This study evaluates the applicability of common climatic seasonal division methods in Tibet of China, utilizing daily temperature data from 38 meteorological stations spanning from 1981 to 2022. The analysis highlights the limitations of various seasonal division approaches and emphasizes the suitability of Tibetan phenological and growing season division methods for agricultural activities in Plateau region of Tibet. Temperature thresholds for seasonal division were determined based on Tibetan phenology and the main crops’ growing periods. The research reveals that: (1) While general methods for climatic season division exhibit certain limitations in Tibet, the Tibetan phenological and growing season division methods align well with agricultural requirements. (2) Employing temperature thresholds of “6 ℃, 15 ℃”, “5 ℃, 16 ℃”, “6 ℃, 16 ℃”, and “6 ℃, 17 ℃”, the study analyzes the variation in the lengths of the four seasons at typical weather stations. Gerze experiences a longer winter, while Zayu has a prolonged summer. In Lhasa, Qamdo, Gerze, and Zayu stations, summer durations have extended, whereas autumn and winter have contracted. (3) Mutation tests indicate that the average summer temperatures at Lhasa and Qamdo stations underwent significant changes in 2011 and 2017, respectively, supporting the use of 17 ℃ as the summer threshold. (4) The newly proposed four-season division method for Tibet, characterized by the “6 ℃, 17 ℃” index, demonstrates a distribution pattern of weather stations mainly along the lower elevation areas of the Yarlung Tsangpo River Line during summer. Spring and autumn durations are shorter in the northwest and south, and longer in the central and eastern regions. Conversely, summer is extended in the central areas and reduced in the peripheral regions, with the opposite pattern observed for winter, spring, and autumn. This spatiotemporal distribution aligns with Tibet’s climatic reality. The average onset dates for spring, summer, autumn, and winter are March 21, June 16, July 25, and November 3, respectively.

Utilizing meteorological observation data from 20 national meteorological stations in Ningxia, China, spanning from 1961 to 2020, along with socioeconomic statistical data from the past four decades, this study established indicators for drought process events in Ningxia. Subsequently, it developed an interdecadal drought disaster risk assessment model in line with disaster risk assessment theory. The study analyzed the interdecadal variation characteristics and regional differences of drought events and the associated risks to major crops in Ningxia, aiming to identify the factors influencing regional crop interdecadal risk changes. The findings are as follows: (1) The cumulative effect, duration, and intensity indicators of drought events in Ningxia over the past six decades exhibit distinct interdecadal variation characteristics, with notable shifts in trends and mean values in the central northern region and southern mountainous areas around 1980 and 2010, respectively. Additionally, the spatial distribution of high-value areas for drought event and disaster risk indicators demonstrated a pattern of initial increase, followed by a decrease, another increase, and a final decrease over the decades. (2) Since the 1980s, the risk levels of corn drought disasters in Ningxia’s regions, in descending order, are the Yellow River irrigation area, the central arid zone, and the southern mountainous area. Influenced by the continuous expansion of the corn planting area and the growth of the gross domestic product (GDP), the drought risk levels in the central and southern regions have seen an interdecadal increase. Moreover, the increase amplitude in wheat drought disaster risk levels, in descending order, are the central arid zone, the southern mountainous area, and the Yellow River irrigation area. The primary reasons for the heightened drought risk in parts of the central arid zone during the 2010s include the confluence of high disaster risk, wheat planting area, and GDP. (3) Given the future challenges of water scarcity and inadequate irrigation in Ningxia’s central and southern regions, it is advisable to adopt measures such as enhancing artificial rainfall capabilities, developing new crop varieties, and encouraging farmland returning to forestry and grassland or migration to mitigate the disaster risk. These strategies aim to reduce the induced disaster risk, disaster bearing body exposure and pregnant environment vulnerability, thereby lowering the drought disaster risk levels for local corn and wheat production. The insights from this analysis offer a scientific foundation for the region’s strategic agricultural planning, efficient water use, drought mitigation, and disaster response efforts, contributing to the ecological protection and high-quality development initiatives in the Yellow River Basin of Ningxia.

Global warming has led to the increased frequency of extreme events such as droughts, posing significant threats to ecological security and sustainable socioeconomic development, particularly in arid regions, which are highly sensitive and responsive to climate changes. This paper employs the distributed hydrological model HEC-HMS, utilizing observed meteorological and hydrological data from basin stations and global climate model data from the Sixth International Coupled Model Intercomparison Program (CMIP6), to simulate and forecast the historical (1986—2014) and future (2015—2100) runoff trends and hydrological drought risks in the Yarkant River Basin (an essential tributary of the Tarim River), Xinjiang, China. The findings indicate that: (1) The HEC-HMS model is well-suited for arid basin areas. Under the three shared socioeconomic pathways (SSPs) scenarios, the runoff and standardized runoff index (SRI) in the Yarkant River Basin are projected to significantly increase (P<0.1), with the SRI growth rate estimated at approximately 0.13-0.27·(10a)^-1. (2) A comparative analysis of the marginal distributions of four drought characteristic variables in the basin for both historical and future periods reveals that the duration and intensity of future droughts will exceed those in the historical record, with a continuous rise in drought event magnitudes. (3) Moreover, the joint probability of future hydrological droughts in the Yarkant River Basin is expected to decrease relative to the historical period, leading to a prolonged return period for future droughts. The outcomes of this study offer valuable scientific references for water resource management and the development of strategies to mitigate hydrological drought risks in the basin.

Utilizing Landsat TM/ETM+/OLI imagery and digital elevation model (DEM) data, this study extracted the boundaries of glaciers and glacial lakes in Poiqu Basin, Xigaze City, Xizang Autonomous Region, China from 1990 to 2020 through the ratio threshold method and visual interpretation. The distribution and variation of glaciers and glacial lakes over three decades were analyzed, alongside the exploration of their co-evolution and response to climate change within the basin. The findings revealed: (1) A notable acceleration in glacier shrinkage within the Poiqu Basin over the last decade, with glaciers primarily situated between 5500 m and 6100 m. While the count of large-scale glaciers (≥10 km²) remained constant, small-scale glaciers (≤0.5 km²) exhibited an upward trend. (2) Both the number and area of glacial lakes witnessed a significant increase, with an expansion rate of 74.24%. Predominantly located between 4900 m and 5300 m, the expansion was more pronounced in larger glacial lakes (≥0.07 km²), whereas smaller lakes (≤0.03 km²) also saw a marked rise in numbers. (3) Glacial lakes connected to their parent glaciers emerged as the most significant type contributing to glacial lake expansion, registering a 72.08% increase. (4) The past 30 years have experienced a gradual temperature rise and a minor decline in precipitation. These climatic shifts, particularly the temperature increase and precipitation decrease, have been crucial in glacier retreat, while meltwater from glaciers has facilitated the expansion of glacial lakes. Through examining the distribution, changes, and interrelation of glaciers and glacial lakes in Poiqu Basin, this study aims to provide valuable data support for understanding glacier area dynamics and aiding in the prediction and mitigation of glacial lake outburst floods.

