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Groundwater plays a critical water resources role in arid and semi-arid areas. Quantitative evaluation of groundwater recharge is crucial in hydrogeological investigations. Under the complex hydrogeological and climatic conditions in China's arid and semi-arid regions, groundwater recharge shows significant spatio-temporal heterogeneity. Although there has been much research, including hydrochemical analysis, isotope tracing, in-situ tests and numerical simulations, accurate quantitative groundwater recharge is still a great challenge. This paper reviews the progress in research on groundwater recharge in arid and semi-arid regions of China, focusing on the principles and current applications of the main techniques, as well as the achievements in nine typical arid and semi-arid regions (Tarim Basin, Junggar Basin, Shule River Basin, Heihe River Basin, Yinchuan Plain, Badain Jaran Desert, Loess Plateau, Ordos Plateau, North China Plain). The paper reveals that the chloride mass balance method is a popular method to estimate groundwater recharge rate, whereas stable isotopes and hydrochemistry analyses, as well as the joint use of both, have been widely used in the understanding of groundwater recharge processes and mechanisms in the arid and semi-arid regions of China. Numerical modeling and remote sensing technology will become important approaches to quantify large-scale groundwater recharge. It is also suggested that various estimation methods should be used in combination, in order to improve the reliability of recharge estimates. Furthermore, this review shows that the theoretical research so far still cannot meet the needs of regional development, and the paper highlights some scientific problems that need to be further explored. [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]

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]

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]

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]

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]

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]

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]

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]

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]

[Objective] The present paper aimed to analyze the effects of sowing date and film mulching on yield and quality of direct seeding winter rapeseed to provide a theoretical basis for suitable sowing and high-yielding cultivation of winter rapeseed in dryland in southwest China. [Method] A two-factor completely randomized block design was adopted to explore the effect of sowing date(20th September, 30th September, 10th October, 20th October, 30th October, 10th November, 20th November) and film mulching (film mulching and no film mulching) on field soil temperature, dry matter accumulation, agronomic characteristics, yield and quality of Chuanyou 36. [Result] Film mulching effectively increased the 0-20 cm soil temperature, dry matter accumulation, plant height, length of main inflorscence and effective pods, thereby increasing rapeseed yield by 3.61%-44.47%, which was more obvious with the delay of sowing date. However, the sowing date delayed longer, dry matter accumulation and agronomic traits of rapeseed decreased significantly. The regression equation showed that the rapeseed yield rose first and then declined with the delay of sowing date, which had a significant polynomial relationship with sowing date. The optimal sowing date for rapeseed was 10th October, which was 2.13%, 47.97%, 74.19% and 136.64% higher than 30th September, 30th October, 10th November and 20th November, respectively. In addition, the delay of sowing date effectively reduced the content of linolenic acid, erucic acid and glucosinolates in rapeseed, but also reduced the oil content, while film mulching effectively decreased the difference in rapeseed quality resulted from the delay of sowing date. [Conclusion] 30th September to 10th October was a suitable sowing date for high yield of direct seeding rapeseed in dry land in southwest China, and a proper delay of the sowing period in combination with film mulching technology was more conducive to achieving goals of high yield, efficiency and quality. [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]

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]

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]

Drought prediction plays an important guiding role in drought risk management. The standardized precipitation index (SPI) is a popular meteorological drought indicator to measure the degree of drought. The SPI time series is non-stationary, whereas the conventional artificial neural network (ANN) model has limitations to predict non-stationary time series. To overcome this limitation, it is essential to investigate input data preprocessing to improve the ANN model. In this paper, a hybrid model coupled with singular spectrum analysis (SSA) and backpropagation ANN is proposed (SSA-BP-ANN). The advantage of this model is that the SSA of finite-length SPI sequences does not require the adoption of boundary extensions to suppress boundary effects, while the most predictable components of the SPI can be efficiently extracted and incorporated into the model. The proposed SSA-BP-ANN model is tested in case studies at three meteorological stations in Northern Shannxi Province, China. The results show that the SSA-BP-ANN model can produce more accurate predictions than the BP-ANN model. In addition, the performance improvement of SSA on the BP-ANN model is slightly better than wavelet decomposition and empirical mode decomposition. This new hybrid prediction model has great potential for promoting drought early warning in arid regions. [ABSTRACT FROM AUTHOR]

Soil wind erosion is the main cause of land degradation in arid and semi-arid areas in northern China, which is mainly affected by surface type, climate and so on. Strong soil wind-erosion will not only accelerate regional desertification and influence the quality of human life, but also cause serious ecological and environmental problems. Since the 2000 s, our country has gradually strengthened the control of land desertification and carried out a series of sand control works, which effectively improved the overall ecological environment of the sandy land. But in recent years, there are some common phenomenon that extensive grassland and brushland was turned into cultivated land in the southeast and southwest of Mu Us sandy land. However, in the dry and windy winter or spring, these new reclaimation land is usually so exposed that it is vulnerable to suffer from strong wind erosion. Therefore, it is great significance to study the characteristics of soil wind erosion in new reclaimation land and find out the control methods. Based on the above question, this paper selected the southern part of Mu Us sandy land (38°05′27″-38°13′58″N, 107°24′28″-107°37′30″E) as the research area, as well as set up 5 observation points on different surfaces, which were represented respectively by A, B, C, D and E. Point A was on the brushland, point B was on the middle of the grassland, and other three points were respectively on different parts of the cultivated land. On the day with strong wind activity, 12 groups simultaneous observation of wind and sand were made at these 5 points (A, B, C, D, E), with each observation time at least 20 minutes. After these observations, the material of the sand samplers were weighed with an electronic balance of 1/1 000, and the material of surface and sand samplers on cultivated land were analyzed by Mastersizer2000 Laser Particle Size Analyzer. The results showed that the soil wind erosion intensity increased exponentially after grassland and shrubland were cultivated; on cultivated land, with the increase of height, the sediment transport rate decreases with exponential function within 0-10 cm height and power function within 10-20 cm height. Due to the height of the sand collector used in this paper is 20cm, lower than the height of the sand flow layer. In order to obtain the total sediment transport rate of the surface of the cultivated land, this paper must calculate it through the function simulation obtained from the above result. After calculating the total sediment transport rate, fitting it with the wind speed. We found that the total sediment transport rate has a good power function relationship with the wind speed in the cultivated land with sufficient erodibility particles. Based on the formula of the relationship between wind speed and total sediment transport rate, as well as the wind speed data of the meteorological stations in the region, the wind erosion modulus of the new reclaimation land can be preliminarily calculated. The result shows that the wind erosion modulus of the new reclaimed land is 9 657 t/(km2·a). Through the results obtained in this paper, combined with the former research results, this paper argues that the emergence of new reclaimed land has an important impact on regional desertification, and its area should be used as an important index when evaluating regional desertification. Meanwhile, Controlling cultivated land area, establishing windbreak and sand fixation forest, as well as retaining stubble at a certain height can effectively control soil wind erosion in newly reclaimed land. [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]

