Vegetation Dynamics in the “Three Water Lines” Region of Northwest China:The Role of Climate Change and Human Activities

Developing bioenergy from plant feedstocks is considered an opportunity to reduce greenhouse gas emissions and secure biofuel supply. This study is an assessment of the availability of field crop residues for bioenergy feedstocks in northwest China (NWC) and southwest China (SWC). The amount of field crop residues was calculated by analyzing statistical data on crop acreages and yields at the provincial and county levels in the NWC and SWC regions. Total residue mass varied from 58.1 to 62.0 million tons (Mt) in NWC and from 92.8 to 97.2 Mt in SWC from 2008 to 2010. Field residues accounted for 86 % in NWC and 94 % in SWC of the total residue mass; the process residue mass accounted for 14 and 6 % of the total residue mass in the NWC and SWC, respectively. In the NWC region, wheat, maize, and cotton were the main crops, providing 17.0, 14.0, and 8.1 Mt of the field residue mass, respectively. In the SWC region, rice, maize, and canola provided 30.6, 15.2, and 9.7 Mt of the total residue mass, respectively. In NWC, maize cob (1.98 Mt) and cotton seed hull (1.93 Mt) formed the majority of the process residues. In SWC, rice hull (5.9 Mt), maize cob (3.7 Mt), and sugarcane bagasse (3.2 Mt) were the main contributors. Most crop residues became available from August to September in the NWC region, whereas harvesting was spread over the whole year in the SWC region. Converted to standard coal equivalent (SCE), total residues in the NWC region amounted to 32.6–34.1 Mt SCE, with 30.7 Mt of field residues and 2.7 Mt of process residue mass. In the SWC region, the total residue mass was equivalent to 48.7–50.8 Mt SCE, including 42.5 Mt of field residues and 7.2 Mt of process residues. Total crop residue availability for biofuels amounted to 16.9 and 28.1 Mt of field residues in NWC and SWC, respectively. Considering transport conditions, surplus amounts, residue densities, and harvest timings, Chongqing Municipality and Shaanxi province showed the best conditions for producing biofuel feedstocks.

Evapotranspiration (ET) is a major component linking the water, energy, and carbon cycles. Understanding changes in ET and the relative contribution rates of human activity and of climate change at the basin scale is important for sound water resources management. In this study, changes in ET in the Heihe agricultural region in northwest China during 1984–2014 were examined using remotely-sensed ET data with the Soil and Water Assessment Tool (SWAT). Correlation analysis identified the dominant factors that influence change in ET per unit area and those that influence change in total ET. Factor analysis identified the relative contribution rates of the dominant factors in each case. The results show that human activity, which includes factors for agronomy and irrigation, and climate change, including factors for precipitation and relative humidity, both contribute to increases in ET per unit area at rates of 60.93% and 28.01%, respectively. Human activity, including the same factors, and climate change, including factors for relative humidity and wind speed, contribute to increases in total ET at rates of 53.86% and 35.68%, respectively. Overall, in the Heihe agricultural region, the contribution of human agricultural activities to increased ET was significantly greater than that of climate change.

The last millennium (LM, 1000–1850 AD) is crucial for studying historical climate change on decadal to multidecadal timescales. The summer surface air temperature (SAT) evolutions on regional scales (e.g. over China) are more uncertain than the globe/Northern Hemisphere, especially in response to external forcing factors and internal climate variability. Here, we provide one‐signal (full‐forcing) fingerprints of summer SAT in China derived from three large ensemble model archives with a multi‐proxy reconstruction during the LM, Little Ice Age (LIA, 1451–1850 AD), and Medieval Climate Anomaly (MCA, 1000–1250 AD), respectively. Our results show that (a) SATs in the northeast, southeast, northwest, and Tibetan Plateau (TP) regions of China show evident decreasing trends during the LM. External forcing response from all model archives agrees with the regional SAT reconstruction but underestimates variability in northwest China at the multidecadal timescale. (b) During the LIA, the summer regional SAT exhibits a cold condition in the reconstruction and simulations, especially in the northeast and northwest regions of China. External forcing responses in most model archives are the dominant factor on multidecadal SAT evolutions in the southeast, northeast, and TP regions of China and decadal SAT evolutions in northwest China. (c) During the MCA, detection and attribution of SAT shows that internal climate variability dominates in southeast, northeast, and TP regions of China, but external forcing dominates in northwest China at decadal to multidecadal timescales. These results contribute to a better understanding of the causes and mechanisms of regional climate change.