In the arid and ecologically sensitive Tarim River Basin, a vital hub for grain and cotton production in China, the harmonious development of water, arable land, and agricultural resources is crucial for sustainable growth. This study constructs a water-cropland-grain-cotton system model for the basin, evaluates its development index, and assesses the system’s coupling coordination using a coupling coordination degree model. Furthermore, the Fractional Logit model was employed to identify factors influencing the system’s coordinated development. The findings reveal that: (1) The development indices indicate a hierarchy of water system>water-cropland-grain-cotton system>cropland system>grain-cotton system. Post-2013, the development index of the cropland system in Aksu and Kashgar Prefetures surged, surpassing those of the combined water-cropland-grain-cotton system and the individual water system. Changes in other areas were minimal. (2) The coordination level of the basin’s coupled system ranges from 0.475 to 0.680, indicating a transition from minimal to basic coordination. Kashgar exhibits the highest coordination, while Kizilsu Kirgiz Autonomous Prefecture the lowest. This index, after an initial gradual increase, experienced a notable decline post-2017, particularly in the Aksu Prefecture. (3) The number of reservoirs, general public budget expenditure, and population size emerge as critical factors influencing the system’s coordination. An increase of one unit in these variables corresponds to a rise in the coupling coordination degree by 1.0%, 21.0%, and 35.6%, respectively.

Drought is one of the most disastrous extreme climate events. Studying the changes in drought risk against the background of future global warming is beneficial for scientifically advancing disaster prevention and reduction work deployment. The standardized precipitation evapotranspiration index was calculated using data from 20 climate models from the sixth phase of the Coupled Model Intercomparison Project. Drought characteristic variables were extracted for the baseline period and global temperature rise scenarios of 2 ℃, 3 ℃, and 4 ℃ in China, and the drought hazard index (DHI) was calculated. Based on the disaster-bearing body projection data, the drought exposure index (DEI), drought vulnerability index (DVI), and drought risk index (DRI) were comprehensively calculated. The distribution pattern of drought risk in China was further analyzed, and a spatial attribution analysis of future drought risk changes was performed using a geodetector. The results showed that the spatial distribution of DHI, DEI, and DVI exhibited higher values in the northwest and southeast, a pattern of being high in the east and low in the west, and a trend of being high in the west and low in the east, respectively. Based on this, the DRI specially showed a spatial positive correlation dominated by high- and low-value clustering. With an increase in the temperature rise level, the future drought risk will mainly increase across China, and the increase in the eastern coastal areas would be the most obvious. Changes in population, gross domestic product, and the proportion of cultivated land were found to be the main factors affecting changes in drought risk.

Based on daily precipitation data from 337 meteorological monitoring stations in Qinling Mountains and surrounding areas during 1980—2021, the spatiotemporal characteristics of extreme precipitation were analyzed. The generalized extreme value distribution and climate statistics methods were used to compare the differences in extreme precipitation years and seasons (spring, summer, and autumn) between two phases: the first phase (1980—2000) and the second phase (2001—2021). The results are as follows: (1) Extreme precipitation in Qinling and surrounding areas mainly concentrated from April to November, with July registering the highest number of extreme precipitation days. Over the past 40 years, extreme precipitation has shown an overall increasing trend. Spatially, the southeast exhibits higher values for the extreme daily precipitation threshold and daily maximum precipitation than the northwest. Additionally, a clear boundary along the north-south direction, aligning with the Qinling, highlights more occurrences in the southern region than in the northern region. (2) On an annual scale, there is a discernible rise in both the number and intensity of extreme precipitation events during 2001—2021 compared with 1980—2000. The spatial changes in the extreme daily precipitation threshold, the number of extreme precipitation days, and daily maximum precipitation also show an overall increasing trend, with more meteorological stations exhibiting an increasing trend. (3) Considerable seasonal differences in extreme precipitation exist, particularly between spring and summer/autumn. The probability and frequency of extreme precipitation were generally higher in spring during 1980—2000, whereas in 2001—2021, extreme precipitation peaks in summer and autumn. Spatial distribution differences are also evident. In spring, the extreme daily precipitation threshold and the number of extreme precipitation days generally show an increasing trend in the western region, contrasting with a decreasing trend in the eastern region, transitioning from positive to negative values. A greater number of stations display a decreasing trend than an increasing trend. In contrast, in summer and autumn, the number of stations demonstrating an increase in the extreme daily precipitation threshold and the number of extreme precipitation days exceeds those witnessing decreasing trends, particularly in autumn, where the proportion of stations with increasing trends is higher.

Based on daily precipitation data from 28 national meteorological stations in northern Shanxi Province, China, from 1972 to 2020, temporal and spatial changes in extreme precipitation in northern Shanxi and their correlation with atmospheric circulation factors and periodic characteristics were studied using linear regression, Pearson correlation analysis, continuous wavelet analysis, and cross wavelet transform analysis. The results show the following: (1) In terms of time, the eight extreme precipitation indices in northern Shanxi increased significantly in the late 1970s and from the late 2010s to the early 2000s: annual total wet-day precipitation (PRCPTOT), number of heavy precipitation days (R10mm), soaked days (R95P), extremely wet days (R99P), maximum 1-day precipitation amount (Rx1day), and maximum 5-day precipitation amount (Rx5day). The simple daily intensity index (SDII) increased significantly, and consecutive wet days (CWD) also increased slightly. Precipitation was unusually low throughout the 1980s. (2) Spatially, the extreme precipitation indices gradually increased from northeast to southwest. From the analysis of the stations’ trend change, the extreme precipitation indices of most stations showed an upward trend, with the most significant upward trend of the stations located southwest of Xinzhou City. PRCPTOT and SDII in Shuozhou City and southeast of Xinzhou City showed an increasing trend. However, days of CWD showed a decreasing trend, indicating that the probability of extreme precipitation events in Shuozhou City and the southeast of Xinzhou City was high. (3) Through wavelet transform analysis, it was discovered that the extreme precipitation indices in northern Shanxi had a periodic feature of recurring in approximately 4 years in the past 30 years. Among the selected atmospheric circulation indices, the North Atlantic Oscillation Index (NAO) had the most obvious influence on extreme precipitation in northern Shanxi. The larger the NAO, the smaller the PRCPTOT, R10mm, R95p, R99p, Rx1day, Rx5day, and SDII, and the lower the CWD, the greater the probability of low rainfall and drought in northern Shanxi, which is prone to flash flooding. The research results can provide a scientific theoretical basis for the prevention of meteorological disasters in northern Shanxi.