• Quantitatively describes the groundwater recharge process for lakes. • Constructed a model for the groundwater table-lake area relationship in groundwater-dependent lakes in arid regions. • Suggested a groundwater depth of 1.73 m to maintain stable lake area within the Hetao Irrigation District. • Constructed model can serve as an effective reference tool for groundwater management and the protection of lake ecosystems. The groundwater table constitutes a significant factor in sustaining the ecosystems of lakes in arid regions. To elucidate the mechanism by which variations in groundwater tables affect lake areas, this paper presents a case study of a typical groundwater-fed lake in China's Hetao Irrigation District. An analytical model correlating groundwater tables with lake areas was developed to simulate and predict the impact of changes in groundwater tables on lake areas. The findings indicate that the analytical model adeptly simulates the lake area dynamics of the groundwater-fed lake cluster (Taerhu lake cluster) from 1998 to 2018, achieving a Nash-Sutcliffe efficiency (NSE) value exceeding 0.6 and a root mean square error (RMSE) value below 0.1 square kilometers. Maintaining a groundwater depth at 1.73 m ensures the stability of the lake area; a decrease in groundwater depth to 1.93 m would result in a 79.5 % reduction in lake area. The model constructed in this study offers a crucial tool for the ecological protection of lakes and groundwater management in arid regions. [ABSTRACT FROM AUTHOR]

Whether there is a transition underway, from a warm-dry climate to a warm-wet climate in Northwest China remains a controversial and scientifically significant issue. Will this trend continue in the future? Another hot issue is whether the climate in Northwest China will continue to be warm and humid over the next few decades. In this paper, eight CMIP6 models were employed to investigate temperature and precipitation changes under five principal Shared Socioeconomic Pathway (SSP) scenarios (from 2015 to 2099) to project the future warming and humidification in Northwest China using the SPEI (standardized precipitation evapotranspiration index) method. The results revealed that (1) the simulated temperature and precipitation of eight CMIP6 models were consistent with that of observed data during 1961-2014, which showed an increase of approximately 28.2 mm, while simulated data revealed an increase of approximately 9.4 mm. The annual precipitation gradually decreased from Eastern Inner Mongolia and the Southern Northwest Mongolia region (.700 mm) to the Central Northwest Mongolia region (,100 mm) from 1961 to 2014; (2) the MME significantly overestimated the temperature and slightly underestimated the precipitation in Northwest Mongolia. The temperature difference between the simulated and observed data was approximately 0.4 °C. The observed data showed an increase of approximately 0.9 °C from 1961 to 2014, whereas the simulated data revealed an increase of approximately 0.7 °C; (3) in the SSP5-8.5 scenario, the percentage of precipitation anomalies at 1.5, 2, 3, and 4 °C were 166.64, 190.58, 226.44, and 274.56%, respectively; thus, alleviating the drought situation while facilitating the warm-dry to warm-wet climate transition; (4) the water balance between rising temperatures and increased evapotranspiration resulting from increased precipitation suggested that not all sites will be wet in the future. There was still a drying trend in some areas, where drought was more severe under the high emissions scenario than the low emissions scenario. [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]

Abstract In arid and semiarid regions of northwest China, there are abundant shallow coal reserves throughout the region, yet during the mining process, the shallow water resources available are typically depleted due to the formation of fractures in the shallow subsurface. Water-preserved mining is the only option for coal mining in arid regions of northwest China. Based on the geological and hydrogeological conditions of the study area, this paper investigates the basic conditions and mechanisms of goaf water storage. A time series model for goaf water storage is proposed, along with a method for estimating the quantity of goaf water storage. Finally, hydrochemical characteristics of mine water and water quality characteristics after purification in the study area were analyzed. As indicated by the analysis results, after simple purification, the goaf water can meet industrial, ecological and agricultural water consumption standards. In the end, combined with current monitoring results of goaf water pressure and the status of goaf water utilization in the study area, this paper describes the quantity and the effect of utilizing goaf water storage. Goaf water storage can effectively alleviate the scarcity of local production and domestic water, and provides the most effective approach of large-scale water-preserved mining of shallow coal seams in the arid regions of northwest China. [ABSTRACT FROM AUTHOR]

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [ABSTRACT FROM AUTHOR]

