Search

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]

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

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

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

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

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

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

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

• 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]

Introduction: With global warming, the disaster losses caused by extreme precipitation events are increasing. The poor natural conditions and climate change make the arid and semi-arid mountainous grassland area a sensitive region of climate change. The study on the spatio-temporal variation characteristics of extreme precipitation events in this region is helpful to improve the ability of climate prediction and disaster prevention and reduction in grassland. Methods: Based on the daily precipitation data of four meteorological monitoring stations in the Yinshanbeilu from 1970 to 2020, the trend analysis, M-K test and wavelet analysis were used to select seven typical extreme precipitation indicators to analyze the temporal and spatial characteristics of extreme precipitation. Results and Discussion: The results showed that the precipitation in the Yinshanbeilu increased in the past 51a, and the number of heavy rain days increased significantly. The significance test of CDD and CWD showed that the number of continuous dry days and continuous wet days decreased abruptly. The spatial analysis showed that the high value areas of R95p, R95d and PRCRTOT were all located in Siziwang Banner, and it could be concluded that the extreme precipitation risk was the highest in Siziwang Banner, while the low value areas of SDII, Rx1day, R95p and PRCRTOT were all located in Sonid Right Banner, which could be inferred that the Sonid Right Banner was relatively dry. The first main cycle of the seven indexes of extreme precipitation almost runs through the whole time series, and the starting point of the minimum main cycle changes inconsistent. In addition to the number of consecutive dry days, the other indices have a good correlation with annual precipitation, flood season and monthly precipitation from June to September, and July is the peak period of extreme precipitation events. [ABSTRACT FROM AUTHOR]

Research on endophytic fungi in desert plants, particularly the epiphytic or endophytic fungi of leaves, remains limited. In the extremely arid regions of northwest China, the ultra-xerophytic desert plant Haloxylon ammodendron harbors white fungi on its assimilating branches during autumn. The hyphae of these fungi intertwine, both internally and externally, comprising superficial, bridging, and endophytic types. The superficial hyphae attach to the surface of the assimilating branches and continuously grow and intersect, forming a thick layer of felt-like hyphae. This thick, felt-like layer of hyphae facilitates the adsorption of atmospheric water vapor on the surface of the hyphae or the assimilating branches, allowing H. ammodendron to capture atmospheric moisture, even under low humidity. Some superficial hyphae penetrate the cuticle into the epidermis, becoming bridging hyphae, which can rapidly transport water from the outside of the epidermis to the inside. The endophytic hyphae shuttle within the epidermis, achieving rapid water transfer within the epidermis of the assimilating branches. The presence of these three types of hyphae not only enables the assimilating branches of H. ammodendron to achieve rapid water absorption and transmission, but also facilitates the uptake of atmospheric water vapor under low humidity conditions. We discuss the mechanism by which the hyphae promote water absorption from the perspectives of hyphal composition, the formation of felt-like structures, and environmental conditions. We consider the presence of fungal hyphae on the surface of the H. ammodendron assimilating branches as an inevitable ecological process in arid environments. This study provides important theoretical insights into the mechanisms underlying the strong drought resistance of desert plants in extremely arid regions and offers strategies for desertification control. [ABSTRACT FROM AUTHOR]

Soil amendments have been proposed as an effective way to enhance soil carbon stocks on degraded soils, particularly in dryland farming areas. Soil organic carbon (SOC) plays an important role in improving soil quality, and soil aggregates are known to be crucial in sequestering and protecting SOC. However, how aggregation and protection of SOC by aggregates respond to a single application of bentonite combined with maize straw remains unknown, especially in the sandy soil of a semi-arid region. A three-year field experiment with four treatments [no amendment (CK), maize straw amendment addition only (T1, 6 Mg ha−1), bentonite amendment addition only (T2, 18 Mg ha−1), and maize straw combined with bentonite amendment (T3, 6 Mg ha−1 maize straw plus 18 Mg ha−1 bentonite)] was conducted in the Loess Plateau of China to assess the effects of bentonite and maize straw on aggregation and SOC. The results indicated that soil bulk density decreased by 2.72–5.42%, and soil porosity increased by 3.38–8.77% with three years of T3 application, especially in the 20–40 cm layer, compared with CK. T3 increased the amount of C input, SOC stock, and SOC stock sequestration rate by 1.04 Mg ha−1 y−1, 0.84–1.08 Mg ha−1, and 0.49 Mg ha−1 y−1, respectively, and it increased the mass proportions and aggregate-associated C stock of >0.25 mm aggregates by 1.15–2.51- and 1.59–2.96-fold compared with CK. Correlation analysis showed a positive correlation of total SOC stock with the C concentration of >2 mm, 0.25–2 mm, and 0.053–0.25 mm aggregates. Aggregates of various sizes in sandy soils have the potential for greater SOC stock. Our findings suggest that the application of maize straw (6 Mg ha−1) combined with bentonite (18 Mg ha−1) would be an effective management strategy to enhance the bulk soil C pools by improving the soil structure and thereby improving soil fertility. [ABSTRACT FROM AUTHOR]

