Search Results (18)

Lakes on the Inner Mongolia–Xinjiang Plateau (IMXP) are increasingly vulnerable to eutrophication under climate change and human pressure, yet long-term monitoring remains limited by sparse field sampling. Here, we reconstruct multi-decadal trophic dynamics across the IMXP using Landsat time series and temporally transferable machine-learning models and further quantify the underlying natural and anthropogenic drivers. We compiled monthly in situ water-quality observations (chlorophyll-a, Chl-a; total phosphorus, TP; total nitrogen, TN; Secchi depth, SD; and permanganate index, COD_Mn;) and calculated the trophic level index (TLI). After rigorous quality control and monthly aggregation, we compiled a dataset of 1345 matched lake–month samples spanning 2000–2024, and divided it into a training set (n = 1076; ≤2019) and an independent test set (n = 269; 2020–2024) to evaluate temporal transferability. We utilized Google Earth Engine to generate monthly surface reflectance composites from Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2. Four supervised regression algorithms—ridge regression (RR), support vector regression (SVR), random forest (RF), and eXtreme Gradient Boosting (XGBoost)—were trained to estimate TLI. On the independent test period, XGBoost performed best (R² = 0.780, RMSE = 3.290, MAE = 1.779), followed by RF (R² = 0.770, RMSE = 3.364), SVR (R² = 0.700, RMSE = 3.842), and RR (R² = 0.630, RMSE = 4.267); we then used XGBoost to reconstruct monthly and yearly TLI for 610 perennial grassland lakes from 2000 to 2024. From 2000 to 2024, the annual mean TLI (48–49) across the IMXP exhibited a statistically significant upward trend (slope = 0.0158 TLI yr⁻¹; 95% confidence interval (CI) = 0.0050–0.0267; p = 0.006). Meanwhile, spatial heterogeneity was distinct (TLI: 41.51–59.70). High values concentrated in endorheic and desert–oasis basins (e.g., Eastern Inner Mongolia Plateau, >51), whereas lower values characterized high-altitude regions (e.g., Yarkant River, <45). Overall, trends ranged from −0.49 to 0.51 yr⁻¹, increasing in 54% of lakes (15.6% significantly) and decreasing in 46% (15.4% significantly). Attribution analyses identified NDVI (33.92%) and temperature (21.67%) as dominant drivers (55.59% combined), followed by precipitation (13.99%) and human proxies (30.42% combined: population 10.66%, grazing 10.31%, built-up 9.45%). Across 53 sub-basins, NDVI was the primary driver in 28, followed by temperature (11), population (7), precipitation (3), grazing (3), and built-up land (1); notably, the top two drivers explained 56.6–87.1% of variations. TWFE estimates revealed bidirectional NDVI effects (significant in 31/53): positive associations in 22 basins were linked to nutrient retention, contrasting with negative effects in nine basins associated with agricultural return flows. Temperature effects were significant in 15 basins and predominantly negative (14/15), except for the Qiangtang Plateau. Overall, eutrophication risk across the IMXP lake region reflects the combined influences of climatic conditions, vegetation conditions, and human activities, with their relative contributions varying among basins. Full article

Against global ecological and environmental challenges, water ecological security in arid desert regions is of great significance to regional ecological balance and socio-economic development. This study focuses on the Kashgar Prefecture, specifically the Yarkant River Basin and Kashigaer River Basin, in Xinjiang, China. Employing the perspective of the “Ecology-production-life Space” and the Drive-Pressure-Status-Influence-Respond (DPSIR) model, this study utilizes the objective entropy value method to construct a comprehensive evaluation index system to assess the status of water ecological security and its spatial security in the three regions from 2012 to 2019. The results show that the two major river basins and Kashgar Prefecture present an underbalanced state of production-led ecology, and life space lagging in the Ecology-production-life Space, with different trends and substantial fluctuations in the comprehensive indices of ecology, production, and life of the three. From the DPSIR model, the changes in the indices of the dimensions of the three are complicated, and the response indices are generally low. The composite indices of the two basins and the Kashgar Prefecture are in fair condition, which is affected by the synergistic influence of human activities and natural factors. The production pressure threatens the safety of water ecology, while the ecological protection has a certain degree of effectiveness, but still needs to be improved overall. The rate of improvement is slow due to the limitations of production-led and ecological lag in the future, although there is an upward trend. This study establishes a coupled, complementary assessment framework integrating spatial patterns and causal chains. It validates an evaluation model applicable to discontinuous multi-basin networks in an arid desert region, revealing the evolution patterns and core contradictions of water ecological security in arid multi-basin areas. The results of this study can provide a scientific basis and data support for the study of water ecological security in arid desert multi-basin watersheds. Full article