This paper reviews 110 years of global runoff estimation. By employing the method of ordinary least square regression on a sample region's runoff coefficient, an empirical formula of a runoff coefficient is calculated for China. Based on this empirical formula applied with a high-resolution grid of precipitation, runoff is calculated resulting in an equally high-resolution map of global runoff using a geographic information system (GIS). The main results are (1) the global total runoff volume is 47,884 km³, (2) the average runoff depth is 359 mm, (3) the interior drainage region's runoff volume is 1,663 km³, and (4) the average runoff depth is 58.4 mm. The results are compared with the results of the existing literature on global runoff. This study emphasizes the importance of runoff and groundwater recharge in arid and semi-arid regions where the estimation value of runoff depth is significantly increased. [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 reliability of the ratio between Artemisia and Chenopodiaceae pollen percentage (i.e. A / C) in differentiating vegetation and reflecting moisture conditions in arid and semi-arid regions has been disputed and this hindered its potential application in palaeoclimate reconstructions. In this paper, we investigated the A / C ratios of lake-centre surface sediment from 45 lakes in the Inner Mongolia Plateau and the Qaidam Basin in arid and semi-arid China, and numerically studied the relationships of A / C ratios with vegetation and moisture. We found that the A / C ratio of lake-centre surface sediments can be used as an effective index to differentiate desert and steppe and also can be used as a valid indicator to infer mean annual precipitation (MAP) in the Inner Mongolia Plateau and the Qaidam Basin in arid and semi-arid China. Moreover, the A / C ratio from lake-centre surface sediments is more reliable and robust than that of soil-surface samples in differentiating vegetation and reflecting moisture conditions, and this might be attributed to its larger pollen source area and regional representation. In addition, the (A − C)/(A + C) index helps to overcome the inherent weakness of non-linearity of the A / C ratio and may be useful in paleo-vegetation reconstruction. These findings provide useful references for pollen-based vegetation and climate reconstructions of lake cores in arid and semi-arid China. [ABSTRACT FROM AUTHOR]

【Objective】The objective of the paper is to provide a reference for soil nutrient management and sustainable operation in Karst areas.【Method】The soil samples were collected from woodland and dry land in Baiduo Village(dolomite areas) and Shiqiao Village(limestone areas) in Shibing County,Guizhou Province,and then the soil nutrient was analyzed.【Result】The soil developed from dolomite was featured with higher organic matters,total N,available P,available K and hydrolysable N.The soil developed from limestone was featured with higher total P and total K.Total N was positively and very significantly related to hydrolysable N and organic carbon in soil developed from limestone and dolomite.Hydrolysable N was positively and significantly related to organic carbon in limestone areas.Hydrolysable N was positively and very significantly related to organic carbon in dolomite areas.Land use patterns had obvious effects on nutrient content in soil developed from limestone and dolomite.Soil total K,total N,hydrolysable N and organic carbon content in limestone woodland was higher than dry land,and available K,total P,available P and pH was lower than dry land.Soil total P and available P in dolomite woodland are lower than dry land,and other indexes are higher than dry land.The organic matter,total N,total P and total K content in dolomite-developed soil was Grade II,Grade I,Grade VI and Grade III respectively.The organic matter,total N,total P and total K content in limestone-developed soil was Grade II,Grade I,Grade V and Grade I separately.【Conclusion】Soil nutrient was not only affected by soil forming rock,but also affected by land use pattern. [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]

Drought is a natural hazard caused by long-term precipitation deficiency and high evaporation resulted from high temperature, which is among the most common disasters around the world. In recent decades, with the intensification of climate change and human activities, drought occurrence is becoming more frequent in China, causing negative impacts on agricultural production, ecological environment and social economy. Therefore, it is significant to explore the impact of drought on vegetation for agricultural production and healthy development of ecological systems. In this paper, the response and sensitivity of vegetation to drought in different climatic zones in China were analyzed, and the effects of different climatic factors, including water balance (precipitation-potential evapotranspiration), annual precipitation, mean temperature and sunshine hours, on the relationship between different vegetation types including forestland, grassland and cultivated land and drought were explored, so as to reveal the response mechanism of ecological vegetation to drought from a macro perspective. Using the self-calibrating Palmer drought severity index (scPDSI) and normalized difference vegetation index (NDVI) data for the period of 1982-2015, the response rule and sensitivity of different types of vegetation to drought were analyzed by applying time-delay correlation method, and the influence of various climate factors on the relationship between vegetation and drought was analyzed by applying linear regression method. The results of the research showed that in northwest China, Inner Mongolia, north China plain and southern Qinghai-Tibet plateau, the correlation of shorter lag time scPDSI (1-3 months) and NDVI was close (Rmax>0.4), which indicated that vegetation growth was more sensitive to drought in these regions and that vegetation biomass were influenced mainly by the spatiotemporal characteristics of the water availability. In the humid areas of south China, including the middle and lower reaches of the Yangtze River and the Pearl River basin, the precipitation is abundant so that the correlation between NDVI and scPDSI was negative, and the response of vegetation was not sensitive to drought. The growth of vegetation is mainly controlled by energy factors such as temperature and sunshine hours. The relationship between vegetation and drought was significantly affected by the average annual water balance, precipitation, sunshine hours and temperature, among which the annual water balance was the main water controlling factor (R²=0.45). It can be concluded that the change of water availability was the key factor behind the change of vegetation vigor. Sunshine hours were the main energy controlling factor. When average annual temperature was less than 5, the effect of ℃ temperature on the correlation between scPDSI and NDVI was also significant. The sensitive areas of drought impact on vegetation were mainly in the northern arid regions, while the southern humid areas had strong resilience and resilience to drought. The sensitivity of different types of vegetation to drought varied greatly, and the order of sensitivity is grassland >forestland>cultivated land. The results can provide a scientific basis for the evaluation of the impact of drought on ecological vegetation in different regions of China, and thus help to guide agricultural and environmental production, protect vulnerable ecosystems and provide implications for sustainable socioeconomic development. [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]

