Weather and Climate

Spatiotemporal variations in drought conditions in Xinjiang based on TVDI

  • LI Xiaopeng ,
  • LI Kang ,
  • LEI Shuang ,
  • JIA Fugui ,
  • XU Jing
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  • 1. School of Agricultural and Forestry Economics and Management, Lanzhou University of Finance and Economics, Lanzhou 730000, Gansu, China
    2. School of Accounting, Lanzhou University of Finance and Economics, Lanzhou 730000, Gansu, China

Received date: 2024-11-29

  Revised date: 2024-12-28

  Online published: 2025-04-10

Abstract

Drought is a significant factor affecting the ecological stability and agricultural productivity of Xinjiang. Timely drought monitoring is crucial for ensuring food security in the region. This study constructed the TVDI based on the Land Surface Temperature and the Normalized Difference Vegetation Index derived from the MODIS data between 2001 and 2020. This study explores the spatial distribution characteristics of drought in Xinjiang and its potential future evolution trends. The results indicate that: (1) On average, 78.7% of the region experiences drought of varying degrees, with a mean TVDI of 0.58 over the past two decades, suggesting a generally mild drought. (2) Future drought conditions in Xinjiang are expected to ease, with a TVDI decline rate of 0.0017 per year, and 81% of the region showing a trend toward increasing moisture levels. (3) TVDI correlates weakly with meteorological factors but strongly with elevation. When the degree of drought is relatively high, unused land contributes significantly to the TVDI, whereas grassland contributes significantly to the TVDI when the degree of drought is relatively low. Additionally, the unused land area correlates positively with drought, whereas forest and grassland areas correlate negatively with drought. These findings highlight the importance of reducing unused land and expanding forest and grassland areas to mitigate drought conditions.

Cite this article

LI Xiaopeng , LI Kang , LEI Shuang , JIA Fugui , XU Jing . Spatiotemporal variations in drought conditions in Xinjiang based on TVDI[J]. Arid Zone Research, 2025 , 42(4) : 589 -599 . DOI: 10.13866/j.azr.2025.04.02

