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Groundwater is crucial for multiple uses over the world, especially in arid and semiarid regions. However, human activities significantly decreased groundwater quality. In this study, the spatiotemporal variation of groundwater quality was evaluated in an arid area where long-term paper wastewater irrigation has been implemented. For this study, seven wells were regularly monitored for physicochemical parameters over a period of 1 year. Statistical and graphical approaches were applied to interpret the spatiotemporal variation of groundwater quality parameters in the wastewater irrigation zone. Correlation analysis was also carried out to reveal the sources of some major ions. The results indicate that the groundwater type in the study area is dominated by the Cl-Na, followed by the HCO-Na, the HCO-Ca·Mg, and the SO·Cl-Ca·Mg types. Groundwater in the area is significantly contaminated locally with fluoride, nitrite and ammonia, and the chemical oxygen demand levels were increased in some groundwater monitoring wells. Most contaminants showed an increasing trend from the Yellow River water irrigation zone toward the wastewater irrigation zone. Rock weathering, mineral dissolution, and cation exchange are important processes controlling groundwater quality, but human activities, such as wastewater irrigation, play an undeniable role in affecting groundwater quality in this area. The results of this study contribute to the understanding of the formation and circulation of groundwater under human activities and provide a scientific basis for regional water quality evaluation, water quality improvement, and protection. [ABSTRACT FROM AUTHOR]

Drylands are vast and face threats from climate change and human activities. Traditional reviews cannot capture interdisciplinary knowledge, but bibliometric analysis provides valuable insights. Our study conducted bibliometric research of scientific production on climate change and land degradation in drylands using remote sensing. We examined 1527 Scopus-indexed publications to identify geographic and thematic hotspots, extracting leading authors, journals, and institutions. China leads in publications, followed by the US, Germany, and Australia. The US has the highest citation count. Collaboration networks involve the US, China, and European countries. There has been an exponential increase in remote sensing of land degradation in drylands (RSLDD) publications since 2011. Key journals include "International Journal of Remote Sensing" and "Remote Sensing of Environment". The analysis highlights the growing interest in the field, driven by Australia, the US, and China. Key areas of study are vegetation dynamics and land use change. Future perspectives for this scientific field involve promoting collaboration and exploring emerging technologies for comprehensive land degradation and desertification research. [ABSTRACT FROM AUTHOR]

Arid zone grassland is a crucial component of terrestrial ecosystems and plays a significant role in ecosystem protection and soil erosion prevention. However, accurately mapping grassland spatial information in arid zones presents a great challenge. The accuracy of remote sensing grassland mapping in arid zones is affected by spectral variability caused by the highly diverse landscapes. In this study, we explored the potential of a rectangular tile classification model, constructed using the random forest algorithm and integrated images from Sentinel-1A (synthetic aperture radar imagery) and Sentinel-2 (optical imagery), to enhance the accuracy of grassland mapping in the semiarid to arid regions of Ordos, China. Monthly Sentinel-1A median value images were synthesised, and four MODIS vegetation index mean value curves (NDVI, MSAVI, NDWI and NDBI) were used to determine the optimal synthesis time window for Sentinel-2 images. Seven experimental groups, including 14 experimental schemes based on the rectangular tile classification model and the traditional global classification model, were designed. By applying the rectangular tile classification model and Sentinel-integrated images, we successfully identified and extracted grasslands. The results showed the integration of vegetation index features and texture features improved the accuracy of grassland mapping. The overall accuracy of the Sentinel-integrated images from EXP7-2 was 88.23%, which was higher than the accuracy of the single sensor Sentinel-1A (53.52%) in EXP2-2 and Sentinel-2 (86.53%) in EXP5-2. In all seven experimental groups, the rectangular tile classification model was found to improve overall accuracy (OA) by 1.20% to 13.99% compared to the traditional global classification model. This paper presents novel perspectives and guidance for improving the accuracy of remote sensing mapping for land cover classification in arid zones with highly diverse landscapes. The study presents a flexible and scalable model within the Google Earth Engine framework, which can be readily customized and implemented in various geographical locations and time periods. [ABSTRACT FROM AUTHOR]

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Lanzhou City is located in the semi-arid region of northwest China, which experiences serious desertification. Moreover, the high intensity of land development, with the accelerated industrialization and urbanization, causes increasingly aggravated conflict between humans and the environment. Exploring the response of the ecological environment quality to the natural environment and anthropogenic activities is important to protect the sustainable development of urban economic construction and the environment. Based on the Google Earth Engine (GEE) platform, this paper constructed a modified Remote Sensing Ecological Index (MRSEI) model which could reflect the ecological environment quality by integrating the desertification index (DI) into the Remote Sensing Ecological index (RSEI) model. This paper explores the spatiotemporal variation in the environmental quality from 2000 to 2020 in Lanzhou, China, and analyzes the natural and anthropogenic factors affecting the environment quality in terms of temperature, precipitation, gross domestic product (GDP), land use, night lighting, and population. The results showed that the mean value of MRSEI ranged from 0.254 to 0.400. The area undergoing fast growth in ecological quality was in the northwestern part of Lanzhou, and the area of decrease was in the central part. Various factors have different degrees of influence on the ecosystem, with temperature, precipitation, and land use having a greater impact, and GDP and population having a limited impact. Precipitation and temperature showed a strong impact when interacting with other factors, demonstrating that precipitation and temperature were also key factors affecting MRSEI. Overall, climate change and the implementation of ecological restoration projects have led to an improvement in the quality of the ecological environment in Lanzhou. This study provides a reference for understanding the spatiotemporal changes in the ecological environment in semi-arid Lanzhou and is conducive to formulating proper protection strategies. [ABSTRACT FROM AUTHOR]

The Tarim Basin is a large inland arid basin in the arid region of northwest China and has been experiencing significant "warming and wetting" since 1987. As a result, the purpose of this paper is to determine whether the climate transition phenomenon occurred in the Tarim Basin as well as the role of atmospheric circulation in this process. We use meteorological data and atmospheric circulation indexes to study the seasonal trends of climate change in this region from 1987 to 2020 to understand how they are affected by atmospheric circulation. The findings show that, from 1987 to 2020, the Tarim Basin experienced significant warming and wetting; with the exception of the winter scale, all other seasonal scales exhibited a clear warming and wetting trend. From the perspective of spatial distribution, most of the areas showed a significant warming trend, and the warming amplitude around the basin is greater than that in the central area of the basin. However, there are significant regional differences in precipitation change rates. Meanwhile, wavelet analysis shows that there is a significant oscillation period of 17–20 years between climate change and the atmospheric circulation index during 1987–2020. The correlation analysis shows that the Pacific decadal oscillation (PDO) and El Niño-Southern Oscillation (ENSO) are the main influencing factors of climate change in the Tarim Basin at different seasonal scales, while the teleconnection of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) is low and the PDO dominates the summer and autumn temperature changes in the Tarim Basin. The research results of this paper show that, despite the warming and wetting trends since 1987 in the Tarim Basin, the climate type did not change. From 1987 to 2020, the main teleconnection factors of climate change in the Tarim Basin were PDO and ENSO. [ABSTRACT FROM AUTHOR]

The net primary productivity (NPP) of vegetation is an important indicator reflecting the vegetation dynamics and carbon sequestration capacity in a region. In recent years, China has implemented policies to carry out ecological protection. To understand the changes in the distribution of vegetation NPP in China and the influence of climate factors, the Carnegie–Ames–Stanford approach (CASA) model was used to estimate the NPP from 2001 to 2020. In this paper, several sets of measurement datasets and products were collected to evaluate the effectiveness of the model and suggestions were provided for the modification of the CASA model based on the evaluation results. In addition to the correlation analysis, this paper presents a statistical method for analyzing the quantitative effects in individual climatic factors on NPP changes in large regions. The comparison found that the model has a better estimation effect on grassland and needleleaf forest. The estimation error for the evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF) decreases with the warming of the climatic zone, while the evergreen broadleaf forest (EBF) and deciduous needleleaf forest (DNF) do the opposite. The changes in total CASA NPP were consistent with the trends of other products, showing a dynamic increasing trend. In terms of the degree of correlation between the NPP changes and climatic factors, the NPP changes were significantly correlated with temperature in about 10.39% of the vegetation cover area and with precipitation in about 26.92% of the vegetation cover area. It was found that the NPP variation had a negative response to the temperature variation in Inner Mongolia grasslands, while it had a positive but small effect (±10 g C) in the Qinghai–Tibet Plateau grasslands. Precipitation had a facilitative effect on the grassland NPP variation, while an increase in the annual precipitation of more than 200 mm had an inhibitory effect in arid and semi-arid regions. This study can provide data and methodological reference for the ecological assessment of large-scale regional and climate anomalous environments. [ABSTRACT FROM AUTHOR]

