Relationship between NDVI and precipitation in the Hexi Corridor desert area

doi:10.7522/j.issn.1000-694X.2025.00024

Journal of Desert Research ›› 2025, Vol. 45 ›› Issue (5): 318-327.DOI: 10.7522/j.issn.1000-694X.2025.00024

Relationship between NDVI and precipitation in the Hexi Corridor desert area

Lingfei Zhong¹(), Hu Liu², Lihua Zhang¹()

^1.College of Geography and Environment Science，Northwest Normal University，Lanzhou 730030，China
^2.Northwest Institute of Eco-Environment and Resources，Chinese Academy of Sciences，Lanzhou 730000，China

Received:2024-11-23 Revised:2025-02-19 Online:2025-09-20 Published:2025-09-27
Contact: Lihua Zhang

Abstract

Abstract:

In arid desert areas， some natural vegetation mainly depends on groundwater for survival， which is known as groundwater-dependent vegetation. Protecting groundwater-dependent vegetation is an important task in ecological construction in arid areas， and using remote sensing products to rapidly identify groundwater-dependent vegetation has important practical significance for ecological protection in arid areas. We selected six sample areas dependent on different sources of moisture in the Hexi Corridor， analysed the correlation between vegetation NDVI changes and precipitation from 2001 to 2020 in each sample area， and explored the feasibility of applying NDVI products to identify groundwater-dependent vegetation. The result shows that the average NDVI value of the six sample areas from 2001 to 2020 was between 0.11-0.29， and the coefficient of variation was between 0.07-0.59； the maximum value was between 0.20-0.32， and the minimum value was between 0.07-0.26. Pearson's correlation results showed that the correlation coefficients between the average NDVI and growing season precipitation in the six sampling areas ranged from 0.16 to 0.55， the correlation coefficients between the maximum NDVI and growing season precipitation ranged from 0.24 to 0.65， and the correlation coefficients between the minimum NDVI and growing season precipitation ranged from 0.10 to 0.30； the correlation coefficients between the variability of NDVI and the growing season precipitation ranged from 0.21 to 0.70. The correlation coefficients between NDVI variability and growing season precipitation ranged from 0.21 to 0.70. In general， the correlation of desert vegetation NDVI variability with growing season precipitation was greater than that with annual precipitation， and the correlation between groundwater-dependent vegetation NDVI and precipitation was smaller than that of precipitation-dependent vegetation； the correlation of NDVI growing season variability with growing season precipitation was higher than that with the correlation of the mean growing season NDVI with growing season precipitation. Therefore， the growing season NDVI variability can better infer the dependence of vegetation on groundwater through the dependence of vegetation on precipitation.

Key words: Hexi Corridor, precipitation, groundwater burial depth, NDVI, dependence of vegetation on groundwater

CLC Number:

Q948

Lingfei Zhong, Hu Liu, Lihua Zhang. Relationship between NDVI and precipitation in the Hexi Corridor desert area[J]. Journal of Desert Research, 2025, 45(5): 318-327.