Oasification is a complex oasis expansion and ecological processes caused by climate changes and human activities under available water supply in arid and semiarid regions. The process can effectively improve soil productivity, vegetation cover, and biomass production in fighting against land degradation, such as desertification and soil erosion. However, the significance of oasification has not yet reached the general cognition compared to desertification, which is regarded as one of the most severe global eco-environmental issues. This paper identifies desertification and oasification processes and their perspectives in cognition. The implication of oasification in combating desertification and controlling land degradation is emphasized by the justification between desertification and oasification processes. As opposite process of desertification, the oasification is an unable evasive process that can provide positive environmental effects in the control of desertification, ecological restoration, and land rehabilitation. According to the interaction of climatic variations and human activities, the oasification processes is classified into six main forms: natural oasis evolution process, engineering forest construction, conversion of natural landforms into farmlands, urban encroachment, constructed environments, and coupled ecosystems. These processes gradually modify the productive capacity of soils, increase vegetation cover for restoring degraded lands, and improve the living environment for human settlement and sustainability of an oasis ecosystem. Moreover, an overview of oasification research is detailed, and Northwest China as an example is used to illustrate the progress of the oasification research in recent decades. Currently, the oasification process and its mechanistic research still remain less concern in the arid and semiarid regions. A new science framework of the oasification research is proposed to effectively deal with ecological and environmental issues in the arid and semiarid regions. • Desertification and oasification and their perspectives are identified. • Implication of oasification is emphasized in comparison with desertification. • Oasification processes are classified into six main forms. • Overview of oasification research is detailed and illustrated in Northwest China. • A new science framework of the oasification research is proposed. [ABSTRACT FROM AUTHOR]

Understanding the origins of groundwater and its movement from mountain to plain during different high intensity rainfall events is critical for conserving water supplies, determining water-use policies and controlling pollution. These factors are also the keys for understanding the dominant processes in hydrological models. In this study, groundwater resources and recharge processes during heavy precipitation were explored by using stable isotope tracers in the hilly area of Taihang Mountain. It was found that the δ2H and δ18O values of precipitation exhibited obvious precipitation amount effect during different precipitation intensity events. The stable isotopic values in groundwater and river water showed significantly varied during the single extreme heavy precipitation and the continuous heavy precipitation events. In the rainy season, precipitation amounts greater than 40 mm/d could effectively recharge the shallow groundwater in the study area. By comparing the spatial isotopic distribution of groundwater, soil water, and river water with precipitation, we showed distinct groundwater recharge patterns in terms of their water resources, timing, and the degree of river water and groundwater interaction during the single extreme heavy precipitation and the continuous heavy precipitation. After the single extreme heavy precipitation, the δ2H and δ18O values of groundwater, soil water, and river water showed stable over time and had the same similar variations, suggested that the groundwater recharge was mainly dominated by precipitation with preferential flow or bypass flow. While after the continuous heavy precipitation, the variation of δ2H and δ18O in all water is consistent with the previous precipitation, which shown a mixing effect of previous enrich precipitation and depleted heavy precipitation, suggested that groundwater source was dominated by a continuous recharge of previous heavier precipitation with translatory flow. The groundwater main recharge mechanism is not constant, but changes with rainfall intensity. The rainfall intensity play an important role in groundwater recharge change affecting runoff process. Overall, this paper presents a new insight to understand the effect of rainfall intensity on hydrological process, which could be used to provide vital information in the semi-humid and semi-arid regions where water resources are critical in climate change adaptation strategies. [Display omitted] • We identified the controls on groundwater recharge during different precipitation intensity events. • Precipitation greater than 40 mm/d could effectively recharge shallow groundwater. • Bypass flow after extreme precipitation produced stream water and groundwater recharge. • Groundwater recharge was by a continuous recharge with translatory flow after the continuous heavy precipitation. [ABSTRACT FROM AUTHOR]

The arid regions of northwestern China are dominated by extensive areas of mobile sand dunes. These features cause environmental problems and exert global climatic impacts; however, due to the lack of systematically-applied indicators of aeolian activity, direct evidence of past changes in aeolian activity is unreliable, especially for aeolian sand source regions. In this paper, we analyze the end-member (EM) distributions of various types of surface soil across the Tengger Desert in northwestern China, and devise a sensitive proxy for aeolian activity using a spatio-temporal substitution approach. This proxy is then used to evaluate a Quaternary aeolian succession and to understand the response of aeolian activity to regional climate change. Our results suggest that gradual increases in the coarse-grained EM components 3–5 reflect enhanced dune mobility and reduced vegetation coverage, which are a direct function of the intensity of regional aeolian activity. In the aeolian section, coarse- and medium-grained sand layers resemble modern semi-mobile and mobile dunes, whereas fine-grained sand layers are analogous to vegetated fixed/semi-fixed or semi-mobile dunes. Combining this record with independent multi-proxy evidence from the same section leads us to conclude that strong aeolian activity coincided with a dry climate, sparse vegetation cover, and strong surface winds during the Last Glacial Maximum, and that these conditions gradually attenuated at the beginning of the Last Deglacial. These inferences are in accord with independent paleoclimate records from this region, confirming that the intensity of aeolian activity in the southeastern Tengger Desert is closely associated with large-scale climate change. Our findings show that our EM proxy can be used to infer the intensity of aeolian activity and to reliably reconstruct the evolution of deserts in northwestern China. [Display omitted] • Coarse grain-size End-members (EM) 3–5 are a proxy of the strength of aeolian activity. • This proxy is applied to a palaeo-aeolian sequence to reconstruct the history of desert evolution. • Aeolian activity was closely associated with large-scale climate change. [ABSTRACT FROM AUTHOR]