Groundwater evapotranspiration (ETg) is a significant component of water and energy balance analyses in arid and semiarid environments; however, it is also one of the most challenging items to estimate. Estimation of ETg using diurnal groundwater-level fluctuation is considered cost-effective and straightforward, while more accurate estimation technology continues to be developed due to the complex set of factors that influence the variation of groundwater level. This paper proposes a method for calculating ETg that combines the analytical solution of the Boussinesq equation and dynamic harmonic regression analysis, which is a nonstationary approach to groundwater-level signal extraction. The presented approach can calculate ETg values with a high time resolution consistent with the groundwater-level monitoring frequency, and it is robust enough to handle large amounts of measurement data. More importantly, this method eliminates the influence of recharge during the groundwater-level-rise stage. The method is tested in bushland dominated by Sminthopsis psammophila in Mu Us Desert (northern China), which has a shallow water table. The results show that this method is easy to perform and it obtains a reasonable estimate of ETg in the unfrozen seasons, regardless of the disturbance of recharge that results in a sharp rise in groundwater level. However, the method does not work well in the frozen seasons because of the physical mechanisms of change in groundwater movement in the vadose zone and a strong barometric effect. Overall, the method provides a step toward accuracy of ETg estimation using diurnal groundwater-level fluctuation, and this paper provides guidelines for its use. [ABSTRACT FROM AUTHOR]

Highly accurate near-real-time satellite precipitation estimates (SPEs) are important for hydrological forecasting and disaster warning. The near-real quantitative precipitation estimates (REGC) of the recently developed Chinese geostationary meteorological satellite Fengyun 4A (FY4A) have the advantage of high spatial and temporal resolution, but there are errors and uncertainties to some extent. In this paper, a self-adaptive ill-posed least squares scheme based on sequential processing (SISP) is proposed and practiced in mainland China to correct the real-time biases of REGC hour by hour. Specifically, the scheme adaptively acquires sample data by setting temporal and spatial windows and constructs an error-correction model based on the ill-posed least squares method from the perspectives of climate regions, topography, and rainfall intensity. The model adopts the sequential idea to update satellite precipitation data within time windows on an hour-by-hour basis and can correct the biases of real-time satellite precipitation data using dynamically changing parameters, fully taking into account the influence of precipitation spatial and temporal variability. Only short-term historical data are needed to accurately rate the parameters. The results show that the SISP algorithm can significantly reduce the biases of the original REGC, in which the values of relative bias (RB) in mainland China are reduced from 11.2% to 3.3%, and the values of root mean square error (RMSE) are also reduced by about 17%. The SISP algorithm has a better correction in humid and semi-humid regions than in arid and semi-arid regions and is effective in reducing the negative biases of precipitation in each climate region. In terms of rain intensity, the SISP algorithm can improve the overestimation of satellite precipitation estimates for low rain intensity (0.2–1 mm/h), but the correction for high rain intensity (>1 mm/h) needs further improvement. The error component analysis shows that the SISP algorithm can effectively correct the hit bias. This study serves as a valuable reference for real-time bias correction using short-term accumulated precipitation data. [ABSTRACT FROM AUTHOR]

Continuous evapotranspiration (ET) data with high spatial resolution are crucial for water resources management in irrigated agricultural areas in arid regions. Many global ET products are available now but with a coarse spatial resolution. Spatial-temporal fusion methods, such as the spatial and temporal adaptive reflectance fusion model (STARFM), can help to downscale coarse spatial resolution ET products. In this paper, the STARFM model is improved by incorporating the temperature vegetation dryness index (TVDI) into the data fusion process, and we propose a spatial and temporal adaptive evapotranspiration downscaling method (STAEDM). The modified method STAEDM was applied to the 1 km SSEBOP ET product to derive a downscaled 30 m ET for irrigated agricultural fields of Northwest China. The STAEDM exhibits a significant improvement compared to the original STARFM method for downscaling SSEBOP ET on Landsat-unavailable dates, with an increase in the squared correlation coefficients (r2) from 0.68 to 0.77 and a decrease in the root mean square error (RMSE) from 10.28 mm/10 d to 8.48 mm/10 d. The ET based on the STAEDM additionally preserves more spatial details than STARFM for heterogeneous agricultural fields and can better capture the ET seasonal dynamics. The STAEDM ET can better capture the temporal variation of 10-day ET during the whole crop growing season than SSEBOP. [ABSTRACT FROM AUTHOR]

Accurately grasping the distribution and area of cotton for agricultural irrigation scheduling, intensive and efficient management of water resources, and yield estimation in arid and semiarid regions is of great significance. In this paper, taking the Xinjiang Shihezi oasis agriculture region as the study area, extracting the spectroscopic characterization (R, G, B, panchromatic), texture feature (entropy, mean, variance, contrast, homogeneity, angular second moment, correlation, and dissimilarity) and characteristics of vegetation index (normalized difference vegetation index/NDVI, ratio vegetation index/DVI, difference vegetation index/RVI) in the cotton flowering period before and after based on GF-6 image data, four models such as the random forests (RF) and deep learning approach (U-Net, DeepLabV3+ network, Deeplabv3+ model based on attention mechanism) were used to identify cotton and to compare their accuracies. The results show that the deep learning model is better than that of the random forest model. In all the deep learning models with three kinds of feature sets, the recognition accuracy and credibility of the DeepLabV3+ model based on the attention mechanism are the highest, the overall recognition accuracy of cotton is 98.23%, and the kappa coefficient is 96.11. Using the same Deeplabv3+ model based on an attention mechanism with different input feature sets (all features and only spectroscopic characterization), the identification accuracy of the former is much higher than that of the latter. GF-6 satellite image data in the field of crop type recognition has great application potential and prospects. [ABSTRACT FROM AUTHOR]

Over the past two decades, China's spatial distribution of cultivated land has been stable, yet there remains an urgent need to amplify grain productivity. The central scientific question addressed in this study is: How can we effectively evaluate the natural resource thresholds of cultivated land at a regional scale? Despite existing systems, there is a noticeable gap, particularly in this area of inquiry. Recognizing the present state of these resources and introducing more efficient management strategies is pivotal. This paper aims to research the restrictive situation of the natural resources background quality (NRB-quality) of China's cultivated land by developing an innovative classification method and a short-board identification method and adopting cluster analysis and other technical methods. The results showed that (1) China mainly maintains medium-quality land (57.30%). The soil texture displayed a fine average grade of 1.39, while the biodiversity, soil pH, secondary land types, and cropping systems indicated poor conditions, with average scores of 2.01, 2.06, 2.26, and 2.33. (2) A notable difference in the restrictive factors of cultivated land quality emerged, with secondary land types of cultivated land (including paddy field, irrigated land, and dry land) being the only national short-board factor. Regionally, the cropping system, secondary land types of cultivated land, and natural region were identified as short-board factors in 31, 24, and 23 natural regions. (3) The regional difference in cultivated land quality leads to six different management strategies. Eastern regions emphasized stabilizing land distribution and infrastructure enhancement, while China's western areas advocated cautious development and heightened ecological protection. The findings demonstrated regional differences in the status of cultivated land quality factors; implementing classified management approaches for cultivated land quality factors based on their characteristics is vital to preventing irreversible decline. The study serves as an important basis for the protection and utilization of cultivated land in the new era to clarify the NRB-quality differences of cultivated land in China. [ABSTRACT FROM AUTHOR]

Slurries with quicklime for fissure restoration in earthen sites in northwest China can reduce dry shrinkage and reinforce the soil on both sides of fissure. However, their full-scale properties need to be investigated and a compatibility assessment needs to be carried out in order to proceed with further research. The paper pays attention to the full-scale properties of the slurry and typical site soils. A total of 3 slurries with different mix proportions and 35 earthen sites in northwest China are selected to test properties, including basic physical properties, mechanical properties, thermal properties, and water-physical properties. The test results show the properties of the slurries are close and that the properties of the site soils are obviously different. Then, a compatibility assessment is considered as a multi-criteria decision-making problem to solve. Three universal and necessary steps in the paper are to select assessment indicators, weigh each indicator, and sort all of the samples. The AHP, CRITIC, and TOPSIS methods are adopted in the process of the compatibility assessment. The results of assessment show that most site soils are commonly or highly compatible with three slurries; few site soils are very highly or lowly compatible; and that no site soils are very lowly compatible, which means that the three slurries with quicklime with different mix proportions are acceptable for most earthen sites in NW China. The paper provides much basic data of the slurries with quicklime and site soils widely distributed in arid region in NW China, and also builds a model of the compatibility assessment which has potential for the further application of slurries with quicklime. [ABSTRACT FROM AUTHOR]