Background: Drought stress severely impedes plant growth, and only a limited number of species exhibit long-term resistance to such conditions. Pinus sylvestris var. mongolica, a dominant tree species in arid and semi-arid regions of China, exhibits strong drought resistance and plays a crucial role in the local ecosystem. However, the molecular mechanisms underlying this resistance remain poorly understood. Results: Here, we conducted transcriptome sequence and physiological indicators analysis of needle samples during drought treatment and rehydration stages. De-novo assembly yielded approximately 114,152 unigenes with an N50 length of 1,363 bp. We identified 6,506 differentially expressed genes (DEGs), with the majority being concentrated in the heavy drought stage (4,529 DEGs). Functional annotation revealed enrichment of drought-related GO terms such as response to water (GO:0009415: enriched 108 genes) and response to water deprivation (GO:0009414: enriched 106 genes), as well as KEGG categories including MAPK signaling pathway (K04733: enriched 35 genes) and monoterpenoid biosynthesis (K21374: enriched 27 genes). Multiple transcription factor families and functional protein families were differentially expressed during drought treatment. Co-expression network analysis identified a potential drought regulatory network between cytochrome P450 genes (Unigene4122_c1_g1) and a core regulatory transcription factor Unigene9098_c3_g1 (PsNAC1) with highly significant expression differences. We validated PsNAC1 overexpression in Arabidopsis and demonstrated enhanced drought resistance. Conclusions: These findings provide insight into the molecular basis of drought resistance in P. sylvestris var. mongolica and lay the foundation for further exploration of its regulatory network. [ABSTRACT FROM AUTHOR]

Water vapor adsorption on soil, a crucial non-rainfall water resource in arid regions, warrants further experimental investigation, particularly on two typical land surfaces: bare soil and gravel. This study examined the formation characteristics and influencing factors of vapor adsorption in an arid region of Northwestern China. Observations and analyses were conducted on adsorption and evaporation measurements taken by two small weighing lysimeters (SLSs); soil temperature at a depth of 5 cm; surface temperature; relative humidity; and air temperature at a height of 30 cm above the ground from 2019 to 2020. The adsorbed water in this area was more abundant at night and less abundant during the day, with a stable nightly adsorption rate of 0.013 mm/h. Adsorption was more frequent in spring and winter (from January to June and November to December), accounting for about 90% of the total annual adsorption. In 2019 and 2020, the ratio values of adsorption to evaporation were 0.16 and 0.10 for bare soil, and 0.10 and 0.12 for gravel, respectively. Adsorption was more likely to occur when the soil moisture content was less than 13%; the highest adsorption frequency was close to 20% when the RH was between 75 and 95%; low soil temperatures were more conducive to the occurrence of adsorption. The effect of temperature differences (Ta−Ts) on adsorption was stronger than that of relative humidity. The adsorption frequency generally showed a bimodal change with increasing temperature difference, but the effect of temperature differences was less effective for gravel than bare soil. When the relative humidity was high and the temperature difference was weakly positive, the maximum adsorption intensity could reach 0.18 mm/h. [ABSTRACT FROM AUTHOR]

