Attribution of satellite observed vegetation trends in a hyper-arid region of the Heihe River Basin, Central Asia

Abstract. Terrestrial vegetation dynamics are closely influenced by both climate change and by direct human activities that modify land use and/or land cover (LULCC). Both can change over time in a monotonic way and it can be difficult to separate the effects of climate change from LULCC on vegetation. Here we attempt to attribute the trend of fractional green vegetation cover to climate change and to human activity in Ejina region, a hyper-arid landlocked region in northwest China. This region is dominated by extensive deserts with relatively small areas of irrigation located along the major water courses as is typical throughout much of Central Asia. Variations of fractional vegetation cover from 2000 to 2012 were determined using Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index data with 250 m spatial resolution over 16 day intervals. We found that the fractional vegetation cover in this hyper-arid region is very low, but that the mean growing season vegetation cover has increased from 3.4% in 2000 to 4.5% in 2012. The largest contribution to the overall greening was due to changes in green vegetation cover of the extensive desert areas with a smaller contribution due to changes in the area of irrigated land. Comprehensive analysis with different precipitation data sources found that the greening of the desert was associated with increases in regional precipitation. We found that the area of land irrigated each year was mostly dependent on the runoff gauged one year earlier. Taken together, water availability both from precipitation in the desert and runoff inflow for the irrigation agricultural lands can explain at least 52% of the total variance in regional vegetation cover from 2000 to 2010.

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Attribution of satellite-observed vegetation trends in a hyper-arid region of the Heihe River basin, Western China

Hydrology and Earth System Sciences ◽

10.5194/hess-18-3499-2014 ◽

2014 ◽

Vol 18 (9) ◽

pp. 3499-3509 ◽

Cited By ~ 14

Author(s):

Y. Wang ◽

M. L. Roderick ◽

Y. Shen ◽

F. Sun

Keyword(s):

Vegetation Cover ◽

Arid Region ◽

Vegetation Index ◽

Northwest China ◽

Western China ◽

Heihe River ◽

Terrestrial Vegetation ◽

Small Areas ◽

Fractional Vegetation Cover ◽

Green Vegetation

Abstract. Terrestrial vegetation dynamics are closely influenced by both climate and by both climate and by land use and/or land cover change (LULCC) caused by human activities. Both can change over time in a monotonic way and it can be difficult to separate the effects of climate change from LULCC on vegetation. Here we attempt to attribute trends in the fractional green vegetation cover to climate variability and to human activity in Ejina Region, a hyper-arid landlocked region in northwest China. This region is dominated by extensive deserts with relatively small areas of irrigation located along the major water courses as is typical throughout much of Central Asia. Variations of fractional vegetation cover from 2000 to 2012 were determined using Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index data with 250 m spatial resolution over 16-day intervals. We found that the fractional vegetation cover in this hyper-arid region is very low but that the mean growing season vegetation cover has increased from 3.4% in 2000 to 4.5% in 2012. The largest contribution to the overall greening was due to changes in green vegetation cover of the extensive desert areas with a smaller contribution due to changes in the area of irrigated land. Comprehensive analysis with different precipitation data sources found that the greening of the desert was associated with increases in regional precipitation. We further report that the area of land irrigated each year can be predicted using the runoff gauged 1 year earlier. Taken together, water availability both from precipitation in the desert and runoff inflow for the irrigation agricultural lands can explain at least 52% of the total variance in regional vegetation cover from 2000 to 2010. The results demonstrate that it is possible to separate the satellite-observed changes in green vegetation cover into components due to climate and human modifications. Such results inform management on the implications for water allocation between oases in the middle and lower reaches and for water management in the Ejina oasis.

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Drivers and Environmental Impacts of Vegetation Greening in a Semi-Arid Region of Northwest China since 2000

Remote Sensing ◽

10.3390/rs13214246 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4246

Author(s):

Zhenzong Wu ◽

Jian Bi ◽

Yifei Gao

Keyword(s):

Arid Region ◽

Vegetation Index ◽

Climatic Factors ◽

Agricultural Practices ◽

Northwest China ◽

Terrestrial Vegetation ◽

Moderate Resolution Imaging Spectroradiometer ◽

Semi Arid Region ◽

Semi Arid ◽

Dynamics Of Vegetation

The dynamics of terrestrial vegetation have changed a lot due to climate change and direct human interference. Monitoring these changes and understanding the mechanisms driving them are important for better understanding and projecting the Earth system. Here, we assessed the dynamics of vegetation in a semi-arid region of Northwest China for the years from 2000 to 2019 through satellite remote sensing using Vegetation Index (VI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and analyzed the interannual covariation between vegetation and three climatic factors—air temperature, precipitation, and vapor pressure deficit (VPD)—at nine meteorological stations. The main findings of this research are: (1) herbaceous land greened up much more than forests (2.85%/year vs. 1.26%/year) in this semi-arid region; (2) the magnitudes of green-up for croplands and grasslands were very similar, suggesting that agricultural practices, such as fertilization and irrigation, might have contributed little to vegetation green-up in this semi-arid region; and (3) the interannual dynamics of vegetation at high altitudes in this region correlate little with temperature, precipitation, or VPD, suggesting that factors other than temperature and moisture control the interannual vegetation dynamics there.

