Arid Regions Of China Research Articles

Multi-Scale Supply and Demand Relationships of Ecosystem Services Under Multiple Scenarios and Ecological Zoning to Promote Sustainable Urban Ecological Development in Arid Regions of China

Predicting and analyzing the supply and demand relationship of ecosystem services provides theoretical support for the improvement of the ecological environment. This paper takes Bortala, a typical oasis city with a fragile ecological environment in the arid northwest region, as a case study. Based on the GMOP-PLUS-InVEST coupled model, it predicts the coupling coordination and matching degree of the supply and demand connection of ecosystem services such as habitat quality (HQ), carbon storage (CS), water yield (WY), and soil erosion (SD) under four scenarios. The findings indicate that from 2020 to 2035, HQ, CS, and WY have basically achieved coupling coordination at both scales. However, there is a notable disparity in the supply and demand of water resource production and carbon emission production. To ensure the long-term balance of ecosystem service supply and demand (ESSD), the research area was ultimately divided into five ecological zones: ecological conservation zone, ecological agriculture zone, ecological moderate development zone, ecological improvement zone, and ecological protection zone. It could offer insights for guiding the sustainable growth of ecologically vulnerable zones in the future.

Investigating climatic drivers of snow phenology by considering key-substage heterogeneity

Investigating the main climatic drivers responsible for changes in snow cover phenology (SCP) is crucial for making scientific countermeasures to ensure water resources security in global mountainous regions. However, most studies have explored drivers of SCP changes using a fixed substage division scheme and correlation analysis (referred to as the traditional method), potentially limiting reliability and accuracy in mountainous areas with complex terrain and climate. Here, a novel method is developed to efficiently identify main climatic drivers of SCP changes. This method employs a flexible scheme to account for the spatial heterogeneity of the dominant sub-period (the sub-period with the major climatic effect) in combination with regression analysis. Using the arid region of China as a case study, the new method was applied to three SCP parameters including snow cover days, snow start date, and snow end date, based on a seamless snow cover dataset from 2002 to 2019. The method’s effectiveness was evaluated by comparing it with the traditional method. The results indicate significant spatial heterogeneity in the dominant sub-period(s), closely associated with local temperature and elevation. The traditional method failed to accurately identify the main drivers of SCP changes, as evidenced by sub-region and elevation zone analyses showing adjusted coefficient of determination (R2) of < 0.5 in most cases. This inadequacy is attributed to its fixed and inappropriate scheme of substage division. In contrast, the new method, with its flexible scheme, achieved much higher adjusted R2 values (mostly > 0.5) and exhibited better performances in predicting SCP changes. Thanks to the new method, climatic causes of SCP changes were successfully identified in 12 hotspots (regions with significant SCP changes), all with adjusted R2 > 0.5. The climatic causes were found to vary significantly across different hotspot regions and SCP parameters. The proposed method holds significant potential to enhance the reliability of analyses concerning main climatic drivers of SCP changes in mountainous regions globally.

Redefining the modified water benefit-based ecological index to evaluate the impact of cropland expansion on the ecological environment in an arid area

Global land-use changes have a significant impact on the environment and food security, and escalating human activity and uncontrolled agricultural land expansion pose a grave threat to regional ecosystems. This study aims to assess the challenges faced by the environment and food security, with a particular focus on the impact of land use change on ecosystems. The study selected the Ebinur Lake Basin, a typical arid region in China, as the object and analyzed the land type changes from 2013 to 2021 using the Google Earth Engine platform and the China Land Cover Dataset. We created an Improved Water-Benefit-Based Ecological Index (IWBEI) based on the poor air quality environment in the watershed, and then calculated the ecological index of the watershed. The results indicate that the grassland and bare land areas in the Ebinur Lake Basin have fluctuated and shown an overall downward trend. The trend of farmland expansion is to expand to surrounding areas on the basis of existing farmland. The overall center of gravity of cultivated land in the watershed is moving from northwest to southeast, mainly towards the water source area. The IWBEI index is more prominent in identifying cultivated land and wetlands in arid regions. According to IWBEI's calculations, the priority order of land types is: forest > cultivated land > wetland > water > snow > grassland > impermeable surface > bare land. The overall ecological environment quality of the watershed is showing a deteriorating trend. Therefore, relevant departments should pay attention to the impact of farmland expansion on the local ecological environment to avoid the continuous deterioration of the ecological environment.

