•Comparison of the aquifer response to the current irrigation system and the improved irrigation methods.•Quantification of saved-water by the improved irrigation methods and corresponding recovery ...of the Amu Darya River runoff.•Estimating the groundwater flux from the Nukus irrigation area into the South Aral Sea, and discussing the lake variation trend.•Investigation on the spatial variation characteristics of the aquifer to the proposed improved irrigation methods.
Suitable groundwater levels have a significant influence on vegetation growth, regional salinization, and ecological sustainability. Because of long-term low-efficiency irrigation methods and water canals, the stream flows vanish before reaching the South Aral Sea, leading to a rapid shrinkage of lake coverage since 1960. Meanwhile, the groundwater table in agricultural zones has continued to grow and recharge the Aral Sea, leading to increased salinization. Using a joint application of observation, remote sensing, and reanalysis data, a groundwater model was established to represent the historical aquifer condition and the efficiency of four possible management scenarios: drip irrigation under plastic mulch (Drip scenario), surface water-groundwater conjunctive irrigation (Conjunction scenario), drainage system methods (Drainage scenario), and mixing of the aforementioned methods (Mixed scenario). The simulation results demonstrate distinct spatial distribution of groundwater tables: the decline in the groundwater level was discovered in all proposed methods, but the decline was more drastic in the Conjunction and Mixed scenarios, and least in the Drainage scenario. The decrease in the groundwater table can be attributed to the decrease in the recharge rate (Drip and Conjunction scenarios) and the increase in the pumping rate (Conjunction scenario). Of all the scenarios, the Drainage scenario shows the smallest global decline in the water table, with an average decline of 0.15 m, but a maximum regional decline of 3.93 m (on the sides of the drainage). Evaluated by analyzing the water balance at a regional scale, evapotranspiration (ET) is still the major consumer of groundwater resources, at approximately 52%. Groundwater extraction and leakage into drainage accounted for approximately 6.9% and 23.5%, respectively. However, improved irrigation measures could reduce surface runoff and convert excessive groundwater into drainage systems. The improved irrigation methods could increase the total surface water runoff to 19.16 km3/yr, which is 29% higher than the maximum annual runoff (14.82 km3) and 406% higher than the mean annual runoff (3.79 km3) of the Amu Darya River over the past two decades. This study indicates that proper groundwater management measurements in irrigation areas could greatly help address water scarcity problems and promote sustainability in these ecosystems.
Soil moisture, as a crucial indicator of dryness, is an important research topic for dryness monitoring. In this study, we propose a new remote sensing dryness index for measuring soil moisture from ...spectral space. We first established a spectral space with remote sensing reflectance data at the near-infrared (NIR) and red (R) bands. Considering the distribution regularities of soil moisture in this space, we formulated the Ratio Dryness Monitoring Index (RDMI) as a new dryness monitoring indicator. We compared RDMI values with in situ soil moisture content data measured at 0–10 cm depth. Results showed that there was a strong negative correlation (R = −0.89) between the RDMI values and in situ soil moisture content. We further compared RDMI with existing remote sensing dryness indices, and the results demonstrated the advantages of the RDMI. We applied the RDMI to the Landsat-8 imagery to map dryness distribution around the Fukang area on the Northern slope of the Tianshan Mountains, and to the MODIS imagery to detect the spatial and temporal changes in dryness for the entire Xinjiang in 2013 and 2014. Overall, the RDMI index constructed, based on the NIR–Red spectral space, is simple to calculate, easy to understand, and can be applied to dryness monitoring at different scales.
•Topographic gradient-vegetation distribution information Tupu can visually display topographic differentiation characteristics of vegetation on the elevation gradient.•Topographic composite index ...was constructed to analyze topographic gradients-vegetation distribution relationship.•Different vegetation types have different dominant and limiting factors.•Provide useful information for ecological conservation policy making.