In the context of global warming, snow cover changes have an extremely important impact on the hydrological cycle and the redistribution of water resources in arid and semi-arid regions. In this paper, based on the daily cloud-free snow area remote sensing product data in the source region of Yangtze River (SRYR) from 2000 to 2019, the snow phenology variables such as the snow cover day (SCD), snow onset date (SOD), snow end date (SED), and snow duration day (SDD) were extracted separately for each hydrological year, and the vertical distribution of snow cover area (SCA) in the SRYR was analyzed by combining with the digital elevation model (DEM). In addition, we also combined climate factors and land cover types to further explore the spatiotemporal variation characteristics of snow phenology in response to different influencing factors, in order to reveal the spatiotemporal variation patterns of snow cover in the SRYR. The results showed that: (1) The SCA in the SRYR has a more obvious vertical distribution, with the maximum SCA reaching 61.58% at high elevation, while at low elevation, the SCA is mostly below 20%. The distribution of SCD in the study area showed a significant exponential correlation with DEM (R2 = 0.87). (2) The area of SOD in the SRYR showed an advanced trend of about 63.37%, while the area of SED showed a delayed trend of about 69.59%, and the area which showed significant trends is 4.29% and 4.36%, respectively. Therefore, the trends of both SOD and SED showed insignificant changes. (3) Temperature change is the main factor affecting the change of snow cover in the SRYR. Among them, 90.9% of the regions showed a significant positive correlation between temperature and SCD, while precipitation showed a significant negative correlation with SCD in about 75.3% of the total area of SRYR. Under the stable snow area (SCD > 60), the land cover type is glacial or permanent snow about 1.5 × 103 km2, which covers almost the entire glacial or permanent snow of the SRYR. [ABSTRACT FROM AUTHOR]

The global climate shows an obvious warming trend, and the impact on water resources is increasing. Abrupt temperature change and warming hiatus are two important states of temperature change. The quantitative impacts of temperature change and warming hiatus on surface runoff remain unclear. Based on the measured runoff data from 60 representative hydrological stations in China from 1956 to 2016 and the Water Balance Model developed by the Research Center for Climate Change (RCCC-WBC), this paper analyzes the quantitative impacts of abrupt temperature change and warming hiatus on surface runoff. The results showed that the effects of three types of abrupt temperature changes on runoff in different basins in China are significantly different. The effects of abrupt temperature changes and warming stagnation on runoff in northern China are greater than those in southern China, and the effects of abrupt temperature changes and warming stagnation on runoff in the upper, middle, and lower reaches of the same basin are also different. Before the abrupt change in temperature, the influence of temperature on the surface runoff was less than 9%, and the influence of temperature on the runoff in some southern areas was weaker, only affecting less than 3% of the runoff. When the temperature changes abruptly, the influence of air temperature on the surface runoff in a small part of the arid region is up to 30%. The abrupt change in mean maximum temperature has both positive and negative driving effects on runoff in China, and the negative driving effect is concentrated in the areas with abrupt warming, affecting about 8% of the runoff on average. The average influence of abrupt mean temperature change on runoff in China is about 10%, and the area with a large influence on runoff change is concentrated in the area north of 40° N. The abrupt change in temperature in the middle and lower reaches of the Yellow River Basin has a great influence on the runoff change, up to 13%. The maximum impact of abrupt mean minimum temperature on runoff is concentrated in Northeast China, ranging from 9% to 12%. During the period of temperature stagnation, air temperature and runoff showed an obvious reverse trend. During this period, the average negative influence of drastic changes in air temperature on runoff was about 15%, but precipitation and runoff still maintained a good consistency, which may be due to the effect of other influencing factors which offset the negative driving effect of air temperature. [ABSTRACT FROM AUTHOR]

Introduction: Understanding the impact of deep groundwater depth on vegetation communities and soil in sand dunes with different underground water tables is essential for ecological restoration and the conservation of groundwater. Furthermore, this understanding is critical for determining the threshold value of groundwater depth that ensures the survival of vegetation. Method: This paper was conducted in a semi-arid region in eastern China, and the effects of deep groundwater depth (6.25 m, 10.61 m, and 15.26 m) on vegetation communities and soil properties (0-200 cm) across three dune types (mobile, semi-fixed, and fixed dunes) were evaluated in a sand ecosystem in the Horqin Sandy Land. Results: For vegetation community, variations in the same species are more significant at different groundwater depths. For soil properties, groundwater depth negatively influences soil moisture, total carbon, total nitrogen, available nitrogen, available phosphorus concentrations, and soil pH. Besides, groundwater depth also significantly affected organic carbon and available potassium concentrations. In addition, herb species were mainly distributed in areas with lower groundwater depth, yet arbor and shrub species were sparsely distributed in places with deeper groundwater depth. Discussion: As arbor and shrub species are key drivers of ecosystem sustainability, the adaptation of these dominant species to increasing groundwater depth may alleviate the negative effects of increasing groundwater depth; however, restrictions on this adaptation were exceeded at deeper groundwater depth. [ABSTRACT FROM AUTHOR]

Drought seriously endangers the development of agro‐pastoral ecotone in arid and semi‐arid regions. However, drought evolution characteristics of semi‐arid sandy grassland and its drivers are not well understood in the complex climate change context. Thus, in this paper, the revised standardized precipitation evaporation indices on one‐month (SPEI‐1) and growing‐season (SPEI‐6) scale, flash drought and dry spells (DS) were calculated as drought indicators, and the temporal variabilities and meteorological drivers of drought in Horqin Sandy Land during the growing period (April–September) from 2007 to 2021 were studied. The results showed that SPEI‐1 and SPEI‐6 exhibited negative trends and periodic change. This drought aggravation was manifested in increased grades and numbers of drought months. Flash droughts can occur every month during the growing season. And its occurrence was not only positively correlated with all drought events in frequency but also synchronized in time. The increased number of DS showed an asymmetrical shift towards 7‐day‐and‐longer DS. SPEI sensitivity to precipitation (P) was noticeably higher than to atmospheric evapotranspiration demand (AED) at both monthly and growing season scales. SPEI sensitivity to AED was modulated by P amounts, which was higher during low P period. Apart from the amounts of P and AED, their temporal variability also strongly determined how they affect the drought severity. P was also the main driver for flash drought and long DS, but AED with larger amount and higher variability is the reason for their aggravation. Our results demonstrate the complexity of drought intensification in semi‐arid sandy grasslands and highlight the important role of AED anomalies in it. [ABSTRACT FROM AUTHOR]

Groundwater exploitations in semi‐arid regions result in significant declines of groundwater levels and streamflow and even trigger seasonal streamflow drying up, which may bring adverse impacts on riparian ecosystems. It is critical to explore future streamflow changes caused by variable climate scenarios and groundwater exploitation intensities; however, a comprehensive assessment of the streamflow drying up frequency remains lacking. Furthermore, the thresholds of controlling factors beyond which streamflow drying up occurs have rarely been explored. Here we develop an integrated surface water‐groundwater model for the Taoer River Basin (TRB), a typical semi‐arid watershed in northeast China. We apply the model to multiple future scenarios to reveal the frequency of potential streamflow drying up and explore the thresholds of controlling factors of streamflow drying up based on a decision tree method. We find that the groundwater level in the lower region of the TRB (LTRB) is hard to recover to the riverbed elevation and the streamflow drying up frequency is still high unless the groundwater exploitation is reduced by 50%. However, this leads to a competition between the ecological and economic objectives. Our results also show that the streamflow drying up frequency in the LTRB is very sensitive to the upstream water inflow that can be regulated through the reservoir operation or inter‐basin water diversion, indicating the importance of a basin scale strategic management. The findings of this paper can help policy makers sustainably exploit water resources in semi‐arid regions. [ABSTRACT FROM AUTHOR]