Unraveling the complex interconnections between food-energy-water nexus sustainability and the supply-demand of related ecosystem services

Matching the supply and demand of related ecosystem services can be an effective way to realize long-term sustainable management of the food-energy-water nexus (FEW Nexus) in drylands. However, few studies have focused on the matching of supply and demand for ecosystem services associated with advancing the sustainability of FEW-Nexus, there is limited research in this domain, which lacks systematic and quantitative analysis of the relationship between them and FEW Nexus sustainability. Here, this research takes the West Liaohe River Basin in the arid region of China as a case study. Based on a localized FEW Nexus sustainability evaluation index system, the FEW Nexus sustainability and the supply-demand matching characteristics of the corresponding ecosystem services in the West Liaohe River Basin from 2005 to 2015 were assessed. The relationship between them was analyzed quantitatively through the methods of coupling coordination degree and geographical detector. The results showed a synergistic improvement in both FEW Nexus sustainability and the supply-demand situation of combined ecosystem services. The supply of food production and water yield were able to meet their demands adequately from 2005 to 2015, with a strengthening surplus, leading to an overall surplus and gradual improvement in the integrated ecosystem services. This surplus synergistically promoted the process of FEW Nexus sustainability. The results of the geographical detector indicate that the supply-demand ratio of carbon sequestration was the main factor influencing FEW Nexus sustainability. Areas with higher FEW Nexus sustainability tended to have larger deficits in carbon sequestration, which was more evident in areas with high levels of urbanization. Therefore, the key to enhancing FEW Nexus sustainability in the basin is to balance the supply of and demand for carbon sequestration services. Overall, the present study not only provides a basis for strengthening the management of the supply-demand of ecosystem services associated with FEW to achieve regional sustainable development, but also offers insights into how the growing demand for the FEW Nexus is exerting pressure on the balance between supply and demand of related ecosystem services.

Optimizing nitrogen application rates to maximize productivity while reducing environmental risk by regulating nitrogen and water utilization in mixed cropping systems

Optimizing the nitrogen (N) fertilization level and cropping system is critically important for achieving good production performance with low environmental pollution. However, there is a knowledge gap on the relationship between crop production sustainability, water and nitrogen consumption, greenhouse gas (GHG) emission under the change in N application rate under cereal and legume mixed systems. A 3-year field experiment with two cropping systems [sole forage sorghum (SS) and forage sorghum/lablab mixed cropping (SL) with four N fertilizer application rates (N0, 0 kg N ha−1; N90, 90 kg N ha−1; N180, 180 kg N ha−1; and N270, 270 kg N ha−1)] was conducted. Results obtained showed that mixed cropping combined with N fertilization enhanced forage biomass and crude protein yield by 34.0 % and 51.1 %, respectively, particularly in mixed cropping combined with the N180 treatment compared with the N0 level in the sole cropping system. Similar improvements were observed for yield stability and sustainability (2.97 % and 0.95, respectively), which reached maximum values at N180 in the mixed cropping system. In addition, mixed cropping increased the water productivity of dry matter yield (WPDM) and water productivity of crude protein yield (WPCPY) by 17.2 % and 27.6 %, respectively, at 180 kg N ha−1 compared with the corresponding treatments of the sole planting system. Furthermore, mixed cropping combined with appropriate N application significantly improved N physiological efficiency (PEN) and reduced GHG intensity (GHGI), where N application of 180 kg ha−1 N increased PEN by 21.3 % and reduced GHGI by 17.6 % compared with the corresponding monoculture in the mixed cropping system. This study demonstrated that reducing N fertilization in cereal–legume cropping systems can promote forage productivity by optimizing water and N management while decreasing environmental pollution. Therefore, forage sorghum mixed with lablab and fertilization at 180 kg N ha–1 is a preferable approach for sustainable agricultural production in the Northwest arid region of China.

