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现代地质 ›› 2024, Vol. 38 ›› Issue (03): 612-623.DOI: 10.19657/j.geoscience.1000-8527.2024.026

• 表生资源观测模拟与预测评价 • 上一篇    下一篇

1982—2020年黄河流域(河南段)NDVI动态演变及其与气候变化响应研究

姚瑞晨1(), 郝仕龙1(), 李秀萍1, 侯佳成1, 陈浩源1, 张岩2   

  1. 1.华北水利水电大学测绘与地理信息学院, 河南 郑州 450046
    2.河南省水土保持监测总站,河南 郑州 450002
  • 出版日期:2024-06-10 发布日期:2024-07-05
  • 通讯作者: 郝仕龙,男,教授, 1972年出生,主要从事水土资源与遥感技术应用研究。Email: haoshilong@ncwu.edu.cn。
  • 作者简介:姚瑞晨,男,硕士研究生,1996年出生,主要从事水土保持研究。Email:yaoruichen0327@163.com

Dynamic Evolution of the Vegetation and Its Response to Climate Changes from 1982 to 2020 in the Yellow River Basin (Henan Section)

YAO Ruichen1(), HAO Shilong1(), LI Xiuping1, HOU Jiacheng1, CHEN Haoyuan1, ZHANG Yan2   

  1. 1. School of Surveying, Mapping and Geographic Information, North China University of Water Resources and Hydropower, Zhengzhou, Henan 450046, China
    2. Henan Provincial Water and Soil Conservation Monitoring Station, Zhengzhou, Henan 450002, China
  • Online:2024-06-10 Published:2024-07-05

摘要:

基于GIMMS NDVI3g和MODIS NDVI数据,利用一元线性回归模型,本文构建了1982—2020年黄河流域(河南段)GIMMS-MODIS NDVI数据集;在此基础上,结合Sen趋势、Mann-Kendall(M-K)及偏相关分析等方法探究了黄河流域(河南段)NDVI时空演变及其对气候因子的响应。结果表明:(1)重构的GIMMS MODIS NDVI和GIMMS NDVI拟合效果较好,其R2达到了0.8799(P<0.01),二者的月均值直方图差值在[-0.02,0.02]之间的占比高达81.47%;(2)1982—2020年黄河流域(河南段)年和春、夏、秋、冬四季NDVI值均呈现波动增加的趋势,其增加速率分别为0.0018 a-1(P<0.01)、0.0027 a-1(P<0.01)、0.0006 a-1(P<0.1)、0.0013 a-1(P<0.01)和0.0024 a-1(P<0.01);空间上,该流域年和春、夏、秋、冬四季NDVI显著增加的面积占比分别为76.62%、76.62%、33.64%、57.19%和77.16%,显著下降的区域主要位于流域中南部地区;(3)1982—2020年黄河流域(河南段)年均气温呈现显著增加的趋势(slope=0.0377 ℃·a-1,P<0.01)。从季节变化来看,春季和秋季的平均气温增加速率最快,降水的变化在年及其春、夏、秋、冬四季变化均不显著;(4)1982—2020年黄河流域(河南段)年、春季及其冬季NDVI变化主要受到气温控制,夏季NDVI变化主要受降水影响;从空间分布来看,年、春季和冬季NDVI与气温呈显著相关的站点比例分别为82.14%、50%和75%,春季、夏季和秋季NDVI与降水呈显著正相关的站点比例分别为3.57%、14.29%和3.57%,主要零星分布在流域的中部地区。

关键词: 黄河流域河南段, NDVI, 时空演变, 气候变化

Abstract:

We constructed the GIMMS-MODIS NDVI dataset of the Yellow River Basin (Henan section) from 1982 to 2020 using a monadic linear regression model with the GIMMS NDVI3g and MODIS NDVI data. In this study, we also investigated the temporal and spatial evolution of NDVI and its response to climate factors in the Henan section of the Yellow River Basin by using Sen trend, Mann-Kendall (M-K) test, and partial correlation analysis. The results show that (1) the reconstructed GIMMS MODIS NDVI and GIMMS NDVI have a better fitting index with the R2 of 0.879,9(P<0.01). The discrepancy of the monthly mean difference between GIMMS MODIS NDVI and GIMMS NDVI is ±0.02, between 81.47%. (2) From 1982 to 2020, the NDVI values in the Yellow River Basin (Henan section) showed an increasing trend in the annual and each season from spring to winter, and the increase rates were 0.001,8 a-1 (P<0.01), 0.002,7 a-1 (P<0.01), 0.000,6 a-1 (P<0.1), 0.001,3 a-1 (P<0.01) and 0.002,4 a-1 (P<0.01), respectively. Spatially, the proportions of proparea with significant increase of NDVI in the interannual and each season were 76.62%, 76.62%, 33.64%, 57.19% and 77.16%, respectively. The area with significant decrease was mainly distributed in the central and southern part of the basin. (3) From 1982 to 2020, the average annual temperature in the Yellow River Basin (Henan Section) showed a significant increasing trend (Trend=0.037,7 ℃·a-1, P<0.01). In terms of seasonal changes, the average temperature in spring and autumn increased at the fastest rate and the precipitation change was not pronounced along the year. (4) The annual, spring and winter NDVI changes in the Yellow River Basin from 1982 to 2020 were mainly controlled by temperature, and the summer NDVI changes were mainly affected by precipitation. In terms of spatial distribution, 82.14%, 50% and 75% of stations showed significant correlations between NDVI and temperature in annual, spring and winter, respectively. Moreover, 3.57%, 14.29% and 3.57% of stations showed significant positive correlations between NDVI and precipitation in spring, summer and autumn, respectively, which mainly are distributed in the central part of the basin.

Key words: Henan section of the Yellow River Basin, NDVI, spatial and temporal evolution, climate change

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