To accurately forecast the future development trend of vegetation in dry areas, it is crucial to continuously monitor phenology, vegetation health indices, and vegetation drought indices over an extended period. This is because drought caused by high temperatures significantly affects vegetation. This study thoroughly investigated the spatial and temporal variations in phenological characteristics and vegetation health indices in the abdominal part of Maowusu Sandland in China over the past 20 years. Additionally, it established a linear correlation between vegetation health and temperature indices in the arid zone. To address the issue of predicting long-term trends in vegetation drought changes, we have developed a method that combines the Informer deep learning model with seasonal and Seasonal Trend decomposition using Loess (STL) and empirical mode decomposition (EMD). Additionally, we have utilized the linearly correlated indices of vegetation health and meteorological data spanning 20 years to predict the Normalized Difference Vegetation Index (NDVI) and Temperature Vegetation Dryness Index (TVDI). The study's findings indicate that over the 20-year observation period, there was an upward trend in NDVI, accompanied by a decrease in both the frequency and severity of droughts. Additionally, the STL-EMD-Informer model successfully predicted the mean absolute percentage error (MAPE = 1.16%) of the future trend in vegetation drought changes for the next decade. This suggests that the overall health of vegetation is expected to continue improving during that time. This work examined the plant growth circumstances in dry locations from several angles and developed a complete analytical method for predicting long-term droughts. The findings provide a strong scientific basis for ecological conservation and vegetation management in arid regions. [ABSTRACT FROM AUTHOR]

Background: Accurate estimation of potential evapotranspiration (PET) is the key for studying land-air interaction hydrological processes. Several models are used to estimate the PET based on standardized meteorological data. Although combination-based models have the highest level performance estimation of PET, they require more meteorological data and may therefore be difficult to apply in areas lacking meteorological observation data. Results: The results showed significant differences in the spatial trends of PET calculated by different models in China, the Doorenbots–Pruitts model revealed the highest PET (1902.6 mm), and the Kuzmin model revealed the lowest PET (349.6 mm), with the largest difference being 5.5 times. The Romanenko and the Rohwer models were the recommended temperature-based and aerodynamic-based models. On the other hand, the Abtew model was more suitable for arid and semi-arid regions, while the Priestley–Taylor model was more suitable for humid regions. Combination-based models revealed ideal calculation accuracies, among which the Penman–Monteith model was the best option for PET calculation. Conclusions: The accuracy range of Romanenko, Rohwer, Abten, Priestley Taylor, and Penman Monteith models improved in MPZ and TCZ is higher than that improved in TMZ and SMZ. This does not mean that the improved models have higher accuracy in MPZ and TCZ than in TMZ and SMZ. On the contrary, the original model performed poorly in MPZ and TCZ, so the improved accuracy was relatively large. The unimproved model was already more suitable in TMZ and SMZ, so the improved accuracy was relatively small. Therefore, regional calibration of the PET models can improve the accuracy and applicability of PET calculation, providing a reference for studying hydrological processes in different climatic zones. [ABSTRACT FROM AUTHOR]