References

[1] 黄睿茜, 赵俊芳, 霍治国, 等. 深度学习技术在农业干旱监测预测及风险评估中的应用[J]. 中国农业气象, 2023, 44(10): 943-952.
  [Huang Ruiqi, Zhao Junfang, Huo Zhiguo, et al. Application of deep learning technology in monitoring, forecasting and risk assessment of agricultural drought[J]. Chinese Journal of Agrometeorology, 2023, 44(10): 943-952.]
[2] Abbas H, Ali Z. A novel statistical framework of drought projection by improving ensemble future climate model simulations under various climate change scenarios[J]. Environmental Monitoring and Assessment, 2024, 196(10): 938.
[3] 龚栋栋, 高凡, 吴彬, 等. 基于GRACE的新疆平原区地下水干旱时空变化及其对气象干旱的响应[J]. 干旱区地理, 2024, 47(9): 1496-1507.
  [Gong Dongdong, Gao Fan, Wu Bin, et al. Spatiotemporal change of groundwater drought in the plain area of Xinjiang based on GRACE and its response to meteorological drought[J]. Arid Land Geography, 2024, 47(9): 1496-1507.]
[4] 董通. 新疆干旱时空演变特征及其对草地物候影响研究[D]. 乌鲁木齐: 新疆农业大学, 2022.
  [Dong Tong. The Satiotemporal Eolution of Dought and Its Effect on Grassland Phenology in Xinjiang[D]. Urumqi: Xinjiang Agricultural University, 2022.]
[5] 徐云蕾. 东北三省玉米干旱遥感监测及其对产量变化的影响分析[D]. 合肥: 安徽大学, 2023.
  [Xu Yunlei. Remote Sensing Monitoring of Drought in Maize and Its Impact on Yield Change in the Three Provinces of Northeast China[D]. Hefei: Anhui University, 2023.]
[6] 沙莎, 王丽娟, 王小平, 等. 基于温度植被干旱指数(TVDI)的甘肃省农业干旱监测方法研究[J]. 干旱气象, 2024, 42(1): 27-38.
  [Sha Sha, Wang Lijuan, Wang Xiaoping, et al. Study on monitoring method of agricultural drought in Gansu Province based on Temperature Vegetation Dryness Index[J]. Journal of Arid Meteorology, 2024, 42(1): 27-38.]
[7] Sandholt I, Rasmussen K, Andersen J. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J]. Remote Sensing of Environment, 2002, 79(2): 213-224.
[8] 王鹏新, 龚健雅, 李小文. 条件植被温度指数及其在干旱监测中的应用[J]. 武汉大学学报(信息科学版), 2001(5): 412-418.
  [Wang Pengxin, Gong Jianya, Li Xiaowen. Vegetation-temperature condition index and its application for drought monitoring[J]. Geomatics and Information Science of Wuhan University, 2001(5): 412-418.]
[9] 陈斌, 张学霞, 华开, 等. 温度植被干旱指数(TVDI)在草原干旱监测中的应用研究[J]. 干旱区地理, 2013, 36(5): 930-937.
  [Chen Bin, Zhang Xuexia, Hua Kai, et al. Application study of temperature vegetation drought index(TVDI) in grassland drought monitoring[J]. Arid Land Geography, 2013, 36(5): 930-937.]
[10] 康尧, 郭恩亮, 王永芳, 等. 温度植被干旱指数在蒙古高原干旱监测中的应用[J]. 应用生态学报, 2021, 32(7): 2534-2544.
  [Kang Yao, Guo Enliang, Wang Yongfang, et al. Application of temperature vegetation dryness index for drought monitoring in Mongolian Plateau[J]. Chinese Journal of Applied Ecology, 2021, 32(7): 2534-2544.]
[11] Wang Y, Wu Y, Ji L, et al. Assessing the spatial-tmporal pattern of spring maize drought in Northeast China using an optimised remote sensing index[J]. Remote Sensing, 2023, 15(17): 4171.
[12] 王椰, 史海静, 姜艳敏, 等. 基于TVDI的黄土高原干旱时空变化与其影响因素[J]. 农业机械学报, 2023, 54(7): 184-195.
  [Wang Ye, Shi Haijing, Jiang Yanmin, et al. Spatio-temporal variation of drought characteristics and its influencing factors in Loess Plateau based on TVDI[J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(7): 184-195.]
[13] 覃艺, 张廷斌, 易桂花, 等. 2000年以来内蒙古生长季旱情变化遥感监测及其影响因素分析[J]. 自然资源学报, 2021, 36(2): 459-475.
  [Qin Yi, Zhang Tingbin, Yi Guihua, et al. Remote sensing monitoring and analysis of influencing factors of drought in Inner Mongolia growing season since 2000[J]. Journal of Natural Resources, 2021, 36(2): 459-475.]
[14] Younes K, Saeid H, Andre S. An integrated dryness index based on geographically weighted regression and satellite earth observations[J]. The Science of the Total Environment, 2023, 911: 168807.
[15] 韩凯旭, 康乾坤, 贺金鑫, 等. 基于TVDI指数的四平市梨树县夏玉米生育期干旱监测[J]. 安徽农业科学, 2020, 48(9): 81-84, 87.
  [Han Kaixu, Kang Qiankun, He Jinxin, et al. Drought monitoring of summer maize growth period in Lishu County of Siping City based on TVDI index[J]. Journal of Anhui Agricultural Sciences, 2020, 48(9): 81-84, 87.]
[16] 许超杰, 窦燕, 孟琪琳. 基于EMD-GWO-LSTM模型的新疆标准化降水蒸散指数预测方法研究[J]. 干旱区研究, 2024, 41(4): 527-539.
  [Xu Chaojie, Dou Yan, Meng Qilin. Prediction of the standardized precipitation evapotranspiration index in the Xinjiang region using the EMD-GWO-LSTM model[J]. Arid Zone Research, 2024, 41(4): 527-539.]
[17] 黄静, 张运, 汪明秀, 等. 近17年新疆干旱时空分布特征及影响因素[J]. 生态学报, 2020, 40(3): 1077-1088.
