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

doi:10.19657/j.geoscience.1000-8527.2024.026

Abstract

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

CLC Number:

P962

YAO Ruichen, HAO Shilong, LI Xiuping, HOU Jiacheng, CHEN Haoyuan, ZHANG Yan. Dynamic Evolution of the Vegetation and Its Response to Climate Changes from 1982 to 2020 in the Yellow River Basin (Henan Section)[J]. Geoscience, 2024, 38(03): 612-623.

Figures/Tables 15

Table 1 Distribution of land use types in the Yellow River Basin (Henan section) in 2000 and 2020

年份	土地类型	耕地	林地	草地	水体	建设用地	未利用地
2000	类型面积(km²)	22065	8219	4080	1533	2907	117
2000	类型比例(%)	56.69	21.12	10.48	3.94	7.47	0.30
2020	类型面积(km²)	21177	8208	3540	1344	4908	13
2020	类型比例(%)	54.04	20.94	9.03	3.43	12.52	0.03

Fig.1 Land use in the study area of the Yellow River Basin (Henan Section)

Table 2 Data profile of meteorology and land use

参数	数据来源	空间分辨率(km)	时间分辨率(d)	数据名称
NDVI	GIMMS NDVI	8	15	美国国家航空航天局
NDVI	MODIS NDVI	1	30	美国国家航空航天局
气象数据	气温	—	1	中国气象数据网
气象数据	降水	—	1	中国气象数据网
辅助数据	土地利用	1	1	资源环境科学与数据中心

Fig.2 Monthly (a) and multi-year monthly average (b) changes of GIMMS NDVI and MODIS NDVI in the Yellow River Basin (Henan section) from 2001 to 2015

Fig.3 Scatterplot (a) and difference histogram (b) of GIMMS NDVI and GIMMS MODIS NDVI before and after the reconstruction

Fig.4 Time variation trend of annual average (a) and seasonal (b) NDVI in the Yellow River Basin (Henan section) from 1982 to 2020

Fig.5 Annual NDVI trend (a) and significance (b) spatial distribution in the Yellow River Basin (Henan section) from 1982 to 2020

Fig.6 NDVI trend and spatial pattern of significance in spring, summer, autumn, and winter of the Yellow River Basin (Henan section) from 1982 to 2020

Fig.7 Temporal variation trends of annual and seasonal temperature and precipitation in the Yellow River Basin (Henan section) from 1982 to 2020

Table 3 Partial correlation coefficients between NDVI and precipitation and temperature in interannual, spring, summer, autumn, and winter in the Yellow River Basin (Henan section) from 1982 to 2020

参数	年	春季	夏季	秋季	冬季
NDVI-气温	0.6340^**	0.5912^**	0.1631	0.0557	0.4961^**
NDVI-降水	0.0122	0.2372	0.2443	-0.0177	0.0660

Fig.8 Spatial distribution of annual (a), spring (b), summer (c), autumn (d) and winter (e) temperature changes in the Yellow River Basin (Henan section) from 1982 to 2020

Fig.9 Spatial distribution of annual(a), spring (b), summer (c), autumn (d) and winter (e) precipitation changes in the Yellow River Basin (Henan section) from 1982 to 2020

Fig.10 Spatial distribution of partial correlation coefficients between NDVI and temperature in interannual (a), spring (b), summer (c), autumn (d) and winter (e) in the Yellow River Basin (Henan section) from 1982 to 2022

Fig.11 Spatial distribution of partial correlation coefficients between NDVI and precipitation in interannual(a), spring (b), summer (c), autumn (d) and winter (e) in the Yellow River Basin (Henan section) from 1982 to 2022

Table 4 NDVI variation of different vegetation types

参数	耕地	林地	草地	建设用地
NDVI趋势	0.0027	0.0035	0.0029	0.0016
NDVI显著性	P<0.1	P<0.01	P<0.05	P>0.1