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Evaluation of water productivity under climate change in irrigated areas of the arid Northwest China using an assemble statistical downscaling method and an agro-hydrological model

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-379-393-2018 ◽

2018 ◽

Vol 379 ◽

pp. 393-402

Author(s):

Liu Liu ◽

Zezhong Guo ◽

Guanhua Huang

Keyword(s):

Climate Change ◽

River Basin ◽

Statistical Downscaling ◽

Arid Region ◽

Meteorological Data ◽

Water Productivity ◽

Northwest China ◽

Heihe River ◽

Climate Change Scenarios ◽

Increasing Trend

Abstract. The Heihe River Basin (HRB) is the second largest inland river basin, located in the arid region of Northwest China with a serious water shortage. Evaluation of water productivity will provide scientific implications for agricultural water-saving in irrigated areas of the arid region under climate change. Based on observed meteorological data, 23 GCMs outputs and the ERA-40 reanalysis data, an assemble statistical downscaling model was developed to generate climate change scenarios under RCP2.6, RCP4.5, RCP8.5 respectively, which were then used to drive the SWAP-EPIC model to simulate crop growth in the irrigated areas of the middle HRB for the future period from 2018 to 2047. Crop yield showed an increasing trend, while crop water consumption decreased gradually in Gaotai and Ganzhou irrigated areas. The water productivity in future 30 years showed an increasing trend in both Gaotai and Ganzhou areas, with the most significant increase under RCP4.5 scenario, which were both larger than 2 kg m−3. Compared with that of the period from 2012 to 2015, the water productivity during 2018–2047 under three RCP scenarios increased by 9.2, 14.3 and 11.8 % in the Gaotai area, and 15.4, 21.6, 19.9 % in the Ganzhou area, respectively.

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30 Years Climate Change Impact on Weather Elements and Green Coverage: GIS and Remote Sensing Geo-Environmental Case Study in Jordan

Iraqi Geological Journal ◽

10.46717/igj.54.1d.5ms-2021-04-25 ◽

2021 ◽

Vol 54 (1D) ◽

pp. 57-68

Author(s):

Thair Al-Azzawi

Keyword(s):

Climate Change ◽

Relative Humidity ◽

Vegetation Cover ◽

Vegetation Index ◽

Annual Rainfall ◽

Maximum Temperature ◽

Analysis Methods ◽

Gis Database ◽

Average Annual Rainfall ◽

Green Vegetation

This study deals with climate change and its geo-environmental impact in Jordan for thirty years period (1982-2012). It comprised the building of a geographic information system (GIS) database for the most important basic climatic elements of temperature, rainfall, and relative humidity. Data is obtained from the Meteorological Department of Jordan for the study period. Digital descriptive and statistical analysis methods for the GIS database are implemented using ArcGIS 10.4 software and Normalized Difference Vegetation Index extracted from Moderate Resolution Imaging Spectroradiometer satellite images to forecast that impact on weather elements and green vegetation cover, respectively. Three different criteria are used for analysis and verification to achieve the objectives of the study. The criteria are the average annual minimum and maximum temperature, which is considered the most important criterion for this study, average annual rainfall, and average annual relative humidity. Results showed a speedy increase in the annual rate of the local temperature, particularly since 1990. Despite the local temperatures' average volatility, the increment reached about 1.5-2.0 oC degrees Celsius. An increase in the relative humidity is observed, but with no evident change in the average annual rainfall, both in Jordan's northern and eastern parts. At the same time, there were increases for Jordan's central region during the period 1985-2012. The green vegetation cover area showed a decrease during the studied period 2002-2008 as that is probably due to the evident increase in annual average temperature and evaporation. Results reveal the increase of the greater temperature change region has increased in the northern part of Jordan by eight times for the 1982-2002 period as mentioned in this study. The area of vegetated area decreased to 3725.8 km² in 2008 compared to 9305.5 km² in 2002. The study demonstrated efficiency in applying descriptive and statistical GIS analysis methods on the climatic database, which better understanding of the climate change phenomenon.