Climate change in Xinjiang, China, has been remarkable in recent decades. With a significant shift from warm-wet to warm-dry, regional vegetation productivity, atmospheric drought conditions, and the response relationship between them will inevitably be affected. Based on multisource data such as ground meteorological observations and reanalysis data, considering remote sensing products, vegetation gross primary productivity (GPP), and vapor pressure deficit (VPD) as indicators, this study analyzed the spatial-temporal distribution and evolution patterns of vegetation GPP and VPD in Xinjiang from 1982 to 2018, as well as the influence of VPD changes on GPP. The results are as follows: (1) The annual mean GPP in Xinjiang was higher in the northern region, especially the mountains, than in the southern region. The annual mean GPP in Xinjiang was 256.6 g C·m^-2·a^-1 with a significant upward trend in interannual variability (R²=0.72, P<0.01). Approximately 82.00% of the total vegetation area showed an increasing trend, of which the area with significant increase accounted for 42.81%, mostly distributed in the oasis at the edge of the Tarim Basin in southern Xinjiang and agricultural areas on the north slope of Tianshan Mountains. The area with a decreasing GPP trend accounted for a small percentage, and its distribution was scattered. (2) VPD showed a distinct difference of “low in the mountains and high in the basins”. A nonsignificant fluctuating upward trend was observed in the VPD, with an annual mean value of 0.66 kPa. Significant increases in VPD occurred in approximately 82.02% of the whole territory, predominantly in the Tarim and Junggar Basins. In contrast, decreasing trends occurred sporadically in the high-altitude mountainous areas of the Kunlun Mountains. (3) Overall, the response of GPP to VPD was characterized by a distinct spatial heterogeneity with positive and negative correlations. The negative correlation between GPP and VPD accounted for 54.52% of the total vegetation area, mainly in the grassland at the front edge of the mountain. While the positive correlation was mainly distributed at the edge of the Tarim Basin, the northern slope of the Tianshan Mountains and its eastern section were dominated by cultivated crops and shrubs. Comparative analyses showed that GPP-VPD correlations differed significantly across vegetation types. The study proved that the change in VPD has already affected the vegetation productivity in Xinjiang. Although it has not yet become a major limiting factor, there is still a need to strengthen the tracking of the GPP and VPD response relationship to provide a scientific reference for optimizing ecological restoration and governance.

The Aral Sea was once the fourth largest lake in the world. Since the 1960s, due to the demands of agricultural irrigation, the regions of the Aral Sea basin have diverted a large amount of water from the Amu Darya and Syr Darya rivers, resulting in the rapid shrinkage of the Aral Sea, the reduction of water levels, and also the deterioration of water quality. By the beginning of the 21^st century, the lake’s surface had shrunk to 1/8 of its original size, and the dried lake bottom had become a salt desert with high salinity. Many biological species decreased and the ecological environment deteriorated, causing an ecological crisis. After the independence of the Central Asian countries, the conflict between the upper and lower parts of the Amu Darya River and Syr Darya River resulted from the lack of water, which seriously affected the relations between these countries. Despite repeated negotiations, the Central Asian countries failed to come up with a common solution to the Aral Sea water crisis. In the absence of regional cooperation, Kazakhstan took independent measures and saved part of the waters of the northern part of Aral Sea. Moreover, Uzbekistan also took a proactive approach to managing the Aral Sea crisis in recent years. The prevailing academic opinion is that the Aral Sea crisis is human-made and that linking it to global climate change is inappropriate. Thus, the Aral Sea crisis, which has been improved because of governance and groundwater recharge, may not disappear as previously predicted and considerable uncertainty remains as to how much it will recover. This study offers a complete discussion of the history, status, and prospects of the Aral Sea crisis to provide a reference for the governance of the arid environment in northwestern China.

Several factors affect the evapotranspiration process. Potential evapotranspiration (ET₀) interacts with meteorological variables in a complex manner. Therefore, there is an urgent need to determine the response mechanism of ET₀ changes to meteorological variables. Based on meteorological data from 21 meteorological stations in the Hexi Corridor, Gansu Province, China and its surrounding areas, qualitative and quantitative methods were adopted to reveal the spatiotemporal variation of ET₀ and to clarify the sensitivity of ET₀ to changes in various meteorological factors and contributions by taking two spatial scales of the Hexi Corridor as a whole and three subdistricts. The results showed the following: (1) ET₀ in both the Hexi Corridor and the subdistrict showed a significant fluctuating upward trend (Z>1.98), with a linear change rate of 2.94 mm·a^-1, and the most obvious change was observed in the Heihe subdistrict. (2) ET₀ increased from the southeast to northwest. It was smaller in the Shiyang River subdistrict (1003.78 mm) and Heihe subdistrict (1031.30 mm) in the central and eastern parts of the Hexi Corridor, and larger in the Shule River subdistrict (1171.89 mm) in the western part of the Hexi Corridor. (3) The sensitivity of ET₀ to changes in meteorological factors in the Hexi Corridor was ranked as relative humidity (RH), daily maximum temperature (T_max), sunshine duration (n), average wind speed (u), and daily rainfall (P), with ET₀ being the most sensitive to decreases in RH and least sensitive to changes in P. (4) The increase in u was the main cause of the increase in ET₀ in the Hexi Corridor, followed by a decrease in RH, increase in T_max, and increase in n. (5) The ET₀ in the subdistricts of the Shule River, Heihe River, and Shiyang River showed an increasing change, with the factors that contributed the most being T_max (5.13%), u (8.22%), and T_max (5.97%), respectively, and the factor that contributed the least being n. Variations in wind speed and air temperature were important factors that influenced the ET₀ change in the Hexi Corridor. The research results are significant for the rational planning of irrigation water use and improvement of the utilization efficiency of agricultural water resources.