References 41

[1]	孙高鹏, 刘宪锋, 王小红, 等. 2001—2020年黄河流域植被覆盖变化及其影响因素[J]. 中国沙漠, 2021, 41(4): 205-212. DOI
[2]	王晓蕾, 石守海. 基于GEE的黄河流域植被时空变化及其地形效应研究[J]. 地球信息科学学报, 2022, 24(6): 1087-1098. DOI
[3]	LAVERGNE A, GRAVEN H, DE KAUWE M G, et al. Observed and modelled historical trends in the water-use efficiency of plants and ecosystems[J]. Global Change Biology, 2019, 25(7): 2242-2257. DOI PMID
[4]	金晓媚, 万力, 薛忠歧, 等. 宁夏地区水资源对植被生长的影响研究[J]. 现代地质, 2007, 21(4): 632-637.
[5]	马炳鑫, 和彩霞, 靖娟利, 等. 1982—2019年中国西南地区植被变化归因研究[J]. 地理学报, 2023, 78(3): 714-728. DOI
[6]	PIAO S L, WANG X H, PARK T, et al. Characteristics, drivers and feedbacks of global greening[J]. Nature Reviews Earth & Environment, 2020, 1: 14-27.
[7]	赵安周, 张安兵, 刘海新, 等. 退耕还林(草)工程实施前后黄土高原植被覆盖时空变化分析[J]. 自然资源学报, 2017, 32(3): 449-460. DOI
[8]	LIU C X, ZHANG X D, WANG T, et al. Detection of vegetation coverage changes in the Yellow River Basin from 2003 to 2020[J]. Ecological Indicators, 2022, 138: 108818.
[9]	LIU X F, SUN G P, FU Z, et al. Compound droughts slow down the greening of the Earth[J]. Global Change Biology, 2023, 29(11): 3072-3084. DOI PMID
[10]	TYE M R, DAGON K, MOLINA M J, et al. Indices of extremes: Geographic patterns of change in extremes and associated vegetation impacts under climate intervention[J]. Earth System Dynamics, 2022, 13(3): 1233-1257.
[11]	牛海鹏, 赵晓鸣, 肖东洋, 等. 黄河流域(河南段)耕地多功能时空格局演变及其权衡协同关系[J]. 农业工程学报, 2022, 38(23): 223-236.
[12]	LIU Y Q, LONG H L, LI T T, et al. Land use transitions and their effects on water environment in Huang-Huai-Hai Plain, China[J]. Land Use Policy, 2015, 47: 293-301.
[13]	CHEN C, PARK T, WANG X H, et al. China and India lead in greening of the world through land-use management[J]. Nature Sustainability, 2019, 2(2): 122-129. DOI PMID
[14]	贺洁, 何亮, 吕渡, 等. 2001—2020年黄土高原光合植被时空变化及其驱动机制[J]. 植物生态学报, 2023, 47(3): 306-318. DOI
[15]	赵安周, 田新乐. 基于GEE平台的1986—2021年黄土高原植被覆盖度时空演变及影响因素[J]. 生态环境学报, 2022, 31(11): 2124-2133. DOI
[16]	陈春波, 李刚勇. 1981—2020年昆仑山—阿尔金山草地NDVI时空变化及其对气温、降水的响应[J]. 中国草地学报, 2023, 45(2): 13-25.
[17]	WANG Y X, CHEN T T, WANG Q, et al. Time-lagged and cumulative effects of drought and anthropogenic activities on China’s vegetation greening from 1990 to 2018[J]. International Journal of Digital Earth, 2023, 16(1): 2233-2258.
[18]	HIGGINS S I, CONRADI T, MUHOKO E. Shifts in vegetation activity of terrestrial ecosystems attributable to climate trends[J]. Nature Geoscience, 2023, 16(2): 147-153.
[19]	刘海, 刘凤, 郑粮. 气候变化及人类活动对黄河流域植被覆盖变化的影响[J]. 水土保持学报, 2021, 35(4): 143-151.