In the arid and semi-arid areas of northwest China, moderate irrigation is a necessary condition for the early stage survival of vegetation reconstruction in the mining area. Through the method of field periodic observation and laboratory analysis, the ideal state of vegetation irrigation of mine dump slope should meet the following requirements: (1) Neither deep leakage nor slope runoff occurs in the irrigation process, so as to prevent secondary soil and water loss. (2) Soil moisture should be controlled below the safe threshold of slope stability to prevent excessive water from forming the phenomenon of the slump. Through the analysis of the field test data, the following conclusions are drawn: (1) Water-saving irrigation system should be developed for different vegetation types and configurations for different hydrological years. (2) Two sets of water-saving irrigation technology schemes suitable for local areas were proposed. (3) A graded gradient irrigation technology, namely the primary irrigation water, should be completed in sections according to the up-slope: mid-slope: down-slope ratio of 55%: 30%: 15% to make full use of irrigation water and avoid slope runoff. [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 study is nationwide multicenter epidemiological research, aimed at investigating the distribution changes and seasonal patterns of various airborne allergens among preschool children with allergic rhinitis (AR) in different regions of China, and analyzing the clinical correlation between sensitization to various airborne allergens and AR symptoms in children. Information on children was collected through standard questionnaires, and total IgE (tIgE) and specific IgE (sIgE) for 11 inhalant allergens were tested. The results showed that dust mites are the primary allergens for preschool AR children (39%). Among pollen allergens, Amb a had the highest positivity rate (8.1%), followed by Art v (7.8%). The sensitization rates for two mites peaked in May (46.9% and 40.6%). Art v peaked in August (21.5%), while Amb a had peaks in May (12.7%) and August (17.8%). The sensitization peaks for various tree pollens mainly occurred in August. In the Eastern monsoon region, the sensitization rate to mites was significantly higher than in the Northwest arid and semi-arid regions; whereas, for pollen allergens, the sensitization rates to Amb a, Pla a, Pin a, Pop d, and Bet v were significantly higher in the Northwest arid and semi-arid regions than in the Eastern monsoon region. The correlation among various tree pollens, specifically between Pla a, Pin r, Pop d, and Bet v was strong (0.63 ~ 0.79), with a cross-overlapping percentage of 53.9%. Children with multiple pollen sensitizations had higher cumulative nasal symptom scores than those negative for pollen (P < 0.01). Children with only pollen sensitization had higher cumulative rhinitis symptom scores than the all-negative group (P < 0.0001) and the mite-only sensitization group [P < 0.05], while the mite-only sensitization group also had higher scores than the all-negative group [P < 0.05], and the group sensitized to both pollen and mites had lower scores than the pollen-only group [P < 0.05]. This study indicates that sensitization to mites and grass pollens exhibits significant regional differences, with grass pollen allergies primarily occurring in autumn, sensitization to pollens in general exhibits a pronounced seasonal pattern. Moreover, pollen sensitization aggravates nasal and ocular symptoms in AR children. [ABSTRACT FROM AUTHOR]

Revegetation is one of the most effective ways to combat desertification and soil erosion in semiarid and arid regions. However, the impact of the perturbation of revegetation on ecohydrological processes, particularly its effects on the interplay between hydrological processes and vegetation growth under water stress, requires further investigation. This study evaluated the effects of revegetation on the energy, water, and carbon fluxes in a desert steppe in Yanchi County, Ningxia Province, northwest China, by simulating two vegetated scenarios (shrub–grassland ecosystem and grassland ecosystem) using the STEMMUS–SCOPE (Simultaneous Transfer of Energy, Mass and Momentum in Unsaturated Soil–Soil Canopy Observation of Photosynthesis and Energy fluxes) model. The model was validated by field observations from May to September of 2016–2019. The evaluation of revegetation effects relied on comparing simulated fluxes between two vegetated scenarios in 2016 and 2019. In both scenarios, turbulent energy was dominated by latent heat flux, which was stronger in the shrub–grassland ecosystem (+ 7 %). A higher leaf area index and root water uptake of C 3 shrubs (Caragana intermedia) resulted in increased carbon fixation (+ 83 %) and transpiration (+ 72 %) of the shrub–grassland ecosystem compared to the C 3 grassland ecosystem. Accompanied by a marked increase in root water uptake (+ 123 %), revegetation intensified water consumption beyond the levels of received precipitation. These results highlight the critical importance of considering both energy and water budgets in water-limited ecosystems during ecological restoration to avert soil water depletion. [ABSTRACT FROM AUTHOR]

Wetlands within dryland regions are highly sensitive to climate change and human activities. Based on three types of land use data sources from satellite images and a spatial data analysis, the spatiotemporal characteristics of wetland evolution in China's drylands and their relationship with human interference and climate change from 1990 to 2020 were analyzed. The results were as follows: (1) The wetlands within China's drylands expanded, including rivers, lakes, and artificial wetlands, apart from marshes, which shrunk. Meanwhile, wetland fragmentation increased, with rivers being particularly severely fragmented. (2) Temperature and precipitation showed an increasing trend from 1990 to 2020 in China's drylands. Lakes and rivers expanded with regional differences due to the uneven distribution of precipitation and rising temperature. (3) Human activities, more than climate change, became the key driving factor for the changes in wetland patterns in China's drylands. The increased areas of farmland and grassland along with increased levels of drainage and irrigation activities led to the shrinkage of marshes and the fragmentation of rivers. The increase in the number of artificial reservoirs was the main reason for the expansion of artificial wetlands. This study clarifies the specific driving factors of different types of wetlands within China's drylands, which is of great use for better protecting wetlands and the gradual restoration of degraded wetlands. [ABSTRACT FROM AUTHOR]