  [Huang Jing, Zhang Yun, Wang Mingxiu, et al. Spatial and temporal distribution characteristics of drought and its relationship with meteorological factors in Xinjiang in last 17 years[J]. Acta Ecologica Sinica, 2020, 40(3): 1077-1088.]
[18] 迪里胡玛尔·阿汗木江, 玉素甫江·如素力, 亚夏尔·艾斯克尔. 基于TVDI的天山新疆段土壤湿度时空分布及影响因素分析[J]. 测绘工程, 2022, 31(5): 61-69.
  [Dilihumaer Ahanmujiang, Yusufujiang Rusuli, Yaxiaer Aisikeer. Temporal and spatial distribution of soil moisture and its influencing factors in Xinjiang section of Tianshan Mountains based on TVDI[J]. Engineering of Surveying and Mapping, 2022, 31(5): 61-69.]
[19] 张皓哲, 薛亚永, 马圆圆, 等. 新疆绿洲生态系统固碳潜力研究[J]. 干旱区研究, 2024, 41(6): 998-1009.
  [Zhang Haozhe, Xue Yayong, Ma Yuanyuan, et al. Carbon sequestration potential of oasis ecosystem in Xinjiang, China[J]. Arid Zone Research, 2024, 41(6): 998-1009.]
[20] 褚家琦, 蒋志辉. 新疆农业水资源绿色效率时空演变及影响因素研究[J]. 干旱区地理, 2024, 47(7): 1231-1241.
  [Chu Jiaqi, Jiang Zhihui. Spatiotemporal evolution and influencing factors of green efficiency of agricultural water resources in Xinjiang[J]. Arid Land Geography, 2024, 47(7): 1231-1241.]
[21] Liu Y, Wu L, Yue H. Biparabolic NDVI-Ts space and soil moisture remote sensing in an arid and semi-arid area[J]. Canadian Journal of Remote Sensing, 2015, 41(3): 159-169.
[22] 王欣毅, 杨洁, 林良国, 等. 基于Sen+Mann-Kendall陕西省植被覆盖度时空变化规律研究[J]. 农业与技术, 2023, 43(7): 62-66.
  [Wang Xinyi, Yang Jie, Lin Liangguo, et al. Study on the spatio-temporal variation of vegetation coverage in Shaanxi Province based on the Sen+Mann-Kendall method[J]. Agriculture and Technology, 2023, 43(7): 62-66.]
[23] 刘智源, 李继红. 2000—2020年黑龙江省植被时空变化对气候因子响应[J]. 森林工程, 2024, 40(1): 85-97.
  [Liu Zhiyuan, Li Jihong. Responses of temporal and spatial changes of vegetation to climate factors in Heilongjiang Province from 2000 to 2020[J]. Forest Engineering, 2024, 40(1): 85-97.]
[24] 范虎, 党星海, 赵健赟, 等. 基于温度植被干旱指数的西北干旱区干旱时空变化[J]. 科学技术与工程, 2024, 24(27): 11537-11546.
  [Fan Hu, Dang Xinghai, Zhao Jianyun, et al. Temporal and spatial variation of drought in Northwest arid region based on temperature vegetation drought index[J]. Science Technology and Engineering, 2024, 24(27): 11537-11546.]
[25] 汤连盟, 吕伟才, 蒲涛, 等. 西北地区干旱时空动态分布及成因分析[J]. 遥感信息, 2023, 38(5): 66-72.
  [Tang Lianmeng, Lv Weicai, Pu Tao, et al. Spatio-temporal dynamic distribution and cause analysis of dought in Northwest China[J]. Remote Sensing Information, 2023, 38(5): 66-72.]
[26] 王姣妍. 基于MSWEP降水产品的新疆干旱时空特征分析[J]. 干旱区研究, 2022, 39(5): 1398-1409.
  [Wang Jiaoyan. Study on spatiotemporal characteristics of drought in Xinjiang based on Multi-Source Weighted-Ensemble Precipitation multi-source merged precipitation product[J]. Arid Zone Research, 2022, 39(5): 1398-1409.]
[27] 尹本酥, 李振发, 岳蓉, 等. 基于温度植被干旱指数的关中地区旱情监测[J]. 农业工程学报, 2024, 40(17): 111-119.
  [Yin Bensu, Li Zhenfa, Yue Rong, et al. Monitoring drought in Guanzhong areas using temperature-vegetation drought index[J]. Transactions of the Chinese Society of Agricultural Engineering, 2024, 40(17): 111-119.]
[28] 李雯晴, 赵勇, 刘招, 等. 2001—2020年渭北黄土台塬区农业干旱变化特征及影响因素分析[J]. 水资源与水工程学报, 2024, 35(5): 1-10, 19.
  [Li Wenqing, Zhao Yong, Liu Zhao, et al. Characteristics of agricultural drought and its influencing factors in the Loess Tableland of the north of the Wei River from 2001-2020[J]. Journal of Water Resources and Water Engineering, 2024, 35(5): 1-10, 19.]
[29] 覃佳盛, 杨婷, 吕洋. 1980—2022年我国骤旱特征及趋势分析[J]. 中山大学学报(自然科学版中英文), 2024, 63(5): 48-62.
  [Qin Jiasheng, Yang Ting, Lv Yang. Flash drought pattern and trend in China during 1980-2022[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni (Chinese and English Edition), 2024, 63(5): 48-62.]
[30] Chen Guojian, Fang Ning, Li Jianfeng, et al. Spatiotemporal variation and drivers of drought based on TVDI in the lower reaches of the Jinsha River[J]. Journal of Resources and Ecology, 2024, 15(1): 44-54.
[31] 蒋烨林, 王让会, 彭擎, 等. 干旱区景观格局演变及碳收支状况研究: 以塔里木盆地为例[J]. 生态与农村环境学报, 2019, 35(7): 875-884.
  [Jiang Yelin, Wang Ranghui, Peng Qing, et al. Study on landscape changes and carbon budget situation in arid land: A case study in Tarim Basin, Xinjiang[J]. Journal of Ecology and Rural Environment, 2019, 35(7): 875-884.]
[32] 吴万民, 刘涛, 陈鑫. 西北干旱半干旱区NDVI季节性变化及其影响因素[J]. 干旱区研究, 2023, 40(12): 1969-1981.
  [Wu Wanmin, Liu Tao, Chen Xin. Seasonal changes of NDVI in the arid and semi-arid regions of Northwest China and its influencing factors[J]. Arid Zone Research, 2023, 40(12): 1969-1981.]
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