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).

Terrestrial evapotranspiration (ET) is an important process of land-atmosphere exchange and an important link in the global water migration and energy transfer system. Identifying the temporal and spatial dynamic characteristics of ET is of great significance in the study of regional water cycle and energy conversion. In this study, we compared the appropriateness of the three different ET products (GLEAM, MOD16, and PML-V2) in China using the flux data of nine tower stations in the country. We used the dataset of ET products between 2003 and 2020 to analyze the temporal and spatial dynamic characteristics of evapotranspiration in China. The results showed the following: (1) The ET products of PML-V2 is the most suitable for China. (2) On the time scale, ET gradually increased during the research period. On the spatial scale, ET exhibited an increasing tendency during 2003—2020 from northwest to southeast of China. (3) According to the Hurst index, the future ET of the whole nation is expected to show the opposite trend compared to the past. This means that ET increased in the past but is expected to decrease in the future. This study analyzed the spatiotemporal dynamic characteristics of ET in China, which could provide a reference for regional water resources utilization and optimal allocation.

Wavelet analysis and other methods were used to analyze the spatiotemporal distribution characteristics of rainstorm in Shanxi Province of China based on the daily precipitation data of 27 meteorological stations in Shanxi Province from 1957 to 2019. Based on the theory of natural disaster, the decision analysis method (AHP) is used to conduct the risk assessment of rainstorm disasters. The following results were obtained: (1) Regarding the timescale, the time of rainstorm has presented periodicity and seasonality. The interannual variation of rainstorm has four-timescale oscillations of 4 years, 9 years, 14-15 years, and 27-28 years. The oscillation period shortened, and the frequency shows an increasing trend. Rainstorm season uneven distribution mostly concentrated in the summer and the probability of the formation of rainstorm disasters was great. The number of cumulative rainstorm days between June and August each year accounted for 85.23% of the total, with July accounting for the largest proportion of 45.18%. (2) Regarding the spatial scale, the rainstorm mostly occurs in the central and southern parts and the mountainous areas with higher altitudes, presenting a decreasing trend from southeast to northwest and obvious regional differences. The heavy rainfall and the amount of rainstorm in the south area show a high probability than the north area with Hengshan as the boundary, among which the annual average rainstorm is more than 65 mm in Yuanqu, Wutaishan, and Yangcheng meteorological stations, and the number of cumulative rainstorm days is over 60 days. (3) The result of the assessment of rainstorm disaster risk shows that the comprehensive risk classification of rainstorm disaster in Shanxi Province shows a decreasing trend from south to north. The northeast of the Yuncheng Basin belongs to the high-risk area, while the northeast and northwest of Shanxi Province belong to the low-risk area. The rest belong to the medium-risk and the sub-high-risk areas.

The variation in fractional vegetation cover (FVC) is not only closely related to climatic factors but is influenced by human activities. Only a few studies have been conducted on the spatiotemporal characteristics of FVC in China at the provincial scale and quantitative analysis of the impact of climate factors combined with human activities on FVC. Based on the Google Earth Engine platform and Landsat data for 2000—2020, as well as contemporaneous climate and nighttime lighting data, the study is analyzed using the dimidiate pixel method, linear regression analysis, coefficient of variation, partial correlation analysis, and contribution model. The results showed the following: (1) The rate of increasing of FVC in China is 0.32%·a^-1 from 2000 to 2020. The vegetation cover area is dominated by the high cover level, accounting for 38% of the study area, with an overall decreasing trend from southeast to northwest. (2) FVC of the Loess Plateau, Yunnan Province, Tibet Autonomous Region, and western Xinjiang Uygur Autonomous Region showed an increasing trend. Interannual fluctuations in the FVC are more stable in the south than in the north and in the east than in the west. Heilongjiang Province has the highest vegetation cover at 91.7%, while Xinjiang Uygur Autonomous Region has the lowest at 14.4. The rate of variation of FVC in the Ningxia Hui Autonomous Region is 0.98%·a^-1, with significant improvement in FVC. (3) A significant spatial variability was observed in the effects of climatic factors and urbanization on FVC. Temperature and precipitation have negative and positive correlations on FVC in northern China, respectively, and urbanization mainly affects the more economically developed provinces. Temperature is the main contribution factor in the Ningxia Hui Autonomous Region, with an average contribution of 84.3%. Precipitation is the main contribution factor in Taiwan Province, with an average contribution of 71.7%. Moreover, urbanization is the main contribution factor in Shanghai, with an average contribution of 26.5%.