Land use/cover change (LUCC) is a dominant driver of ecosystem service dynamics in arid inland basins. Focusing on the Yarkant River Basin (YRB), Xinjiang, we coupled the PLUS land-use simulation with the InVEST Habitat Quality Model to project 2040 land-use patterns under four policy scenarios—Natural Development (ND), Arable Protection (AP), Ecological Protection (EP), and Economic Development (ED)—and to quantify their impact on habitat quality. Model validation against the 2020 map indicated strong agreement (Kappa = 0.792; FOM = 0.342), supporting scenario inference. From 1990 to 2023, arable land expanded by 58.17% and construction land by 121.64%, while forest land declined by 37.45%; these shifts corresponded to a basin-wide decline and increasing spatial heterogeneity of habitat quality. Scenario comparisons showed the EP pathway performed best, with 32.11% of the basin classified as very high-quality habitat and only 8.36% as very low-quality. In contrast, under ED, the combined share of very low + low quality reached 11.17%, alongside greater fragmentation. Spatially, high-quality habitat concentrates in forest and grassland zones of the middle–upper basin, whereas low-quality areas cluster along the oasis–desert transition and urban peripheries. Expansion of arable and construction land emerges as the primary driver of degradation. These results underscore the need to prioritize ecological-protection strategies especially improving habitat quality in oasis regions and strengthening landscape connectivity to support spatial planning and ecological security in dryland inland river basins. Full article

The downstream irrigation district of the Yarkant River basin has experienced increasing soil salinization driven by shallow groundwater levels, constraining the sustainable development of regional agriculture. However, the dynamic relationship between soil salinity and groundwater depth in this region remains unclear, limiting the effectiveness of saline–alkali land remediation strategies based on groundwater level regulation. In this study, field data were collected in 2025 on total soil salinity, concentrations of eight major ions, groundwater depth, and groundwater salinity in the irrigation district. The spatiotemporal distribution patterns of soil salinity, groundwater depth, and groundwater salinity were analyzed, along with their interrelationships. The soils in the irrigation district are predominantly mildly to moderately saline. Overall, soil salinity exhibits clear seasonal patterns, characterized by accumulation due to evaporation in spring and autumn and dilution through irrigation in summer. The dominant anions in the soil were SO₄²⁻ and Cl⁻, while Ca²⁺ and Na⁺ were the dominant cations, indicating a chloride–sulfate salinity type. Soil salinity shows a significant positive correlation with groundwater mineralization. A clear Boltzmann function relationship was identified between soil salinity and groundwater depth, revealing a critical groundwater depth of 2.10–2.18 m for salt accumulation in the irrigation district. The critical groundwater depths corresponding to soil salinity and major salt ions, from lowest to highest, are Cl⁻ < Na⁺ < total salts < SO₄²⁻ < Ca²⁺. Random forest regression analysis identified the main factors influencing soil salinity and their relative importance, ranked from highest to lowest as follows: groundwater depth > Na⁺ > Cl⁻ > groundwater salinity > Ca²⁺ > SO₄²⁻ > Mg²⁺ > HCO₃⁻ > K⁺ > CO₃²⁻. Maintaining groundwater depth below the critical threshold and focusing on groundwater ions that strongly influence soil salinity can effectively alleviate soil salinization in the lower Yarkant River irrigation district caused by shallow, highly mineralized groundwater. Full article