Ecosystems in arid regions with sandy substrates are vulnerable to various environmental challenges. Understanding the vegetation evolution of such regions over a long timescale and the possible drivers of change is important for optimizing ecological restoration. In this paper, we present multi-proxy data to understand Holocene vegetation dynamics and their drivers in the Horqin Sandy Land in northern China. Phytoliths are used to reconstruct vegetation; grain size and magnetic susceptibility are used to reconstruct the climate; and sedimentary charcoal contents and the numbers of regional archaeological sites are used to reconstruct the fire activity and human activity intensity, respectively. Results indicate that the Horqin Sandy Land was covered mainly by grassland vegetation during the Holocene, and that the trajectory of vegetation evolution was as follows: sparse and species-poor Leymus chinensis grassland from 9300 to 6150 cal yr BP, relatively sparse and species-rich mesophytic herb grassland from 6150 to 2300 cal yr BP, and dense and species-rich L. chinensis grassland from 2300 to 250 cal yr BP. Climate change was the main driver of vegetation evolution, but fire and human activities also influenced the vegetation to varying degrees. Fire made the greatest contribution to the vegetation change during the 6150–2300 cal yr BP interval, and human activities contributed throughout the 8200–2300 cal yr BP interval. The evolution of plant species richness and the number of C 3 plants show a significant ∼1000-yr periodicity during 9300–4500 cal yr BP, which we speculate was caused by the effect of solar activity on East Asian monsoon intensity, which likely controlled the vegetation change on a millennial timescale. • The Holocene vegetation in Horqin Sandy Land is qualitatively reconstructed. • Climate dominated the vegetation evolution, while fire and human activity were additional influences. • The vegetation change shows a ∼ 1000-yr periodicity during 9300–4500 cal yr BP. • The vegetation change on a millennium cycle was likely driven by the solar activity. [ABSTRACT FROM AUTHOR]

The Soil and Water Assessment Tool (SWAT) model is diffusely applied to areas with uniform precipitation distribution and gentle slopes. However, the SWAT has apparent defects in the process of ecohydrological simulation in mid-high latitudes and arid regions. This model can merely be used in agricultural catchments with gentle slopes and uniform rainfall, and the simulation is not suitable for high-altitude alpine catchment. To this point, this paper makes appropriate improvements to the runoff module, and specifically corrects the key sensitive parameters. The global sensitivity and performance assessment of the model's parameters were carried out before and after the improvement using the monthly data of runoff and evaporation from 1990 to 2018 in the Kaidu River basin in northwestern China. It is indicated that the Modified SWAT simulates the performance of monthly runoff and evapotranspiration better than the original SWAT, which overestimates the runoff volume throughout hydrological changes in different periods. Compared with the monthly water production under different land use/cover conditions, the highest water production was found in forest and grassland. By modifying the SWAT algorithm, the structural non-determinacy of the Modified SWAT is significantly reduced, and the adaptability of the model is improved. Thus, the Modified SWAT shows a better simulation performance in arid areas with considerable terrain variation and scarce rainfall data. [Display omitted] [ABSTRACT FROM AUTHOR]

The arid region in the northern part of China is a bridge between China and neighbouring countries in the Silk Road Economic Belt, and the severe desertification in this region restricts its sustainable development. In this paper, MODIS data, including albedo, reflectance, normalized vegetation index, and land surface temperature, were selected in 2000, 2005, 2010, and 2015 to construct a decision tree to extract spatio‐temporal information of the desertified land in the arid area. The trend in desertification and transfer directions was analysed by the GIS method, and the dynamic characteristics of the desertification at different units (provincial administrative unit and typical sandy land) and with different topographic factors (slope and aspect) are discussed. Our conclusions include (a) desertification in the arid region in the northern part of China showed improvement overall and local deterioration. The deteriorating areas were located primarily in the western region of the Hunshandake Sandy Land, the tectonic zone of the Taklimakan Desert, and the Qaidam Basin; (b) the degree of desertification transfer occurred primarily at adjacent levels; (c) the desertified area in each province showed a different trend in fluctuation, and Maowusu Sandy Land recovered better among the 4 large sands; and (d) the desertified area was distributed primarily along 0o–3o slopes and showed a rapid decline at increased slopes. The change in the degree of desertification in each aspect largely was a general reversal, and the area of the north aspect was larger than that of other areas of aspects. This study provides some theoretical support for the control of desertification in the Silk Road Economic Belt. [ABSTRACT FROM AUTHOR]

Understanding spatiotemporal urbanization is one of the key questions related to sustainable urbanization in the drylands of northern China (DNC). However, urban expansion in the DNC has not been quantified and assessed effectively due to a lack of reliable data and methods. In this paper, we investigate urban expansion in the DNC at multiple scales, ranging from the whole region to four dryland subtypes, and six urban agglomerations in the DNC from 1992 to 2015. We also simulate urban expansion in the DNC from 2015 to 2050 by coupling the scenario framework of the Shared Socioeconomic Pathways (SSPs) with the Land Use Scenario Dynamics-urban (LUSD-urban) model. Despite of the uncertainty in the research, our findings provide useful insight into the past and the future urban expansion in the DNC. The results indicate that the urban land in the DNC expanded rapidly from 4110 km 2 in 1992 to 20,969 km 2 in 2015. Furthermore, the urban land in the DNC will continue to expand from 20,969 km 2 to 22,987–36,622 km 2 by 2040, with an annual growth of 80.72–403.48 km 2 under all SSPs. Thus, it is suggested that effective measures are urgently needed to facilitate sustainable urban development in the DNC. [ABSTRACT FROM AUTHOR]