The land surface temperature considerably influences land surface processes. Based on MOD11A2 land surface temperature data, the annual, seasonal, monthly, and diurnal land surface temperature changes in the Qinghai Lake Basin of China during 2002—2021 were analyzed using the digital elevation model, land use type, meteorology and normalized difference vegetation index, ArcGIS spatial analysis, and mathematical statistics. The results revealed that: (1) The average annual land surface temperature of the Qinghai Lake Basin increased over the years, and the average land surface temperature was 2.20 ℃. The spatial distribution exhibited a regular characteristic of gradually decreasing from the southeast to the northwest of the basin. The north and east shores of Qinghai Lake exhibited the most significant increasing trend of the land surface temperature, and the area with increasing trend accounted for the main part of the basin. (2) The land surface temperature values in various seasons were in the sequence summer>spring>autumn>winter. With the exception of spring, in which a decreasing trend was observed over the year, an increasing trend was observed annually for summer, autumn, and winter. (3) The land surface temperature between months exhibited a regular increase and subsequent decrease, with July as the “symmetry axis” showing a significantly similar trend. (4) The land surface temperatures of various land use types from high to low followed the order arable land>forest land>shrubs>grassland>wasteland>glacier. (5) The annual average land surface temperature was significantly negatively correlated with elevation (P<0.05), and the annual average land surface temperature decreased by approximately 0.8 ℃ for every 100 m increase in the elevation. (6) Single-factor detection results revealed differences in the explanatory power of environmental factors on the land surface temperature. Among these factors, altitude and the mean annual temperature exhibited high explanatory power on the land surface temperature, whereas the land use type exhibited the lowest explanatory power. Among the interactions of all factors, the annual mean temperature and altitude interacted with the highest explanatory power of q value (0.90). This result indicated that the coupling of the annual mean temperature and altitude was closely related to the land surface temperature of Qinghai Lake Basin.

In this study, based on the RClimDex model, we considered daily precipitation data from 126 meteorological stations in Central Asia from 1960 to 2020 to calculate eight extreme precipitation indices in Central Asia. We performed linear regression, Mann-Kendall, correlation, wavelet, and rescaled range analyses to investigate the characteristics of extreme precipitation events in Central Asia. The results revealed that: (1) The frequency and intensity of extreme precipitation events in Central Asia have increased considerably in the last 60 years. The climate trend of the simple precipitation intensity index (SDII) increased at an average of 0.02 mm·d⁻¹·(10a)⁻¹. The change tendency rates of extreme precipitation index heavy precipitation (R95p), maximum daily precipitation (Rx1day), maximum precipitation for five consecutive days (Rx5day), total annual precipitation (PRCPTOT)] were 1.93 mm·(10a)⁻¹, 0.24 mm·(10a)⁻¹, 0.66 mm·(10a)⁻¹, and 0.73 mm·(10a)⁻¹, respectively. The extreme precipitation days index [middle precipitation days (R10), continuous dry days (CDD), continuous wet days (CWD)] also exhibited a slight increase, with the exception of the number of CDD, which exhibited a decreasing trend. The change tendency rates were 0.02 d·(10a)⁻¹, −0.65 d·(10a)⁻¹, and 0.08 d·(10a)⁻¹, respectively. Extreme precipitation exhibit obvious spatial variability and high altitude dependence and occur frequently near highlands and mountains. The extreme precipitation cycle in Central Asia is characterized by a multipeaked spectrum with short-period oscillations of approximately 5 years, medium-period oscillations of 6-9 years, and long-period oscillations of 10-15 years. (2) The extreme precipitation index exhibits an excellent correlation with the total annual precipitation, and CWD contributes most to the total annual precipitation. The Pacific interdecadal oscillation (PDO) and the North Atlantic interdecadal oscillation (AMO) exhibit significant positive correlation with extreme precipitation events. Both PDO and AMO are the primary climate system internal variability modes that affect abrupt changes in extreme precipitation in Central Asia. The results of the R/S analysis indicates that in the future, the indices of PRCPTOT R95p, Rx1day, Rx5day, SDII, and CWD are likely to continue to increase in the future with high persistence, whereas CDD is likely to continue to exhibit a decreasing trend with average persistence. This study can provide a scientific basis for the extreme climate prediction, natural environment protection, disaster prevention, and mitigation in Central Asia.