Using the Gravity Recovery and Climate Experiment (GRACE) satellite to monitor groundwater storage (GWS) anomalies (GWSAs) at the local scale is difficult due to the low spatial resolution of GRACE. Many attempts have been made to downscale GRACE-based GWSAs to a finer resolution using statistical downscaling approaches. However, the time-lag effect of GWSAs relative to environmental variables and optimal model parameters is always ignored, making it challenging to achieve good spatial downscaling, especially for arid regions with longer groundwater infiltration paths. In this paper, we present a novel spatial downscaling method for constructing GRACE-based 1 km-resolution GWSAs by using the back propagation neural network (BPNN) and considering the time-lag effect and the number of hidden neurons in the model. The method was validated in Alxa League, China. The results show that a good simulation performance was achieved by adopting varying lag times (from 0 to 4 months) for the environmental variables and 14 hidden neurons for all the networks, with a mean correlation coefficient (CC) of 0.81 and a mean root-mean-square error (RMSE) of 0.70 cm for each month from April 2002 to December 2020. The downscaled GWSAs were highly consistent with the original data in terms of long-term temporal variations (the decline rate of the GWSAs was about −0.40 ± 0.01 cm/year) and spatial distribution. This study provides a feasible approach for downscaling GRACE data to 1 km resolution in arid regions, thereby assisting with the sustainable management and conservation of groundwater resources at different scales. [ABSTRACT FROM AUTHOR]

Altay Prefecture, a typical arid region in northwestern China, has experienced the climate transition from warming-drying to warming-wetting since 1980s and has attracted widespread attention. Nonetheless, it is still unclear how climate change has influenced the distribution of vegetation in this region. In this paper, a reaction–diffusion model of the climate–vegetation system is proposed to study the impact of climate change (precipitation, temperature and carbon dioxide concentration) on vegetation patterns in Altay Prefecture. Our results indicate that the tendency of vegetation growth in Altay Prefecture improved gradually from 1985 to 2010. Under the current climate conditions, the increase of precipitation results in the change of vegetation pattern structures, and eventually vegetation coverage tends to be uniform. Moreover, we found that there exists an optimal temperature where the spot vegetation pattern structure remains stable. Furthermore, the increase in carbon dioxide concentration induces vegetation pattern transition. Based on four climate change scenarios of the Coupled Model Intercomparison Project Phase 6 (CMIP6), we used the power law range (PLR) to predict the optimal scenario for the sustainable development of the vegetation ecosystem in Altay Prefecture. [ABSTRACT FROM AUTHOR]

This is a paper about the speed and intensity with which new and intensive human land use in a semi-arid environment can bring about large-scale environmental change. In particular, this paper pinpoints how and why it was that the Yellow River shifted from a long-term condition of relative stability to a later state of frequent floods and course changes in the eleventh century. It is possible to trace the environmental history of this dramatic and sudden change of state with precision and confidence. Historical sources that record the dates and characteristics of flood events downstream align well with those that note the locations and dates of human activity upstream. More important, each aligns well not only with one another, but also with information from environmental science: sediment cores that preserve soil and pollen evidence for the timing and processes of systematic change. [ABSTRACT FROM AUTHOR]

Lakes are sensitive indicators of climatic change and are important resources for regional economic development. In recent years, there have been many studies related to the changes in lake area and lake volume. However, further studies are still required to understand the responses of lakes to climatic change and human activities. This paper utilizes lakes in the Qaidam Basin, an inland arid region of China, as the object of study and investigates the characteristics of variability in lake changes and its driving forces by combining multi-source remote sensing, model simulations and historical data. We first analyzed the spatiotemporal pattern of climatic change in the basin under the background of global warming. The response of lake water volume to climatic change and human activities is then discussed. Finally, the main factors that affect the change in lake water volume in different regions of the basin are delineated. The water volume of lakes in the Qaidam Basin increased by 3.81 km3 from 1990 to 2020. Particularly since the 21st century, the water volume of lakes has increased rapidly, and an increasingly abrupt change appeared around 2015. The increases in precipitation and vegetation area are the main and secondary factors that led to the increase in total lake water volume in the basin, respectively. However, the main influencing factors still vary in different regions. The impact of air temperature, evaporation, and changes in the cropland area on the change in lake water volume is generally not obvious. Human activities, such as the development of salt lakes and damming, have led to substantial changes in the spatial pattern of lakes in the middle of the basin and are associated with the replacement, genesis, and disappearance of Yiliping Lake, Yahu Lake and West Taijinar Lake, respectively. This study reveals the changing characteristics of climate and lake water volume in inland arid basins in China, which are highly important to understand the responses of lakes to climatic change and human activities, and provides a scientific basis for the rational development and utilization of lake resources in arid basins. [ABSTRACT FROM AUTHOR]

Flood disaster is one of the natural disasters which cause the most serious economic losses, the most casualties, and the greatest social impact. Flood frequency analysis is very important for reducing flood disaster. In this paper, based on the flood data of Manas River and tools of Box–Cox and Johnson normal transformation, the nonparametric statistical method for flood frequency analysis is studied in order to analyze the adaptability between it and the rivers in arid region of north-western China. The calculation result of the fitness index is divided into two parts: high flood discharge and low flood discharge. One of the two evaluation indexes has an advantage in fitting, and the number of advantages of the three methods in each part has been counted. After analysis, for the flood peak discharge frequency of rivers in arid region of north-western China, the frequency curve of Johnson transformation fits best with empirical data. The high flood discharge advantage is 6, and the low flood discharge is 4. For the flood volume frequency of rivers in arid region of north-western China, Box–Cox transform fits well with empirical data at the high flood discharge frequency curve, and its advantage is 12; Johnson transformation has a better fit between the low flood discharge frequency curve and empirical data, and its advantage is 12. Therefore, it is the way of improving the precision of flood frequency analysis to use the method of P-III distribution and normal transformation comprehensively. [ABSTRACT FROM AUTHOR]

Water system management is a worldwide challenge, especially in arid and semi-arid regions. Ecological water conveyance projects aim to raise the groundwater table, thereby saving natural vegetation and curbing ecological deterioration. Since 2000, these projects have been implemented in the arid zone of northwest China, with generally successful outcomes. Taking a portion of the lower reaches of the Tarim River as the study area, this paper analyzes in detail the ecohydrological effects which have occurred since the launching of artificial water conveyance 20 years ago. The results show that the groundwater table in the upper, middle and lower segments of the Tarim River's lower reaches has been raised on average 4.06, 4.83 and 5.13 m, respectively, while the area of surface water bodies connected to those sections has expanded from 49.00 km2 to 498.54 km2. At the same time, Taitema Lake, which is the terminal lake of the Tarim River, has been revived and now boasts a water area of 455.27 km2. Other findings indicate that the surface ecological response is extremely sensitive and that the area of natural vegetation has expanded to 1423 km2. Furthermore, the vegetation coverage, vegetation index (NDVI), and Net Primary Productivity (NPP) have increased by 132 km2, 0.07 and 7.6 g C m−2, respectively, and the Simpson dominance, McIntosh evenness, and Margalef richness indices have risen by 0.33, 0.35 and 0.49, respectively, in the monitored sample sites. As well, the carbon sink area has expanded from 1.54% to 7.8%. Given the increasing intensity of the occurrence of extreme hydrological events and successive dry years, similar ecological water conveyance projects should be considered elsewhere in China and in other parts of the world. The water conveyance scheme has generally proven successful and should be optimized to enhance the benefits of ecological water conveyance under water resource constraints. [ABSTRACT FROM AUTHOR]

Poverty and disasters are globally prevalent in ecologically fragile areas. Ecological migration is regarded as an effective way to address these issues. This paper investigates the spatial pattern of ecological migration and the corresponding spatiotemporal changes in land use and vegetation restoration in Gulang County, located in northwest China, between 2010 and 2018. For this purpose, we calculated three indicators: the transfer matrix of land use, normalized difference vegetation index (NDVI), and vegetation restoration degree (VRD). We found that ecological migrants in Gulang County moved from the Qilian Mountain National Park to the intersection between flat area and desert. The spatial patterns ranged from high-altitude to low-altitude, and the slopes became less steep. The distribution of the resettlements is more clustered and shaped by the traffic conditions and guided by the local governments. Unused land in the whole-village migration area and construction land in the resettlement area were dramatically impacted by ecological migration (625% and 279.3%, respectively). The cropland and construction land in the outmigration areas were mainly replaced with grassland and forest. In contrast, the grassland and unused land in the resettlement area were transferred to cropland and construction land. After ecological migration, the mean NDVI and VRD in Gulang County significantly increased, indicating that the vegetation in the outmigration areas quickly recovered. Moreover, the VRD in the whole-township migration areas was greater than that in the whole-village migration areas (121% > 68%). The main contribution to the increase in NDVI was the conversion of forest to grassland, accounting for 33%. In addition, the transition from other types of land to grassland made a larger contribution to the NDVI than conversions to forest. [ABSTRACT FROM AUTHOR]

