Reconstructing the hydrological change based on dendrohydrological data has important implications for understanding the dynamic distribution and evolution pattern of a given river. The widespread, long-living coniferous forests on the Altay Mountains provide a good example for carrying out the dendrohydrological studies. In this study, a regional composite tree-ring width chronology developed by Larix sibirica Ledeb. and Picea obovata Ledeb. was used to reconstruct a 301-year annual (from preceding July to succeeding June) streamflow for the Haba River, which originates in the southern Altay Mountains, Xinjiang, China. Results indicated that the reconstructed streamflow series and the observations were fitting well, and explained 47.5% of the variation in the observed streamflow of 1957-2008. Moreover, floods and droughts in 1949-2000 were precisely captured by the streamflow reconstruction. Based on the frequencies of the wettest/driest years and decades, we identified the 19^th century as the century with the largest occurrence of hydrological fluctuations for the last 300 years. After applying a 21-year moving average, we found five wet (1724-1758, 1780-1810, 1822-1853, 1931-1967, and 1986-2004) and four dry (1759-1779, 1811-1821, 1854-1930, and 1968-1985) periods in the streamflow reconstruction. Furthermore, four periods (1770-1796, 1816-1836, 1884-1949, and 1973-1997) identified by the streamflow series had an obvious increasing trend. The increasing trend of streamflow since the 1970s was the biggest in the last 300 years and coincided with the recent warming-wetting trend in northwestern China. A significant correlation between streamflow and precipitation in the Altay Mountains indicated that the streamflow reconstruction contained not only local, but also broad-scale, hydro-climatic signals. The 24-year, 12-year, and 2.2-4.5-year cycles of the reconstruction revealed that the streamflow variability of the Haba River may be influenced by solar activity and the atmosphere-ocean system.

Accurate inversion of land surface evapotranspiration (ET) in arid areas is of great significance for understanding global eco-hydrological process and exploring the spatio-temporal variation and ecological response of water resources. It is also important in the functional evaluation of regional water cycle and water balance, as well as the rational allocation and management of water resources. This study, based on model validation analysis at varied scales in five Central Asian countries and China’s Xinjiang, developed an appropriate approach for ET inversion in arid lands. The actual ET during growing seasons of the study area was defined, and the changes in water participating in evaporation in regional water cycle were then educed. The results show the simulation error of SEBS (Surface Energy Balance System) model under cloud amount consideration was 1.34% at 30-m spatial scale, 2.75% at 1-km spatial scale and 6.37% at 4-km spatial scale. ET inversion for 1980–2007 applying SEBS model in the study area indicates: (1) the evaporation depth (May–September) by land types descends in the order of waters (660.24 mm) > cultivated land (464.66 mm) > woodland (388.44 mm) > urbanized land (168.16 mm) > grassland (160.48 mm) > unused land (83.08 mm); and (2) ET during the 2005 growing season in Xinjiang and Central Asia was 2,168.68×108 m3 (with an evaporation/precipitation ratio of 1.05) and 9,741.03×108 m3 (with an evaporation/precipitation ratio of 1.4), respectively. The results unveiled the spatio-temporal variation rules of ET process in arid areas, providing a reference for further research on the water cycle and water balance in similar arid regions.