Among numerous vegetation studies, there are few studies on the elevation gradient distribution control mechanism and horizontal law of small-scale vegetation. In the same climate zone, topography is one of the most important factors affecting vegetation pattern. Here, we used the geo-informatic Tupu theory to construct topographic gradient-vegetation distribution information Tupu (TG-VDI Tupu) to display the topographical differentiation characteristics of vegetation. Moreover, an improved evaluation of topographical differentiation characteristics of vegetation was proposed based on topographic gradients, and the topographic composite index (TCI) was constructed to analyse the topographic variation in vegetation distribution. Meanwhile, the dominant factors and limiting factors affecting vegetation distribution under different topographic gradients were determined through statistical analysis. Combined with field surveys, Gaofen-1 (GF-1) satellite images were used to extract vegetation types, and the solar radiation value (SRV), topographic wetness index (TWI) and topographic variables were extracted from DEM data. The results indicate that TG-VDI Tupu can visually display topographic differentiation characteristics of vegetation on an elevation gradient. Elevation controls the horizontal distribution of vegetation on a small scale by changing ecological factors. At the same elevation, slope affects vegetation distribution by changing the SRV and TWI, while aspect changes the TWI. Coniferous forest is separated along a slope gradient and is more abundant on steep slopes. The percentage of broadleaf forest is negatively correlated with SRV and positively correlated with TWI, and the proportion is higher on the leeward slope facing north. The distribution of shrubs is more abundant on more xeric aspects and on steeper and more xeric slope configurations. In alpine areas above 2800 m, the abundance of vegetation types declines. This decline may be related to the weak solar radiation and widespread glacial landforms, exposed rocks and strong weathering. The methodology in our study can be applied to other regions and is expected to provide useful information for ecological conservation policy making.
•Decoupling of soil moisture and vapor pressure deficit by sorting and binning.•Soil moisture promoted photosynthesis in 94% of the vegetation areas.•Vapor pressure deficit inhibited photosynthesis ...in 60% of the vegetation areas.•Photosynthesis is dominated by soil moisture in Central Asia.
Soil moisture (SM) and vapor pressure deficit (VPD) are key factors affecting photosynthesis, and quantifying their effects on this process can help us to understand the mechanisms of carbon cycling in terrestrial ecosystems. However, the strong coupling of SM and VPD makes it difficult to quantify their relative importance in the ecosystem carbon cycle. In this study we decoupled the negative correlation between SM and VPD by sorting and binning reanalysed SM and VPD data, and based on this, we quantified the relationship between VPD and SM and sunlight-induced chlorophyll fluorescence (SIF) in dryland Central Asia (CA). We found that SM promoted and suppressed photosynthesis in CA, accounting for 94.08% and 5.92% of the vegetated areas in CA, respectively; VPD promoted and suppressed photosynthesis in CA accounted for 39.68% and 60.32% of the vegetation area, respectively. The effects of SM and VPD on the photosynthesis of different vegetation types were different: the photosynthesis of croplands and forests tended to increase and then decrease with increasing SM, and the photosynthesis of grasslands, shrublands and sparse vegetation tended to increase with increasing SM; the photosynthesis of croplands, grasslands and forests increase with VPD, while the opposite is true for shrublands and sparse vegetation. Relative effects on photosynthesis indicated that the areas where SM had a greater effect than VPD on photosynthesis accounted for 74.26% of the vegetation area, mainly in the central part of Kazakhstan and Kyrgyzstan, which was related to the fact that the main vegetation types in these regions were croplands, grasslands, forests and sparse vegetation. The areas with greater effects of VPD than SM on photosynthesis were mainly located in the northern part of Kazakhstan and most of Uzbekistan and Turkmenistan (25.74% of vegetated areas). Our study contributes to further understanding of the key processes involved in carbon cycling in terrestrial ecosystems.
Plastic mulching has been widely practiced in crop cultivation worldwide due to its potential to significantly increase crop production. However, it also has a great impact on the regional climate ...and ecological environment. More importantly, it often leads to unexpected soil pollution due to fine plastic residuals. Therefore, accurately and timely monitoring of the temporal and spatial distribution of plastic mulch practice in large areas is of great interest to assess its impacts. However, existing plastic-mulched farmland (PMF) detecting efforts are limited to either small areas with high-resolution images or coarse resolution images of large areas. In this study, we examined the potential of cloud computing and multi-temporal, multi-sensor satellite images for detecting PMF in large areas. We first built the plastic-mulched farmland mapping algorithm (PFMA) rules through analyzing its spectral, temporal, and auxiliary features in remote sensing imagery with the classification and regression tree (CART). We then applied the PFMA in the dry region of Xinjiang, China, where a water resource is very scarce and thus plastic mulch has been intensively used and its usage is expected to increase significantly in the near future. The experimental results demonstrated that the PFMA reached an overall accuracy of 92.2% with a producer’s accuracy of 97.6% and a user’s accuracy of 86.7%, and the F-score was 0.914 for the PMF class. We further monitored and analyzed the dynamics of plastic mulch practiced in Xinjiang by applying the PFMA to the years 2000, 2005, 2010, and 2015. The general pattern of plastic mulch usage dynamic in Xinjiang during the period from 2000 to 2015 was well captured by our multi-temporal analysis.