Taking metropolitan areas as space carriers has become the engine of the Chinese government in its promotion of high-quality development, and this has also become an important measure by which to balance regional development. We used Zipf's law and the gravity model to study the urban scale distribution characteristics of the Kashgar Metropolitan Area (KMA) in this paper. We also constructed a spatial structure judgment vector for the KMA and put forward the development objectives of different circles. The findings show the following: (1) large cities have a high primacy of development, while small and medium-sized cities are underdeveloped. At present, the KMA is a concentrated monocentric-pattern metropolitan area, with Kashgar City as its core city. (2) The urban built-up area of Kashgar City is expanding to the east and south, where it has broken through the administrative boundary and become integrated with the urban built-up area of Shule County. The spatial structure characteristics of the KMA have been further clarified. The KMA forms three circles: core, middle, and outer. (3) Tumxuk City, Bachu County, Yecheng County, Shache County, and other counties are far from the core city and cannot be connected with Kashgar, but they are closely related to the surrounding cities, forming the Bachu–Tumxuk Urban Group and the Shache–Zepu–Yecheng Urban Group. This study contributes to the understanding of the characteristics of urban scale distribution and the spatial structure of metropolitan areas in arid regions, as well as providing guidance for the formulation of policies for the development of different circles in the KMA. [ABSTRACT FROM AUTHOR]

Dynamic changes in soil organic carbon (SOC) have become a popular topic in global research on organic carbon as part of the increasing attention being paid to food security and reducing greenhouse gas emissions. In this paper, the semiarid regions of China were selected as a research focus, and SOC data from 1980 to 2015 were analysed using IBM SPSS Statistics 20.0 software. SOC in farmland varied according to cultivated land type, mulching material type and planting method in the studied regions. The SOC content is 10.3–10.8 g kg−1 in supplementally irrigated land and flat dry land, 7.1–8.7 g kg−1 in terraced dry land and river beach land, and 6.2–6.4 g kg−1 in sloping dry land. The SOC content increased to 16.1–17.4 g kg−1 when crop stalks were used as mulch. The increase was only 11.5–13.5 g kg−1 in soils mulched with film or sandstone. The SOC value in wheat, maize and potatoes sown on single or double ridges was 2.4%–3.2%, 35.7%–36.4% and 4.4%–4.8%, respectively, which are higher than the values for wheat, maize and potatoes sown using the flat planting method. The SOC sequestering potential also varied according to the previously noted factors and was improved from 224.1% to 383.8% depending on cultivated land type, from 96.5% to 182.3% depending on mulching material type and from 96.1% to 191.3% depending on planting method. The SOC sequestering potential can be improved by 453.2%–757.4% with the integration of the optimal cultivated land type, mulching material type and planting method. Thus, there is substantial soil carbon sequestration potential in China's semiarid regions. [ABSTRACT FROM AUTHOR]

Glacier mass balance can visually indicate the degree of glacier response to climate change. The mountain glaciers are an essential source of recharge for rivers in arid regions and play a vital role in maintaining regional ecological stability and production life. This paper drives a spatially distributed degree-day model using multi-source remote sensing data such as MOD11C3 and TRMM3B43 to simulate the mass balance in the Tianshan Mountains' south and north slope basins. The spatiotemporal heterogeneity of the mass balance was compared and attributed using a Geographical detector. The results show that: (1) The glaciers in the north and south basins are mainly distributed at an altitude of 3900–4300 m, and the total glacier area accounts for 85.71%. The number of less than 1 km2 glaciers is the most in the whole region. (2) During the study period, the glaciers in the north and south basins were negative (−465.95 mm w.e.) an entire interannual change rate was −28.36 mm w.e./a. The overall trend of ablation can be divided into two stages: from 2000 to 2010a, the persistence increased, and from 2010 to 2016a, the volatility decreased. (3) In the attribution of mass balance, the factors affecting glacier mass balance can be divided into two parts: climate and topography. The cumulative contribution rate of climate factors in Kaidu is nearly 20% higher than that of topographic factors, but the contribution rate of climate factors in Manas is only 7.3% higher. Therefore, the change of glacier mass balance in the Kaidu river basin is more driven by climate factors, while the glacier mass balance in the Manas river basin is more affected by the combination of climate and topographic factors. (4) The climate accumulation is the dominant factor in the Manas river basin (69.55%); for the ablation area, the Kaidu river basin is dominated by climate (70.85%), and the Manas river basin is dominated by topographic factors (54.11%). Due to the driving force of climate and topographic factors and the different coupling modes, glacier mass balance's spatiotemporal heterogeneity in the north and south slope basins is caused. This study contributes to analyzing the mechanism of regional changes in the glacier mass balance. It provides a scientific basis for investigating the characteristics of water resource changes and water resource regulation in the north and south slope basins of the Tianshan Mountains. [ABSTRACT FROM AUTHOR]

Ecological vulnerability is one of the core issues in the study of achieving sustainable development and is important for ecological conservation and environmental management, especially for ecologically vulnerable regions. Scientific assessment of ecological vulnerability can improve decision-making capacity and provide appropriate information for sustainable development. The Hexi Corridor is located in the inland northwest of China, and its ecological environment is very fragile. Under the influence of climate change and human activities, the Hexi Corridor is facing a crisis of ecological degradation. Therefore, this paper assessed the influence of various factors on ecological vulnerability, followed the principles of scientificity and data accessibility, and constructed a comprehensive assessment framework to reflect the spatio-temporal characteristics of ecological vulnerability in the Hexi Corridor from three aspects: natural factors, socio-economic factors and human interference factors so as to provide theoretical and practical guidance for regional ecological protection. The results showed that: (1) The ecological vulnerability of the Hexi Corridor was dominated by extreme vulnerability, mainly in the arid desert region, while mildly and lowly vulnerable areas were mainly distributed in the southern Qilian Mountains and the plain oasis region, which was closely related to its physical geography. The index values showed an overall decreasing trend, and the environmental situation was improving from 2000 to 2020. (2) The distribution of ecological vulnerability had obvious directional characteristics, and it gradually decreased from north to south. Moreover, it exhibited a significant positive spatial correlation, and its spatial aggregation pattern was basically consistent with the spatial distribution state. (3) Based on the spatio-temporal patterns of ecological vulnerability, the Hexi Corridor was divided into five zones: ecological core protection zone, integrated ecological monitoring zone, ecological optimization concern zone, ecological restoration management zone and ecological potential governance zone. Different environmental protection policies have been taken for different zones according to its basic conditions. Spatial principal component analysis (SPCA) method was used to analyze the ecological vulnerability factors based on the GIS technology. The partitions of ecological vulnerability for configuration and optimization has been classified and practical application. Geographic detector and national policies were considered for ecological vulnerability driver factors. [ABSTRACT FROM AUTHOR]

The arid region of northwest China (ARNC) is one of the most sensitive areas to global warming. However, the performance of new Global Climate Models (GCMs) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating climate in this region, especially in the subregions, is not clear yet. Based on the temperature dataset from historical runs of CMIP6, this paper analyzed and evaluated the simulation ability of 29 GCMs in reproducing the annual mean temperature (tas), annual mean maximum temperature (tasmax) and annual mean minimum temperature (tasmin) in the ARNC and subregions from 1961 to 2014. The results show that (1) the correlation coefficients (CCs) between simulation and observation time series for the mean of two model ensembles (MME for equal-weight multi-model ensemble and PME for preferred-model ensemble) are generally better than those of 29 individual GCMs, with CCs ranging from 0.38 to 0.87 (p < 0.01). (2) All the models can simulate the significant warming trend of the three temperature elements in the study area well. However, the warming magnitude simulated by most of the models (41%) is smaller than the observations except for tasmax, which is also shown in the MME. (3) The spatial pattern of the three temperature elements can be better reflected by most models. Model simulation ability for the ARNC is better compared to that of the four subregions, with a spatial CC greater than 0.7 (p < 0.01). Among the subregions, the simulation performance of the north of Xinjiang for spatial pattern is superior to that of the other regions. (4) The preferred models for each subregion are various and should be treated differently when used. Overall, the PME outperforms both the MME and the individual models; it can not only simulate the linear trend accurately but also reduce the deviation effectively. [ABSTRACT FROM AUTHOR]