The Datong River Basin is located on the northeastern edge of the Qinghai-Tibet Plateau and is a sensitive and fragile ecological environment. It is of great significance to conduct research on the evolution and attribution of water resources in changing environments for the protection of the water ecological environment in the area and the construction of water ecocivilization. Statistical methods such as linear regression, concentration degree, concentration period, ordered clustering test, and wavelet analysis were used to analyze the characteristics of annual variation, seasonal distribution, periodicity, and abrupt changes in basin runoff. On the basis of the cumulative slope change rate method and double cumulative curve, the effects of climate factors and human activities on runoff changes were quantitatively evaluated. The results showed the following: (1) The climate in the Datong River Basin had warmed and humidified significantly in the past 60 years, with increases in average annual temperature, precipitation, and potential evapotranspiration of 0.42 ℃·(10a)^-1, 8.9 mm·(10a)^-1, and 5.6 mm·(10a)^-1, respectively. The annual runoff showed a decreasing trend, with a tendency rate of 0.67×10⁸ m³·(10a)^-1. (2) The concentration degree and uneven coefficient of runoff showed a weak downward trend, and the increasing dry season runoff trend was evident. The seasonal distribution was more uniform, and the concentration period showed a delayed trend, with a delay rate of 3.0 d·(10a)^-1. (3) The annual runoff oscillated significantly at a scale of approximately 44 years, and the mutation occurred in 1990. After the mutation, runoff decreased by 3.52×10⁸ m³. The distribution of glaciers in the basin showed a decreasing trend, whereas the vegetation cover did not show a significant change. (4) The contributions of climate and human activities to the runoff decrease in the Datong River were -17.7% and 117.7%, respectively. Precipitation was the main source of water supply in the Datong River Basin, and interbasin water transfer was the main driving factor for runoff reduction.

Qilian Mountains is a climate-sensitive area in the arid areas of northwest China, where extreme megadrought events considerably impact vegetation, frozen soil, and other ecological elements. This paper uses three hydroclimate reconstruction datasets to analyze the occurrence, evolution, and possible driving mechanism of megadrought and pluvial events in the Qilian Mountains over the past 500 years. The results showed that the climate in the Qilian Mountains has shown a clear wetting trend since the recent decades, and the wetness trend after 1951 has exceeded the range of natural variability in the historical period. The RAP dataset provided a good representation of the historical dry and wet conditions in the study area. Significant variations were observed in precipitation during the past seven megadrought events in the region, with the highest severity occurring during the drought period of 1786—1796. Furthermore, considerable variations were noted in the duration of the four megapluvial events, with the longest duration being a wet event that lasted for 42 years from 1968 to 2009. Megadrought and pluvial events were influenced by climate forcing and internal variability of sea surface temperatures (SST). The decadal SST modes in the Pacific and Atlantic Oceans and their phase combinations were key factors regulating the megadrought and pluvial events in the Qilian Mountains. Solar radiation exhibited an in-phase variation with the precipitation in the Qilian Mountains, while volcanic activity primarily affected megadrought events. This study highlights the importance of a long-term perspective for assessing current hydroclimate anomalies in the Qilian Mountains and including possible roles of external forcing and sea surface temperature variability in assessing the future megadrought and pluvial risks in this region.

Oases are unique and ecologically sensitive landscape types in arid and semiarid regions and play a crucial role in sustaining human survival and socioeconomic development. However, climatic changes and human activities are causing drastic changes to water resources and the oasis eco-environment. This study analyzes terrestrial water storage changes and assesses the ecological security of oases in the Tarim River Basin of Xinjiang, China. The assessment was performed using the fraction of vegetation cover, a remote sensing ecological index, and net primary productivity (NPP) using the Carnegie-Ames-Stanford approach. The analysis used moderate-resolution imaging spectroradiometer satellite images, GRACE data, land use data, and climatic gridded and observed data from 2002 to 2020. The results indicate the following: (1) Terrestrial water storage in the Tarim River Basin decreased at a rate of 0.27 mm per month. Spatially, terrestrial water storage in the northern and western regions of the Tarim River Basin exhibited a negative trend, whereas that in the southern regions of the Basin showed a positive trend. (2) The total oasis area in the Tarim River Basin expanded by 6.49% (0.42×10⁴ km²) from 2000 to 2020. The ecological security of the basin improved, and the eco-environment ranged from poor to general grade. Approximately 69% of the region’s eco-environment improved, whereas the area of ecological degradation was less than 5%. The normalized difference vegetation index increased from 0.13 in 2000 to 0.16 in 2020, the fraction of vegetation cover increased by 36.79%, and the NPP expanded by 31.55% in the past 20 years. (3) Rising temperatures and precipitation contributed to increased downstream river runoff and spatiotemporal variability of water resources in the Tarim River Basin. However, human activities are a key factor in the expansion of oases.

Based on temperature, precipitation, and snow depth data from five hydrological stations in four sources of the Tarim River Basin of Xinjiang, China, from 1981 to 2020, flood magnitude, frequency, and peak time were analyzed using maximum and peak-over-threshold (POT) sampling methods. Moreover, correlation analysis was performed to reveal the relationship between different flood indicators and influencing factors and identify key influencing factors. The results show the following: (1) From 1981 to 2020, the peak discharge of each hydrological station in “four sources” of the Tarim River Basin is as follows: Kaqung>Xehera>Tongguzlok>Sharikilank>Daschankou. The annual and seasonal flood peak discharge generally exhibited an increasing trend, and the occurrence time of the flood peak in winter exhibited an earlier state, among which the average annual advance of Sharikilank was 2.61 days, whereas that of the Kaqung station was only 0.67 days. (2) There were two periods of high flooding in the Tarim River Basin, namely, 1994—2002 and 2006—2011, with several flood occurrences in the Tarim River Basin after 1990. (3) The minimum temperature, precipitation, and snow depth at different times before the floods mainly exhibited an increasing trend, while the maximum temperature mainly exhibited a decrease. The highest correlation was found between spring flood indicators and maximum 3-day precipitation, whereas the highest correlation was found between autumn flood indicators and maximum 7-day precipitation. The correlation between multi-day precipitation and flood indicators was higher than that between single-day precipitation and flood indicators. Among the snow depth-related factors, the maximum 15-day snow depth had the highest correlation with spring flood indicators at each station. These findings provide a theoretical basis for regional water resource management and flood disaster prediction.