Greenhouse gas emission of carbon dioxide (CO2) is one of the major factors causing global climate change. Urban green space plays a key role in regulating the global carbon cycle and reducing atmospheric CO2. Quantifying the carbon stock, distribution and change of urban green space is vital to understanding the role of urban green space in the urban environment. Remote sensing is a valuable and effective tool for monitoring and estimating aboveground carbon (AGC) stock in large areas. In the present study, different remotely-sensed vegetation indices (VIs) were used to develop a regression equation between VI and AGC stock of urban green space, and the best fit model was then used to estimate the AGC stock of urban green space within the beltways of Xi’an city for the years 2004 and 2010. A map of changes in the spatial distribution patterns of AGC stock was plotted and the possible causes of these changes were analyzed. Results showed that Normalized Difference Vegetation Index (NDVI) correlated moderately well with AGC stock in urban green space. The Difference Vegetation Index (DVI), Ratio Vegetation Index (RVI), Soil Adjusted Vegetation Index (SAVI), Modified Soil Adjusted Vegetation Index (MSAVI) and Renormalized Difference Vegetative Index (RDVI) were lower correlation coefficients than NDVI. The AGC stock in the urban green space of Xi’an in 2004 and 2010 was 73,843 and 126,621 t, respectively, with an average annual growth of 8,796 t and an average annual growth rate of 11.9%. The carbon densities in 2004 and 2010 were 1.62 and 2.77 t/hm ², respectively. Precipitation was not an important factor to influence the changes of AGC stock in the urban green space of Xi’an. Policy orientation, major ecological greening projects such as “transplanting big trees into the city” and the World Horticultural Exposition were found to have an important impact on changes in the spatiotemporal patterns of AGC stock.

Meteorological drought is a natural hazard that can occur under all climatic regimes. Monitoring the drought is a vital and important part of predicting and analyzing drought impacts. Because no single index can represent all facets of meteorological drought, we took a multi-index approach for drought monitoring in this study. We assessed the ability of eight precipitation-based drought indices (SPI (Standardized Precipitation Index), PNI (Percent of Normal Index), DI (Deciles index), EDI (Effective drought index), CZI (China-Z index), MCZI (Modified CZI), RAI (Rainfall Anomaly Index), and ZSI (Z-score Index)) calculated from the station-observed precipitation data and the AgMERRA gridded precipitation data to assess historical drought events during the period 1987-2010 for the Kashafrood Basin of Iran. We also presented the Degree of Dryness Index (DDI) for comparing the intensities of different drought categories in each year of the study period (1987-2010). In general, the correlations among drought indices calculated from the AgMERRA precipitation data were higher than those derived from the station-observed precipitation data. All indices indicated the most severe droughts for the study period occurred in 2001 and 2008. Regardless of data input source, SPI, PNI, and DI were highly inter-correlated (R²=0.99). Furthermore, the higher correlations (R²=0.99) were also found between CZI and MCZI, and between ZSI and RAI. All indices were able to track drought intensity, but EDI and RAI showed higher DDI values compared with the other indices. Based on the strong correlation among drought indices derived from the AgMERRA precipitation data and from the station-observed precipitation data, we suggest that the AgMERRA precipitation data can be accepted to fill the gaps existed in the station-observed precipitation data in future studies in Iran. In addition, if tested by station-observed precipitation data, the AgMERRA precipitation data may be used for the data-lacking areas.

The assessment of the water losses by actual evapotranspiration plays a very important role in water resources management, especially in particular environments suffering soil water stresses and water shortages. The rationales of this study are the scarcity of experimental data, the difficulties in the measurement of direct and continuous evapotranspiration fluxes, and the switching between controls by climate and soil water availability. The temporal patterns of observed soil moisture and air temperature of over three years at an experimental site in southern Italy have been analysed to investigate the relation between them and the actual evapotranspiration volume, estimated using the soil water budget method. To this end, an event-based empirical analysis has been performed, exploring the relation between the mentioned variables. One of the major findings of the explorative phase is the qualitative and quantitative identification of the switching between climate and soil water balance as the controls over actual evapotranspiration at the experimental site. This threshold process has then been modelled at the event and sub-event scale, establishing simple empirical equations to predict actual evapotranspiration losses as a function of soil water content. Multilevel-recorded data also allowed the investigation of the importance of soil depth.