In this paper, Changji, Xinjiang, northwest China, was selected as the study area, and platinum group elements (PGEs) in PM2.5 were quantified by ICP-MS using microwave digestion. The results indicated that the average concentrations (and range) of Rh, Pd, and Pt in PM2.5 were 0.21 (n.d. −1.41) ng/m3, 8.09 (n.d. −59.50) ng/m3, and 0.12 (n.d. −0.83) ng/m3, respectively. The concentration of Pd was significantly higher than Rh and Pt. Moreover, the seasonal variations of Rh and Pd were the same: highest in summer and lower in other seasons. However, the seasonal variation of Pt was opposite to that of Rh and Pd: highest in winter and lower in other seasons. Seasonal differences in emission sources of PGEs and the climatic characteristics of arid regions played important roles in the seasonal changes of PGEs. Rh and Pd had a common source and similar diurnal variation. The major influencing factors were traffic volume and meteorological conditions. The diurnal variation regularity of Pt was different from Rh and Pd. The superimposed effect of vehicle exhaust emissions and coal-fired emissions was the main reason why the diurnal variation of Pt was more complicated than those of Rh and Pd. The diurnal concentration of Pt varied with the seasons. It is caused by seasonal coal combustion and meteorological conditions. [ABSTRACT FROM AUTHOR]

Drought is a complex natural disaster affected by multiple climate factors and underlying surface. In recent years, drought monitoring indices of remote sensing have been widely applied to monitor drought in a certain region or global. However, some remote sensing drought monitoring indices do not consider the drought-causing factors enough to reflect the comprehensive drought situation of a region fully. In this paper, a new remote sensing drought monitoring index, called Remote Sensing Drought Evaluation Index (RSDEI), was constructed by combining Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Precipitation Condition Index (PCI), and Soil Moisture Condition Index (SMCI) using the spatial principal component analysis (SPCA) method. The reasonableness of RSDEI was test and verified using Net Primary Productivity (NPP), Standardized Precipitation Evapotranspiration Index (SPEI), and unit area crop yield. The RSDEI was also applied to the drought condition monitoring of the northwest arid and semi-arid region from 2001 to 2019.The result demonstrated that the results showed that the RSDEI had a high correlation coefficient with SPEI-12 (R=0.85, p<0.01). It is concluded that the correlation coefficient between RSDEI and NPP is 0.74 at 95% confidence level, which indicates that RSDEI and NPP have a strong correlation. Then, the correlation between RSDEI and crop yield per unit area is 0.89. The results of RSDEI showed that the drought in northwest China started in May and lasted in September from 2001 to 2019. The lowest value of RSDEI appeared in May, which inflected the significant difference of drought level in different month in northwest China. The result of CV (coefficient of variation) showed that the drought variation in the study area had a stable low fluctuation condition as a whole, in the northwest and northeast of study area, which indicated that the changes of drought were different in the past 19 years. The Hurst exponent analysis showed that the area with the positive evolution of Hurst index (0.52,which accounts for 75.9% of the total area, while the area with reverse evolution characteristics (H<0.5) accounts for 24.1% of the total area. The result obtained above reflected that the drought changes in most regions are better than that in the past 19 years. The trend gradually changes from drought to humid. [ABSTRACT FROM AUTHOR]

Lakes are threatened ecosystems in drylands of Central Asia. The Wuliangsuhai Lake ('W-Lake') is a case in point. Located in the Hetao Irrigation Area ('HIA'), W-Lake is a rare multifunctional inland lake in arid North China. It provides a wide range of ecosystem services, including provision of products, regulation of water and climate, water purification, biodiversity conservation and cultural services. The lake's major water input is the drainage water from HIA's farmlands. Those farmlands divert water directly from the Yellow River for irrigation. Unsustainable agricultural practice in HIA has gravely impacted on W-Lake in terms of reduced water quantity and degraded water quality. However, the linkage between agricultural practice in HIA and the environmental changes of W-Lake has been rarely investigated. Existing data focus mainly either on W-Lake or on HIA's farmlands with overwhelmingly technical and end-of-the-pipe solutions. In view of the above, this paper develops four qualitative scenarios on HIA from social, economic and ecological perspectives. The four scenarios are: (a) green growth; (b) strong sustainability; (c) shift to swamp; and (d) worst case. The main aims of this paper are (1) to assist local decision makers of HIA in policy-making and (2) to develop concepts and strategies within the larger framework of integrated water management that shall inspire conservation efforts in other Central Asian regions. [ABSTRACT FROM AUTHOR]

Monitoring drought and mastering the laws of drought propagation are the basis for regional drought prevention and resistance. Multivariate drought indicators considering meteorological, agricultural and hydrological information may fully describe drought conditions. However, series of hydrological variables in cold and arid regions that are too short or missing make it difficult to monitor drought. This paper proposed a method combining Soil and Water Assessment Tool (SWAT) and empirical Kendall distribution function (KC′) for drought monitoring. The SWAT model, based on the principle of runoff formation, was used to simulate the hydrological variables of the drought evolution process. Three univariate drought indexes, namely meteorological drought (standardized precipitation evapotranspiration index; SPEI), agricultural drought (standardized soil moisture index; SSI) and hydrological drought (standardized streamflow drought index; SDI), were constructed using a parametric or non-parametric method to analyze the propagation time from meteorological drought to agricultural drought and hydrological drought. The KC′ was used to build a multivariable comprehensive meteorology–agriculture–hydrology drought index (MAHDI) that integrated meteorological, agricultural and hydrological drought to analyze the characteristics of a comprehensive drought evolution. The Jinta River in the inland basin of northwestern China was used as the study area. The results showed that agricultural and hydrological drought had a seasonal lag time from meteorological drought. The degree of drought in this basin was high in the northern and low in the southern regions. MAHDI proved to be acceptable in that it was consistent with historical drought records, could catch drought conditions characterized by univariate drought indexes, and capture the occurrence and end of droughts. Nevertheless, its ability to characterize mild and moderate droughts was stronger than severe droughts. In addition, the comprehensive drought conditions showed insignificant aggravating trends in spring and summer and showed insignificant alleviating trends in autumn and winter and at annual scales. The results provided theoretical support for the drought monitoring in the Jinta River basin. This method provided the possibility for drought monitoring in other watersheds lacking measured data. [ABSTRACT FROM AUTHOR]

Aeolian desertification, a serious degradation of soil and vegetation, is one of the most important issues in arid and semi-arid regions in terms of society/economy and environment. However, there still remains problematic on the study of climate change and its impact on aeolian desertification in the such region. To reverse aeolian desertified land (ADL), it is necessary to identify the causes of ADL. The paper uses meteorological data to characterize climate change and its impact on ADL during 1970–2015 with the method of geostatistics, and the results showed that the climate tended to be warmer and drier. The linear trend rates of annual mean temperature for the whole year (WY), winter half year (WHY), and summer half year (SHY) were 0.24 °C (10 a)−1, 0.25 °C (10 a)−1, and 0.18 °C (10 a)−1, respectively. The linear trend rates of average precipitation were − 8.29 mm (10 a)−1, 2.69 mm (10 a)−1, and − 8.27 mm (10 a)−1, respectively. Rising temperatures in WY, WHY, and SHY lead to increase topsoil evaporation and may trigger ADL development. However, the decreasing precipitation in SHY weakened soil erosion, and the increasing precipitation with a rate of 0.26 mm a−1 in WHY improved the soil moisture content. Therefore, our results show that climatic change has a relatively high sensitivity, especially in WHY, to the expansion or reversal of ADL in semi-arid regions. [ABSTRACT FROM AUTHOR]

At present, most of the international research cases on badlands are based on semiarid regions, while there are few studies on badlands in humid regions. Therefore, the research on badlands in humid regions has strong theoretical and practical significance. By taking the Nanxiong Basin, which is located in the humid regions of southern China as the research object, this paper analyzes the scale and spatial distribution variation characteristics of redbed badlands and builds a set of factors that influence redbed badlands to explore the driving forces influencing the variation of redbed badlands based on remote sensing images of the American KH-4A satellite from 1969 and a Landsat 8 image from 2017. The result shows that the scale of redbed badlands in the Nanxiong Basin had generally decreased from 1969 to 2017. The area of redbed badlands decreased from 1693.97 hm2 in 1969 to 127.4 hm2 in 2017, with a decrease of 92.48%. The spatial distribution of redbed badlands had gradually changed from the contiguous planar distribution form in 1969 to the dispersed island distribution form in 2017, forming four agglomerations. The influence degree of the driving forces for the scale variation of redbed badlands is in the order of lithology > road > aspect > residential locations > slope > water system > vegetation > garden plots. Among these driving forces, except vegetation and garden plots, which have a negative correlation with the variation of redbed badlands, other factors have a positive correlation. Lithology is positively correlated with the variation of redbed badlands and has the strongest influence on the redbed badlands of all the influencing factors. The road factor is second to the lithological factor; the more accessible an area is, the stronger the human influence will be and the more serious the damage to vegetation will be, which easily cause surface vegetation damage, induce land degradation, and form redbed badlands. [ABSTRACT FROM AUTHOR]