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.

On April 2, 2021, a catastrophic snowstorm, which exceeded the historical extreme value, occurred, causing large financial losses in Baicheng County, the northern edge of the Tarim Basin, Xinjiang, China. The hourly European Center for Medium-Range Weather Forecasts fifth-generation (ERA5) high-resolution reanalysis data (0.25º×0.25º), meteorological observation data, and FY-2G satellite data were used to fully analyze the atmospheric circulation anomalies, multi-scale atmospheric circulation characteristics, and physical mechanisms. The following results were obtained: (1) The atmospheric circulation of the snowstorm was typical of a South Xinjiang snowstorm circulation: upper-level South Asian high, subtropical trough, and subtropical westerly jet, mid-level Central Asian vortex, and low-level easterly jet and converging lines combined with the cold high pressure and converging lines at the surface. (2) Extreme snowstorm was caused by the interplay of different-scale atmospheric circulation anomalies. The upper-level anomalies of Iran subtropical high and anomalous easterly airflow at low latitudes led to the anomalous combination of the Central Asian vortex and the plateau vortex at 500 hPa and also generated anomalous easterly airflow at 700 hPa, guiding warm and humid air from the South China Sea and the Bay of Bengal along the Hexi Corridor to the central Tarim Basin, causing water vapor convergence and enhancing vertical upward movement, with the triggering of the surface convergence line, resulting in an extreme snowstorm. A stable maintenance of surface high-pressure systems and cold front produce continuous cooling in the Tarim Basin. Moreover, Baicheng County is located in a shallow mountainous area with an altitude above 1000 m, and the combination produced extreme snowstorm in April. (3) For Baicheng County, the key roles are the upward motion in the middle layer of the troposphere and the vertical wind shear at 300-500 hPa. The vertical profile shows that the level of upward motion of the snowstorm is located at 500-700 hPa, showing mesoscale symmetric instability characteristics. Using the frontogenetic function equation and the moist potential vorticity equation, we found that the intensity of the vertical potential temperature gradient and westerly wind anomalies lead to the development of baroclinic instability, causing surface frontogenesis, generating 300 hPa and surface moist potential vorticity anomalies, affecting the development of snowstorm through upward motion changes. (4) The consistency of the moving and propagation directions determines the evolutionary characteristics of mesoscale clouds production and extinction. In turn, the continuous development of mesoscale clouds moving northeastward through Baicheng County increases the duration and intensity of the snowstorm. The above findings can deepen the knowledge of extreme snowstorms in the Tarim Basin and provide scientific support for accurate forecasting and precise services.