Spatio-Temporal Changes and Driving Mechanisms of Vegetation Net Primary Productivity in Xinjiang, China from 2001 to 2022

Net primary productivity (NPP), a key indicator of terrestrial ecosystem quality and function, represents the amount of organic matter produced by vegetation per unit area and time. This study utilizes the MOD17A3 NPP dataset (2001–2022) to analyze the spatio-temporal dynamics of NPP in Xinjiang and projects future trends using Theil-Sen trend analysis, the Mann–-Kendall test, and the Hurst Index. By integrating meteorological data, this study employs partial correlation analysis, the Miami model, and residual analysis to explore the driving mechanisms behind NPP changes influenced by climatic factors and human activities. The results indicate that: (1) The average NPP in Xinjiang has increased over the years, displaying a spatial pattern with higher values in the north and west. Regions with increasing NPP outnumber those with declining trends, while 75.18% of the area shows un-certain future trends. (2) Precipitation exhibits a stronger positive correlation with NPP compared to temperature. (3) Climate change accounts for 28.34% of the variation in NPP, while human activities account for 71.66%, making the latter the dominant driving factor. This study aids in monitoring ecological degradation risks in arid regions of China and provides a scientific basis for developing rational coping strategies and ecological restoration initiatives.

Does ambient Particulate Matter 1 Increase the Risk of Gastric Cancer? Empirical research in a high-risk, arid region in China

Does ambient Particulate Matter 1 Increase the Risk of Gastric Cancer? Empirical research in a high-risk, arid region in China

Semi-arid rather than arid regions of China deserve the priority in drought mitigation efforts

The integration of drought assessment, mitigation priority analysis and mitigation measures development is a forward-looking strategy to achieve water resources allocation, implement anti-drought techniques and formulate corresponding mitigation measures strategies. However, since most drought indices cannot be based on surface water-balance to estimate water demand for drought recovery, there is a gap between drought assessment and proactive drought mitigation. Here, we established the Standardized Water Availability Index (taking water yield as surface water deficit/surplus) to identify hydrological drought, and further use it to determine the water demand for hydrological drought mitigation. On that basis, a comprehensive framework, integrating with drought assessment-resilience-recovery and water scarcity stress, was proposed to investigate the hydrological drought mitigation priority for basins in different climate regions in China. The results show that non-humid river basins have greater water scarcity stress, lower resilience to hydrological drought, but less water demand for hydrological drought mitigation (3 mm ∼ 7 mm in mild drought, 5 mm ∼ 14 mm in moderate drought, 7 mm ∼ 21 mm in severe drought). In contrast, humid river basins have greater water demand for hydrological drought mitigation (15 mm ∼ 49 mm in mild drought, 27 mm ∼ 93 mm in moderate drought, 32 mm ∼ 119 mm in severe drought), but higher resilience to hydrological drought. The densely populated semi-arid river basins in China should be given priority attention in mitigating hydrological drought on account of their greatest water scarcity stress, lower drought resilience, and less water demand for drought mitigation. This work highlights the complexity of the hydrological drought mitigation, and our findings can help stakeholders to make precise drought mitigation measures and adapt drought-relative water management.

Simulation and Optimal Scheduling of Water Quality in Urban and Rural Water Supply Systems: A Case Study in the Northwest Arid Region of China

Simulation and Optimal Scheduling of Water Quality in Urban and Rural Water Supply Systems: A Case Study in the Northwest Arid Region of China

Residual plastic film decreases crop yield and water use efficiency through direct negative effects on soil physicochemical properties and root growth