The sustainable utilization of cultivated land is a crucial prerequisite for ensuring food security and achieving sustainable socioeconomic development. This study employed a dataset to evaluate sustainable land use and utilized a combination of multi-factor comprehensive evaluation models, structural equation modeling, geographically weighted regression, and Pearson correlation analysis to systematically investigate the overall level, spatial differentiation characteristics, and driving mechanisms of sustainable cultivated land utilization in the Tarim River Basin. Additionally, we compared and tested three spatial interpolation methods using high-resolution data to address the modifiable areal unit problem (MAUP) and enhance the quality of spatial predictions for cultivated land utilization, ultimately identifying inverse distance weighting (IDW) as the optimal method. The results indicate the following: (1) The level of sustainable cultivated land utilization is moderately high, with an average index of 0.581, exhibiting a “U-shaped” trend from the upper to lower reaches of the Tarim River Basin. The highest levels are found in the Kashgar River–Yarkant River Basin, followed by the Hotan River Basin and the Kaidu–Peacock River Basin, while the mainstream area has the lowest levels. (2) The relationships among various cultivated land environmental systems and sustainability demonstrate distinct response characteristics and spatial differentiation patterns. Cultivated land use and management exert the most significant influence on sustainability, followed by soil quality and water resource systems, with climatic factors having the least impact. The effects of each system reveal inverted “U”, inverted “N”, “U”, and “W” patterns from the lower reaches to the upper reaches, respectively. (3) As the complexity of interactions and integrative mechanisms within the regional cultivated land system increases, the sensitivity and vulnerability of the system also rise, resulting in lower levels of sustainable utilization. (4) Based on the current challenges facing the cultivated land environmental system and the primary mechanisms influencing its sustainability, we propose regulatory measures focused on “suitable consolidation”, “suitable resting”, and “suitable planting”. These findings provide valuable insights for formulating differentiated land protection strategies, policies, and spatial planning initiatives. Full article

In hydrological modeling, the accuracy of precipitation data and the reflection of the model’s physical mechanisms are crucial for accurately describing hydrological processes. Identifying reliable data sources and exploring reasonable hydrological evolution mechanisms for hydrology and water resources research in high-altitude mountainous regions with sparse stations and limited data constitute a significant challenge and focus in the field of hydrology. This study focuses on the Yarkant River Basin in Xinjiang, which originates from glaciers and contains a substantial amount of meltwater runoff. A dynamic glacier melt module considering the synergistic effects of multiple meteorological factors was developed and integrated into the original Soil and Water Assessment Tool (SWAT) model. Four precipitation datasets (ERA5-land, MSWEP, CMA V2.0, and CHM-PRE) were selected to train the model, including remote sensing precipitation products and station-interpolated precipitation data. The applicability of the improved SWAT model and precipitation datasets in the source region of the Yarkant River was evaluated and analyzed using statistical indicators, hydrological characteristic values, and watershed runoff simulation effectiveness. The optimal dataset was further used to analyze glacier evolution characteristics in the basin. The results revealed the following: (1) The improved model fills the gap in glacier runoff simulation with respect to the original SWAT model, with the simulation results more closely aligning with the actual runoff variation patterns in the study area, better describing the meltwater runoff process. (2) CMA V2.0 precipitation data has the best applicability in the study area. This is specifically reflected in the rationality of the spatial and temporal distribution patterns of the inverted precipitation, the accuracy observed in capturing precipitation events and actual precipitation characteristics, the goodness of fit in driving hydrological models, and the observed precision in reflecting the composition of watershed runoff, all of which are superior to those pertaining to other precipitation products. (3) The glacier melt calculated using the improved SWAT model informed by CMA V2.0 shows that during the study period, the basin formed a pattern with a positive–negative glacier balance demarcation at 36.5° N, featuring melting at higher latitudes and accumulation at lower latitudes. The results of this study are of significant importance for hydrometeorological applications and hydrological and water resources research in this region. Full article

Studying the relationship between grain planting and the environment is an important means to promote sustainable production. This study takes wheat, a typical grain crop in the Yarkant River oasis irrigation district, the fourth largest agricultural irrigation district in China, as an example to analyze the relationship and changing trends between wheat yield and water footprint (WF), and carbon footprint (CF) from 2001 to 2020. The study found that during the research period, wheat yield, ${WF}_{green,blue},{WF}_{grey}$, and CF showed a fluctuating but significantly upward trend. Decoupling analysis indicates that the overall decoupling trend between wheat yield and water footprint and carbon footprint is not obvious. This suggests that the rapid development of wheat production in the Yarkant River Oasis has also led to significant water resource consumption, pollution, and greenhouse gas emissions. Among the three sub–irrigation districts, the Shache sub–irrigation district has the best decoupling state, reflecting that the increase in wheat yield in Shache did not lead to more water resource consumption and pollution which is may due to its abundant water resources and agriculture development. Further analysis found that the use of nitrogen fertilizers and irrigation electricity have contributed to water resource pressure and greenhouse gas emissions. This study reveals that there are significant environmental risks in the current wheat planting in the Yarkant River oasis irrigation district, but it also points out the direction for green development in the irrigation district. Full article