In China, qanats (kan’erjing/karez) exist only in Xinjiang Uygur autonomous region, being one form of traditional irrigation technology that made great contributions to oasis civilizations. There are different opinions on the origin and date of the qanats in Xinjiang due to a lack of adequate evidences. And uncontrolled over-exploitation of groundwater by pumping wells, as well as the expansion of surface water interventions nowadays, has caused serious impacts on not only the qanats, but also local ecological environments. There exist long-time arguments on whether the qanats should be restored or preserved. This study aimed to examine the historical development, geological conditions and characteristics, and modern implications of the qanats for oasis environmental protection, and to discuss the initiatives taken by local governments. The whole Xinjiang Uygur autonomous region was included as the study area, with a specific focus on Turpan prefecture. The materials and data were obtained from literature review and governmental documentation. Based on a systematic examination of three prevailing theories on the origination of Xinjiang’s qanats, it is suggested modern archaeological techniques could be good solutions to explore the origination in addition to historical records used normally. Although qanats fail to fully meet today’s enormous water demands, their rich historical, cultural, ecological and environmental implications in arid areas should not be underestimated. As a cultural heritage and ecologically-friendly engineering creation, qanat systems shall be kept in good condition and function by a valuable number. Recent initiatives to protect and restore target qanat systems in Xinjiang could provide positive examples for the practices in other regions of the world where the protection and restoration of qanats or similar technologies are desired.

Catchments dominated by meltwater runoff are sensitive to climate change as changes in pre-cipitation and temperature inevitably affect the characteristics of glaciermelt/snowmelt, hydrologic circle and water resources. This study simulated the impact of climate change on the runoff generation and streamflow of Chu River Basin (CRB), a glacierized basin in Central Asia using the enhanced Soil and Water Assessment Tool (SWAT). The model was calibrated and validated using the measured monthly streamflow data from three discharge gauge stations in CRB for the period 1961–1985 and was subsequently driven by downscaled future climate projections of five Global Circulation Models (GCMs) in Coupled Model Inter-comparison Project Phase 5 (CMIP5) under three radiative forcing scenarios (RCP2.6, RCP4.5 and RCP8.5). In this study, the period 1966–1995 was used as the baseline period, while 2016–2045 and 2066–2095 as the near-future and far-future period, respectively. As projected, the climate would become warmer and drier under all scenarios in the future, and the future climate would be characterized by larger seasonal and annual variations under higher RCP. A general decreasing trend was identified in the average annual runoff in glacier (–26.6% to –1.0%), snow (–21.4% to +1.1%) and streamflow (–27.7% to –6.6%) for most of the future scenario periods. The projected maximum streamflow in each of the two future scenarios occurred one month earlier than that in the baseline period because of the reduced streamflow in summer months. Results of this study are expected to arouse the serious concern about water resource availability in the headwater region of CRB under the continuously warming climate. Changes in simulated hydrologic outputs underscored the significance of lowering the uncertainties in temperature and precipitation projection.

Check dams are widely used on the Loess Plateau in China to control soil and water losses, develop agricultural land, and improve watershed ecology. Detailed information on the number and spatial distribution of check dams is critical for quantitatively evaluating hydrological and ecological effects and planning the construction of new dams. Thus, this study developed a check dam detection framework for broad areas from high-resolution remote sensing images using an ensemble approach of deep learning and geospatial analysis. First, we made a sample dataset of check dams using GaoFen-2 (GF-2) and Google Earth images. Next, we evaluated five popular deep-learning-based object detectors, including Faster R-CNN, You Only Look Once (version 3) (YOLOv3), Cascade R-CNN, YOLOX, and VarifocalNet (VFNet), to identify the best one for check dam detection. Finally, we analyzed the location characteristics of the check dams and used geographical constraints to optimize the detection results. Precision, recall, average precision at intersection over union (IoU) threshold of 0.50 (AP₅₀), IoU threshold of 0.75 (AP₇₅), and average value for 10 IoU thresholds ranging from 0.50-0.95 with a 0.05 step (AP_50-95), and inference time were used to evaluate model performance. All the five deep learning networks could identify check dams quickly and accurately, with AP_50-95, AP₅₀, and AP₇₅ values higher than 60.0%, 90.0%, and 70.0%, respectively, except for YOLOv3. The VFNet had the best performance, followed by YOLOX. The proposed framework was tested in the Yanhe River Basin and yielded promising results, with a recall rate of 87.0% for 521 check dams. Furthermore, the geographic analysis deleted about 50% of the false detection boxes, increasing the identification accuracy of check dams from 78.6% to 87.6%. Simultaneously, this framework recognized 568 recently constructed check dams and small check dams not recorded in the known check dam survey datasets. The extraction results will support efficient watershed management and guide future studies on soil erosion in the Loess Plateau.