Film mulching has been extensively used to improve agricultural production in arid regions of China. However, without sufficient mulch film recovery, large amounts of residual film accumulated in the farmland, which would affect crop yield and water use efficiency (WUE). In order to comprehensively analyze the effects of residual film on crop yield and WUE, and clarify its influencing mechanism, present study adopted a meta-analysis to systematically evaluate the impacts of residual film on soil physicochemical properties, crop root growth, yield, and WUE. The results showed that residual film significantly increased soil bulk density and the soil moisture content in 0–20 cm soil layer, but decreased soil porosity, soil organic matter, soil total nitrogen content, and soil moisture content in >20 cm soil layer, especially when residual film amount was >400 kg ha−1. Residual film significantly reduced crop root dry weight, root length, root diameter, root volume and root surface area. Generally, crop yield and WUE decreased with the increase of residual film amount; and crop yield was reduced by about 14.00 % when the residual film amount increased by 1000 kg ha−1. In average, crop yield and WUE under film residual condition were significantly decreased by 13.46 % and 9.21 %, respectively. The negative effects of residual film on root growth, yield and WUE were greater for cash crops (cotton, tomato and potato) than for cereal crops (wheat, maize). The structural equation model indicated that residual film generated indirect negative effects on crop yield and WUE by directly affecting soil physicochemical properties and crop root growth, with the standard path coefficients of −0.302 and − 0.217, respectively. The results would provide a theoretical basis for reducing residual film pollution on farmland and promoting the green and sustainable development of agriculture.

Estimating distributed autumn irrigation water use in a large irrigation district by combining machine learning with water balance models

Autumn irrigation (AI) after crop harvesting is vital for agricultural production in cold arid regions, typically requiring more water than regular irrigation during crop growth phases. Understanding distributed AI water use (AIWU) is key to optimizing irrigation strategies and refining agro-hydrological simulations. However, field-scale monitoring of irrigation water use is challenging, particularly in large districts, and quantification methods for distributed AIWU have seldom been investigated. Given this, we proposed a remote sensing-based model to estimate AIWU from water balance analysis, with key components derived through machine learning algorithms. Specifically, to address the unique challenge of short water ponding duration during AI, we selected MODIS as the primary data source, supplemented with Sentinel-2 data to enrich field-level details. A Sentinel-2 empirical bathymetry model, informed by in-situ measurements, served as a foundation for constructing a MODIS bathymetry model using random forest. This MODIS bathymetry model was essential for determining water ponding depths, which allowed for accurate estimation of infiltration rates when applied to the MODIS-based water index time series. By integrating these estimates into the water balance framework, we achieved a more precise estimate of AIWU. The proposed model was applied to Hetao Irrigation District (HID), the largest irrigation district in the arid region of China. The estimated steady infiltration rate and canal efficiency align with similar studies. The results indicate that the average AIWU per unit AI area in the HID remains stable during 2010–2020 with substantial spatial variability at the pixel level, providing new insights into the local hydrological cycle. The AIWU of HID has been decreasing by 19 million m3 per year during this period mainly due to the reduction in AI area, with a more prominent trend from 2010 to 2017. Our study deepens insights into the spatial–temporal dynamics of AIWU in arid regions, contributing to better irrigation management.

Deficit Irrigation-Based Improvement in Growth and Yield of Quinoa in the Northwestern Arid Region in China

Given the current global water scarcity issues, which particularly affect arid regions such as northwestern China, it is crucial to find crop planting patterns that result in efficient water resource utilization. Quinoa, as a drought-resistant and highly nutritious crop, has garnered significant attention from agricultural researchers in recent years. From 2019 to 2020, a series of experimental studies were conducted under non-mulching drip irrigation conditions to investigate the growth adaptability and the response to different irrigation levels of quinoa in an arid region in northwestern China. A comparative analysis of quinoa’s dry matter accumulation, yield, thousand-grain weight, harvest index, and water use efficiency under varying irrigation levels revealed that increasing irrigation significantly enhanced quinoa’s dry matter accumulation and yield. By optimizing the irrigation strategies, we found that the water-saving practice of initiating moderate irrigation in the sensitive water-demanding stages (flowering and fruiting) of quinoa increased the yield. The experiment results showed that, in 2020, the optimal irrigation amount was 3675 m3·ha−1 during a 14-day irrigation cycle, meeting quinoa’s growth requirements while improving water resource utilization efficiency. This study not only provides a scientific basis for the efficient cultivation of quinoa in the arid regions of northwestern China, but also offers new insights into and technical support for agricultural water resource management in the region, contributing to the sustainable development of agriculture in arid areas.