Based on daily precipitation and geographic and socioeconomic data collected from 50 national and 39 traffic meteorological stations in Qinghai Province of China from January 2012 to December 2021, this study analyzes the spatiotemporal distribution and characteristics of rainfall intensities along the highway. The analytic hierarchy process and natural breakpoint methods were applied to summarize the risk indices of rainstorms and flood disasters. These indices include the disaster-bearing environment, meteorological risk, and disaster prevention and reduction capability. By integrating these factors, a rainstorm and flood disaster risk model for a highway in Qinghai Province was developed. The key findings are as follows: (1) The spatial distribution of rainfall days along highways decreases from southeast to northwest. High-risk areas include the Xining-Tianjun section of National Highway G315 and the Xining-Ebaoling section of National Highway G227. (2) Environmental vulnerability risk gradually decreases from the southeast and northeast to the west. High-risk areas include the Qilian section of National Highway G227 and the Gonghe-Nangqian section of National Highway G214. (3) The risk of disaster body exposure is concentrated in the Minhe-Gonghe section of National Highway G109 and the Xining-Ebaoling section of National Highway G227. (4) Regions with high disaster prevention and reduction capability are mainly Xining City, Haidong City, east Haibei Prefecture, and west Haixi Prefecture. (5) The rainstorm and flood disaster risk model, categorized into five levels (lowest, low, medium, high, and higher risk), offers a practical tool for meteorological disaster risk management and provides a scientific basis for local transportation departments’ disaster prevention and relief efforts.

Using RA5 monthly reanalysis data from the European Centre for Medium-Range Weather Forecasts and monthly precipitation records from the Global Precipitation Climatology Centre spanning 1980 to 2019, this study examines the influence of May soil moisture anomalies on subsequent June precipitation variability in Central Asia. The findings unveil the following key insights: (1) The spatial distribution of springtime soil moisture exhibited elevated levels in Central Asia’s northern and central regions and lower levels in the southwest and southeast. Maximum standard deviations occurred in southwest Central Asia during March and April. In the north of Central Asia, soil moisture experiences a noteworthy increasing trend in March but displays a declining trend from April to May. Conversely, southwest Central Asia witnessed substantial decreases in March. (2) June precipitation in Central Asia positively correlates with local soil moisture in May. Persistent wet soil moisture anomalies from May to June contribute to increased atmospheric precipitable water, modifying regional evaporation patterns in June. Heightened evaporation leads to increased latent heat flux and reduced sensible heat flux. A small Bowen ratio indicates a relatively shallow boundary layer that promotes low-layer moist entropy and a heightened potential for convective activity. Consequently, June rainfall over the central regions of Central Asia increased. (3) A notable positive correlation exists between soil moisture in May and precipitation in June over middle Central Asia and the preceding winter Niño3.4 index. The influence of the preceding El Nino-Southern Oscillation (ENSO) on June precipitation in middle Central Asia is mediated by May soil moisture. Nonetheless, soil moisture anomalies can independently impact the variability of June precipitation, separate from the influence of ENSO.

The predominant share of total water consumption is currently attributed to agricultural water, which serves as the fundamental input for agricultural production and development. However, the intricate climate environment presents formidable challenges to the effective use of agricultural water, accentuating the imbalance between the supply and demand of agricultural water resources. This study delves into micro-level dynamics, specifically exploring the impact of irrigation behavior goal preferences on irrigation water use efficiency. This study aims to optimize strategies and select methods that enhance agricultural water use efficiency, thereby maximizing agricultural benefits within available resources and environmental context constraints. Focusing on traditional farmers in Xayar County, Aksu Prefecture of Xinjiang, China, this study employs a stochastic frontier model to calculate farmers’ technical efficiency in agricultural production and irrigation water efficiency. Subsequently, the Tobit model was applied to examine the influences of irrigation behavior goal preferences and other factors on irrigation water use efficiency. The findings reveal that the average technical efficiency of farmers’ agricultural production is 0.824, with an average irrigation water efficiency of 0.560. Both technical efficiency in agricultural production and irrigation water efficiency fall short of achieving total technical efficiency, indicating potential for improvement. Upon analyzing the influencing factors, we observed that age, education level, proportion of agricultural income in total income, irrigated area, awareness of water shortage, village cadres status, participation in training, preference for profit maximization, and preference for water conservation exert substantial positive effects on irrigation water efficiency. Consequently, the proportion of planting area for water-consuming crops to the total sown area and the preference to reduce labor input have notable negative impacts on irrigation water efficiency. The agricultural labor force, proportion of water-saving irrigated area in the total irrigated area, water use cost, preference for timely irrigation, and sustainable development have no substantial effects on irrigation water use efficiency. Notably, water use costs negatively influence improving irrigation water use efficiency. Several strategic recommendations have been proposed to enhance irrigation water use efficiency, including increasing farmers’ awareness of water conservation, adjusting planting structures, and refining the irrigation water price mechanism.

The reduction in gross primary productivity (GPP) resulting from drought can significantly impact the terrestrial carbon sink. Based on the standard precipitation evapotranspiration index (SPEI) calculated from the monthly meteorological data of 618 sites from the entire country and two publicly available GPP datasets (i.e., EC-LUE GPP and GLASS GPP, respectively), changes in the GPP affected on different scales by different degrees of drought in a typical drought year during 1982—2017 (2001 and 2011) in China were analyzed systematically. The results revealed that: (1) Based on the five selected indicators of the SPEI, the typical drought years during 1982—2017 were selected as 2001 and 2011. (2) On the annual and seasonal scales, the drought-affected GPP in 2001 was observed mainly in north China, northeast China, and the northern part of middle east region of China, as well as in the southeast and middle east of the southwest region of China in 2011. On the monthly scale, the GPP in May 2001 was the most severely affected by drought, mainly concentrated in most of north China and northeast China; however, in January 2011, the GPP was mainly concentrated in majority of the middle east region of China. (3) Irrespective of the annual, seasonal, or monthly scale, with the increase in the degree of drought, the decline rate of GPP was higher, and the impact of extreme drought was the highest. For example, on the seasonal scale, the decline in the GPP during extreme drought in the summer of 2001 was 19.96% (EC-LUE GPP) and 15.57% (GLASS GPP), and the decline in the GPP during extreme drought in the spring of 2011 was 14.32% (EC-LUE GPP) and 8.75% (GLASS GPP). The results revealed can further deepen the understanding of the effect of different grades of drought on GPP, which is key for understanding the exchange of carbon between the land and atmosphere under drought conditions.