Today, cultural tourism space is one of the significant directions of research on culture and tourism integration. Taking 2346 POI cultural tourism space spots of Xinjiang, China, as the research objects, the distribution pattern characteristics of the cultural tourism space of Xinjiang are presented with graphic visualization through quantitative statistics and analysis, with the help of the topography of geographic information system space analysis software and geomorphic elevation analysis, kernel density analysis, Tyson polygon analysis, and standard deviation elliptic analysis. The research shows the following results: (1) The distribution of the cultural tourism space of Xinjiang adapts with the characteristics of natural and geographic environments, mainly distributed at both sides of the rivers, river valleys, mountainous vertical regions, and oasis buffer zone on the edge of the desert. Regions with high-value kernel density exhibit distribution characteristics such as large dispersion and small aggregation, ribbon pattern, block, and scattered pattern. (2) The distribution of the cultural tourism space of Xinjiang has the characteristics of there are more in the north region and less in the south region, the east region and west region are connected, and the radiation influence range of natural tourism space is wider than that of the humanity tourism space. (3) The cultural tourism space of Xinjiang is inherited in a continuous strain. The connection with humanity tourism space and natural tourism space gradually changes into resources, products, and images of cultural tourism space. The relationship of each other is gradually intensified, with the characteristics of obvious inclusiveness, integration, and extensity. Based on the above analysis result, the optimized suggestions are proposed on development research on the whole region, hierarchy, and diversity of the cultural tourism space of Xinjiang.

Clarifying the spatial distribution characteristics of red tourism resources and mastering their spatial accessibility are the prerequisite basis for tourism planning to formulate the red tourism routes. The red tourism resources in Inner Mongolia of China are rich and varied, having a great ethnic regional characteristics and playing an irreplaceable role in promoting ethnic identity and forging the Chinese national community. However, the limited cognition of the spatial distribution and accessibility of red tourism resources in Inner Mongolia has seriously hindered the high-quality development of red tourism. In this study, the kernel density and geographical concentration index were used to reveal the spatial distribution characteristics of red tourism resources in Inner Mongolia. The spatial accessibility measurement model of red scenic spots was constructed based on real-time road traffic conditions obtained from the path planning function of the Amap. Geographical detectors reveal the differences in accessibility for the red tourism spots. The following results were obtained: (1) The spatial distribution of red tourism spots in Inner Mongolia has obvious regional differences, with characteristics of “large dispersion and small agglomeration”. The largest kernel density values are observed in Hohhot City and Xing’an League, especially in Hohhot City. Obvious differences are found in the types of red tourism spots in each city. Hohhot City and Baotou City have relatively complete types, but the spatial distribution equilibrium is poor. (2) The cost of travel time between red tourism spots in Inner Mongolia is high, with an average travel time of 256.229 min. The accessibility of red tourism spots in Inner Mongolia is poor, and the internal difference is significant. The range of accessibility coefficient is 0.752-1.816. The spatial distribution of accessibility of red tourism spots shows the “center-periphery” circle gradually decreasing structure. The accessibility of red scenic spots in the Hulun Buir City and Alagxa League is low. (3) The spot regional location and regional spot density had the strongest explanatory power for the difference in accessibility, and the interaction of these two factors had the greatest explanatory power. The interaction of any two factors on accessibility differentiation is a two-factor enhancement or a nonlinear enhancement relationship, and no independent or weakening relationship is observed.

Understanding glacier changes on the north slope of the Tianshan Mountains on the basin scale is critical for the rational development and use of water resources in downstream oases. The recent glacier boundaries on the north slope of the Tianshan Mountains were obtained based on multisource remote sensing images. Combined with the glacier inventory released earlier and ASTER DEM, changes in the glacier area and mass balance in this region were analyzed. The results revealed that: (1) A total of 10061 glaciers were distributed on the north slope of the Tianshan Mountains around 2015, with a total area of 4855.85±245.86 km². The glacier area on the north slope of the Tianshan Mountains in China decreased at a rate of 0.52%·a⁻¹±0.06%·a⁻¹ from 1960s to 2015. Furthermore, an accelerated decreasing trend was observed (0.96%·a⁻¹±0.88%·a⁻¹). The glacier area in the foreign part of the north slope of Tianshan Mountains decreased at a rate of 0.56%·a⁻¹±0.31%·a⁻¹ from 1999 to 2015. (2) The change rate of glacier surface elevation on the north slope of Tianshan Mountains from 2000 to 2020 was −0.57±0.01 m·a⁻¹, and the glacier mass balance was −0.39±0.04 m w.e.·a⁻¹. (3) An obvious spatial difference exists in the changes of glacier area and mass balance in the eastern and western parts of the north slope of Tianshan Mountains, and high decreasing rates of glacier area and mass balance were observed in the eastern part.