Irrigation guarantee capacity is the critical factor in evaluating the development level of irrigated agriculture and is also a future development trend. It is necessary to carry out scientific planning and reasonable allocation of irrigation water resources to ensure the sustainable development of irrigated agriculture and improve the efficiency and effectiveness of water resource utilization. This study is based on remote sensing meteorological data and the principles of the Miami model and water balance. We calculated the annual irrigation water requirement and effective irrigation water, and used the ratio between the effective irrigation water and irrigation water requirement as the basis for evaluating an irrigation guarantee capability index. By using irrigation guarantee capability evaluation indicators from multiple years, we evaluated and assessed the irrigation guarantee capability in the arid region of northwest China. In addition, we analyzed three indicators (i.e., irrigation water requirement IWR, effective irrigation water EIW, and irrigation guarantee capacity index IGCI) to explore the rational allocation of water resources in the northwest arid area. IWR, EIW, and ICGI in northwest China from 2001 to 2020 were analyzed, and the average values were 379.32 mm, 171.29 mm, and 0.50, respectively. Simultaneously, an analysis was conducted on the temporal and spatial distribution of IWR, EIW, and IGCI in the northwest region of China from 2001 to 2020. The results indicated that the rainfall in the southwestern edge of the Yellow River Basin and the eastern part of the Qaidam Basin could meet the irrigation water demand. The northwest edge of the Yellow River Basin, the central Hexi Inland River Basin, most of Northeast Xinjiang, central and southeastern Xinjiang, and other regions mainly rely on irrigation to meet agricultural water requirements. The rest of the region needs to rely on irrigation for supplementary irrigation to increase crop yield. All districts in the ‘Three Water Lines’ area of northwest China should vigorously develop sprinkler irrigation, micro-irrigation, pipe irrigation, and other irrigation water-saving technologies and support engineering construction. Under the premise of ensuring national food security, they should reduce the planting area of rice, corn, and orchards, and increase the planting area of economic crops such as beans and tubers in the ’Three Water Lines’ area. That is conducive to further reducing the agricultural irrigation quota and improving the matching degree of irrigation water resources. It provides a scientific reference for optimizing water resource allocation and improving irrigation water-use efficiency in northwest arid areas.

Vegetation net primary productivity (NPP) is a key indicator for assessing vegetation dynamics and carbon cycle balance. Xinjiang is located in an arid and ecologically fragile region in northwest China, but the current understanding of vegetation dynamics in the region is still limited. This study aims to analyze Xinjiang’s NPP spatial and temporal trends, using random forest regression to quantify the extent to which climate change and human activities affect vegetation productivity. CMIP6 (Coupled Model Intercomparison Project Phase 6) climate scenario data help assess vegetation restoration potential and future risks. Our findings indicate that (1) Xinjiang’s NPP exhibits a significant increasing trend from 2001 to 2020, with three-quarters of the region experiencing an increase, 2.64% of the area showing significant decrease (p < 0.05), and the Ili River Basin showing a nonsignificant decreasing trend; (2) precipitation and radiation are major drivers of NPP variations, with contribution ratios of 35.13% and 30.17%, respectively; (3) noteworthy restoration potential exists on the Tian Shan northern slope and the Irtysh River Basin, where average restoration potentials surpass 80% relative to 2020, while the Ili River Basin has the highest future risk. This study explores the factors influencing the current vegetation dynamics in Xinjiang, aiming to provide references for vegetation restoration and future risk mitigation, thereby promoting sustainable ecological development in Xinjiang.