Glacier mass balance is a crucial indicator of climate change and is of great significance for assessing the regional ecological environment, thereby preventing and controlling glacier disasters. Based on Landsat series images, the ratio threshold method and visual interpretation method are applied to extract the glacier boundaries of Qomolangma Nature Reserve from 1990 to 2020. Moreover, the distribution and change characteristics of the glacier area in the past 30 years are investigated while the regional glacier deformation characteristics are monitored based on SBAS-InSAR technology to invert the changes in the glacier mass balance. The following results were observed. (1) From 1990 to 2020, the glacier area in the Qomolangma Nature Reserve continuously retreated, with this trend becoming much more prevalent in the last 10 years. Moreover, the total glacier area shrank by 247.16 km² with a change rate of -18.92%. (2) The glaciers in the Qomolangma Nature Reserve were mostly situated at an altitude of 5400-6200 m and a slope of 10°-15°, and the highest ice loss occurred at an altitude of 5400-5600 m and a slope of 10°-15°. (3) In 2020, the average glacier deformation rate was between -129.069 mm·a^-1 and 140.252 mm·a^-1. The subsidence and surface deformation of glaciers are most severe at altitudes of 4200-4400 m and a slope of 40°-45°. (4) Rising temperatures and decreasing precipitation are believed to be the main causes of most glacier material losses in the Qomolangma Nature Reserve. Meanwhile, spatial climate and topographic differences may affect mass balance changes.

The western Tianshan Mountains in China experiences the highest precipitation in Central Asia. The unique valley topography of the mountains at its westward opening and westerly circulation lead to an exclusive cloud-precipitation physical process in Central Asia. The formation of snow and glaciers and runoff by precipitation considerably affects the social economy and ecological environment of Central Asia. The proposal and implementation of the national “Silk Road Economic Belt” construction have posed serious scientific and technological challenges to water resources, meteorological disaster prevention and mitigation, and ecological environment protection in Central Asia. The observation and research on cloud-precipitation physical processes in this region is the basis of science and technology; however, it is still in its nascent stage and cannot meet the requirements of the national plan and China’s meteorological development. Hence, herein, a scientific experimental base was built for the field observation of cloud and precipitation physics in the western Tianshan Mountains of China in 2019, and relevant research was conducted on the macro and microphysical characteristics of clouds, raindrop spectrum characteristics of stratiform and convective clouds, similarities and differences in the raindrop spectrum characteristics between the central and western Tianshan Mountains, and microphysical characteristics of cold front snowstorm. This paper summarizes the frontier achievements to promote the development of cloud and precipitation physics in Central Asia.

Brackish water is widely distributed in the arid and semiarid areas of northwest China. Understanding the relationship between surface water and groundwater transformation in brackish water areas is significant for promoting the rational development of brackish water resources. Taking the Kushui River Basin in Ningxia, China as the research object, this study analyzes the spatial and temporal distribution characteristics of hydrochemistry and hydrogen-oxygen stable isotopes of surface water and groundwater using hydrogen-oxygen stable isotope technology combined with field investigation, statistical analysis, and hydrochemical analysis. The spatial and temporal variations in the conversion relationship between surface water and groundwater in the basin were systematically revealed. The following results were observed: (1) SO₄·Cl-Na·Mg is the main hydrochemical type of surface water and upstream and midstream groundwater in the Kushui River Basin. The hydrochemical formation of surface water was evaporation concentration, and the hydrochemical type of downstream groundwater was transformed into a mixed type, which was controlled by rock weathering. (2) Atmospheric precipitation has a significant recharge effect on surface water and groundwater in the wet season and has a limited recharge effect in the dry season. Climate, topography, and hydrogeological conditions controlled the upper and middle reaches of the river basin, and the relationship between surface water and groundwater showed significant differences and complexity in different river reaches and periods. The irrigation of the Yellow River obviously affected the downstream. (3) In the dry season, the areas with close hydraulic connection between surface water and groundwater are distributed in the middle and lower reaches. The water cycle mode was referred to as groundwater recharge surface water, with recharge ratios of 51.8% and 57.8%, respectively. In the wet season, the hydraulic connection between the surface water of the mainstream and the groundwater in the upper and middle reaches is weak. The downstream surface water supplied the groundwater, with a recharge ratio of 38.8%. At the same time, the downstream canal water supplied the surface water to a certain extent, with a recharge ratio of 29.8%.

High-precision remote sensing monitoring of dynamic changes in wetlands is of great practical significance for wetland conservation and restoration. Taking the wetland of Bosten Lake in Xinjiang as the research object, we use the multiple endmember spectral mixture analysis (MESMA) method to extract the vegetation, water body, and bare land area from Landsat images, verify the accuracy by UAV images, and then combine with the trend analysis method to explore the spatial and temporal change characteristics and trends of Bosten Lake wetland from 2000 to 2022. The results show that: (1) The MESMA classification results verified by the resampling accuracy of UAV images showed that the goodness of fit (R²) of vegetation image element is 0.75 and the R² of water body image element R² is 0.84, indicating that the classification results were consistent with the actual feature conditions. (2) From 2000 to 2022, the vegetation area of Bosten Lake increased by 536.65 km², an increase of 183.14%; the water area decreased by 595.76 km², a decrease of 37.07%; the bare land area increased by 99.12 km², an increase of 25.42%. (3) The area of vegetation in the wetlands of Bosten Lake with an increasing trend accounts for 30.6% of the total area, which is located in the northwestern part of the Great Lake and the northern part of the Small Lake; on the contrary, the area of water with a decreasing trend accounts for 34.6% of the total area, which is located in the northern and eastern shores of the Great Lake and the wetlands of the Small Lake. To accurately grasp the spatial and temporal changes of Bosten Lake wetlands and their trends, it provides a reference basis for monitoring and protecting inland wetlands in the arid zone.