Analyzing the future changes in runoff is crucial for efficient water resources management and planning in arid regions with large river systems. This paper investigates the future runoffs of the headwaters of the Tarim River Basin under different emission scenarios by forcing the hydrological model SWAT-Glacier using six regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) project. Results indicate that compared to the period of 1976~2005, temperatures are projected to increase by 1.22 ± 0.72 °C during 2036~2065 under RCP8.5 scenarios, with a larger increment in the south Tianshan mountains and a lower increment in the north Kunlun Mountains. Precipitation is expected to increase by 3.81 ± 14.72 mm and 20.53 ± 27.65 mm during 2036–2065 and 2066–2095, respectively, under the RCP8.5 scenario. The mountainous runoffs of the four headwaters that directly recharge the mainstream of the Tarim River demonstrate an overall increasing trend in the 21st century. Under the RCP4.5 and RCP8.5 scenarios, the runoff is projected to increase by 3.2% and 3.9% (amounting to 7.84 × 10⁸ m³ and 9.56 × 10⁸ m³) in 2006–2035. Among them, the runoff of the Kaidu River, which is dominated by rainfall and snowmelt, is projected to present slightly decreasing trends of 3~8% under RCP4.5 and RCP8.5 scenarios. For catchments located in the north Kunlun Mountains (e.g., the Yarkant and Hotan Rivers which are mix-recharged by glacier melt, snowmelt, and rainfall), the runoff will increase significantly, especially in summer due to increased glacier melt and precipitation. Seasonally, the Kaidu River shows a forward shift in peak flow. The summer streamflow in the Yarkant and Hotan rivers is expected to increase significantly, which poses challenges in flood risk management. Full article

As the largest irrigation area in northwest China, the middle and lower reaches of the Yarkant River basin are limited in economic development by the shortage of surface water resources and the increasing demand for groundwater resources from agriculture and industry, and the phenomenon of over-exploitation is becoming increasingly serious, which is not in line with the concept of sustainable development. Therefore, improving the efficiency of water resource utilization while curbing the trend of declining groundwater levels is an important issue that needs to be addressed in the middle and lower reaches of Yarkant at present, specifically, by establishing a distributed hydrological model MIKE SHE based on a soil texture dataset. The model efficiency coefficient Ens, the water balance coefficient (WB), the correlation coefficient r, and the relative error Re were selected to evaluate the model’s applicability. The results were: Ens = 0.84, WB = 0.80, and r = 0.96 for the annual scale runoff simulation and Ens = 0.85, RE = 0.61, and r = 0.96 for the monthly scale runoff simulation. The relative errors between the simulated and observed values of the typical observation wells were 3.45%, 1.59%, 2.52%, and 0.35%. According to the analysis of the soil parameters on the runoff sensitivity and groundwater table sensitivity, the saturated hydraulic conductivity had the greatest effect on the peak discharge. The results show that the MIKE SHE model has some applicability in the lower and middle reaches of the Yarkant River basin. Full article

This study quantitatively analyzes the effects of flooding on the growth and species diversity of riparian forests along the Yarkant River and the Tarim River, Xinjiang, in northwest China, and provides important information for the efficient utilization of water and water resource management in arid regions. Monitoring of species diversity of riparian forests was conducted every year from 2016 to 2019 in the Xiamale forest district in the lower reaches of the Yarkant River, and in the Shaya forest district and the lunnan forest district in the upper and middle reaches of the Tarim River. The Pielou index, Shannon–Wiener index, Simpson index, and importance value were used to analyze the influence of flooding. The results showed the following: (1) After three years of flooding, indices for the lower reaches of the Yarkant River and Tarim River were significantly increased and 11 new plant species appeared. (2) With increasing distance from the river channel, plant density and species diversity decreased. Flooding trends are the main factors affecting the distribution of plant species and water is the main restricting factor that influences plant growth in arid areas; thus, desert riparian forests improved significantly after flooding. (3) Flooding increases the regeneration capacity and species diversity of plant communities in desert riparian forests. In order to maintain the current trend of ecological improvement, flooding irrigation must continue. Full article