•The Schrenk spruce tree-ring widths and PDSI values showed a significant positive correlation.•The extreme drought years were verified in the Tianshan Mountains.•The drought trends in different ...regions of Tianshan Mountains have been discovered and confirmed.
In Central Asia, the frequency and severity of droughts have a strong impact on the climate and lives of people. Therefore, it is essential to explore climate change, especially its impacts on the cycle and extent of drought occurrence. To determine drought conditions, the Palmer drought severity index (PDSI) is diffusely implemented and can be reconstructed using tree-ring chronologies. We collected Schrenk spruce (Picea schrenkiana) cores from six distinct areas in the Tianshan Mountains and used them to establish tree-ring chronologies. Correlation and reaction research revealed that the main impact on tree growth was humidity from previous years and the present growing season. To reconstruct the historical PDSI for the Tianshan Mountains, chronologies were applied. The reconstructed PDSI was considered to describe the climate change in the Tianshan Mountains because it captured severe drought events that were observed in other research findings. Furthermore, the spatial analysis results covered almost all of the Tianshan Mountains at 0.5° resolution. A large-scale drought event in the 1910s that was prevalent in the Tianshan Mountains was detected with tree rings. The extreme drought years of 1917, 1919, and 1944 detected on the chronologies were also specifically verified. A decadal analysis showed that the eastern and western Tianshan Mountains experienced continuous drought in the 1880s and during the 1810s ~ 1830s, the central and western Tianshan Mountains experienced continuous drought in the 1770s and 1640s, while it experienced a continuous wetting in the 1750s, and large-scale wetting occurred in Central Asia in the 2000s. This research offers a new perspective on the instability and spatial spread of drought in the Tianshan Mountains.
•Wetlands show an increasing trend despite the decrease runoff into the delta.•Wetlands restoration is a result of the water resources redistribution.•Human activities are the main reasons for ...wetland variation and exacerbated the Aral Sea shrinkage.
The Aral Sea in Central Asia has shrunk by 90% since 1960. The resulting desertification and salt and dust storms have diminished biodiversity in the Amu Darya River Delta, triggering the Aral Sea Crisis. Timely monitoring of trends and spatial patterns in deltaic wetlands is beneficial for biodiversity conservation and ecological restoration. Existing studies have mainly focused on the response of vegetation and microbial communities to ecological changes while ignoring the indicative role of wetlands-associated changes. This study analyzed the spatial and temporal patterns of long time series wetland changes extracted from remote sensing imagery through cover frequency maps and landscape indices. The hydrological data, land use/land cover change maps, and statistical data were combined to explore the driving factors of wetland change over the past 40 years. The results showed that the wetland area increased by 2242.96 km2 (90.72%) from 1977 to 2019. The wetland area increased at 268.01 km2/a from the 1970s to the early 1990s, with a fluctuating change since 1994. Wetlands are mainly distributed in the transition zone between the delta and the Aral Sea, accounting for approximately 81.61% of the total wetland area. The proportion of wetlands on the east and west sides significantly expanded along the canal system, increasing from 0.13% in 1977 to 9.74% in 2019. The degree of fragmentation of the wetland landscape in the entire delta increased by 1.7 times. With decreasing runoff into the delta, the expansion of cultivated land and the construction of reservoirs and irrigation canals changed the spatio-temporal distribution of water resources. In contrast, agricultural irrigation has raised the groundwater level. Human activities, such as the expansion of cultivated land and the construction of reservoirs and irrigation canals, are the main reasons for the spatio-temporal changes in wetland distribution, and exacerbated the decrease in water flow into the Aral Sea and its shrinkage. The restoration of wetlands is not a proof of ecological improvement, it resulted from the redistribution of water resources in the delta. The increase in wetland area represents an apparent ecological contrast with the drying up of the Aral Sea, and the phenomenon is not conducive to the ecological restoration of the delta.