Measurement and characteristics of radon flow in an extremely arid region based on a closed-system earth-air model

Radon (222Rn) is a radioactive gas that occurs naturally in the soil and is harmful to the environment and health. However, the measuring the amount of radon flowing is challenging. This study reveals the mechanism responsible for radon transportation and concentration variation, the main driving forces acting, and the key factors operating in the vadose zone. In this study, two separate holes were used to monitor the amount of earth-air and radon flowing in and out of the soil in the extremely arid region in China where the Mogao Grottoes are located. Using a closed-system model, the quantity, characteristics, and regularity of the flow of earth-air and radon were thus determined on daily and yearly timescales. The same patterns of variation in earth-air flow and radon concentration were found at the two sites, both depending on the variation in the atmospheric pressure (AP). When the AP decreases, earth-air flows out from the soil with a high radon concentration. Conversely, when the AP increases, earth-air enters into the soil with a low radon concentration. Thus, radon is continuously emitted from the soil. The concentration of radon in the earth-air is proportional to the rate of flow of earth-air and therefore increases as the AP decreases. The radon emission also varies with the seasonal variation in temperature and AP, which is high in summer and low in winter. On a daily timescale, the radon varies in a bimodal manner. Therefore, the net amount of radon emitted from the soil is positively correlated with the amplitude of the AP fluctuation, temperature, soil porosity, and thickness of the vadose zone. The atmospheric pumping is the main driving force responsible for the radon emission. However, the surface closure, landform, cracks, faults, grain size, pore structure, soil adsorption, basal uranium/radium, salts, wind, lunar cycle, latitude and altitude have important effects on the number of radon emission. As such, it provides a scientific basis for the effective utilization of radon and prevention of its emission from soil.

Improving the accuracy of precipitation estimates in a typical inland arid region of China using a dynamic Bayesian model averaging approach

Improving the accuracy of precipitation estimates in a typical inland arid region of China using a dynamic Bayesian model averaging approach

Carbon cycle responses to climate change across China's terrestrial ecosystem: Sensitivity and driving process

Investigations into the carbon cycle and how it responds to climate change at the national scale are important for a comprehensive understanding of terrestrial carbon cycle and global change issues. Contributions of carbon fluxes to the terrestrial sink and the effects on climate change are still not fully understood. In this study, we aimed to explore the relationship between ecosystem production (GPP/SIF/NDVI) and net ecosystem carbon exchange (NEE) and to investigate the sensitivity of carbon fluxes to climate change at different spatio-temporal scales. Furthermore, we sought to delve into the carbon cycle processes driven by climate stress in China since the beginning of the 21st century. To achieve these objectives, we employed correlation and sensitivity analysis techniques, utilizing a wide range of data sources including ground-based observations, remote sensing observations, atmospheric inversions, machine learning, and model simulations. Our findings indicate that NEE in most arid regions of China is primarily driven by ecosystem production. Climate variations have a greater influence on ecosystem production than respiration. Warming has negatively impacted ecosystem production in Northeast China, as well as in subtropical and tropical regions. Conversely, increased precipitation has strengthened the terrestrial carbon sink, particularly in the northern cool and dry areas. We also found that ecosystem respiration exhibits heightened sensitivity to warming in southern China. Moreover, our analysis revealed that the control of terrestrial carbon cycle by ecosystem production gradually weakens from cold/arid areas to warm/humid areas. We identified distinct temperature thresholds (ranging from 10.5 to 13.7 °C) and precipitation thresholds (approximately 1400 mm yr−1) for the transition from production-dominated to respiration-dominated processes. Our study provides valuable insights into the complex relationship between climate change and carbon cycle in China.