The Human Critical Area (HCA) is an area that characterizes the surface landscape created by human beings in the Anthropocene. Based on the signatures left by major human activities over the Earth′s surface, this research demarcates an arid inland region of Northwest China, the “Three Water Lines”, into four HCA types: Agricultural Area, Built-up Area, Ecological Area, and Bare Area. This paper explores the HCA′s distribution and changes in the “Three Water Lines” region between 2000 and 2020 with land use/cover data, as well as the impact of socioeconomic factors on the HCA dynamics with statistics sourcing from authoritative yearbooks. To achieve this, the Land Use Transition Matrix is used to investigate the changes in area and distribution, while binary linear regression and stepwise multiple linear regression are applied to examine the single and joint effects of the socioeconomic factors. The main findings are as follows: (i) The four HCA types are distinguished quantitatively and by their distribution patterns. Ecological Area and Bare Area cover most (more than 90% in total) of the territory with extensive and continuous distribution. Agricultural Area is mainly found on the eastern and western parts of the region, with flat terrain, abundant water resources, and moderate temperatures. Built-up Area is the most concentrated but has an unbalanced distribution and the lowest quantity. (ii) Despite some discernible spatial and quantity changes at regional and county levels between 2000 and 2020, the general characteristics in HCA’s structure and distribution pattern have mainly remained consistent. (iii) Transitions between HCA types occur constantly, and the primary source type of the transitions differs from one another. Ecological Area and Bare Area form the sources of the most evident transitions. (iv) Agricultural Area and Built-up Area are more prone influence from some socioeconomic dynamics. By contrast, there is no evidence that socioeconomic factors directly affect Bare Area. As the first empirical study of the newly conceived concept, Human Critical Area, this paper sheds light on the renovation of geographic traditions of studying the evolution of the human-environment system through the lens of human activities-driven landscape changes.

The resilience and vulnerability of terrestrial ecosystem in the Tarim River Basin, Xinjiang is critical in sustainable development of the northwest region in China. To learn more about causes of the ecosystem evolution in this wide region, vegetation dynamics can be a surrogate indicator of environmental responses and human perturbations. This paper aims to use the inter-annual and intra-annual coefficient of variation (CoV) derived by the SPOT-VGT Normalized Difference Vegetation Index (NDVI) as an integrated measure of vegetation dynamics to address the environmental implications in response to climate change. To finally pin down the vegetation dynamics, the intra-annual CoV based on monthly NDVI values and the inter-annual CoV based on seasonally accumulated NDVI values were respectively calculated. Such vegetation dynamics can then be associated with precipitation patterns extracted from the Tropical Rainfall Measuring Mission (TRMM) data and irrigation efforts reflecting the cross-linkages between human society and natural systems. Such a remote sensing analysis enables us to explore the complex vegetation dynamics in terms of distribution and evolution of the collective features of heterogeneity over local soil characteristics, climate change impacts, and anthropogenic activities at differing space and time scales. Findings clearly indicate that the vegetation changes had an obvious trend in some high mountainous areas as a result of climate change whereas the vegetation changes in fluvial plains reflected the increasing evidence of human perturbations due to anthropogenic activities. Some possible environmental implications were finally elaborated from those cross-linkages between economic development and resources depletion in the context of sustainable development.