Glaciers have proven to be a particularly sensitive indicator of climate change, and the impacts of glacier melting on downstream water supplies are becoming increasingly important as the world’s population expands and global warming continues. Data scarcity in mountainous catchments, on the other hand, has been a substantial impediment to hydrological simulation. Therefore, an enhanced glacier hydrological model combined with multi-source remote sensing data was introduced in this study and was performed in the Upper Yarkant River (UYR) Basin. A simple yet efficient degree-day glacier melt algorithm considering solar radiation effects has been introduced for the Soil and Water Assessment Tool Plus model (SWAT+), sensitivity analysis and auto calibration/validation processes were integrated into this enhanced model as well. The results indicate that (i) including glacio-hydrological processes and multi-source remote sensing data considerably improved the simulation precision, with a Nash–Sutcliffe efficiency coefficient (NSE) promotion of 1.9 times and correlated coefficient (R²) of 1.6 times greater than the original model; (ii) it is an efficient and feasible way to simulate glacio-hydrological processes with SWAT+Glacier and calibrate it using observed discharge data in data-scarce and glacier-melt-dominated catchments; and (iii) glacier runoff is intensively distributed throughout the summer season, accounting for about 78.5% of the annual glacier runoff, and glacier meltwater provides approximately 52.5% (4.4 × 10⁹ m³) of total runoff in the study area. This research can serve the runoff simulation in glacierized regions and help in understanding the interactions between streamflow components and climate change on basin scale. Full article

Inland river runoff variations in arid regions play a decisive role in maintaining regional ecological stability. Observation data of inland river runoff in arid regions have short time series and imperfect attributes due to limitations in the terrain environment and other factors. These shortages not only restrict the accurate simulation of inland river runoff in arid regions significantly, but also influence scientific evaluation and management of the water resources of a basin in arid regions. In recent years, research and applications of machine learning and in-depth learning technologies in the hydrological field have been developing gradually around the world. However, the simulation accuracy is low, and it often has over-fitting phenomenon in previous studies due to influences of complicated characteristics such as “unsteady runoff”. Fortunately, the circulation layer of Long-Short Term Memory (LSTM) can explore time series information of runoffs deeply to avoid long-term dependence problems. In this study, the LSTM algorithm was introduced and improved based on the in-depth learning theory of artificial intelligence and relevant meteorological factors that were monitored by coupling runoffs. The runoff data of the Yarkant River was chosen for training and test of the LSTM model. The results demonstrated that Mean Absolute Error (MAE) and Root Mean Square error (RMSE) of the LSTM model were 3.633 and 7.337, respectively. This indicates that the prediction effect and accuracy of the LSTM model were significantly better than those of the convolution neural network (CNN), Decision Tree Regressor (DTR) and Random Forest (RF). Comparison of accuracy of different models made the research reliable. Hence, time series data was converted into a problem of supervised learning through LSTM in the present study. The improved LSTM model solved prediction difficulties in runoff data to some extent and it applied to hydrological simulation in arid regions under several climate scenarios. It not only decreased runoff prediction uncertainty brought by heterogeneity of climate models and increased inland river runoff prediction accuracy in arid regions, but also provided references to basin water resource management in arid regions. In particular, the LSTM model provides an effective solution to runoff simulation in regions with limited data. Full article

Quantification of the impacts of climate change on streamflow and other hydrological parameters is of high importance and remains a challenge in arid areas. This study applied a modified distributed hydrological model (HEC-HMS) to the Yarkant River basin, China to assess hydrological changes under future climate change scenarios. Climate change was assessed based on six CMIP6 general circulation models (GCMs), three shared socio-economic pathways (SSP126, SSP245, SSP370), and several bias correction methods, whereas hydrological regime changes were assessed over two timeframes, referred to as the near future (2021–2049) and the far future (2071–2099). Results demonstrate that the DM (distribution mapping) and LOCI (local intensity scaling) bias correction methods most closely fit the projections of temperature and precipitation, respectively. The climate projections predicted a rise in temperature of 1.72–1.79 °C under the three SSP scenarios for the near future, and 3.76–6.22 °C under the three SSPs for the far future. Precipitation increased by 10.79–12% in the near future, and by 14.82–29.07% during the far future. It is very likely that streamflow will increase during both the near future (10.62–19.2%) and far future (36.69–70.4%) under all three scenarios. The increase in direct flow will be greater than baseflow. Summer and winter streamflow will increase the most, while the increase in streamflow was projected to reach a maximum during June and July over the near future. Over the far future, runoff reached a peak in May and June. The timing of peak streamflow will change from August to July in comparison to historical records. Both high- and low-flow magnitudes during March, April, and May (MAM) as well as June, July, and August (JJA) will increase by varying degrees, whereas the frequency of low flows will decrease during both MAM and JJA. High flow frequency in JJA was projected to decrease. Overall, our results reveal that the hydrological regime of the Yarkant River is likely to change and will be characterized by larger seasonal uncertainty and more frequent extreme events due to significant warming over the two periods. These changes should be seriously considered during policy development. Full article