Determining the spatial distribution characteristics and changes in terrestrial water storage and understanding the reasons behind these terrestrial water storage changes (TWSC) are necessary for the sustainable and comprehensive management of water resources. Based on the data of the TWSC obtained by the gravity recovery and climate experiment satellite retrieval, this study first analyzes the trend and spatiotemporal variation characteristics of the TWSC in China using the Mann-Kendall trend test and empirical orthogonal function (EOF) analysis. Subsequently, 10 influencing factors were selected to comprehensively analyze their relationship with the TWSC by employing the following three methods: geographic detector, Pearson correlation analysis, and random forest. The 10 influencing factors were temperature, precipitation, standardized precipitation evapotranspiration index (SPEI), area proportion of impervious layer, area proportion of water body, normalized difference vegetation index (NDVI), elevation, slope, gross domestic product (GDP), and population. The results showed that areas with a significant increase in terrestrial water storage were mainly distributed in the areas near the Songhua River, Nenjiang River, and Songnen Plain, and the belt of the Qaidam Basin-Yangtze River-southeast coastal region, while areas with a significant decrease in terrestrial water storage were mainly distributed in southwest China and the belt of the Xinjiang-Loess Plateau-North China Plain. From high to low latitudes, the terrestrial water storage showed an alternating change pattern of high-low-high-low. Overall, meteorological factors had the strongest explanatory power for the TWSC, followed by socioeconomic factors and geomorphologic and geologic factors. Lag-correlation analyses showed that the monthly TWSC had a time lag response to precipitation, temperature, SPEI, and NDVI. The time lag of the monthly TWSC for each factor was different in the different regions. The response of TWSC to precipitation and SPEI mainly showed one-month lag, and the response of TWSC to temperature and NDVI mainly showed no lag (i.e. 0-month lag).

Rainstorms and the resulted floods represent the second most important type of natural disaster in the Shaanxi Province of China. To clearly describe the risk arising from extreme precipitation events, extreme precipitation amount, frequency, and intensity series were constructed using 1969—2020 flood season (May-October) daily precipitation data for Shaanxi Province. Six extreme-value probability distribution models were selected to fit the constructed series to obtain the optimal probability distribution model for flood season extreme precipitation and to evaluate the future trend of extreme precipitation events in Shaanxi Province. The comprehensive risk of extreme precipitation was evaluated based on spatial risk distributions of different scenarios in Shaanxi Province. The results showed that: (1) Through error analysis and comparison, the Wakeby probability distribution was found to be the optimal model for fitting the sequence of extreme precipitation indicators during the flood season in Shaanxi Province, accounting for the largest proportion of extreme values in the three constructed series. (2) Extreme precipitation values with different return periods were calculated and compared with existing maximum precipitation values. An increased probability of low-probability and high-risk extreme precipitation events was found for most areas of Shaanxi Province. (3) The comprehensive risk of extreme precipitation during the flood season was found to be generally high in the south and low in the north of Shaanxi Province. Risk areas differed between scenarios of 2-, 5-, 10-, 20-, 50-, and 100-year return periods. With increasing return periods, the low-risk area gradually reduced and the high-risk area gradually increased. In the 100-year return period scenario, the high-risk area increased from 0 to 22.0%. The study provides a reference for the investigation of extreme precipitation probability distributions in Shaanxi Province and provides a theoretical basis for extreme precipitation risk management and assessment during flood seasons.

ERA5 is a new generation reanalysis product launched by the European Center for Medium-Range Weather Forecasts that can provide a new source of precipitation data for areas with few ground observation stations. Based on the daily precipitation data of 45 ground stations in Inner Mongolia, China from 2008 to 2017, we evaluated the accuracy of ERA5 reanalysis precipitation data on multiple temporal and spatial scales using multiple evaluation indicators and applied a comprehensive weighting model to construct an extreme precipitation danger index by integrating 13 extreme precipitation indices. We then used principal component analysis, Sen’s slope method, and a Mann-Kendall trend test to analyze the temporal and spatial changes of extreme precipitation and extreme precipitation danger in the region from 1981 to 2021. The results show that: (1) ERA5 can reproduce the precipitation process better; the ERA5 precipitation reanalysis dataset performs better at a monthly time scale than at a daily time scale, and its accuracy is highest in summer and lowest in winter. ERA5 precipitation data are highly correlated with observed data at monthly and seasonal scales (correlation coefficient>0.85) and are strongly correlated with observed data at a daily scale (correlation coefficient=0.68). The detection accuracy of ERA5 data is better for the eastern stations than for the western stations. (2) Extreme precipitation indices showed a downward trend except for daily wet precipitation intensity, total heavy precipitation, and continuous dry days. The annual total wet day precipitation declined fastest, and the Sen’s slope value was -15.74 mm·(10a)^-1. (3) The extreme precipitation indices show clear regional spatial differentiation. Extreme precipitation shows an increase in intensity in western Inner Mongolia, a decrease in frequency, intensity, and duration in mid-Inner Mongolia, and an increase in intensity, frequency, and duration in eastern Inner Mongolia. (4) The extreme precipitation danger index has high central values and shows significant upward trends in Ordos City, Hulun Buir City, Bayannur City, Hinggan League, and other cities/leagues with relatively dense populations and rapid economic development and should therefore receive special attention. The results of this study can facilitate the discovery of better datasets for the analysis of climate factors in Inner Mongolia, and the study provides a theoretical basis for the formulation of climate change adaptation measures and future climate prediction.

Glacial runoff is a major component of runoff in the northwest arid zone of China. Understanding the impact of climate change on glacial runoff is crucial, but few studies have been conducted in this field of study in the Bortala River Basin, Xinjiang, China. In this paper, we present the glacier module that was added to the SWAT model and used to simulate monthly runoff in the headwater area of the upper Bortala River Basin. We successfully simulated monthly runoff at the Wenquan hydrological station during the period 1972—2018. Further, we investigated the impact of future climate change scenarios (RCP4.5 and RCP8.5 scenarios for 2020—2050, based on CMIP5 climate data) on glacier runoff. The model was able to accurately simulate changes in the source area’s runoff process. The results showed that: For the whole simulation period, the Nash-Sutcliffe efficiency was 0.82, the percent bias was -3.22%, the ratio of root mean square error to standard deviation of measured value was 0.42, and the coefficient of determination was 0.84, thus allowing the model to be rated as “excellent”. Increasing runoff trends were identified in the simulations of both future climate scenarios, with total runoff increases of 0.31×10⁸ m³·(10a)^-1 and 0.40×10⁸ m³·(10a)^-1 and increases in the percentage of glacial runoff of 4.84% and 9.38%, respectively, when compared with the historical period, in which the glacial runoff percentage was 27.61%. These increases in glacial runoff percentage are the main causes of the increases in runoff volume. Correlation analysis revealed that as the temperature increases, glacier ablation advances and accelerates, and glacier accumulation time decreases, leading to further future shrinking of glacier area. The study provides a basis for making changes to historical hydrological information, exploring future evolutionary trends, and mitigating potential climate change risks in the region.