Analysis of spatial-temporal variations of desert vegetation under the background of climate changes can provide references for ecological restoration in arid and semi-arid areas. In this study, we used the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI data from 1982 to 2006 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data from 2000 to 2013 to reveal the dynamics of desert vegetation in Hexi region of Northwest China over the past three decades. We also used the annual temperature and precipitation data acquired from the Chinese meteorological stations to analyze the response of desert vegetation to climatic variations. The average value of NDVImax (the maximum NDVI during the growing season) for desert vegetation in Hexi region increased at the rate of 0.65×10–3/a (P<0.05) from 1982 to 2013, and the significant increases of NDVImax mainly appeared in the typical desert vegetation areas. Vegetation was significantly improved in the lower reaches of Shule and Shiyang river basins, and the weighted mean center of desert vegetation mainly shifted toward the lower reaches of the two basins. Almost 95.32% of the total desert vegetation area showed positive correlation between NDVImax and annual precipitation, indicating that precipitation is the key factor for desert vegetation growth in the entire study area. Moreover, the areas with non-significant positive correlation between NDVImax and annual precipitation mainly located in the lower reaches of Shiyang and Shule river basins, this may be due to human activities. Only 7.64% of the desert vegetation showed significant positive correlation between NDVImax and annual precipitation in the Shule River Basin (an extremely arid area), indicating that precipitation is not the most important factor for vegetation growth in this basin, and further studies are needed to investigate the mechanism for this phenomenon.

Gap infilling of daily streamflow data using a machine learning algorithm (MissForest) for impact assessment of human activities

Vegetation in karst areas is crucial for maintaining fragile local ecosystems, driven by climate change and human activities. Southwest China contains the largest continuous karst zone in the world and its vegetation dynamics are more sensitive to climate changes and human activities. However, previous studies rarely studied the driving roles of vegetation dynamics in karst areas during the last 20 years, and whether climate change or human disturbance factors have dominated the vegetation dynamics are still uncertain. The objective of this work is to study vegetation dynamics and its responses to climate change and human activities from 2001 to 2019 using the normalized difference vegetation index (NDVI). Taking the three karst provinces of southwest China as study area. Vegetation variation characteristics under the influence of climate variations and human activities were distinguished through a residual analysis. The results indicated general greening trends with about 90.31% of the study area experiencing an increase in NDVI and about 9.69% of the area showing a decrease. Within the combination of climate change and human activities, human activities became the dominant factor in the process of vegetation cover improvement and degradation in the study area during 2001–2019, with average relative roles of 62 and 59%, respectively. Temperature made the greatest positive contribution among the climatic factors, followed by precipitation and relative humidity. In contrast, sunshine duration had a negative effect on NDVI in the study area. Human activities have had different effects on the vegetation dynamics of the three karst provinces in southwest China, including destruction of vegetation around some cities.

Climate change and land use/cover change (LUCC) are two major factors that alter hydrological processes. The upper reaches of the Tarim River, situated in the northwest region of China, experience a dry and less rainy climate and are significantly influenced by human activities. This study comprehensively assessed the impacts of individual and combined climate changes and LUCCs on streamflow. Three general circulation models (GCMs) were utilized to predict future climate changes under three shared socioeconomic pathways (SSP119, SSP245, and SSP585). Cellular Automata–Markov (CA–Markov) was employed to predict future LUCC under three scenarios (i.e., ecological protection, historical trend, and farmland development). Streamflow for the period 2021–2050 was simulated using the calibrated MIKE SHE model with multiple scenarios. The results showed that from 2021 to 2050, increments in both average annual precipitation and average annual temperature under the three SSPs were predicted to lead to an increased streamflow. In comparison to the conditions observed in 2000, under three LUCC scenarios for 2030, the grassland area decreased by 1.04% to 1.21%, while the farmland area increased by 1.97% to 2.26%, resulting in reduced streamflow. The related changes analysis indicated that the variation in streamflow during winter is most significant, followed by spring. The study predicted that climate change would increase streamflow, while LUCC would decrease it. Due to the greater impact of LUCC, considering the combined effect of both factors, runoff would decrease. The contribution analysis indicated that climate change contributed between −7.16% and −18.66%, while LUCC contributed between 107.16% and 118.66%.

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.