Significant temporal and spatial variability in soil moisture (SM) is observed during the warm season in China and its surrounding regions. Because of the existence of two different evapotranspiration regimes, i.e., soil moisture-limited and energy-limited, averaging the land–atmosphere (L–A) coupling strength for all soil wetness scenarios may result in the loss of coupling signals. This study examines the daytime-only L–A interactions under different soil moisture conditions, by using two-legged metrics in the warm season from May to September 1981–2020, partitioning the interactions between SM and latent heat flux (SM–LH, the land leg) from the interactions between latent heat flux and the lifting condensation level (LH–LCL, the atmospheric leg). The statistical results reveal large regional differences in warm-season daytime L–A feedback in China and its surrounding areas. As the soil becomes wetter, the positive SM–LH coupling strength increases in arid regions (e.g., northwest China, Hetao, and the Great Indian Desert) and the positive feedback shifts to the negative one in semi-arid/semi-humid regions (northeast and northern China). The negative LH–LCL coupling is most pronounced in wet soil months in arid regions, while the opposite is true for the Tibetan Plateau. In terms of intraseasonal variation, the large variability of SM in north China, the Tibetan Plateau, and India due to the influence of the summer monsoon leads to the sign change in the land segment coupling index, comparing pre- and post-monsoon periods. To further examine the impact of SM anomalies on L–A coupling and to explore evapotranspiration regimes in the North China Plain, four sets of sensitivity experiments with different soil moisture levels over a period of 10 years were conducted. Under relatively dry soil conditions, evapotranspiration is dominated by the soil moisture-limited regime with positive L–A coupling, regardless of external moisture inflow. The critical soil moisture value separating a soil moisture-limited and an energy-limited regime lies between 0.24 m3/m3 and 0.29 m3/m3. Stronger positive feedback under negative soil moisture anomalies may increase the risk of drought in the North China Plain. [ABSTRACT FROM AUTHOR]

The high spatial and temporal resolution of recently developed evapotranspiration (ET) products facilitates agricultural water-savings in irrigated areas as well as improved estimates of crop yield, especially in arid and semi-arid regions. However, cloud cover interferes with ET estimates, in particular when using thermal-infrared-based models in temperate and tropical regions. Previous studies have shown that the two-source energy balance (TSEB) model coupled with soil moisture (TSEB-SM) has great potential for estimating surface ET by overcoming this issue. In this study, the TSEB-SM model was first used to generate a spatiotemporally continuous 1 km daily ET dataset across the Heihe River Basin in China from 2000 to 2020, which was then evaluated against four spatially distributed sites (Arou, Huazhaizi, Daman, and Sidaoqiao) and further compared with the two most widely used daily ET datasets (PML-V2 (Penman–Monteith–Leuning) and SEBAL (surface energy balance algorithm for land)). The results showed that the newly developed ET dataset agrees well with ground-based observations and outperforms the PML-V2 and SEBAL products in precisely characterizing the seasonal fluctuations and spatial distribution as well as the spatiotemporal trends of ET. In particular, ET in the Heihe River Basin exhibits clear regional differences. The upstream and midstream grassland and irrigated oasis areas provide much higher annual ET than the downstream desert areas, with a difference of up to 600 mm/year. A three-cornered hat (TCH)-based pixel-by-pixel analysis further demonstrated that the TSEB-SM and PML-V2 products have substantially smaller relative uncertainties as compared to SEBAL ET. In general, the proposed ET datasets are expected to be more beneficial for irrigation scheduling and to provide more efficient water management across the Heihe River Basin. [ABSTRACT FROM AUTHOR]