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Vegetation Change and Its Response to Climate Extremes in the Arid Region of Northwest China

Remote Sensing ◽

10.3390/rs13071230 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1230

Author(s):

Simeng Wang ◽

Qihang Liu ◽

Chang Huang

Keyword(s):

Arid Region ◽

Vegetation Change ◽

Vegetation Index ◽

Pearson Correlation ◽

Time Lag ◽

Climate Extremes ◽

Northwest China ◽

Precipitation Extremes ◽

Temperature Extremes ◽

Increasing Trend

Changes in climate extremes have a profound impact on vegetation growth. In this study, we employed the Moderate Resolution Imaging Spectroradiometer (MODIS) and a recently published climate extremes dataset (HadEX3) to study the temporal and spatial evolution of vegetation cover, and its responses to climate extremes in the arid region of northwest China (ARNC). Mann-Kendall test, Anomaly analysis, Pearson correlation analysis, Time lag cross-correlation method, and Least absolute shrinkage and selection operator logistic regression (Lasso) were conducted to quantitatively analyze the response characteristics between Normalized Difference Vegetation Index (NDVI) and climate extremes from 2000 to 2018. The results showed that: (1) The vegetation in the ARNC had a fluctuating upward trend, with vegetation significantly increasing in Xinjiang Tianshan, Altai Mountain, and Tarim Basin, and decreasing in the central inland desert. (2) Temperature extremes showed an increasing trend, with extremely high-temperature events increasing and extremely low-temperature events decreasing. Precipitation extremes events also exhibited a slightly increasing trend. (3) NDVI was overall positively correlated with the climate extremes indices (CEIs), although both positive and negative correlations spatially coexisted. (4) The responses of NDVI and climate extremes showed time lag effects and spatial differences in the growing period. (5) Precipitation extremes were closely related to NDVI than temperature extremes according to Lasso modeling results. This study provides a reference for understanding vegetation variations and their response to climate extremes in arid regions.

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Annually Urban Fractional Vegetation Cover Dynamic Mapping in Hefei, China (1999–2018)

Remote Sensing ◽

10.3390/rs13112126 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2126

Author(s):

Yuliang Wang ◽

Mingshi Li

Keyword(s):

Standard Deviation ◽

Vegetation Cover ◽

Vegetation Index ◽

Dynamic Range ◽

Dynamic Change ◽

Estimation Model ◽

Sparse Vegetation ◽

Fractional Vegetation Cover ◽

Dynamic Mapping ◽

Multi Temporal

Vegetation measures are crucial for assessing changes in the ecological environment. Fractional vegetation cover (FVC) provides information on the growth status, distribution characteristics, and structural changes of vegetation. An in-depth understanding of the dynamic changes in urban FVC contributes to the sustainable development of ecological civilization in the urbanization process. However, dynamic change detection of urban FVC using multi-temporal remote sensing images is a complex process and challenge. This paper proposed an improved FVC estimation model by fusing the optimized dynamic range vegetation index (ODRVI) model. The ODRVI model improved sensitivity to the water content, roughness degree, and soil type by minimizing the influence of bare soil in areas of sparse vegetation cover. The ODRVI model enhanced the stability of FVC estimation in the near-infrared (NIR) band in areas of dense and sparse vegetation cover through introducing the vegetation canopy vertical porosity (VCVP) model. The verification results confirmed that the proposed model had better performance than typical vegetation index (VI) models for multi-temporal Landsat images. The coefficient of determination (R2) between the ODRVI model and the FVC was 0.9572, which was 7.4% higher than the average R2 of other typical VI models. Moreover, the annual urban FVC dynamics were mapped using the proposed improved FVC estimation model in Hefei, China (1999–2018). The total area of all grades FVC decreased by 33.08% during the past 20 years in Hefei, China. The areas of the extremely low, low, and medium grades FVC exhibited apparent inter-annual fluctuations. The maximum standard deviation of the area change of the medium grade FVC was 13.35%. For other grades of FVC, the order of standard deviation of the change ratio was extremely low FVC > low FVC > medium-high FVC > high FVC. The dynamic mapping of FVC revealed the influence intensity and direction of the urban sprawl on vegetation coverage, which contributes to the strategic development of sustainable urban management plans.

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Reduced resilience of terrestrial ecosystems locally is not reflected on a global scale

Communications Earth & Environment ◽

10.1038/s43247-021-00163-1 ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Yuhao Feng ◽

Haojie Su ◽

Zhiyao Tang ◽

Shaopeng Wang ◽

Xia Zhao ◽

...