Climate change may affect water resources by altering various processes in natural ecosystems. Dynamic and statistical downscaling methods are commonly used to assess the impacts of climate change on water resources. Objectively, both methods have their own advantages and disadvantages. In the present study, we assessed the impacts of climate change on water resources during the future periods (2020-2029 and 2040-2049) in the upper reaches of the Kaidu River Basin, Xinjiang, China, and discussed the uncertainties in the research processes by integrating dynamic and statistical downscaling methods (regional climate models (RCMs) and general circulation modes (GCMs)) and utilizing these outputs. The reference period for this study is 1990-1999. The climate change trend is represented by three bias-corrected RCMs (i.e., Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA), Regional Climate Model version 4 (RegCM4), and Seoul National University Meso-scale Model version 5 (SUN-MM5)) and an ensemble of GCMs on the basis of delta change method under two future scenarios (RCP4.5 and RCP8.5). We applied the hydrological SWAT (Soil and Water Assessment Tool) model which uses the RCMs/GCMs outputs as input to analyze the impacts of climate change on the stream flow and peak flow of the upper reaches of the Kaidu River Basin. The simulation of climate factors under future scenarios indicates that both temperature and precipitation in the study area will increase in the future compared with the reference period, with the largest increase of annual mean temperature and largest percentage increase of mean annual precipitation being of 2.4°C and 38.4%, respectively. Based on the results from bias correction of climate model outputs, we conclude that the accuracy of RCM (regional climate model) simulation is much better for temperature than for precipitation. The percentage increase in precipitation simulated by the three RCMs is generally higher than that simulated by the ensemble of GCMs. As for the changes in seasonal precipitation, RCMs exhibit a large percentage increase in seasonal precipitation in the wet season, while the ensemble of GCMs shows a large percentage increase in the dry season. Most of the hydrological simulations indicate that the total stream flow will decrease in the future due to the increase of evaporation, and the maximum percentage decrease can reach up to 22.3%. The possibility of peak flow increasing in the future is expected to higher than 99%. These results indicate that less water is likely to be available in the upper reaches of the Kaidu River Basin in the future, and that the temporal distribution of flow may become more concentrated.

The drought has enormous adverse effects on agriculture, water resources and environment, and causes damages around the world. Drought risk assessment and prioritization of drought management can help decision makers and planners to manage the adverse effects of drought. This paper aims to determine the risk of drought in Iran. At the first stage, standardized precipitation index (SPI) was calculated for the period 1981-2016. Then the probability map of different drought classes or drought hazard probability map were prepared. After that the indicator-based vulnerability assessment method was used to determine the drought vulnerability index. Five indices including climate, topography, waterway density, land use and groundwater resources were chosen as the most critical factors of drought in Iran and followed by the analytical hierarchy process questionnaire, the weights of each index were obtained based on expert opinions. Fuzzy membership maps of each index and sub-index were prepared using ArcGIS software. The drought vulnerability map of Iran was plotted using these weights and maps of each indicator. Finally, the drought risk map of Iran was provided by multiplying drought hazard and vulnerability maps. According to the 43-completed questionnaires by experts, climate index has the highest vulnerability to drought. Climate does not have an important role in drought hazard index, but it is the most crucial factor to classified drought vulnerability index. The results showed that central, northeast, southeast and west parts of Iran are at high risks of drought. There are regions with different risks in Iran due to unusual weather and climatic conditions. We realized that the climate and the groundwater situation is almost the same in the central, east and south parts of Iran, because the land use plays a crucial role in the drought vulnerability and risk in these areas. The drought risk decreases from the center of Iran to the southwest and northwest.