Climate varies along geographic gradients, causing spatial variations in the effects of energy and water on species richness and the explanatory power of different climatic factors. Species of the Quercus genus are important tree species in China with high ecological and socioeconomic value. To detect whether the effects of energy and water on species richness change along climatic gradients, this study built geographically weighted regression models based on species richness and climatic data. Variation partition analysis and hierarchical partitioning analysis were used to further explore the main climatic factors shaping the richness distribution pattern of Quercus in China. The results showed that Quercus species were mainly distributed in mountainous areas of southwestern China. Both energy and water were associated with species richness, with global slopes of 0.17 and 0.14, respectively. The effects of energy and water on species richness gradually increased as energy and water in the environment decreased. The interaction between energy and water altered the effect of energy, and in arid regions, the effects of energy and water were relatively stronger. Moreover, energy explained more variation in species richness in both the entire study area (11.5%) and different climate regions (up to 19.4%). The min temperature of coldest month was the main climatic variable forming the richness distribution pattern of Quercus in China. In conclusion, cold and drought are the critical climatic factors limiting the species richness of Quercus, and climate warming will have a greater impact in arid regions. These findings are important for understanding the biogeographic characteristics of Quercus and conserving biodiversity in China. [ABSTRACT FROM AUTHOR]

Introduction: Arid and semi-arid regions encompass nearly 40% of the Earth's land surface and are characterized by extensive undeveloped land, scarce water resources, and fragile ecosystems. The arid northwestern China is a representative arid and semi-arid region. It has developed rapidly in recent years, leading to a significant increase in human activity. This increased activity has had a pronounced impact on the ecosystem, posing a major challenge to the environment. The close relationship between human activities and ecosystem service value (ESV) is crucial for the healthy development of both humans and ecosystems. However, the intricate nature of this relationship and the degree to which they are codependent remain unclear and require further investigation. Methods: This study investigates the impact of human activities on land use intensity (LUI) and degree of urbanization (URB). It comprehensively evaluates the spatial and temporal distribution of human activities and ESV, quantifying their coordination through coupling models. Results: This work provides valuable insights and theoretical support for promoting the coordinated development of human activities and ESV. Overall, the LUI in the arid northwestern region decreased (from 0.485 in 2000 to 0.459 in 2020), while the URB increased (from 0.060 in 2000 to 0.087 in 2020). The ESV significantly increased, with a total growth of 556.58 billion yuan. In prefecture- level cities, the growth in ESV values ranges from 75.19 yuan/hm2 to 10,062.49 yuan/hm2.The coupling coordination degree between ESV and LUI has changed over time, transitioning from uncoordinated development to coordinated development. In addition, the coordination between ESV and URB has evolved from uncoordinated development to transitional coordination. The level of coordination between human activities and ESV in provincial capital cities significantly influences the coordination in surrounding cities. Discussion: In conclusion, effective development recommendations are provided based on the ESV, LUI, and URB of different cities, along with a proposed development strategy for ecosystem service functions that aligns with the 14th Five-Year Plan and "Vision 2035" of each province. This work provides important insights into the relationship between human activities and ESV, and its findings can be used to guide coordinated and sustainable urban development. [ABSTRACT FROM AUTHOR]

Dissolved organic carbon (DOC) in lakes, as a regulatory agent and light-absorbing compound, is a key component of the global carbon cycling in lacustrine ecosystems. Hence, continuous monitoring of the DOC concentration in arid regions is extremely important. This study utilizes the QAA-CDOM semi-analytical model, which has good accuracy in retrieving the CDOM (colored dissolved organic matter) concentration of Lake Ebinur. We chose to invert the CDOM time-series data from May to October during the 2018–2022 period. A DOC estimation model was then established using the linear regression approach based on the CDOM inversion data and the field DOC measurements. In general, the DOC concentration in Lake Ebinur exhibited an increasing trend from 2018 to 2022, typically lower in May and higher in June. When comparing the average values of DOC in Lake Ebinur for the same months across different years, it can be observed that the month of September exhibits the greatest variability, whereas June shows the least variability. In sum, this study successfully retrieved CDOM concentrations for a saline lake within an arid region and developed a DOC estimation model, thereby providing a reference for investigating carbon cycling in typical lakes of arid areas. [ABSTRACT FROM AUTHOR]