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.

Two phenological identification methods, namely, the logistic curve curvature extreme value method and the dynamic threshold method of cumulative NDVI, were used to extract the data based on the normalized difference vegetation index (NDVI) and enhanced vegetation index remote sensing vegetation indices from 2001 to 2020, as well as the highest temperature, the lowest temperature, and precipitation data of 94 meteorological stations in the Mongolian Plateau. The temporal and spatial changes of the Mongolian Plateau’s asymmetric circadian warming and its impact on the start of growing season were analyzed. The research shows the following: (1) The average maximum temperature [0.7 ℃·(10a)^-1] and the minimum temperature [0.3 ℃·(10a)^-1] in the preseason 6 months (November of the previous year to April of the current year) in the Mongolian Plateau from 2001 to 2020 both showed an upward trend, and the warming rate of the highest temperature was 2.3 times that of the lowest temperature. (2) The asymmetric warming of the preseason day and night has an early effect on the start of growing season; however, compared with the highest temperature, the lowest temperature has a greater impact on the start of growing season, and the impact range is wider. (3) The preseason asymmetrical warming of day and night has different effects on the start of growing season of different vegetation types. The effect of daytime warming on the start of the growing season of shrubs, farmland, and sparse vegetation is more obvious, and the effect of nighttime warming on the start of the growing season of forest and grassland is more obvious, especially in forest areas (25.5%). Studying the effects of daytime and nighttime asymmetric warming on vegetation phenology on the Mongolian Plateau is of great significance to reveal the mechanism of temperature effects on vegetation phenology in spring.

It is difficult to evaluate the water resource consumption effectiveness at a regional scale in the arid northwest due to the lack of monitoring information and other factors. This paper uses the MODIS remote sensing data to drive a hybrid dual-source trapezoidal evapotranspiration model (HTEM), to continuously simulate the spatiotemporal processes of land surface evapotranspiration in the Yanqi Basin of Xinjiang, China, and to evaluate the effectiveness of water consumption in irrigation areas. The following results were obtained: (1) The multiyear average evapotranspiration in the irrigation area of Yanqi Basin from 2013 to 2020 is 624.4 mm, of which the evapotranspiration from April to October during the crop fertility period accounts for 89.6% of the year. (2) The multiyear average of vegetation evapotranspiration and soil evaporation in the irrigation area is 508.9 mm and 115.5 mm, respectively, accounting for 81.5% and 18.5% of the total evapotranspiration. (3) The multiyear average evapotranspiration water consumption in the irrigation area was 13.82×10⁸ m³, of which high-, medium-, and low-efficiency water consumption accounted for 81.5%, 5.6% and 12.9% of the total water consumption, respectively, and the effectiveness of water consumption was closely related to the vegetation cover. This study reveals the effectiveness of evapotranspiration water consumption in irrigation areas on a regional scale with a spatiotemporal continuum, which can provide a reliable theoretical basis for water resource control in arid zones.

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.

Geohazards such as landslides, rock fall, debris flow, and ground collapse occur frequently in the Ili Valley, Xinjiang, China, and there are various influencing factors for the formation of these geohazards. Based on the database of geohazards in the Ili Valley, this paper uses statistical analysis methods such as the frequency ratio and receiver operating characteristic curve to study the distribution characteristics and main controlling factors of geohazards in the Ili Valley. The results show the following: (1) The overall development degree of geohazards in the Ili Valley is greater in the east than in the west, and they are distributed in the middle and low mountains with 500-3500-m elevation. In terms of time of occurrence, they are mainly clustered in the spring and summer snowmelt and rainfall seasons. (2) The development of geohazards is affected by stratigraphic lithology, geological structure, topography and geomorphology, precipitation, and other factors. However, the main controlling factors for different types of geohazards are different. Landslides are most obviously affected by stratigraphic lithology, elevation, slope, and annual precipitation, while rock falls are mainly controlled by slope, elevation, and distance from faults. Ground collapses are obviously affected by elevation, distance from fault, and precipitation, and are basically induced by underground mining activities. The distance and elevation from faults are the main controlling factors for the development of debris flows.

