基于TVDI的近20 a吐鲁番市干旱及影响因素分析

doi:10.12118/j.issn.1000-6060.2024.234

摘要/Abstract

摘要：

全球温室效应加剧背景下，干旱监测对保障区域的生态安全、经济发展以及农业生产具有重要的指导意义。近年来，由于吐鲁番市自身地理位置、气候变化以及水资源短缺，其干旱问题愈发显著，阻碍了其自身以及周边地区社会经济的长期、稳定发展。基于2001—2022年的MODIS归一化植被指数（NDVI）和地表温度（LST）数据建立温度植被干旱指数（TVDI）模型，利用趋势分析、M-K趋势检验、地理探测器等方法揭示了吐鲁番市近20 a的干旱时空变化及特征、干旱演变规律并探讨了不同因素（气温、降雨量、潜在蒸散发、土地覆被类型、人口密度、高程、坡度）对TVDI的影响。结果表明：（1）吐鲁番市干旱区TVDI空间分布区域特征明显，自北向南呈逐渐递增趋势，吐鲁番市总体呈现干旱化加剧，其中有89.6%的区域TVDI呈现显著增加，仅有3.5%的区域为干旱程度未有加剧。（2）TVDI年际变化表明，吐鲁番市近20 a来的干旱程度呈增加趋势，TVDI月际变化呈明显季节差异，总体表现为春季>秋季>夏季。（3）单因素监测结果表明，吐鲁番市干旱变化趋势影响比重最大因素分别为潜在蒸散发、气温和高程；多因素交互作用下，潜在蒸散发与高程、气温、降水以及土地覆被因素相互作用共同驱动干旱化的发生为当地制定干旱防治措施、提高处理生态隐患和地缘风险的能力提供理论依据。

关键词: 干旱, 温度植被干旱指数（TVDI）, 趋势分析, 地理探测器, 吐鲁番市

Abstract:

In the context of an intensifying global greenhouse effect, accurate drought monitoring is critical for ensuring regional ecological security, economic development, and agricultural production. Turpan City, a key base for grape and cantaloupe cultivation in Xinjiang and a significant transportation hub on the Silk Road in China, holds a strategic position. In recent years, water resource scarcity due to the city’s geographic and climatic conditions has exacerbated drought issues, impeding the long-term and stable socio-economic development of Turpan City and its surrounding regions. This study establishes the temperature-vegetation drought index (TVDI) model using MODIS normalized difference vegetation index and land surface temperature data from 2001—2022. The spatial and temporal variations of drought in Turpan City over the past 20 years and its evolving patterns were analyzed using trend analysis, the Mann-Kendall trend test, and Geodetector methods. Additionally, the influence of various factors (including mean annual temperature, rainfall, potential evapotranspiration, land cover type, population density, elevation, and slope) on TVDI was investigated. The results indicate that: (1) The spatial distribution of TVDI in Turpan City exhibits distinct regional characteristics, with a gradual increase in aridity from north to south. Analysis of the trends reveals that the overall aridity of Turpan City has intensified, with 89.6% of the area showing a significant increase in TVDI, 6.9% showing a non-significant increase, and only 3.5% showing no increase in aridity. (2) The interannual trend of TVDI demonstrates a progressive increase in drought severity over the past 20 years, peaking in 2022. Notably, there are marked seasonal differences in the monthly variability of TVDI, generally following the order spring>autumn>summer. (3) Single-factor analysis highlights that potential evapotranspiration, temperature, and elevation are the top three factors influencing drought trends in Turpan City. Under multifactor interactions, potential evapotranspiration interacts with elevation, temperature, precipitation, and land cover to collectively drive aridification.

Key words: drought, temperature-vegetation drought index (TVDI), trend analysis, Geodetector, Turpan City

周孝明, 张喆, 张越, 王俣凝. 基于TVDI的近20 a吐鲁番市干旱及影响因素分析[J]. 干旱区地理, 2024, 47(12): 2104-2114.

ZHOU Xiaoming, ZHANG Zhe, ZHANG Yue, WANG Yuning. TVDI-based analysis of drought and influencing factors in Turpan City in the last 20 years[J]. Arid Land Geography, 2024, 47(12): 2104-2114.

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年份	拟合干边公式	R²	拟合湿边公式	R²
2001	T_s=51.1-41.1NDVI	0.85	T_s=3.97+74.6NDVI	0.75
2002	T_s=52.6-41.6NDVI	0.87	T_s=5.37+61.6NDVI	0.73
2003	T_s=54.4-43.3NDVI	0.86	T_s=3.11+75.0NDVI	0.77
2004	T_s=53.9-41.5NDVI	0.83	T_s=6.00+64.6NDVI	0.75
2005	T_s=53.2-38.5NDVI	0.89	T_s=3.05+65.5NDVI	0.78
2006	T_s=51.1-36.6NDVI	0.81	T_s=5.32+62.6NDVI	0.75
2007	T_s=51.1-36.7NDVI	0.86	T_s=4.48+56.9NDVI	0.68
2008	T_s=52.5-38.1NDVI	0.75	T_s=4.72+59.4NDVI	0.71
2009	T_s=52.1-37.4NDVI	0.87	T_s=4.90+56.8NDVI	0.67
2010	T_s=50.5-38.3NDVI	0.85	T_s=3.48+68.3NDVI	0.78
2011	T_s=51.8-37.4NDVI	0.84	T_s=3.68+69.7NDVI	0.75
2012	T_s=52.2-34.8NDVI	0.83	T_s=4.15+66.9NDVI	0.79
2013	T_s=53.0-37.0NDVI	0.86	T_s=3.95+54.6NDVI	0.69
2014	T_s=52.2-39.2NDVI	0.85	T_s=4.62+54.7NDVI	0.57
2015	T_s=52.3-35.1NDVI	0.88	T_s=2.06+65.8NDVI	0.74
2016	T_s=53.0-35.0NDVI	0.85	T_s=4.79+57.7NDVI	0.73
2017	T_s=52.7-33.5NDVI	0.86	T_s=3.76+63.9NDVI	0.77
2018	T_s=52.6-38.4NDVI	0.89	T_s=3.50+62.8NDVI	0.74
2019	T_s=51.7-35.5NDVI	0.78	T_s=4.56+56.5NDVI	0.71
2020	T_s=53.4-36.9NDVI	0.90	T_s=2.44+63.0NDVI	0.72
2021	T_s=54.0-36.5NDVI	0.81	T_s=4.06+58.7NDVI	0.76
2022	T_s=54.2-37.6NDVI	0.88	T_s=5.41+59.0NDVI	0.71

影响因子	气温	降雨量	蒸散发	坡度	高程	土地覆被类型	人口密度
气温	0.880^*	0.904	0.912	0.895	0.892	0.889	0.884
降雨量	-	0.789^*	0.914	0.833	0.890	0.844	0.802
蒸散发	-	-	0.906^*	0.909	0.911	0.911	0.908
坡度	-	-	-	0.504^*	0.882	0.684	0.514
高程	-	-	-	-	0.870^*	0.884	0.875
土地利用类型	-	-	-	-	-	0.486^*	0.548
人口密度	-	-	-	-	-	-	0.007^*