Search Results (9)

The Kekeya oilfield is located at the southwestern edge of the Tarim Basin, in the southern margin of the Yecheng depression, at the western end of the second structural belt of the northern foothills of the Kunlun Mountains. It is one of the important oil and gas fields in western China, with significant oil and gas resource potential in the X4-X5 section of the Xihepu Formation. This study focuses on the edge of the alluvial fan depositional system, employing various techniques, including core data and well logging data, to precisely characterize the sand body architecture and comprehensively analyze the reservoir architecture in the study area. First, the regional geological background of the area is analyzed, clarifying the sedimentary environment and evolutionary process of the Xihepu Formation. Based on the sedimentary environment and microfacies classification, the sedimentary features of the region are revealed. On this basis, using reservoir architecture element analysis, the interfaces of the reservoir architecture are finely subdivided. The spatial distribution characteristics of the planar architecture are discussed, and the spatial distribution and internal architecture of individual sand body units are analyzed. The study focuses on the spatial combination of microfacies units along the profile and their internal distribution patterns. Additionally, a quantitative analysis of the sizes of various types of sand bodies is conducted, constructing the sedimentary model for the region and revealing the control mechanisms of different sedimentary architectures on reservoir properties and oil and gas accumulation patterns. This study pioneers a quantitative model for alluvial fan fringe in gentle-slope basins, featuring the following: (1) lobe width-thickness ratios (avg. 128), (2) four base-level-sensitive boundary markers, and (3) a retrogradational stacking mechanism. The findings directly inform reservoir development in analogous arid-climate systems. This research not only provides a scientific basis for the exploration and development of the Kekeya oilfield but also serves as an important reference for reservoir architecture studies in similar geological contexts. Full article

Under accelerating global warming, the northern slope of the Middle Kunlun Mountains in Xinjiang, China, has seen a marked rise in extreme rainfall, posing increasing challenges for flood risk management and water resources. To improve our predictive capabilities and deepen our understanding of the driving mechanisms, we combine the European Centre for Medium-Range Weather Forecasts Reanalysis-5 (ERA5) reanalysis, regional observations, and high-resolution Weather Research and Forecasting model (WRF) simulations to dissect the 14–17 June 2021, extreme rainfall event. A deep Siberia–Central Asia trough and nascent Central Asian vortex established a coupled upper- and low-level jet configuration that amplified large-scale ascent. Embedded shortwaves funnelled abundant moisture into the orographic basin, where strong low-level moisture convergence and vigorous warm-sector updrafts triggered and sustained deep convection. WRF reasonably replicated observed wind shear and radar echoes, revealing the descent of a mid-level jet into an ultra-low-level jet that provided a mesoscale engine for storm intensification. Momentum–budget diagnostics underscore the role of meridional momentum transport along sloping terrain in reinforcing low-level convergence and shear. Together, these synoptic-to-mesoscale interactions and moisture dynamics led to this landmark extreme-precipitation event. Full article

The Kunlun, Arjin, and Qilian mountain ranges mark the northern edge of the Qinghai–Tibet Plateau (QTP), where rapid uplift and Quaternary glacial cycles have shaped a unique cold desert ecosystem and species distribution. Despite sampling challenges, phylogeographic studies are crucial for understanding reptile populations such as the Qinghai toad-headed agama (Phrynocephalus vlangalii), a viviparous lizard with limited dispersal and multiple subspecies in the northeastern QTP. Our fieldwork identified populations of P. vlangalii on the northern slope of the Kunlun–Arjin Mountains, similar to the controversial subspecies P. v. lidskii. We analyzed 130 individuals from the northern slope of the Kunlun–Arjin–Qilian Mountains and 253 individuals from GenBank, using three mitochondrial genes and two nuclear genes to assess intraspecific differentiation and demographic history. We found high haplotype diversity and low nucleotide diversity in P. vlangalii, with phylogenetic analyses revealing six distinct clades. Clade VI, confirmed as P. v. lidskii, and Clade IV, a new genetic lineage, were identified alongside three recognized subspecies. Genetic variation was largely attributed to clade splitting, indicating significant divergence. The Mantel test indicated that geographical and environmental factors drove population differentiation. Bayesian molecular clock analysis suggested that the most recent common ancestor of P. vlangalii lived 2.55 million years ago, influenced by the Qinghai–Tibet Movement and glacial cycles. Demographic history and ecological niche modeling (ENM) indicated no population decline during the Last Glacial Maximum, supporting the glacial maximum expansion model, with ENM predicting future habitat expansion for P. vlangalii. In addition, morphological data from 13 meristic and 15 metric characters confirmed clade differences. Our findings significantly advance our understanding of P. vlangalii diversification, population dynamics and response to geological and climatic changes in the QTP. Full article