In recent years, climate extreme events have caused increasing direct economic and social losses in the arid region of northwestern China. Based on daily temperature and precipitation data from 1960 to 2010, this paper discussed the linear trend and abrupt changes of climate indices. The general evolution was obtained by the empirical orthogonal function (EOF), the Mann-Kendall test, and the distribution-free cumulative sum chart (CUSUM) test. The results are as follows: (1) climate showed a warming trend at annual and seasonal scale, with all temperature indices exhibiting statistically significant changes. The warm indices have increased, with 1.37%days/decade of warm days (TX90p), 0.17 °C/decade of warmest days (TXx) and 1.97 days/decade of warm spell duration indicator (WSDI), respectively. The cold indices have decreased, with − 1.89%days/decade, 0.65 °C/decade and − 0.66 days/decade for cold nights (TN10p), coldest nights (TNn) and cold spell duration indicator (CSDI), respectively. The precipitation indices have also increased significantly, coupled with the changes of magnitude (max 1-day precipitation amount (RX1day)), frequency (rain day (R0.1)), and duration (consecutive dry days (CDD)). (2) Abrupt changes of the annual regional precipitation indices and the minimum temperature indices were observed around 1986, and that of the maximum temperature indices were observed in 1996. (3) The EOF1 indicated the overall coherent distribution for the whole study area, and its principal component (PC1) was also observed, showing a significant linear trend with an abrupt change, which were in accordance with the regional observation results. EOF2 and EOF3 show contrasts between the southern and northern study areas, and between the eastern and western study areas, respectively, whereas no significant tendency was observed for their PCs. Hence, the climate indices have changed significantly, with linear trends and abrupt changes noted for all climate indices, which will have serious impacts on water resources and ecological environment in the arid region of China. [ABSTRACT FROM AUTHOR]

• Optical images are easily affected by clouds and cloud shadows. • Fmask is introduced into the GEE platform and modified for Sentinel-2 images. • The improved SNOWL algorithm considers unstable snow cover areas. • Snow cover extraction accuracy in flat surface and shady slope is the highest. • Snow cover in mountainous is reconstructed by combing the Fmask, Sen2Cor and the improved SNOWL algorithms. Snow is an important type of surface cover and an important freshwater resource in the arid regions of northwest China, and optical satellites are an important means for monitoring variation in snow cover. However, the radiation values measured by satellite sensors are affected by cloud cover and cloud shadows; thus, the reconstruction of snow cover under clouds and cloud shadows becomes a bottleneck problem especially in mountains areas. Based on the digital elevation model (DEM), in this paper, an integrated method of snow cover reconstruction on Sentinel-2 images is created by combining the improved SNOWL (snow line) algorithm considering unstable snow cover areas, Fmask cloud detection algorithms, and the Sen2Cor clear sky snow cover detection tool with a geospatial processing platform, GEE (Google Earth Engine). Considering the Babao River Basin as the study area, 474 Sentinel-2 scenes (10 m) were selected to obtain the snow cover spatiotemporal variations of 158 days from November 2016 to March 2021. Compared with the high-resolution GF-2 satellite images, the integrated method can extract snow under clouds and cloud shadows well, and the improved SNOWL algorithm improves the overall accuracy from 66.05 % to 84.26 %. The experimental results show that approximately half of the Babao River Basin is unstable snow cover, and areas above 3977 m are covered with snow for at least half a year. [ABSTRACT FROM AUTHOR]

Accurate estimation of reference crop evapotranspiration (ET 0 ) is important due to its crucial role in determining crop water requirement in irrigated agriculture. Though a great number of models have been developed, their rigorous evaluation with measurements is still lacking, leading to confusion and arbitrariness in model selection. In this paper daily estimates of 16 ET 0 models, including five combination-, six radiation and five temperature-based ones, were compared with weighing lysimeter measurements during crop growing season (April through October) in 2012 at a semiarid site in China. Daily ET 0 was measured by two weighing lysimeters (area 1.3 m × 1.3 m, depth 2.3 m) located in a fescue grass ( Festuca arundinacea Schreb) plot (100 m × 100 m) surrounded by a 167 ha crop, winter wheat rotated with summer maize. We found the models were ranked decreasingly as: FAO-ppp-17 Penman > 1963 Penman > FAO-24 Blaney-Criddle (BC) > 1996 Kimberly Penman > FAO-24 radiation > FAO-56 Penman-Monteith (PM) > FAO-24 Penman > Turc > DeBruin-Keijman > Jensen-Haise > Priestley-Taylor > Hargreaves > Makkink > Hamon > Blaney- Criddle > Mcloud on basis of RMSE (root mean square error). Overall, the combination models performed best with RMSE ranging from 0.93 to 1.32 mm d −1 , followed by the radiation models with RMSE from 1.28 to 1.79 mm d −1 , and the temperature models with RMSE from 1.09 to 2.48 mm d −1 . The best combination model (FAO-ppp-17 Penman) was respectively 29% and 17% more accurate than the best radiation (FAO-24 radiation) and temperature (FAO-24 BC) models. Better performance of the combination and radiation models resulted because they explicitly contain the dominant factors influencing ET 0 . All models tended to overestimate under low evaporative demand while underestimating the measured values under high demand, but on average the combination and radiation methods underestimated by 0.46 mm d −1 and 0.60 mm d −1 , respectively, whereas the temperature method overestimated by 0.21 mm d −1 . All combination and radiation models, and the Hargreaves and FAO-24 BC in temperature method showed robust structure. To improve them future efforts should be on local calibration, but for temperature models showing structure failure focus should be on its optimization. The coefficients of commonly used models were calibrated and related to meteorological variables. Particularly, those of the Priestley-Taylor, Makkink, Turc and the Hamon were enhanced, while those of the Hargreaves and BC were decreased. In climate similar to the current site in China we suggest continued use of the older Penman equations for combination method and the FAO-24 radiation or Turc for radiation method. Meanwhile, two questions need to be addressed in future studies: i) adoption of the FAO-56 PM equation as the sole standard for computing ET 0 and the proper value for surface resistance; and ii) the effectiveness of the later modifications to the original wind function in the Penman equation. [ABSTRACT FROM AUTHOR]