Keyword(s):

Climate Change ◽

Global Climate Change ◽

Vegetation Index ◽

Global Climate ◽

Terrestrial Ecosystem ◽

Terrestrial Ecosystems ◽

Global Scale ◽

Ecological Resilience ◽

Terrestrial Vegetation ◽

Ecosystem Resilience

AbstractGlobal climate change likely alters the structure and function of vegetation and the stability of terrestrial ecosystems. It is therefore important to assess the factors controlling ecosystem resilience from local to global scales. Here we assess terrestrial vegetation resilience over the past 35 years using early warning indicators calculated from normalized difference vegetation index data. On a local scale we find that climate change reduced the resilience of ecosystems in 64.5% of the global terrestrial vegetated area. Temperature had a greater influence on vegetation resilience than precipitation, while climate mean state had a greater influence than climate variability. However, there is no evidence for decreased ecological resilience on larger scales. Instead, climate warming increased spatial asynchrony of vegetation which buffered the global-scale impacts on resilience. We suggest that the response of terrestrial ecosystem resilience to global climate change is scale-dependent and influenced by spatial asynchrony on the global scale.

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Fractional vegetation cover estimation by using multi-angle vegetation index

Remote Sensing of Environment ◽

10.1016/j.rse.2018.06.022 ◽

2018 ◽

Vol 216 ◽

pp. 44-56 ◽

Cited By ~ 26

Author(s):

Xihan Mu ◽

Wanjuan Song ◽

Zhan Gao ◽

Tim R. McVicar ◽

Randall J. Donohue ◽

...

Keyword(s):

Vegetation Cover ◽

Vegetation Index ◽

Fractional Vegetation Cover

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Water Productivity Evaluation under Multi-GCM Projections of Climate Change in Oases of the Heihe River Basin, Northwest China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16101706 ◽

2019 ◽

Vol 16 (10) ◽

pp. 1706 ◽

Cited By ~ 6

Author(s):

Liu Liu ◽

Zezhong Guo ◽

Guanhua Huang ◽

Ruotong Wang

Keyword(s):

Climate Change ◽

Sustainable Development ◽

River Basin ◽

Water Productivity ◽

Northwest China ◽

Hexi Corridor ◽

Heihe River Basin ◽

Heihe River ◽

Crop Water ◽

The Heihe River Basin

As the second largest inland river basin situated in the middle of the Hexi Corridor, Northwest China, the Heihe River basin (HRB) has been facing a severe water shortage problem, which seriously restricts its green and sustainable development. The evaluation of climate change impact on water productivity inferred by crop yield and actual evapotranspiration is of significant importance for water-saving in agricultural regions. In this study, the multi-model projections of climate change under the three Representative Concentration Pathways emission scenarios (RCP2.6, RCP4.5, RCP8.5) were used to drive an agro-hydrological model to evaluate the crop water productivity in the middle irrigated oases of the HRB from 2021–2050. Compared with the water productivity simulation based on field experiments during 2012–2015, the projected water productivity in the two typical agricultural areas (Gaotai and Ganzhou) both exhibited an increasing trend in the future 30 years, which was mainly attributed to the significant decrease of the crop water consumption. The water productivity in the Gaotai area under the three RCP scenarios during 2021–2050 increased by 9.2%, 14.3%, and 11.8%, while the water productivity increased by 15.4%, 21.6%, and 19.9% in the Ganzhou area, respectively. The findings can provide useful information on the Hexi Corridor and the Belt and Road to policy-makers and stakeholders for sustainable development of the water-ecosystem-economy system.

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A Preliminary Study on the Relationship between Vegetation Cover and Regional Climate Change in Jiangsu Area of China

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.448-453.916 ◽

2013 ◽

Vol 448-453 ◽

pp. 916-922

Author(s):

Yan Rong Yang ◽

Zhe Kong ◽

Chun Ming Liu

Keyword(s):

Climate Change ◽

Vegetation Cover ◽

Vegetation Index ◽

Climate Model ◽

Regional Climate ◽

Precipitation Amount ◽

Regional Climate Change ◽

Research Field ◽

Research Fields ◽

The Relationship

The relationship between vegetation cover and climate change is one of the most important research fields in global change. Herein Jiangsu province and thereabout in China is chosen to be the research field. Under the support of observations from normalized differential vegetation index (NDVI) during years from 1998 to 2008 and corresponding benchmark weather stations, the relationship between vegetation and climate change had been analyzed combined with simulations from regional climate model RegCM3, in perspectives of point vegetation cover amount and area vegetation cover type respectively. Conclusions are: (1) Points observations showed that NDVI had positive correlation with annual total precipitation and negative correlation with annual average temperature. (2) Area simulations showed that two different vegetation types in south and north Jiangsu almost had same 8warming value, but the incremental annual precipitation amount is more significant in south Jiangsu.

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