The development of agriculture in the arid and semiarid regions of China mainly depends on agricultural irrigation. Until 2016, water required for agricultural irrigation has accounted for more than 90% of the total water consumption. But traditionally extensive broad irrigation causes frequent loess geological hazards in irrigation area and it threatens security of local life and property. In this paper, we selected the Heifangtai irrigation district in Yongjing County, Gansu Province, where frequent instabilities occur, as the study area. We used laboratory tests and numerical simulation to examine the mechanism of loess landslides owing to the irrigation hydrological cycle. Irrigation changes the local natural hydrogeological conditions because of the loose and macroporous structure of loess. The numerous pores and fissures constitute preferential migration pathways of irrigation water; thus, irrigation can increase the groundwater level and hydraulic gradient. Broad irrigation is the main inducing factor of geological hazards (including landslides, collapses, and soil salinization) in arid and semiarid regions, and the development of fissures and sinkholes increases the risk of landslides. New water-saving irrigation methods need to replace the traditional irrigation methods and improve the utilization of water resources. A monitoring and warning system in susceptible areas should be established to ensure the sustainability of local agriculture. [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

The groundwater cycle pattern in the arid and semi-arid regions is drastically affected by both natural condition changes and human activities, resulting in serious eco-geological environmental problems. This paper selected the south edge of the Junggar basin as a pilot area for the basin-scale assessment of groundwater renewal capacity. Assessment indicator system was first established, assessment units were then constructed, and the Analytic Hierarchy Process method was used to identify the weights of the assessment indicators. The first three indicators are natural recharge ratio, groundwater residence time, and balance ratio between groundwater recharge and exploration, respectively. Two types of environmental assessment models, including the comprehensive index model and the fuzzy comprehensive model, were used and the results determine that low-lying intermountain areas and alluvial–proluvial piedmont plains have stronger groundwater renewal capacity, whereas that of the alluvial plain is much weaker. Second, at the typical watershed scale, the Manasi watershed was adopted as the study area, and numerical simulation method was used to assess the groundwater renewal capacities of intermountain low-lying land and the pediment alluvial–proluvial plain. They are found to have renewal periods of about 66.95 years and 25.05 years, respectively. These values are favorably compared to the results of isotopic analysis, which is corresponding to 46 years and 30 years, respectively. At last, four schemes were put forward to improve the regulation and storage capacity in different segment of Manasi River watershed. The results not only provide key guidance for reasonable groundwater resource exploitation and eco-environmental protection, but also offer a model for sustainable groundwater utilization for similar northwestern districts in China or other world similar districts. [ABSTRACT FROM AUTHOR]

The relationship between human behaviour and vulnerability is interactive, especially in arid and semi-arid regions. This paper analyses vulnerability and human behaviour in the core areas of Qilian Mountains National Park, which is located in Qilian and Sunan counties. We used the vulnerability index and grey correlation degree methods to analyse the data. The results show that from 2005 to 2017, the vulnerability degree in the Qilian Mountain area decreased gradually (Qilian County vulnerability decreased from 0.0357 to − 0.2237, and Sunan County vulnerability decreased from 0.1428 to − 0.4489). In 2017, the degree had reached its lowest value due to central and local government policy (− 0.2237 and − 0.4489). Considering that human behaviour contributed to the vulnerability degree, we find that land use and agricultural development mode, the acceleration of industrialisation and changes in the spatial patterns of human activities, and the development of urbanization and changes in resident identities are the main concepts driving the relationship between human behaviour and vulnerability. The innovative assessment indicators developed in this study can be applied to thoroughly explore the relationship between human behaviour and vulnerability and to find the influencing factors. Under certain conditions, this approach can be applied to vulnerability research in specific countries and regions. [ABSTRACT FROM AUTHOR]

Maize is a major crop in the semiarid region of northwestern China, and, in recent years, severe drought events have often severely impacted local maize production. In this paper, an assessment model for maize drought vulnerability in the semiarid region of northwestern China was constructed after an in-depth analysis of factors linked to drought vulnerability. The model establishes an evaluation index system for drought vulnerability and assesses the level of environmental sensitivity, degree of exposure, crop sensitivity, and adaptability. An assessment and a regionalization analysis of maize drought vulnerability were then conducted for the semiarid region of northwestern China. The results showed the spatial distribution characteristics of environmental sensitivity, degree of exposure, crop sensitivity, and adaptability. The high and sub high vulnerable areas for maize were located mainly in the northern and southern parts of the warm temperate zone (District I A) and covered most of the central region of the middle temperature zone (District II A). The low and sub low vulnerable areas were in the central part of District I A, in the eastern and western part of District II A, and across the whole of the warm temperate zone (Districts I B), the middle temperature zone (Districts II B), and the plateau area of the sub temperate zone (District III). The main factors affecting high drought vulnerability varied across different areas. These results provide a theoretical basis for the risk management of maize production and will help prevent drought disasters in the semiarid region of northwestern China. [ABSTRACT FROM AUTHOR]

The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

Taking the key research area in the arid region of North China—Minqin County—as a case, this paper analyzes the main factors impacting land desertification. Based on factor analysis method and the collection of data in the last 50 years, this paper researches the spatial changes of driving factors during the course of land desertification in Minqin, Gansu Province. The results of factor analysis indicate that the driving force of human factor on land desertification accounted for 56.33% in 1956–2004 and for 66.19% in 1981–2004, the driving force of nature factor on land desertification accounted for 11.29% in 1956–2004 and 8.11% in 1981–2004, and the synthesis of driving forces of human and natural factors accounted for 11.19% in 1956–2004 and for 14.88% in 1981–2004. This indicated that human driving force on land desertification was increasing in Minqin County gradually. [ABSTRACT FROM AUTHOR]

• This paper constructed a framework for green water assessment in the Loess Plateau gully region using MIKE SHE model. • A new concept and extraction method for green water components was defined based on existing research. • A new concept of the potential of green water was defined in relation to the dried soil layers' classification indicators. • We assessed the dependence on green water components and potential for environmental changes. Exponentially increasing water demand and increasingly uncertain hydrological conditions due to climate change (CC) and land use/cover change (LUCC) undoubtedly pose significant challenges to the sustainability of water systems in arid and semi-arid regions worldwide, and even more so in the rain-fed agricultural area of the Loess Plateau (LP) in China, where green water supports all ecological landscapes and most agriculture. Therefore, an accurate assessment of green water resources is crucial for regional development. This paper constructed a comprehensive framework for assessing green water resources based on the MIKE SHE model, defined a new concept of green water components (GWCs) that can be extracted based on existing studies, proposes the potential of green water (GW P), and present a research methodology. To validate this research framework, we applied it to a typical basin in the LP gully area of the Nanxiaohegou (NXHG) basin. The model was calibrated using runoff data from basin outlet stations to extract four GWCs: high-efficiency green water (GW H), low-efficiency green water (GW L), unused green water (GW U), ineffective green water (GW I). We then assessed the GW P of the basin and analyzed its trends, consistency, and dependence on changing environments. The assessment framework is simple and easy to use, providing valuable information for regional revegetation and basin water management, and is highly recommended for replication in other regions. [ABSTRACT FROM AUTHOR]

• A framework for analyzing urban resilience through the life circle lens was developed. • The spatial match between urban pressures and resilience was examined. • Strategies for a multi-center, cluster-type urban resilience typology were outlined. • A people-oriented resilient planning was advocated. This paper presents an original framework for assessing and enhancing urban resilience from the perspective of the life circle that emphasizes the daily activity spaces of residents, using Urumqi, a major city in northwest China's arid oasis region, as a case study. Based on multi-source urban geographic big data, we introduce Gini coefficient and Lorenz curve to analyze the spatial matching relationship between urban spatial pressure and urban spatial resilience, and divided the priority of planning intervention by priority index. Our findings for the case study Urumqi reveal a strong "center-periphery" structure of urban resilience and spatial pressures. Based on the findings, we proposed targeted planning interventions prioritized by a resilience index that considers the life circle to address disparities and improve urban resilience. Our study advocates for urban planning to focus on the life circle, aiming to develop a multi-center and cluster-type resilient urban spatial structure to foster a "people-oriented" resilient city. [ABSTRACT FROM AUTHOR]