This paper reports a comprehensive study on the observed and projected spatiotemporal changes in mean and extreme climate over the arid region of northwestern China, based on gridded observation data and CMIP5 simulations under the RCP4.5 and RCP8.5 scenarios. The observational results reveal an increase in annual mean temperature since 1961, largely attributable to the increase in minimum temperature. The annual mean precipitation also exhibits a significant increasing tendency. The precipitation amount in the most recent decade was greater than in any preceding decade since 1961. Seasonally, the greatest increase in temperature and precipitation appears in winter and in summer, respectively. Widespread significant changes in temperature-related extremes are consistent with warming, with decreases in cold extremes and increases in warm extremes. The warming of the coldest night is greater than that of the warmest day, and changes in cold and warm nights are more evident than for cold and warm days. Extreme precipitation and wet days exhibit an increasing trend, and the maximum number of consecutive dry days shows a tendency toward shorter duration. Multi-model ensemble mean projections indicate an overall continual increase in temperature and precipitation during the 21st century. Decreases in cold extremes, increases in warm extremes, intensification of extreme precipitation, increases in wet days, and decreases in consecutive dry days, are expected under both emissions scenarios, with larger changes corresponding to stronger radiative forcing. [ABSTRACT FROM AUTHOR]

It is difficult – though important – to assess the necessary allocation of increasingly scarce water resources and yield estimation, by determining the exact amount of evapotranspiration ( ET ) and the partitioning of ET into transpiration ( T ) through the stomata of plants and evaporation ( E ) from the soil. An accurate and effective method for ET partitioning and estimation is, therefore, desirable. This paper aims to evaluate the performance of two main models for ET partitioning and estimation in terms of feasibility and accuracy: the AquaCrop (Version 4.0) model, and the SIMDualKc model. Field experiments were carried out between 2011 and 2015 in an arid region of Northwest China on two sites using full and deficit irrigation under plastic film-mulch, with the ET of maize for seed production and its partitioning components ( T and E ) being strictly measured by using the eddy covariance (EC) system or the sap flow system and micro-lysimeter cylinders. Subsequently, part of the measured data was used to calibrate the two models, so that the calibrated models could then be used to assess whether the agreement between simulation and measurement had proved successful, thus validating the models, or not. The results showed that the two models performed well with regard to their simulation of ET and T under full irrigation conditions. Under deficit irrigation conditions, the ET and T values simulated by the AquaCrop model were much closer to the actual measurement when compared with the results simulated by the SIMDualKc model. This was particularly the case when the soil was re-watered after a period of long-term water stress. For the simulated E , however, both models generated data that were distant from the actual measurements taken under full or deficit irrigation conditions using plastic film-mulch, although when the SIMDualKc model simulated E data, it came closer to the measurement than did the AquaCrop model. The comparison of two models in terms of their accuracy and feasibility based on the data analysis is discussed. [ABSTRACT FROM AUTHOR]

In recent years, ecological degradation caused by irrational groundwater exploitation has been of growing concern in arid and semiarid regions. To address the groundwater-ecological issues, this paper proposes a groundwater-resource exploitation mode to evaluate the tradeoff between groundwater development and ecological environment in the northern Tianshan Mountains, northwest China’s Xinjiang Uygur Autonomous Region. Field surveys and remote sensing studies were conducted to analyze the relation between the distribution of hydrological conditions and the occurrence of ecological types. The results show that there is a good correlation between groundwater depth and the supergene ecological type. Numerical simulations and ecological assessment models were applied to develop an ecology-oriented exploitation mode of groundwater resources. The mode allows the groundwater levels in different zones to be regulated by optimizing groundwater exploitation modes. The prediction results show that the supergene ecological quality will be better in 2020 and even more groundwater can be exploited in this mode. This study provides guidance for regional groundwater management, especially in regions with an obvious water scarcity. [ABSTRACT FROM AUTHOR]

Warming of the climate system is unequivocal, and the change of climate variables will eventually have a great impact on vegetation cover and agricultural practices, especially in the arid area Xinjiang in China, whose agriculture and ecosystems are heavily vulnerable to climate change. In this paper, normalized difference vegetation index (NDVI) was used to study the vegetation growth and its response to climate change in Xinjiang. Firstly, two NDVI datasets (Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging Spectroradiometer (MODIS)) were merged through a pixel-wise regression analysis to obtain a long time series of NDVI data, and then, relationships between yearly NDVI and yearly climate variables, and monthly NDVI and monthly climate variables were extensively investigated for grassland and cropland in northern and southern Xinjiang, respectively. Results show the following: (1) there was an increasing trend in NDVI for both grassland and cropland in both northern and southern Xinjiang over the past decades and trends were significant except that for grassland in northern Xinjiang; (2) precipitation and evaporation were more important than temperature for grassland in northern Xinjiang, while precipitation and temperature were more important than evaporation for grassland in southern Xinjiang and cropland in both northern and southern Xinjiang; (3) NDVI was highly correlated with accumulated monthly precipitation instead of monthly precipitation, and there was a lagged effect of precipitation, temperature, and evaporation on NDVI change. However, lagged effects were only significant in specific months. The results could be helpful to agricultural practices; e.g., based on lagged effect of precipitation, irrigation in July is very important for crop growth. [ABSTRACT FROM AUTHOR]