The response of dryland vegetation to climate change is particularly sensitive in the context of global climate change. This paper analyzes the characteristics of spatial and temporal dynamics of vegetation cover in the Tarim River Basin, China, and its driving factors in order to investigate the response of vegetation growth to water storage changes in the basin. The Enhanced Vegetation Index (EVI), the GRACE gravity satellite, and meteorological data from 2002 to 2022 are used to decipher the characteristics of the response of water storage changes to vegetation changes, which is of great significance to the realization of regional ecological development and sustainable development. The results of the study show the following: (1) The vegetation in the Tarim River Basin has an overall increasing trend, which is mainly distributed in the Aksu Basin and the Weigangkuche River Basin and is spatially distributed in the form of a ring. (2) Vegetation distribution greatly improved during the 20-year study period, dominated by high-cover vegetation, with a change rate of 200.36%. Additionally, vegetation changes are centered on the watersheds and expand to the surrounding area, with a clear increase in vegetation in the Kumukuri Basin. Areas with a vegetation Hurst index of <0.5 account for 63.27% of the study area, and the areas with a continuous decrease were mainly located in the outer contour area of the Tarim River and Kumu Kuri Basins. (3) There are obvious spatial differences in the correlation between EVI and temperature and precipitation elements. The proportion of areas with positive correlation with temperature within the study area is 64.67%. EVI tends to be consistent with the direction of migration of the center of gravity of the population and GDP, and the areas with positive correlation between vegetation and terrestrial water reserves are mainly distributed in the northern slopes of the Kunlun Mountains, with an area proportion of about 50.513%. The Kumukuli Basin also shows significantly positive correlation. Full article

The precipitation on the northern slope of the Kunlun Mountains significantly impacts the green economy of the Tarim Basin’s southern edge. Observations have noted an expansion of the surface water area in this region, though the reasons for this are not yet fully understood. Due to limited instrumental data, this study leverages field measurements from the third Xinjiang comprehensive expedition and multiple gridded datasets. Through trend analysis and a geographical detector model, it examines the precipitation’s decadal, interannual, and seasonal variations across key areas (Hotan River Basin, Keriya River Basin, Qarqan River Basin, and Kumukuli Basin), identifying factors behind the spatial and temporal distribution of regional precipitation. The findings reveal the following: (1) An increase in annual precipitation across the region from 187.41 mm in the 1980s to 221.23 mm in the early 21st century, at a rate of 10.21 mm/decade, with the most significant rise in the eastern Kunlun-Kumukuli Basin. (2) Precipitation exhibits clear seasonal and spatial patterns, predominantly occurring in spring and summer, accounting for 90.27% of the annual total, with a general decrease from the mountains towards downstream areas. (3) Rising average annual temperatures contribute to an unstable atmospheric structure and increased water-holding capacity, facilitating precipitation. Significant influences on precipitation changes include the North Atlantic Oscillation and solar flux, explaining 43.98% and 31.21% of the variation, respectively. Full article

The ecological environment in the mountainous areas of southern Xinjiang is very sensitive and fragile, and identifying the ecological asset retention within the mountainous areas is a top priority at the current stage in the context of comprehensive environmental management in arid zones. This study examines the conversion and ecosystem service values between different land types within the mountainous areas based on a time series of land-use data from 1990 to 2020, and the results show that: (1) The value of ecosystem services on the northern slopes of the Kunlun Mountains shows an overall increasing trend. It increased from CNY 308.645 billion in 1990 to CNY 326.550 billion in 2020. Among them, the value of ecosystem services increased significantly between 2000 and 2010, with an increase of CNY 39.857 billion. Regulatory services accounted for more than 66% of the value of each ecosystem service. (2) Land use on the northern slopes of the Kunlun Mountains has changed significantly since 1990. The areas of cropland, forest land, grassland, watershed, and construction land have all shown an upward trend, with the greatest increase in construction land. The area of unutilized land, on the other hand, has slightly decreased. (3) The value of ecosystem services within the northern slopes of the Kunlun Mountains was spatially high in the south, low in the north, and higher in the west than in the east. The study also found a significant positive spatial correlation between ecosystem service values. In the spatial distribution, the increasing areas were mainly distributed in the southeast, and the decreasing areas were in the north. Changes in land types are expected to include an increase in the area of grassland and woodland, a decrease in unutilized land and cropland, and an overall improvement in the ecological environment of the northern slopes of the Kunlun Mountains in the next decade. This study also provides lessons and references for sustainable development and ecological protection in ecologically fragile regions. Full article