[20]	FAN D L. Research on the establishment of NDVI long-term data set based on a novel method[J]. Scie.pngic Reports, 2023, 13: 9838.
[21]	田智慧, 任祖光, 魏海涛. 2000—2020年黄河流域植被时空演化驱动机制[J]. 环境科学, 2022, 43(2): 743-751.
[22]	JIANG W X, NIU Z G, WANG L C, et al. Impacts of drought and climatic factors on vegetation dynamics in the Yellow River Basin and Yangtze River Basin, China[J]. Remote Sensing, 2022, 14(4): 930.
[23]	WANG X L, SHI S H, ZHAO X, et al. Detecting spatially non-stationary between vegetation and related factors in the Yellow River Basin from 1986 to 2021 using multiscale geographically weighted regression based onlandsat[J]. Remote Sensing, 2022, 14(24): 6276.
[24]	郭永强, 王乃江, 褚晓升, 等. 基于Google Earth Engine分析黄土高原植被覆盖变化及原因[J]. 中国环境科学, 2019, 39(11): 4804-4811.
[25]	肖东洋, 牛海鹏, 闫弘轩, 等. 1990—2018年黄河流域(河南段)土地利用格局时空演变[J]. 农业工程学报, 2020, 36(15): 271-281, 326.
[26]	王琳, 李娜, 文广超, 等. 黄河流域河南段植被覆盖度变化及其驱动力[J]. 水土保持通报, 2022, 42(6): 393-399.
[27]	任芝花, 余予, 邹凤玲, 等. 部分地面要素历史基础气象资料质量检测[J]. 应用气象学报, 2012, 23(6): 739-747.
[28]	肖晶晶, 李正泉, 郭芬芬, 等. 浙江省1901—2017年降水序列构建及变化特征分析[J]. 气候变化研究进展, 2018, 14(6): 553-561.
[29]	张鹏骞, 胡理乐, 白加德. 京津冀地区近20年NDVI时空变化特征[J]. 生态环境学报, 2021, 30(1): 29-36. DOI
[30]	SEN P K. Estimates of the regression coefficient based on Kendall’s Tau[J]. Journal of the American Statistical Association, 1968, 63: 1379-1389.
[31]	KENDALL M G, GIBBONS J D. Rank Correlation Methods[M]. 5thedi. London: Edward Arnold, 1981: 320.
[32]	郝爱华, 薛娴, 段翰晨, 等. 青藏高原典型草地NDVI时空演变的季节差异及其气候驱动[J]. 生态学报, 2023, 43(1): 352-363.
[33]	谢舒笛, 莫兴国, 胡实, 等. 三北防护林工程区植被绿度对温度和降水的响应[J]. 地理研究, 2020, 39(1): 152-165. DOI
[34]	刘海, 黄跃飞, 郑粮, 等. 长时序丹江口水源区NDVI数据集构建及其时空动态变化分析[J]. 长江流域资源与环境, 2020, 29(8): 1780-1789.
[35]	范松克, 郝成元. 2001—2016年河南省NDVI时空变化特征分析[J]. 江苏农业学报, 2019, 35(4): 860-867.
[36]	余玉洋, 宋丰艺, 张世杰. 2000—2020年河南省NDVI时空变化及其驱动因素定量分析[J]. 生态环境学报, 2022, 31(10): 1939-1950. DOI
[37]	张静, 杜加强, 盛芝露, 等. 1982—2015年黄河流域植被NDVI时空变化及影响因素分析[J]. 生态环境学报, 2021, 30(5): 929-937. DOI
[38]	QIAN C, SHAO L Q, HOU X H, et al. Detection and attribution of vegetation greening trend across distinct local landscapes under China’s Grain to Green Program: A case study in Shaanxi Province[J]. Catena, 2019, 183: 104182.
[39]	LI S S, YANG S N, LIU X F, et al. NDVI-based analysis on the influence of climate change and human activities on vegetation restoration in the Shaanxi-Gansu-Ningxia region, central China[J]. Remote Sensing, 2015, 7(9): 11163-11182.
[40]	张绪财, 金晓媚, 朱晓倩, 等. 格尔木河流域植被指数时空分布及其影响因素研究[J]. 现代地质, 2019, 33(2): 461-468.
[41]	王倩, 金晓媚, 张绪财, 等. 河北省张承地区2001—2020年植被动态变化及驱动因素分析[J]. 现代地质, 2023, 37(4): 881-891.