The aim of this research was to use the standardized runoff index (SRI) with a three-month timescale (SRI-3) to analyze hydrological drought risk in two arid river basins characterized by different runoff regimes, Northwest China. Based on SRI-3, hydrological drought levels for different events were defined through run theory. The hydrological drought risk in the two study basins was then comprehensively assessed using a multidimensional copula function that considered the multivariable joint probability of hydrological drought duration, severity, intensity and peak. Results indicate that: (1) the risk of hydrological drought in the two basins between 1961–2018 periodically changed. There was a slight increase in risk within the Yarkant River Basin, while there was a clear decrease in risk within the Kaidu River Basin. The magnitude of drought in the two basins was relatively low; both basins were dominated by mild to moderate hydrological droughts; (2) the drought probabilities of the Yarkant River Basin and Kaidu River Basin from 1961 to 2018 exhibited a falling-rising-falling pattern and a rising-falling trend through time, respectively. These trends were correlated with changes in precipitation and the area of glacial ice, which presumably influenced the amount and source of runoff in the two basins. Hydrological drought risk in the Yarkant River Basin was higher than in the Kaidu River Basin; and (3) the return period of mild, moderate, severe and extreme drought events was 2 yrs, 8 yrs, 20 yrs, and 60 yrs in the Yarkant River Basin, respectively, and 2 yrs, 8 yrs, 23 yrs and 74 yrs in the Kaidu River Basin, respectively. Full article

In recent years, the climate in the arid region of Northwest China has become warmer and wetter; however, glaciers in the north slope of the West Kunlun Mountains (NSWKM) show no obvious recession, and river flow is decreasing or stable. This contrasts with the prevalent response of glaciers to climate change, which is recession and initial increase in glacier discharge followed by decline as retreat continues. We comparatively analyzed multi-timescale variation in temperature–precipitation–snow cover-runoff in the Yarkant River Basin (YRK), Karakax River Basin (KRK), Yurungkax River Basin (YUK), and Keriya River Basin (KRY) in the NSWKM. The Mann–Kendall trend and the mutation–detection method were applied to data obtained from an observation station over the last 60 years (1957–2017) and MODIS snow data (2001–2016). NSWKM temperature and precipitation have continued to increase for nearly 60 years at a mean rate of 0.26 °C/decade and 5.50 mm/decade, respectively, with the most obvious trend (R² > 0.82) attributed to the KRK and YUK. Regarding changes in the average snow-cover fraction (SCF): YUK (SCF = 44.14%) > YRK (SCF = 38.73%) > KRY (SCF = 33.42%) > KRK (SCF = 33.40%). Between them, the YRK and YUK had decreasing SCA values (slope < −15.39), while the KRK and KRY had increasing SCA values (slope > 1.87). In seasonal variation, the SCF of the three of the basins reaches the maximum value in spring, with the most significant performance in YUK (SCF = 26.4%), except for YRK where SCF in spring was lower than that in winter (−2.6%). The runoff depth of all river basins presented an increasing trend, with the greatest value appearing in the YRK (5.78 mm/decade), and the least value in the YUK (1.58 mm/decade). With the runoff response to climate change, temperature was the main influencing factor of annual and monthly (summer) runoff variations in the YRK, which is consistent with the runoff-generation rule of rivers in arid areas, which mainly rely on ice and snow melt for water supply. However, this rule was not consistent for the YUK and KRK, as it was disturbed by other factors (e.g., slope and slope direction) during runoff generation, resulting in disruptions of their relationship with runoff. This research promotes the study of the response of cold and arid alpine regions to global change and thus better serve regional water resources management. Full article