In the dryland area of the Loess Plateau in northwest China, long-term excessive fertilization has led to soil compaction and nutrient loss, which in turn limits crop yield and soil productivity. To address this issue, we conducted experiments using environmentally friendly organic fertilizer and bacterium fertilizer. Our goal was to investigate the effects of additional organic and bacterium fertilizer inputs on soil water migration, crop root architecture, and yield formation. We implemented six different fertilizer strategies, namely: Nm (mulching, N 30 kg/ha), NPK1m (mulching, N 60 kg/ha; P 30 kg/ha; K 30 kg/ha), NPK2m (mulching, N 90 kg/ha; P 45 kg/ha; K 30 kg/ha), NPKOm (mulching, N 90 kg/ha; P 45 kg/ha; K 30 kg/ha; organic fertilizer 2 t/ha), NPKBm (mulching, N 60 kg/ha; P 30 kg/ha; K 30 kg/ha; bacterium fertilizer 10 kg/ha), and N (N 30 kg/ha; no mulching). The results revealed that the addition of bacterium fertilizer (NPKBm) had a positive impact on soybean root system development. Compared with the other treatments, it significantly increased the total root length, total root surface area, and total root length density by 25.96% ~ 94.89%, -19.63% ~ 36.28%, and 9.36% ~ 28.84%, respectively. Furthermore, NPKBm enhanced soil water consumption. In 2018, water storage during the flowering and podding periods decreased by 12.63% and 19.65%, respectively, while water consumption increased by 0.97% compared to Nm. In 2019, the flowering and harvest periods decreased by 23.49% and 11.51%, respectively, while water consumption increased by 0.65%. Ultimately, NPKBm achieved high grain yield and significantly increased water use efficiency (WUE), surpassing other treatments by 76.79% ~ 78.97% and 71.22% ~ 73.76%, respectively. Subsequently, NPK1m also exhibited significant increases in yield and WUE, with improvements of 35.58% ~ 39.27% and 35.26% ~ 38.16%, respectively. The use of bacterium fertilizer has a profound impact on soybean root architecture, leading to stable and sustainable grain yield production. [ABSTRACT FROM AUTHOR]

Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) (IMERG) is the primary high spatiotemporal resolution precipitation product of the GPM era. To assess the applicability of the latest released IMERG_V07 in mainland China, this study systematically evaluates the error characteristics of IMERG_V07 from the perspective of different seasons, precipitation intensity, topography, and climate regions on an hourly scale. Ground-based meteorological observations are used as the reference, and the performance improvement of IMERG_V07 relative to IMERG_V06 is verified. Error evaluation is conducted in terms of precipitation amount and precipitation frequency, and an improved error component procedure is utilized to trace the error sources. The results indicate that IMERG_V07 exhibits a smaller RMSE in mainland China, especially with significant improvements in the southeastern region. IMERG_V07 shows better consistency with ground station data. IMERG_V07 shows an overall improvement of approximately 4% in capturing regional average precipitation events compared to IMERG_V06, with the northwest region showing particularly notable enhancement. The error components of IMERG_V06 and IMERG_V07 exhibit similar spatial distributions. IMERG_V07 outperforms V06 in terms of lower Missed bias but slightly underperforms in Hit bias and False bias compared to IMERG_V06. IMERG_V07 shows improved ability in capturing precipitation frequency for different intensities, but challenges remain in capturing heavy precipitation events, missing light precipitation, and winter precipitation events. Both IMERG_V06 and IMERG_V07 exhibit notable topography dependency in terms of Total bias and error components. False bias is the primary error source for both versions, except in winter, where high-altitude regions (DEM > 1200 m) primarily contribute to Missed bias. IMERG_V07 has enhanced the accuracy of precipitation retrieval in high-altitude areas, but there are still limitations in capturing precipitation events. Compared to IMERG_V06, IMERG_V07 demonstrates more concentrated error component values in the four climatic regions, with reduced data dispersion and significant improvement in Missed bias. The algorithm improvements in IMERG_V07 have the most significant impact in arid regions. False bias serves as the primary error source for both satellite-based precipitation estimations in the four climatic regions, with a secondary contribution from Hit bias. The evaluation results of this study offer scientific references for enhancing the algorithm of IMERG products and enhancing users' understanding of error characteristics and sources in IMERG. [ABSTRACT FROM AUTHOR]

High-resolution oasis maps are imperative for understanding ecological and socio-economic development of arid regions. However, due to the late establishment and relatively niche nature of the oasis discipline, there are no high-precision datasets related to oases in the world to date. To fill this gap, detailed visual interpretation of remote sensing images on Google Earth Professional or Sentinel-2 was conducted in summer 2020, and for the first time, a high-precision dataset of China's oases (abbreviation HDCO) with a resolution of 1 meter was constructed. HDCO comprises 1,466 oases with a total area of 277,375.56 km2. The kappa coefficient for this dataset validated by the field survey was 0.8686 and the AUC value for the ROC curve was 0.935. In addition, information on the geographic coordinates, climatic conditions, major landforms, and hydrological features of each oasis was added to the attribute table of the dataset. This dataset enables researchers to quantitatively monitor location and area of oases, fosters exploration of the relationship between oases and human under climate change and urbanization. [ABSTRACT FROM AUTHOR]

Semiarid regions play a pivotal role in global ecosystem and environmental governance. Changing environment (climate and land use variation) has led to the disruption of hydrology in semi-arid regions and ecological degradation in some area. Understanding their hydrological response to changing environments is crucial for ecological rehabilitation and optimal water resource allocation. This research, conducted in a Chinese semiarid watershed, integrates multi-field models about hydrology, meteorology and geography to investigate hydrological processes in typical hydrological years. The results indicate that the climate in this region is drying, and the likelihood of extreme weather events is increasing with global warming. Projecting changes from 2010 to 2060, 9.21% of grassland converting to 5.63% of forest and 3.58% of gully built-up land. As a result, the flood peak increases by 22.99% in typical drought years, while it decreases by 36.77% in normal years. Based on our analysis of the rainfallrunoff process in typical drought and normal years, we identify two distinct effects: the "local rainfall-runoff effect" and the "global rainfall-runoff effect", respectively. However, in typical wet years, the streamflow state is primarily controlled by intense and concentrated precipitation. This research provides insights into the effect of ecological restoration and typical climate variations on hydrological cycle in semiarid regions, thus contributing to more informed decision-making in environmental management and water resource planning. [ABSTRACT FROM AUTHOR]

Vegetation restoration in dryland regions may be a powerful way to control desertification and promote local habitat recovery. In these artificial revegetation systems, ecosystem processes and functioning are strongly determined by nitrogen (N) availability, while soil inorganic N (SIN) is the major available N form and is absorbed as a main N source for plants. However, SIN dynamics, their influencing factors, and their relative importance to the ecosystem of these N‐limited systems are not well understood. A field investigation was conducted to examine the monthly variations in SIN and its response to planting age and vegetation type in a typical artificial sand‐fixing system in northwestern China. The SIN content in topsoil (0–20 cm) during the growing season ranged from 7.10 to 95.65 mg kg−1, with a mean value of 27.14 mg kg−1. Soil nitrate N had a dominant role in determining SIN monthly dynamics, which showed a fluctuating trend with two peak values in early July and late August. SIN showed a significant increasing trend with the planting age of sand‐fixing vegetation, and it was highest for Nitraria sphaerocarpa (55.66 ± 5.76 mg kg−1), followed by Haloxylon ammodendron (29.81 ± 3.47 mg kg−1) and interspace (11.39 ± 1.13 mg kg−1). SIN displayed a hump‐shaped relationship with air temperature (R2 = 0.96, p < 0.01) and had a maximum at 19.88°C. The change rate of SIN was positively correlated with accumulated precipitation (R2 = 0.99, p < 0.05). SIN was correlated significantly with soil organic carbon (SOC), total nitrogen (TN), and soil clay content. Our results revealed that climatic (air temperature and precipitation), abiotic (soil texture), plant (planting age and vegetation type), and nutrient‐related (SOC and TN) factors regulate SIN dynamics in artificial sand‐fixing vegetation systems. Climate was the predominant factor affecting soil ammonium N, and soil nutrients (SOC and TN) were the predominant factor affecting soil nitrate N. Therefore, these factors should be integrated into optimizing regional vegetation establishment and improving ecosystem management practices in sand‐fixing lands. [ABSTRACT FROM AUTHOR]