Occurrence, source apportionment, and ecological risk of legacy and emerging per- and poly-fluoroalkyl substances (PFASs) in the Dahei river basin of a typical arid region in China

Per- and poly-fluoroalkyl substances (PFASs) are artificial chemicals with broad commercial and industrial applications. Many studies about PFASs have been conducted in densely industrial and populated regions. However, fewer studies have focused on the PFASs’ status in a typical arid region. Here, we investigated 30 legacy and emerging PFASs in surface water from the mainstream and tributaries of the Dahei River. Our results revealed that total PFASs concentrations (∑30PFASs) in water ranged from 3.13 to 289.1 ng/L (mean: 25.40 ng/L). Perfluorooctanoic acid (PFOA) had the highest mean concentration of 2.44 ng/L with a 100% detection frequency (DF), followed by perfluorohexanoic acid (PFHxA) (mean concentration: 1.34 ng/L, DF: 59.26%). Also, perfluorohexane sulfonate (DF: 44.44%), perfluorobutane sulfonate (DF: 88.89%), and perfluorooctane sulfonate (PFOS) (DF: 92.59%) had mean concentrations of 12.94, 2.00, and 1.05 ng/L, respectively. Source apportionment through ratio analysis and principal component analysis-multiple linear regression analysis showed that treated or untreated sewage, aqueous film-forming foam, degradation of precursors, and fluoropolymer production were the primary sources. The PFOS alternatives were more prevalent than those of PFOA. Conductivity, total phosphorus, and chlorophyll a positively correlated with Σ30PFASs and total perfluoroalkane sulfonates concentrations. Furthermore, ecological risk assessment showed that more attention should be paid to perfluorooctadecanoic acid, perfluorohexadecanoic acid, perfluorooctane sulfonate, perfluorohexane sulfonate, and (6:2 and 6:2/8:2) polyfluoroalkyl phosphate mono- and di-esters. The mass load of PFASs to the Yellow River was 1.28 kg/year due to the low annual runoff in the Dahei River in the arid region. This study provides baseline data for PFASs in the Dahei River that can aid in the development of effective management strategies for controlling PFASs pollution in typical arid regions in China.

Multiple cutting increases forage productivity and enhances legume pasture stability in a rainfed agroecosystem

Appropriate harvesting management is essential for sustainable forage production and improving nutritional quality. In this study, four forage crops, including Medicago sativa (Ms), Vicia sativa (Vs), Avena sativa (As), and Sorghum Sudangrass (Ss) were evaluated under two harvesting modes, i.e. single harvest and multiple cuttings. Results showed that multiple cuttings increased the forage yield of Ms., As, and Ss by 82 %–114 %, 7.5 %–51 %, and 21 %–150 % compared to the single harvest. The acid and neutral detergent fiber concentration decreased, while crude protein contents increased with multiple cuttings. Also, multiple cuttings increased the ether extract content of Ms. and Ss and reduced the ash content by 9.42 % to 33.04 % from 2015 to 2016. The variation range of legume forages' annual yield was 18.66 %–33.04 %, while that of gramineous forages was 9.42 %–25.98 %. The relative feeding value (RFV) of Ms. was higher than that of other forages under multiple cuttings. In general, multiple cuttings decreased the SOC content, but the effect was insignificant for the two leguminous forages. Correlations analysis showed a significant positive relationship of RFV and CP with precipitation while a negative relationship of ADF and NDF with temperature. Moreover, results of yield stability, contribution rate, and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) analysis showed that the response of legume crops to multiple cutting was superior to that of gramineous crops. Overall, the cultivation of leguminous forage under multiple cuttings can provide a basis for the development of pastoral agriculture production and animal husbandry in arid regions of China.

Pollution and Ecological Risk Assessment of Metal Elements in Groundwater in the Ibinur Lake Basin of NW China