Figures/Tables 8

References 29

[1]	Orellana F， Verma P， Loheide S P，et al.Monitoring and modeling water-vegetation interactions in groundwater-dependent ecosystems［J］.Reviews of Geophysics，2012，50（RG3003）：1-24.
[2]	Kløve B， Ala-Aho P， Bertrand G，et al.Groundwater dependent ecosystems.part I：hydroecological status and trends［J］.Environmental Science & Policy，2011，14 （7）：770-781.
[3]	Eamus D， Froend R.Groundwater-dependent ecosystems：the where，what and why of GDEs［J］.Australian Journal of Botany，2006，54（2）：91-96.
[4]	Brown J， Bach L， Aldous A，et al.Groundwater-dependent ecosystems in Oregon：an assessment of their distribution and associated threats［J］.Frontiers in Ecology and the Environment，2011，9（2）：97-102.
[5]	Yang X Y， Liu J.Assessment and valuation of groundwater ecosystem services：a case study of Handan City，China［J］.Water，2020，12（5）：11.
[6]	宋子奕，鲁程鹏，吴成城，等.2009-2019年河西走廊地下水位时空分布及演变趋势［J］.水资源保护，2023，39（2）：160-167.
[7]	赵良菊，肖洪浪，程国栋，等.黑河下游河岸林植物水分来源初步研究［J］.地球学报，2008，29（6）：709-718.
[8]	朱建佳，陈辉，邢星，等.柴达木盆地荒漠植物水分来源定量研究：以格尔木样区为例［J］.地理研究，2015，34（2）：285-292.
[9]	周海，赵文智，何志斌.两种荒漠生境条件下泡泡刺水分来源及其对降水的响应［J］.应用生态学报，2017，28（7）：2083-2092.
[10]	李宁，周海，任珩，等.不同地下水位处梭梭（Haloxylon ammodendron）水分来源特征［J］.中国沙漠，2021，41（4）：79-86.
[11]	Eamus D， Zolfaghar S， Villalobos-Vega R，et al.Groundwater-dependent ecosystems：recent insights from satellite and field-based studies［J］.Hydrology and Earth System Sciences，2015，19（10）：4229-4256.
[12]	Eamus D， Fu B， Springer A E，et al.Groundwater dependent ecosystems：classification，identification techniques and threats［M］//Eamus D，Fu B，Springer A E，et al.Integrated Groundwater Management：Concepts，Approaches and Challenges.New York，USA：Springer，2016：313-346.
[13]	Rampheri M B， Dube T， Dondofema F，et al.Progress in the remote sensing of groundwater-dependent ecosystems in semi-arid environments［J］.Physics and Chemistry of the Earth，2023，130：10.
[14]	Liu C， Liu H， Yu Y，et al.Mapping groundwater-dependent ecosystems in arid Central Asia：implications for controlling regional land degradation［J］.Science of The Total Environment，2021，797：149027.
[15]	Duran-Llacer I， Arumí J L， Arriagada L，et al.A new method to map groundwater-dependent ecosystem zones in semi-arid environments：a case study in Chile［J］.Science of The Total Environment，2022，816：151528.
[16]	Martínez-Santos P， Díaz-Alcaide S， De La Hera-Portillo A，et al.Mapping groundwater-dependent ecosystems by means of multi-layer supervised classification［J］.Journal of Hydrology，2021，603：126873.
[17]	Zhou H， Zhao W Z， Zhang G F.Varying water utilization of Haloxylon ammodendron plantations in a desert-oasis ecotone［J］.Hydrological Processes，2017，31 （4）：825-835.
[18]	赵颖，刘冰，赵文智，等.荒漠绿洲湿地水分来源及植物水分利用策略［J］.中国沙漠，2022，42（4）：151-162.
[19]	符淙斌，王强.气候突变的定义和检测方法［J］.大气科学，1992（4）：482-493.
[20]	Jarnevich C S， Stohlgren T J， Kumar S，et al.Caveats for correlative species distribution modeling［J］.Ecological Informatics，2015，29：6-15.
[21]	Shabani F， Kumar L， Ahmadi M.A comparison of absolute performance of different correlative and mechanistic species distribution models in an independent area［J］.Ecology and Evolution，2016，6（16）：5973-5986.
[22]	李传华，朱同斌，周敏，等.河西走廊植被净初级生产力时空变化及其影响因子研究［J］.生态学报，2021，41（5）：1931-1943.
[23]	刘小宁，隆瑞红，罗珠珠，等.甘肃省典型土壤持水特性及影响因素研究［J］.干旱地区农业研究，2017，35（1）：143-151.
[24]	周海，郑新军，唐立松，等.准噶尔盆地东南缘多枝柽柳、白刺和红砂水分来源的异同［J］.植物生态学报，2013，37（7）：665-673.
[25]	杨自辉，方峨天，刘虎俊，等.民勤绿洲边缘地下水位变化对植物种群生态位的影响［J］.生态学报，2007，27（11）：4900-4906.
[26]	Li F， Zhao W Z， Liu H.The response of aboveground net primary productivity of desert vegetation to rainfall pulse in the temperate desert region of Northwest China［J］.Plos One，2013，8（9）：e73003.
[27]	庄艳丽，赵文智.临泽荒漠绿洲湿地植物生态系列及其物种多样性研究［J］.湿地科学，2014，12（4）：477-484.
[28]	赵文智，常学礼，李启森，等.荒漠绿洲区芦苇种群构件生物量与地下水埋深关系［J］.生态学报，2003，23（6）：1138-1146.
[29]	Zeng F， Zhang X， Foetzki A，et al.Water relation characteristics of Alhagi sparsifolia and consequences for a sustainable management［J］.Science in China Series D：Earth Sciences，2002，45（1）：125-131.

样区	年降水量/mm				地下水埋深 /m
样区	平均	丰水年(2019年)	平水年(2011年)	枯水年(2013年)	地下水埋深 /m
金塔北海子湿地	104.9±39.5	220.9	78.5	98.3	1.90±0.57
临泽平川镇湿地	117.5±29.7	146.9	95.9	90.3	2.46±0.28
民勤青土湖边缘区	122.9±23.6	127.0	139.2	84.5	3.24±0.34
民勤青土湖湿地	122.9±23.6	127.0	139.2	84.5	3.24±0.34
临泽一工程固沙区	117.5±29.7	146.9	95.9	90.3	4.37±0.74
山丹荒漠草地	229.9±46.1	358.7	255.0	167.7	12.74±0.52

样区	年降水量/mm				地下水埋深 /m
样区	平均	丰水年(2019年)	平水年(2011年)	枯水年(2013年)	地下水埋深 /m
金塔北海子湿地	104.9±39.5	220.9	78.5	98.3	1.90±0.57
临泽平川镇湿地	117.5±29.7	146.9	95.9	90.3	2.46±0.28
民勤青土湖边缘区	122.9±23.6	127.0	139.2	84.5	3.24±0.34
民勤青土湖湿地	122.9±23.6	127.0	139.2	84.5	3.24±0.34
临泽一工程固沙区	117.5±29.7	146.9	95.9	90.3	4.37±0.74
山丹荒漠草地	229.9±46.1	358.7	255.0	167.7	12.74±0.52