Geological disasters frequently occur in Gansu Province, China, and the proportion of precipitation-type geological disasters is significant in this region. Based on the geological disaster data, encrypted precipitation observations and the CMA multi-source merged precipitation analysis system pertinent to April to October of each year from 2013 to 2021 in Gansu Province, the effective rainfall data were selected as the precipitation factor; and further the geological disaster probability fitting equations of effective rainfall for the two regions were established. A refined grid geological disaster meteorological risk early warning model is constructed using the disaster probability of the precipitation factor, potential risk of geological disaster, and vulnerability. Using real precipitation data and the fine gridded prediction forecasts (QPF) of the Lanzhou Central Meteorological Observatory, a mesh refinement forecast test of the risk model was established to test the geological disaster events that occurred in October 2021 in Gansu Province. The study results show the following: (1) Based on the disaster probability caused by effective rainfall, the critical effective rainfall thresholds of blue, yellow, orange, and red warning levels of geological disasters in the Loess Plateau and Longnan Mountains, respectively. Among them, the critical effective rainfall thresholds for blue and red warning levels in Longnan Mountains are 40.6 mm and 113.5 mm, respectively, which were significantly higher than the blue and red warning levels of 18.0 mm and 73.6 mm, respectively, in the Loess Plateau. (2) The risk discrimination indices of blue, yellow, orange, and red early warning levels of geological disaster meteorological risk in Gansu Province were determined. The index values ranged from 0.004 to 1.000, with values ranging from 0.336 to 1.000, indicating an early red warning level. (3) The refined grid geological disaster meteorological risk early warning model in Gansu Province can effectively provide a warning of geological disaster events, the proportion of each level of early warning is reasonable, and it can effectively reduce the high-level early warning rate and false alarm rate. Thus, the model shows a strong ability to provide geological disaster meteorological risk early warnings.

Drought is one of the most widespread and destructive natural hazards, causing severe impacts on agriculture, energy, society, and ecology. Global warming results in changes in regional precipitation and evapotranspiration patterns, leading to changes in drought characteristics. China is drought prone and is also seriously affected by climate change. Therefore, it is necessary to analyze the characteristics of future meteorological drought response to climate warming in China. In this study, using historical climate simulation data and future projection data from 18 climate models of the Coupled Model Intercomparison Project phase 6 (CMIP6), the 2 ℃ temperature rise scenario was determined by applying a time sampling approach, and the standardized precipitation evapotranspiration index (SPEI) based on the Penman-Monteith method was calculated at a 1-month time scale as the meteorological drought monitoring index. Based on SPEI, drought events were identified using the three-threshold run theory, and four drought-characteristic indicators (drought frequency, average drought duration, average drought intensity, and average drought peak) were extracted for China under the historical reference period and the 2 ℃ temperature rise scenario. Finally, changes in meteorological drought characteristics in China and its seven natural regions were analyzed under the 2 ℃ temperature rise scenario using the future drought-characteristic indicator values minus those of the historical drought-characteristic indicators. The results show clear spatial differentiation patterns in the four drought-characteristic indicators under the 2 ℃ temperature rise scenario. Drought frequency is high in the northwest desert region of China, and is high in the south and low in the north of the eastern monsoon region, while average drought duration, intensity, and peak values are high in the northwest and low in the southeast. From a national perspective, average future values of drought frequency, average drought duration, average drought intensity, and average drought peak are 1.72 times·a^-1, 2.46 months, 1.37, and 1.70 respectively under the 2 ℃ temperature rise scenario, representing increases of 0.17 times·a^-1, 0.27 months, 0.14, and 0.25, respectively, compared with the historical reference period. From a regional perspective, the average values of drought frequency, average drought intensity, and average drought peak increase in all regions, while the average value of average drought duration shows a decrease only in the northeast humid/semi-humid temperate region. The region with the largest increases in values of the four drought-characteristic indicators is the northwest desert region. In summary, based on the results of the multi-model ensemble mean from the 18 CMIP6 models, we predict that more frequent and severe droughts will occur in China, and especially in northwest China, under the 2 ℃ temperature rise scenario. This prediction can serve as a warning in terms of future drought management, and the study can provide a basis for drought prevention and response decision-making in the global warming context.

Based on the normalized difference vegetation index (NDVI) and enhanced vegetation index obtained from remote sensing and on temperature and precipitation data from 60 meteorological stations in Mongolia from 2001 to 2020, the logistic curve method and dynamic threshold method of the cumulative vegetation index were used to extract the vegetation green-up period in Mongolia. Partial correlation analysis was used to explore the relationship between the vegetation green-up period and the asymmetric changes in diurnal temperature in winter and spring. The results were as follows: (1) In the past 20 years, the warming rates for highest winter and spring temperatures were 0.07 ℃·a⁻¹ and 0.15 ℃·a⁻¹ (P<0.05, R²=0.33) respectively, while the change rates of the lowest winter and spring temperatures were −0.01 ℃·a⁻¹ and 0.04 ℃·a⁻¹ respectively. The change rate of the winter and spring diurnal temperature ranges were 0.08 ℃·a⁻¹ and 0.11 ℃·a⁻¹ (P<0.05, R²=0.52) respectively, showing clear seasonal differences. (2) The seasonal response of the start of the growing season to winter and spring climate warming is asymmetric, with the highest temperature and diurnal temperature range having a greater impact in winter, while the lowest temperature has a greater impact in spring; both show negative correlations. (3) The asymmetric impact of climate warming on NDVI in Mongolia is mainly manifested in spring. The highest spring temperature and spring diurnal temperature range have a mainly negative correlation with NDVI, while the lowest spring temperature has a mainly positive correlation with NDVI. This study provides an important reference in the study of the seasonal effects of climate warming on vegetation phenology and late-stage growth.