Analysis of spatiotemporal changes of the human-water relationship using water resources constraint intensity index in Northwest China

Clarifying the impacts of climate changes and human activities on vegetation dynamics is of significant importance to environmental resource managements， as vegetation undergoes notable changes under the dual influences of the two factors. Based on MODIS NDVI data， meteorological data， and human activity intensity （HAI） characterized by land cover data from 2000 to 2020， this study used methods such as trend analysis， Hurst index， partial correlation analysis， bivariate spatial autocorrelation， and random forest modeling. The impact mechanisms and contributions of climate changes and human activities on vegetation dynamics in Shaanxi Province as a whole and in its three regions （northern Shaanxi， central Shaanxi， and southern Shaanxi） were investigated. The results showed as follows： ① From 2000 to 2020， the average NDVI value in Shaanxi Province was 0.71， with a higher value in southern Shaanxi， followed by those in central and northern Shaanxi. During the study period， the overall NDVI of Shaanxi Province and its three regions showed an increasing trend， with a significant improvement in vegetation covering 87.1% of the area， of which 32.7% had a sustainable improvement trend. The most noticeable improvement in vegetation was observed in northern Shaanxi. ② The NDVI responded differently to various climatic factors. Precipitation and average temperature primarily promoted vegetation， while solar radiation had an inhibitory effect. ③ From 2000 to 2020， the average HAI value in Shaanxi Province was 0.06， with a higher value in central Shaanxi， followed by those in northern and southern Shaanxi， and exhibited an increasing trend over time. The cluster patterns were mainly described as high-low， low-high， and low-low in the northern， central， and southern Shaanxi regions， respectively. ④ The NDVI change rates under climate change and human activities were 0.005 4 a-1 and 0.000 5 a-1， respectively， with their contribution rate being 91.5% and 8.5%， in Shaanxi Province. In the three regions， climate change contributed positively to vegetation change， with the highest contribution observed in northern Shaanxi. Human activities contributed positively in northern and southern Shaanxi， with the highest contribution in northern Shaanxi， while in the central region， human activities showed a negative contribution. The vegetation dynamics in Shaanxi Province were influenced by both climate change and human activities， but the impact mechanisms varied across different regions. It is essential to develop scientifically tailored ecological protection plans based on the specific conditions of each region.

Vegetation, as a fundamental component of terrestrial ecosystems, plays a pivotal role in the flux of water, heat, and nutrients between the lithosphere, biosphere, and atmosphere. Assessing the impacts of climate change and human activities on vegetation dynamics is essential for maintaining the health and stability of fragile ecosystems, such as the Yarlung Zangbo River (YZR) basin of the Tibetan Plateau, the highest-elevation river basin in the world. Vegetation responses to climate change are inherently asymmetric, characterized by distinct temporal effects. However, these temporal effects remain poorly understood, particularly in high-altitude ecosystems. Here, we examine the spatiotemporal changes in leaf area index (LAI) and four climatic factors—air temperature, precipitation, potential evapotranspiration, and solar radiation—in the YZR basin over the period 2000–2019. We further explore the time-lag and time-accumulation impacts of these climatic factors on LAI dynamics and apply an enhanced residual trend analysis to disentangle the relative contributions of climate change and human activities. Results indicated that (1) a modest increase in annual LAI at a rate of 0.02 m2 m−2 dec−1 was detected across the YZR basin. Spatially, LAI increased in 66% of vegetated areas, with significant increases (p &lt; 0.05) in 10% of the basin. (2) Temperature, precipitation, and potential evapotranspiration exhibited minimal time-lag (&lt;0.5 months) but pronounced notable time-accumulation effects on LAI variations, with accumulation periods ranging from 1 to 2 months. In contrast, solar radiation demonstrated significant time-lag impacts, with an average lag period of 2.4 months, while its accumulation effects were relatively weaker. (3) Climate change and human activities contributed 0.023 ± 0.092 and –0.005 ± 0.109 m2 m−2 dec−1 to LAI changes, respectively, accounting for 60% and 40% on the observed variability. Spatially, climate change accounted for 85% of the changes in LAI in the upper YZR basin, while vegetation dynamics in the lower basin was primarily driven by human activities, contributing 63%. In the middle basin, vegetation dynamics were influenced by the combined effects of climate change and human activities. Our findings deepen insights into the drivers of vegetation dynamics and provide critical guidance for formulating adaptive management strategies in alpine ecosystems.