样区	群落学特征	主要依赖的水分来源
金塔北海子湿地	湖泊湿地。芦苇为优势植物，少量分布柽柳和黑果枸杞，植被覆盖度约为40%	地表水
临泽平川镇湿地	河岸湿地。有柽柳、芦苇等植物生长，植被覆盖度40%~60%	地表水
民勤青土湖边缘区	白刺沙堆。位于湿地边缘，白刺沙堆为主要景观，优势植物为白刺，有骆驼蓬、驼蹄瓣等，植被覆盖度30%以下	地下水
民勤青土湖湿地	尾闾湖湿地。群落由芦苇、拂子茅、罗布麻等组成，优势植物为芦苇，植被覆盖度50%以上	地下水
临泽一工程固沙区	梭梭人工固沙林。有天然沙拐枣生长，丘间低地有白刺沙堆，植被覆盖度60%~70%	降水
山丹荒漠草地	荒漠草地。植物有红砂、珍珠等，也有羊茅、针茅、芨芨草等，植被覆盖度约为20%以下	降水

样区	群落学特征	主要依赖的水分来源
金塔北海子湿地	湖泊湿地。芦苇为优势植物，少量分布柽柳和黑果枸杞，植被覆盖度约为40%	地表水
临泽平川镇湿地	河岸湿地。有柽柳、芦苇等植物生长，植被覆盖度40%~60%	地表水
民勤青土湖边缘区	白刺沙堆。位于湿地边缘，白刺沙堆为主要景观，优势植物为白刺，有骆驼蓬、驼蹄瓣等，植被覆盖度30%以下	地下水
民勤青土湖湿地	尾闾湖湿地。群落由芦苇、拂子茅、罗布麻等组成，优势植物为芦苇，植被覆盖度50%以上	地下水
临泽一工程固沙区	梭梭人工固沙林。有天然沙拐枣生长，丘间低地有白刺沙堆，植被覆盖度60%~70%	降水
山丹荒漠草地	荒漠草地。植物有红砂、珍珠等，也有羊茅、针茅、芨芨草等，植被覆盖度约为20%以下	降水

样区	NDVI平均值		NDVI最大值		NDVI最小值
样区	相关性	P	相关性	P	相关性	P
金塔北海子湿地	0.31	0.18	0.27	0.24	0.38	0.10
临泽平川镇湿地	0.49	0.03	0.24	0.30	0.14	0.54
民勤青土湖边缘区	0.80	<0.005	0.75	0.01	0.07	0.83
民勤青土湖湿地	0.93	<0.005	0.97	<0.005	0.42	0.20
临泽一工程固沙区	0.34	0.15	0.34	0.13	0.16	0.51
山丹荒漠草地	0.15	0.34	0.13	0.30	0.15	0.33

Relationship between NDVI and precipitation in the Hexi Corridor desert area

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样区	平均值±σ	最大值（年份）	最小值（年份）	突变点	突变前变异性	整体变异性
金塔北海子湿地	0.13±0.04	0.25 (2019)	0.09(2001)	2010	0.09	0.36
临泽平川镇湿地	0.29±0.02	0.32 (2019)	0.26(2001)	—	—	0.07
民勤青土湖边缘区	0.11±0.04	0.20 (2019)	0.09(2001)	2014	0.04	0.32
民勤青土湖湿地	0.14±0.08	0.28 (2019)	0.07(2001)	2012	0.07	0.59
临泽一工程固沙区	0.15±0.03	0.20(2019)	0.10(2001)	—	—	0.20
山丹荒漠草地	0.19±0.03	0.23 (2019)	0.12(2001)	—	—	0.15

样区	平水年（2011年）			枯水年（2013年）			丰水年（2019年）
样区	平均值	最大值	最小值	平均值	最大值	最小值	平均值	最大值	最小值
金塔北海子湿地	0.10±0.04	0.21	0.01	0.10±0.03	0.18	0.02	0.22±0.10	0.39	0.04
临泽平川镇湿地	0.28±0.11	0.52	0.06	0.29±0.11	0.52	0.05	0.29±0.12	0.56	0.03
民勤青土湖边缘区	0.08±0.03	0.13	0.02	0.08±0.03	0.15	0.02	0.18±0.08	0.33	0.02
民勤青土湖湿地	0.07±0.02	0.12	0.02	0.12±0.07	0.25	0.01	0.25±0.13	0.49	0.02
临泽一工程固沙区	0.16±0.06	0.30	0.07	0.16±0.05	0.27	0.05	0.18±0.07	0.32	0.03
山丹荒漠草地	0.15±0.04	0.25	0.06	0.15±0.06	0.29	0.04	0.21±0.08	0.36	0.05

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