Groundwater pollution by metal elements is a serious issue due to its probable risks to the ecosystem and human health. In the present study, 75 groundwater samples were collected from the Ibinur Lake Basin (ILB) of NW China. The contents of As, Se, Pb, Cu, Cr(Ⅵ), Zn, Mn, and Cd were determined. The levels, pollution degrees, and potential ecological risks of metals in groundwater were systematically analyzed for the first time in this area. The potential sources of metals were also discussed. It was observed that the mean contents of metals in groundwater in the ILB were lower than the Class III thresholds of the Standard for Groundwater Quality of China (GB/T 14848–2017), whereas the maximum contents of As, Se, Pb, Cr(Ⅵ), and Mn exceeded the Class III thresholds values. The pollution index of each metal and the Nemerow comprehensive index (NPI) caused by the overall pollution by all these metals in groundwater showed the pollution-free level. The single and comprehensive potential ecological risk index of analyzed metals in groundwater showed a relatively low level of potential ecological risk. Additionally, spatial distribution patterns of contents, pollution levels, and ecological risks of metals in groundwater in the ILB were found to be substantially heterogeneous. Furthermore, As and Se in groundwater originated from anthropogenic sources such as agriculture and mining, whereas Mn mainly originated from natural factors, and Pb, Cu, Cr(Ⅵ), Zn, and Cd were correlated with both natural and anthropogenic sources. Overall, As was identified as the main pollution factor, while As and Se were identified as the main ecological risk factors in the groundwater in the ILB. These results can provide important information for groundwater management in the ILB and will guide authorities in taking the necessary measures to ensure the safety of groundwater supply in the northwestern arid regions of China.

Positive impact of urbanization on vegetation growth has been continuously strengthening in arid regions of China

The ecological environment is fragile in arid regions, and the direct and indirect impacts of continuing urbanization on vegetation growth in cities still need to be studied in depth. In this study, we focused on four provincial capital cities (Urumqi, Lanzhou, Yinchuan, and Hohhot) in arid regions of China. We used continuous 30 m land cover and vegetation greenness (VG) data from 1990 to 2021 to extract the impact of urbanization on vegetation growth by separating the impact of natural conditions. Our results showed that the study area’s urban area (UA) had expanded rapidly at a rate of 39.2 km2/a, increasing by 3.39 times between 1990 and 2021. While urban expansion occurred rapidly, the overall VG of the study area also increased (slope = 2.16 × 10−3), with the enhancement of VG increasing gradually from west to east. The VG and its trend in the UA were significantly higher than those in the natural vegetation area (NA). In addition, the duration of the urban vegetation growth season was longer than that of the NA, which also confirmed the positive impact of urbanization on the vegetation growth period. Furthermore, we found that the positive impact of urbanization on vegetation had continuously strengthened over time. In 1990 and 2021, the VG areas had 83% and 87% above the ‘zero-impact line’ in the UA, respectively, indicating a very significant impact of urbanization on vegetation growth in arid regions with fragile natural conditions. Our study identified the long-term dynamic trends in urbanization and VG in arid regions and clarified the non-linear relationship between the two concurrent growth factors. This has significant implications for correctly understanding the impact of urbanization on vegetation in arid regions and can provide a scientific reference for the ecological construction of urban environments in the region.

Spatiotemporal patterns and main driving factors of drainage water quality of an arid irrigation district with shallow groundwater table.

Drainage water quality is a crucial factor reflecting the regime of agricultural non-point source pollution in irrigation districts and is closely related to land use, soil texture, cropping pattern, fertilization, and irrigation and drainage conditions. However, the response of drainage water quality to various natural and anthropogenic factors needs further exploration in irrigation districts affected by shallow groundwater table. Spatiotemporal patterns of chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), and ammonium nitrogen (NH4-N) were monitored and analyzed in ten agricultural drainage ditches in the arid region of China from 2011 to 2019. Spatially, water pollution in agricultural drainage ditches with small water quantity can be significantly exacerbated by urban sewage, whereas a large amount of agricultural drainage can effectively dilute the pollution of urban sewage. Severe soil salinization in the cropland increases the risk of water pollution due to easier losses of soil nutrient and organic matter. Soil salinization is a key factor in the crop distribution pattern based on the crop salt tolerance, and the maize/wheat field with a higher fertilizer application rate generally results in poorer drainage water quality. Temporally, for the agricultural drainage ditches, the monthly and annual COD, TP, TN, and NH4-N concentrations fluctuate inversely with drainage water quantity and are positively correlated with fertilizer application, among which the monthly COD concentration in drainage water has larger variation in severe salinized areas. There exist critical annual and monthly drainage amounts, above which the probabilities of higher concentrations of COD, TP, TN, and NH4-N reduce greatly.