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.

In the context of rural tourism in Turpan City of Xinjiang, China, this paper explores the influences of tourism involvement, restorative environment perception, and tourist satisfaction on tourists’ intention to revisit, together with the related moderating effect of consumption expectation. The study adopts a structural equation model based on attention recovery theory, in which tourist satisfaction and restorative environment perception as the mediating variables and consumption expectation is the moderating variable. Through data collected through a questionnaire survey, 374 valid samples were obtained. The study found that (1) Tourism involvement had a significant positive impact on restorative environment perception, tourist satisfaction and revisit intention, among which the effect on restorative environment perception is the largest and the effect on tourist satisfaction is the least. (2) Restorative environment perception and tourist satisfaction had multiple chain mediating effects in the structure of “tourism involvement-revisit intention”. (3) The influence of tourism involvement and tourists’ satisfaction on revisiting intention was positively regulated by consumption expectation. The traditional mediation model understates the role of restorative environment perception and many previous studies on this factor have considered it an independent variable. Few studies, in contrast, have considered consumption expectation. To explore the impacts on tourists’ willingness to revisit, the present study innovatively applies restorative environment perception as a mediating variable in the chain mediation effect and applies consumption expectation as a moderating variable, thus providing broader guidance for the governance of scenic locations. The study’s results provide a theoretical basis and a practical reference for the management and development of rural tourism in Turpan City.

Because the Yellow River Basin of China is a vast area with sparse meteorological stations, limited meteorological data are available. Satellite precipitation data are an alternative for precipitation observations. In this study, the precipitation data of the Yellow River Basin for 2002, 2012, and 2020 were considered representative of dry, standard, and wet years to downscale global precipitation measurement (GPM) precipitation data. The normalized difference vegetation index, digital elevation model, slope, land surface temperature, and wind speed that reflect the spatial distribution characteristics of precipitation and the characteristics of spatial nonstationarity were investigated and used in two downscaling methods, namely the geographically weighted regression model (GWR) and mixed geographically weighted regression model (MGWR) to obtain the downscaling precipitation data of 1-km spatial resolution in the Yellow River Basin. The downscaling results were verified by the ground meteorological station data. The results revealed that: (1) GPM annual precipitation data were highly correlated with ground meteorological station observation data in the Yellow River Basin in 2002, 2012, and 2020. (2) Downscaling with the MGWR model considerably improved the spatial resolution. In terms of the spatial details of precipitation, the downscaling results of the MGWR model were superior to those of the GWR model. (3) In the three typical climate years, the accuracy of MGWR downscaling data in the precipitation standard year was slightly higher than that of GWR downscaling data. The results of this study can provide a reference for precipitation downscaling research in related regions and promote regional climate and hydrological research.

Based on measured flood data for 1956—2021 from the Changmabao hydrological station at the outlet of the Changma River in the upper reaches of the Shule River, northwest China, and on temperature and precipitation data from Yu’erhong rainfall station and Tuole meteorological station in the vicinity of the basin, the variation characteristics of annual maximum peak discharge (AMPD), peaks over threshold (POT3M), and floods based on the generalized extreme value (GEV) distribution at different levels were sampled and analyzed using Sen’s slope estimator and the Mann-Kendall test. The results showed the following: (1) Both the magnitude and frequency of floods at the Changmabao hydrological station during the studied period significantly increased, with AMPD and POT3M magnitudes showing highly significant increases (P<0.01) and POT3M frequency showing significant increases (P<0.05). Based on the GEV distribution, floods were mainly small floods and the frequency of total floods was highly significant (P<0.01). (2) Temperature and precipitation showed a fluctuating increasing trend after 1987, and heavy precipitation and increased meltwater from glaciers, alpine snow, and permafrost due to warming were the main causes of the observed significant increases in flood magnitude and frequency in the three sampled series.