Extreme precipitation events have been occurring frequently worldwide, and their causative factors and convection initiation (CI) mechanisms have been attracting more and more attention in recent years. As a comprehensive study on the CI mechanisms of extreme rainstorms over the northern slope of the Kunlun Mountains (KLM), Xinjiang, based on both observational and high tempo-spatial numerical simulation, the major findings of this work are as follows: A cold pool (CP) was formed in the northwestern Tarim Basin under the influence of early precipitation evaporation, and it moved towards the northern slope of the KLM several hours before the CI. With the movement of the CP, a significant vertical temperature gradient was formed close to the leading edge of the CP, thereby enhancing local convective instability (up to ~10 PVU). In addition, the vertical shear of the horizontal winds at the leading edge of the CP led to a notable increase in the baroclinic component of moist potential vorticity, thus reinforcing the local conditional symmetric instability (up to ~8 PVU), providing another important unstable energy for the CI. In addition, the combined effect of the convergent lifting of a boundary layer jet (BLJ, the maximum wind speed below 1 km exceeding 10 m s⁻¹) and the significant frontogenetical forcing (up to ~100 × 10⁻⁸ K m⁻¹ s⁻¹) at the leading edge of the CP were the causes of the release of the unstable energies. Further analysis of the frontogenetical forcing associated with the CP indicates that the convergence (up to ~2 × 10⁻³ s⁻¹), diabatic heating and slantwise terms (indicates the baroclinicity and inhomogeneity of the vertical momentum in horizontal direction) were the major contributors, whereas the deformation term at the leading edge of the CP provided a relatively weaker contribution. Full article

Runoff from the high-cold mountains area (HCMA) is the most important water resource in the arid zone, and its accurate forecasting is key to the scientific management of water resources downstream of the basin. Constrained by the scarcity of meteorological and hydrological stations in the HCMA and the inconsistency of the observed time series, the simulation and reconstruction of mountain runoff have always been a focus of cold region hydrological research. Based on the runoff observations of the Yurungkash and Kalakash Rivers, the upstream tributaries of the Hotan River on the northern slope of the Kunlun Mountains at different time periods, and the meteorological and atmospheric circulation indices, we used feature analysis and machine learning methods to select the input elements, train, simulate, and select the preferences of the machine learning models of the runoffs of the two watersheds, and reconstruct the missing time series runoff of the Kalakash River. The results show the following. (1) Air temperature is the most important driver of runoff variability in mountainous areas upstream of the Hotan River, and had the strongest performance in terms of the Pearson correlation coefficient (ρ_XY) and random forest feature importance (FI) (ρ_XY = 0.63, FI = 0.723), followed by soil temperature (ρ_XY = 0.63, FI = 0.043), precipitation, hours of sunshine, wind speed, relative humidity, and atmospheric circulation were weakly correlated. A total of 12 elements were selected as the machine learning input data. (2) Comparing the results of the Yurungkash River runoff simulated by eight machine learning methods, we found that the gradient boosting and random forest methods performed best, followed by the AdaBoost and Bagging methods, with Nash–Sutcliffe efficiency coefficients (NSE) of 0.84, 0.82, 0.78, and 0.78, while the support vector regression (NSE = 0.68), ridge (NSE = 0.53), K-nearest neighbor (NSE = 0.56), and linear regression (NSE = 0.51) were simulated poorly. (3) The application of four machine learning methods, gradient boosting, random forest, AdaBoost, and bagging, to simulate the runoff of the Kalakash River for 1978–1998 was generally outstanding, with the NSE exceeding 0.75, and the results of reconstructing the runoff data for the missing period (1999–2019) could well reflect the characteristics of the intra-annual and inter-annual changes in runoff. Full article

Under climate change, river ecological base flow becomes particularly critical for the health and stability of inland river ecosystems in arid regions. Taking three typical seasonal inland rivers, including the Kriya River, the Niya River, and the Qarqan River, all on the northern slope of the Kunlun Mountains, as research objects, meteorological data from 1958 to 2019 and hydrological data from 1978 to 2014 were selected to analyze the characteristics of ecological base flow under climate change. The results show that in the past 60 years, the temperature in the Kriya River, Niya River, and Qarqan River basins has warmed at rates of 0.235 °C•(10a)⁻¹, 0.223 °C•(10a)⁻¹, and 0.177 °C•(10a)⁻¹, respectively, while the precipitation has increased at the rates of 0.88 mm•(10a)⁻¹, 3.90 mm•(10a)⁻¹, and 7.92 mm•(10a)⁻¹. The Tennant method was determined as the best algorithm for ecological base flow of inland rivers in arid regions. The interannual maximum values of ecological base flow all occurred in 2010, with three rivers increasing by 5.098 m³·s⁻¹, 2.416 m³·s⁻¹, and 11.343 m³·s⁻¹ respectively, and the regional average increasing by 6.286 m³·s⁻¹. The maximum ecological base flow within the year is in July, and the minimum value is in January, with a high proportion of the flood season. The monthly ecological base flow of rivers has a strong correlation with the monthly temperature and precipitation, with the strongest correlation in the Qarqan River basin and the correlation coefficients of 0.876 and 0.917. We propose ecological base flow guarantee objectives for the three rivers during the dry season, and clarify that the flood season is the key point of ecological base flow guarantee. The guarantee objectives are 0.974 m³·s⁻¹, 0.154 m³·s⁻¹, and 2.167 m³·s⁻¹, for the three rivers, respectively. Our research results can provide scientific reference for the management and regulation of water resources and ecological protection of the northern slope of the Kunlun Mountains. Full article