additionally, the interannual variation of DSI also showed a significant increase, with a trend change rate of 0.089. ET and NDVI showed a spatial pattern, with lower values in the southwest and higher values in the northeast. Conversely, PET showed a spatial pattern of higher values in the southwest and lower values in the northeast. The DSI showed a dry spatial pattern in the west and a wet pattern in the east. The spatial differentiation of the DSI was primarily affected by five factors, such as air temperature, precipitation, land use type, soil type, and the digital elevation model (DEM), with q value exceeding 0.15, indicating these are the main driving factors of drought in the Ordos. Multiple factors interact to drive drought in Ordos, with four key combinations—temperature and DEM, precipitation and DEM, sunshine duration and DEM, and relative humidity and DEM. Among these, the combination of precipitation (0.156) and DEM (0.248) exerted the strongest influence on drought occurrence, with a q value of 0.389. This study can provide a scientific basis for ecological protection and drought management measures in the region.

Key words: Ordos, DSI drought index, geographical detector, spatial temporal change, driving factor

王思楠, 吴英杰, 王宏宙, 黎明扬, 王飞, 张雯颖, 马小茗, 于向前. 基于地理探测器的鄂尔多斯干旱时空变化驱动因素分析[J]. 干旱区研究, 2024, 41(12): 1981-1991.

WANG Sinan, WU Yingjie, WANG Hongzhou, LI Mingyang, WANG Fei, ZHANG Wenying, MA Xiaoming, YU Xiangqian. Spatial and temporal drivers of drought analysis using the geodetector in Ordos[J]. Arid Zone Research, 2024, 41(12): 1981-1991.

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交互作用	判定依据
非线性减弱	q(X₁∩X₂)<min[q(X₁), q(X₂)]
单因子非线性减弱	min[q(X₁), q(X₂)]<q(X₁∩X₂)<max[q(X₁), q(X₂)]
双因子增强	q(X₁∩X₂)>max[q(X₁), q(X₂)]
独立	q(X₁∩X₂)=q(X₁)+q(X₂)
非线性增强	q(X₁∩X₂)>q(X₁)+q(X₂)

基于地理探测器的鄂尔多斯干旱时空变化驱动因素分析

Spatial and temporal drivers of drought analysis using the geodetector in Ordos

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