Aerosol optical depth (AOD) is an important physical variable used to characterize atmospheric turbidity for the management and control of air pollution. This study aims to analyze the factors influencing the spatial and temporal variability in AOD across the arid region of Northwest China (ARNC) using MODIS Aqua C006 aerosol product data from 2008 to 2017. In terms of natural and socioeconomic factors, the correlation coefficient (R) was used to identify the most influential factor in the AOD changes. The results show that AOD values in spring and summer were much higher than those in autumn and winter, especially in spring. In general, AOD had an insignificant decreasing trend, with a small overall changing range. Spatial analysis revealed a significantly decreasing trend, mostly across the Gobi Desert area, which is located in the western region of the ARNC. From the perspective of natural factors, AOD was positively correlated with air temperature (AT), wind speed (WP), land surface temperature (LST), and the digital elevation model (DEM) and negatively correlated with precipitation, relative humidity (RH), and the normalized difference vegetation index (NDVI). The greatest positive correlation, with a maximum R value of 0.8, was found between AOD and wind speed. By contrast, AOD and relative humidity had the strongest negative correlation, with R values of −0.77. In terms of anthropogenic factors, gross domestic product (GDP), secondary industry, and population density were the three major anthropogenic factors that influenced the changes in AOD changes in this region. In general, the effects of anthropogenic factors on AOD are more significant in areas with high urban population densities. [ABSTRACT FROM AUTHOR]

Recent studies on China's arid and semi-arid regions, particularly the Tarim River Basin (TRB), have shown an increase in the intensity and frequency of extreme weather events. This research examines the link between meteorological droughts, as measured by the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts, as indicated by the Standardized Runoff Index (SRI) and the Standardized Terrestrial Water Storage Index (STI), over various time scales. Historical data indicate that SPEI drought frequency (DF) was 14.3–21.9%, with prevalent events in the northern oases. SRI DF ranged from 9.0% to 35.8%, concentrated around the Taklamakan and Kumtag Deserts, while STI DF varied between 4.4% and 32.7%, averaging 15% basin-wide. Future projections show an increased DF of SPEI in deserts and a decrease in oases; SRI DF decreased in deserts but increased in oases. STI changes were more moderate. The study also found a higher risk of drought progression from SPEI to SRI in the southwestern and northeastern oases, exceeding 50% probability, while central and eastern TRB had lower risks. The western TRB and inner Taklamakan Desert faced higher risks of SPEI to STI progression, with probabilities over 45%, in contrast to the lower risks in the eastern and central oases. The concurrence of SRI/STI with moderate to extreme SPEI droughts led to a higher probability and area of SRI/STI droughts, whereas consistent SPEI types showed a reduced induced probability and extent of SRI/STI droughts. This study enhances the understanding of drought propagation from meteorological to hydrological droughts in the TRB and contributes to the prevention of hydrological drought to a certain extent. [ABSTRACT FROM AUTHOR]

Desertification reversal is globally significant for the sustainable development of land resources. However, the mechanisms of desertification reversal at the level of plant community are still unclear. We hypothesized that desertification reversal has clear effects on plant community composition, plant functional types (PFTs), and other vegetation characteristics, including plant diversity and biomass, and their changes in the early stages of reversal are more dramatic than in later stages. We investigated the vegetation of four to five different stages of desertification reversal at each of seven large study sites in southwestern Mu Us Sandy Land, China. The results show that the dominant species in very severe desertification areas were replaced by perennial grasses in potential desertification areas. The importance values of annual forbs and perennial sub-shrubs decreased dramatically (from 42.59 and 32.98 to 22.13 and 5.54, respectively), whereas those of perennial grasses and perennial forbs increased prominently (from 13.26 and 2.71 to 53.94 and 11.79, respectively) with the reversal of desertification. Desertification reversal increased the complexity of plant community composition by increasing plant species in each PFT, and C3 plants replaced C4 plants to become the dominant PFT with reversal. Plant species richness and species diversity rose overall, and aboveground plant biomass significantly (p < 0.05) increased with the reversal of desertification. Most vegetation characteristics changed more strikingly in the early stages of desertification reversal than in later stages. Our results indicate that the type and composition of the plant community were dramatically affected by desertification reversal. Anthropogenic measures are more applicable to being employed in early stages than in later stages, and Amaranthaceae C4 plants are suggested to be planted in mobile dunes for the acceleration of desertification reversal. This study is useful for designing strategies of land management and ecological restoration in arid and semiarid regions. [ABSTRACT FROM AUTHOR]

