Search Results (14)

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

In this paper, a glacial module based on an enhanced temperature-index approach was successfully introduced into the Soil and Water Assessment Tool (SWAT) model to simulate the glacier runoff and water balance of a glacierized watershed, the mountainous region of the Yarkant River Basin (YRB) in Karakoram. Calibration and validation of the SWAT model were based on comparisons between the simulated and observed discharge with a monthly temporal resolution from 1961 to 2011 for the Kaqun hydrological station. The results reaffirmed the viability of the approach for simulating glacier runoff, as evidenced by a Nash–Sutcliff Efficiency (NSE) of 0.82–0.86 as well as a percentage bias (PBIAS) of −4.5% to 2.4%, for the calibration and validation periods, respectively. Over the last 50 years, the total discharge and glacier runoff both exhibited increasing trends with 0.031 × 10⁹ m³·a⁻¹ and 0.011 × 10⁹ m³·a⁻¹. The annual glacier runoff contribution to the streamflow was between 42.3% and 64.5%, with an average of 51.6%, although the glaciers accounted for only 12.6% of the watershed drainage area in the mountainous YRB. The monthly contribution of the glacier runoff ranged from 11.0% in April to 62.1% in August, and the glacier runoff from June to September accounted for about 86.3% of the annual glacier runoff. Runoff from the mountainous regions above 5000 m a.s.l. accounted for 70.5% of the total discharge, with glacier runoff contributions being approximately 46.4%. Full article

Due to the scarcity of field observations and geodetic measurements in catchments in the Karakoram Mountains in Western China, obtaining precipitation data for the high mountains involves large uncertainties and difficulties. In this study, we used a functional relationship between the annual glacier accumulation and summer temperature at the equilibrium line altitude (ELA) to derive precipitation lapse rates (PLAPSs) in a data-scarce watershed. These data were used in a modified Soil and Water Assessment Tool (SWAT) model with a glacier module to simulate glacio-hydrological processes in the Yarkant River basin in the Karakoram. The PLAPS based on the widely-used grid datasets considerably underestimated precipitation, yielding an unreasonable watershed water balance and inaccurate glacier changes. However, the ELA-based PLAPS improved the simulation significantly. In the Yarkant River basin, the annual precipitation reached a peak of 800–1000 mm at approximately 5300 m a.s.l. The model simulations indicated that the contributions of glacier melt and ice melt to total runoff were 52% and 31%, respectively. Moreover, a significant precipitation increase and a non-significant temperature increase during the melt season may be the major reasons for the decreased ice melt and slower glacier shrinkage on the northern slope of the Karakoram during the period of 1968–2007. Full article

Most studies of input data used in hydrological models have focused on flow; however, point discharge data negligibly reflect deviations in spatial input data. To study the effects of different input data sources on hydrological processes at the catchment scale, eight MIKE SHE models driven by station-based data (SBD) and remote sensing data (RSD) were implemented. The significant influences of input variables on water components were examined using an analysis of the variance model (ANOVA) with the hydrologic catchment response quantified based on different water components. The results suggest that compared with SBD, RSD precipitation resulted in greater differences in snow storage in the different elevation bands and RSD temperatures led to more snowpack areas with thinner depths. These changes in snowpack provided an appropriate interpretation of precipitation and temperature distinctions between RSD and SBD. For potential evapotranspiration (PET), the larger RSD value caused less plant transpiration because parameters were adjusted to satisfy the outflow. At the catchment scale, the spatiotemporal distributions of sensitive water components, which can be defined by the ANOVA model, indicate that this approach is rational for assessing the impacts of input data on hydrological processes. Full article