The water resources in the arid region of northwestern China, which are impacted by climate change, tend to be more unstable, and the environment and ecosystems will suffer from severe water shortage. In this paper, potential future climate trends were predicted based on CMIP5 simulations in this region. The water availability and agricultural water demand under future climate change scenarios were estimated. Impacted by increases in temperature, the irrigation water demand will increase by 4.27–6.15 billion m 3 in this region over the next 60 years, compared to the demand of 32.75 billion m 3 during 1971–2000. However, the annual runoff will only increase by 4.8–8.5 billion m 3 , which is equivalent to or even less than the increased irrigation water demand. In fact, the increased demand for industrial, domestic and ecological water were not considered here. Thus, the water supply/demand contradiction will result in more severe water shortages in the future. According to a comparison with simulated irrigation water demand under three adaptation strategy scenarios, we should take effective measures such as improving the efficiency of irrigation water utilization, reducing crop planting areas and adjusting crop planting structures to alleviate the impacts of future climate changes and human activities on the water supply and water use in this region. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the trends of the annual streamflow and precipitation and cross correlations between them were analyzed in nine large river basins of China during 1956–2005. The results indicate that: (1) the annual mean streamflow decreases in arid and semi-arid regions of north China; however, increasing trends occur in south and Southwest China; (2) the annual streamflow and precipitation exhibit reasonable correlation in nine large river basins except those located in inland areas. The annual streamflow over most areas of China is fed by precipitation; however, the decline in streamflow is faster than the decreases of precipitation since 1970s in the arid and semi-arid regions of north China. The relationship between the annual precipitation and streamflow presents a non-stationary state in north China. This non-stationary relationship is strongly influenced by both human activities and precipitation changes; (3) a significant increase of water use might be the major factor responsible for the steeper decline in streamflow than in precipitation in Haihe River, Yellow River and Songliao River basins in north China. In inland river areas, increase of water use and actual evapotranspiration might result in decline in streamflow although precipitation has an increase tendency. This paper sheds light on the non-stationary relationship between annual precipitation and streamflow and possible underlying causes, which will be helpful for a better understanding of the changes of precipitation and streamflow in China at large scale and in other regions of the world. [Copyright &y& Elsevier]

Based on the features of environment and the fact of successful artificial afforestation, the paper points out that the restoration of vegetation in Arid-hot valleys along the Jinshajiang River should be implemented mainly by planting sparse — arbor/ shrub/ tussock Combination. Four ways to restore vegetation in the area are given in the paper. [ABSTRACT FROM AUTHOR]

[Display omitted] • The proportion of vegetation improvement area in QLMs reached 65.06% in the past 21 years, while 52% of the area will be continuously improved in the future. • The distribution of the NDVI in the QLMs maintained a high spatial agglomeration. • Annual sunshine duration is the main meteorological factor affecting vegetation change in Qilian Mountains. • The interaction between different driving factors can improve the explanatory power of vegetation changes compared with a single driving factor. Vegetation is an important indicator reflecting ecological environment stability, and monitoring vegetation change and understanding its potential driving force have important guiding significance for the adjustment and implementation of ecological restoration measures. As an ecological security barrier in northwest China, the Qilian Mountains (QLMs) play an important role in promoting the green development of social and economic development. Currently, the comprehensive driving effects of natural and anthropogenic factors on vegetation change in the QLMs are not clear. Based on the normalized difference vegetation index (NDVI), the spatiotemporal characteristics and trend changes in vegetation in the QLMs were systematically analyzed from 2000 to 2020 in this paper. The effects of natural and anthropogenic driving factors on vegetation change were explored using a geographic detector (GeoDetector). The results showed that the vegetation has improved continuously in the past 21 years, but the overall vegetation coverage was still low. The vegetation distribution was highly clustered, with a decreasing trend from east to west. Annual sunshine duration (q statistic = 0.3347) and distance to the rivers (q statistic = 0.2649) had the greatest explanatory power for vegetation change, while slope, aspect, and landform type had the least explanatory power. The interaction between elevation and sunshine duration, temperature and precipitation, temperature and sunshine duration, elevation and precipitation had the most explanatory power for vegetation change. Finally, we determined the ranges or categories of driving factors that were most suitable for vegetation growth by using a risk detector. The results of this study can help us further understand the potential driving mechanism of vegetation coverage variation in the QLMs and provide theoretical guidance for relevant managers to formulate ecological restoration measures and land management policies in the next step. It is of great significance to maintain the stability of the fragile ecological environment and prevent land degradation in arid and semiarid areas of Northwest China. [ABSTRACT FROM AUTHOR]

• Spatiotemporal variation in vegetation on the Loess Plateau was investigated. • Precipitation was the greatest driving factor. • There was a bivariate or nonlinear enhancement between all factors. • Key factors' adaptation range or type suitable for vegetation cover was identified. Vegetation, being a core component of ecosystems, is known to be influenced by natural and anthropogenic factors. Studying vegetation cover dynamics variation and its drivers is critical to understanding the interactions between vegetation and ecosystems. The Loess Plateau (LP) is located in a semi-arid and semi-humid region with severe soil erosion and fragile ecology. This paper used the annual maximum Normalized Difference Vegetation Index (NDVI ymax) and growing season mean NDVI (NDVI gsmean) as the vegetation cover indicator. The vegetation cover variation of LP from 2000 to 2020 was analyzed using Sen's slope and Mann-Kendall test. Then the influence of natural and anthropogenic factors on the driving mechanisms of spatial vegetation differentiation was explored by the Geodetector model. The results revealed that the growth trends of NDVI ymax and NDVI gsmean were 0.075/10 years and 0.038/10 years, respectively, and the areas with improved vegetation cover accounted for 92.67 % and 88.58 % of the total area. The vegetation cover of the southeastern and northern parts of the LP decreased significantly; however, the central, southwestern, and northeastern parts exhibited a remarkable improvement. Precipitation, vegetation type, soil type, temperature, and land use type were the key driving forces, ranked differently on NDVI ymax and NDVI gsmean. However, precipitation was the most critical factor both on NDVI ymax and NDVI gsmean. The interaction detection showed non-linear and mutual enhancement, with no independent factor. The findings of our study can assist in identifying the vegetation cover status of the LP, as well as the driving forces, which can provide theoretical support for the formulation of environmental conservation policies. [ABSTRACT FROM AUTHOR]