The aim of the current study is to monitor and analyze the rainfall variability and to predict the aridity in northern Egypt. To implement that, parametric and non-parametric statistical methods were ...used for the rainfall data at 13 meteorological stations scattered along the study area from 1947 to 2010. Standard normal homogeneity test, linear regression forecasting methods, Mann-Kendall’s test for trend, time-series plots, the trend-to-noise ratio as a test of significance for the annual and seasonal rainfall, the annual rainfall intensity, inter- and intra-annual variability, and seasonality were calculated. High inter-annual and intra-annual rainfall variability has been observed over space and time. Synchronously, different temporal patterns of annual rainfall were noticed at different stations, and most of the trends were not linear and significant. The results indicated an increase in the number of years, which receive less than the average rainfall. In addition, a marked variation in seasonal rainfall was observed every decade, and the rainfall variability of autumn was higher than that in winter and spring while summer experienced no rainfall and, hence, no variability. In the future, precipitation will decrease overall the region with an increase in temperature for all stations, where the existence of droughts may possibly arise in northern Egypt based on the ensemble mean of multi-Coordinated Regional climate Downscaling Experiment models under RCP4.5 and RCP8.5 emission scenarios. The outcomes of this research can be beneficial for drought hazard mitigation as well as for the preparation and managing agricultural activities in the study area.
As the core area of human activities and economic development in the Xinjiang Autonomous Region, the hilly oasis zone of Xinjiang directly affects the regional sustainable development and stability ...of the ecosystem. Understanding the effects of different geomorphic types on vegetation distribution is crucial for maintaining vegetation growth and development, especially the improvement in the terrestrial ecological environment in arid areas under the background of climate change. However, there are few studies on the effect of spatial differences in detailed geomorphic types on vegetation distribution patterns. Therefore, this paper divides the Xinjiang hilly oasis zone into six geomorphologic level zones and innovatively investigates the influence of detailed geomorphologic types on the spatial distribution of vegetation and vegetation cover. Further, the area proportion of detailed landform types corresponding to different vegetation coverage in each geomorphic area was quantitatively calculated. Finally, the Geodetector method was used to detect the drivers of interactions between vegetation and the environment. The findings are shown as follows: (1) In the same climate zone, the spatial differentiation of landforms has a great influence on the vegetation distribution, manifesting as the significantly different vegetation distribution in different landform types. Grassland is the main vegetation type in the erosion and denudation of Nakayama; cultivated vegetation and meadows have a larger coverage in the alluvial flood plain and alluvial plain; and the distribution of vegetation in the Tianshan economic zone is characterized by obvious vertical zoning with the geomorphology. (2) The landform type and morphological types are the strongest driving factors for vegetation coverage with q values of 0.433 and 0.295, respectively, which effectually fill the gap caused by only using two terrain indicators, slope and elevation, to study the relationship between landforms and vegetation. (3) In addition, the improved nonlinear interaction resulting from the double factor of landform type and slope is 0.486, which has a stronger control on vegetation coverage than the single factor of landform type. These findings are conducive to enhancing the supply services of vegetation to the ecosystem in arid areas as well as providing important scientific guidance for the construction of ecological civilization and sustainable development in Xinjiang.
Modeling and assessing the susceptibility of snowmelt floods is critical for flood hazard management. However, the current research on snowmelt flood susceptibility lacks a valid large-scale modeling ...approach. In this study, a novel high-performance deep learning model called Swin Transformer was used to assess snowmelt susceptibility in the Kunlun Mountains region, where snowmelt floods occur frequently. Support vector machine (SVM), random forest (RF), deep neural network (DNN) and convolutional neural network (CNN) were also involved in the performance comparison. Eighteen potential conditioning factors were combined with a historical flood inventory to form the database. Apart from the susceptibility assessment, sensitivity analysis was also conducted to reflect the impact of the conditioning factors on the susceptibility of different types of snowmelt floods. The results showed that Swin Transformer achieved the highest score in the model performance test (AUC = 0.99) and successfully identified the relationship between conditioning factors and snowmelt flooding. Elevation and distance to rivers are the most important factors that affect snowmelt flooding in the study region, whereas rainfall and snow water equivalent are the dominant natural factors for mixed and warming types. In addition, the north-central parts of the study area have high susceptibility to snowmelt flooding. The methods and results can provide scientific support for snowmelt flood modeling and disaster management.
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