The non-grain production rate (NGPR) of cropland is a grave threat to global grain and food supply, and has been a hot issue across the world. However, few scholars explored the impacts of the NGPRs of different cropland types, such as those of paddy land and irrigated land in the same region. Thus, according to the third land survey data, this research first estimated the NGPRs of cropland, paddy land, irrigated land, and dry land at different scales in Shandong Province, China in 2019. Then, their spatial characteristics at a county scale were identified by combining the standard deviation ellipse model and spatial autocorrelation analysis. Finally, the potential driving factors of the NGPR of cropland were explored with the geographical weight regression model. Results are as follows: (1) The NGPR of cropland is at relatively lower level in Shandong Province and is dominated by that of irrigated land, and the NGPR of dry land is higher than those of other cropland types; (2) Significant regional differences exist in the NGPR of cropland, with profound severity in the southeast and much lower in the northwest; (3) At the provincial scale, the total power of agricultural machinery per capita and utilization degree of cropland factors can relieve the NGPR of cropland in nearly the entire research area. The proportion of GDP of the primary industry in GDP, urban population rate, and DEM are the main obstacles for NGPR decrease. At the county scale, the influences of driving factors varied across regions. This research can provide targeted and regional differentiated references for policy improvement and NGPR management. [ABSTRACT FROM AUTHOR]

In responding to global ecosystem conservation and sustainable social development, numerous ecological restoration projects have been performed in ecologically vulnerable areas around the world, especially in semi-arid areas. Affected by local hydrothermal conditions, whether ecological restoration projects can achieve goals of balanced water-carbon enhancement as well as sustainable development in semi-arid areas is controversial. It is uncertain that to what extent the land use change caused by ecological restoration projects will affect the water-carbon imbalance. This research takes the Bashang Plateau Protection Zone (BPZ), a typical semi-arid area in Hebei Province of China, as a porotype to discover the spatial water-carbon changes and their contributing factors under ecological projects during 2000 to 2020 through root mean square deviation and random forest analysis. Results show: (1) In the past two decades, carbon sequestration in BPZ continued to improve while water conservation decreased significantly. The water-carbon imbalance regions in BPZ increased nearly 6.80 folds, from 338.60 km2 to 2642.38 km2. (2) Precipitation and temperature exerted the most significant impact on the formation of water-carbon imbalance regions, whereas the contribution of land use change could reach 40%, demonstrating that human activities were also strongly responsible for water-carbon imbalance. (3) Ecological restoration pattern of limiting afforestation and agricultural land expansion with priority restoration of grassland is beneficial to achieving water-carbon balance and sustainable goals of ecological restoration in semi-arid regions. [ABSTRACT FROM AUTHOR]

Understanding the impact of irrigation on the spatiotemporal characteristics of precipitation is important for the ecological stability of the arid region of Northwest China (NWC). In this study, the global climate model MPI-ESM-MR is utilized to provide the initial and lateral boundary conditions for the regional climate model RegCM4, enabling the simulation of the long-term climate of the arid NWC region under two Representative Concentration Pathways (RCPs). The study focuses on analyzing the differences in the spatiotemporal distribution, intensity, and frequency of precipitation before and after irrigation. Furthermore, the study explores the primary factors influencing changes in the spatiotemporal distribution characteristics of precipitation in the irrigation district and its downwind region. The results indicate that RegCM4 performs well in simulating the climatology and diurnal cycle of precipitation in the NWC, particularly excelling during the summer. Large-scale irrigation significantly impacts the structure of summer precipitation, leading to a notable increase in convective precipitation near the irrigation district and surrounding mountain ranges. Anomalous cyclonic circulation and enhanced vertical velocity enhancement provide dynamic conditions for increased precipitation in the irrigation district and surrounding mountainous regions. Furthermore, the evaporation of water vapor resulting from large-scale irrigation serves as an additional source of moisture, contributing to increased precipitation in the irrigation district and its downwind region. Due to the difference in climatic conditions between the western and eastern regions around the irrigated areas, the summer extreme precipitation in the west predominantly increases. At the same time, in the east, it predominantly decreases due to irrigation. The findings of this study contribute to a deeper understanding of the physical mechanisms through which agricultural irrigation influences precipitation in the arid region of the NWC, thereby providing scientific evidence for the sustainable utilization of water resources in the region. [ABSTRACT FROM AUTHOR]