Black locust ( Robinia pseudoacacia L.) and Chinese pine ( Pinus tabulaeformis Carr.) are two woody plants that are widely planted on the Loess Plateau for controlling soil erosion and land desertification. In this study, we conducted an excavation experiment in 2008 to investigate the overall vertical root distribution characteristics of black locust and Chinese pine. We also performed triaxial compression tests to evaluate the root cohesion (additional soil cohesion increased by roots) of black locust. Two types of root distribution, namely, vertical root (VR) and horizontal root (HR), were used as samples and tested under four soil water content (SWC) conditions (12.7%, 15.0%, 18.0% and 20.0%, respectively). Results showed that the root lengths of the two species were mainly concentrated in the root diameter of 5–20 mm. A comparison of root distribution between the two species indicated that the root length of black locust was significantly greater than that of Chinese pine in nearly all root diameters, although the black locust used in the comparison was 10 years younger than the Chinese pine. Root biomass was also significantly greater in black locust than in Chinese pine, particularly in the root diameters of 3–5 and 5–10 mm. These two species were both found to be deep-rooted. The triaxial compression tests showed that root cohesion was greater in the VR samples than in the HR samples. SWC was negatively related to both soil shear strength and root cohesion. These results could provide useful information on the architectural characteristics of woody root system and expand the knowledge on shallow slope stabilization and soil erosion control by plant roots on the Loess Plateau.

In recent decades, China has been experiencing rapid economic development, population growth and urbanization. These processes have stressed the shortages of water resources in China, especially in the arid re-gions of northwestern China. In order to sustain the expanding cropland, people increased groundwater exploitation in these regions. The purpose of this study was to quantitatively analyze the changes in land use and water re-sources, and their relationship in the middle reaches of the Heihe River Basin, a typical inland river basin in northwest China. The data of land use change were interpreted using aerial photographs (1965) and Landsat TM images (1986 and 2007). The data of irrigation water volume in the irrigation districts were spatialized in the middle reaches of the Heihe River Basin. The spatial variation of the groundwater depth was interpolated using the geo-statistical method. The results showed that the cultivated cropland area along oasis fringe increased by 15.38% and 43.60% during the periods 1965–1986 and 1986–2007, respectively. Surface water amount for irrigation had almost doubled from 1956 to 2010. The decrease of grassland area mainly occurred at the alluvial fan in front of the Qilian Mountains, with 36.47% during 1965–1986 and 38.56% during 1986–2007, respectively. The groundwater depth in front of the mountain constantly increased from 1986 to 2007. We found that the overuse of surface water and overexploitation of groundwater had direct consequences on the natural environments. We suggests that the efficiency of surface water resources use among different irrigation districts needs to be improved, which will sig-nificantly ease the conflicts between increasing water demand for irrigation and a shortage of water resources in the middle reaches of the Heihe River Basin.

The rapid economic development that the Hotan Oasis in Xinjiang Uygur Autonomous Region, China has undergone in recent years may face some challenges in its ecological environment. Therefore, an analysis of the spatiotemporal changes in ecological environment of the Hotan Oasis is important for its sustainable development. First, we constructed an improved remote sensing-based ecological index (RSEI) in 1990, 1995, 2000, 2005, 2010, 2015 and 2020 on the Google Earth Engine (GEE) platform and implemented change detection for their spatial distribution. Second, we performed a spatial autocorrelation analysis on RSEI distribution map and used land-use and land-cover change (LUCC) data to analyze the reasons of RSEI changes. Finally, we investigated the applicability of improved RSEI to arid area. The results showed that mean of RSEI rose from 0.41 to 0.50, showing a slight upward trend. During the 30-a period, 2.66% of the regions improved significantly, 10.74% improved moderately and 32.21% improved slightly, respectively. The global Moran's I were 0.891, 0.889, 0.847 and 0.777 for 1990, 2000, 2010 and 2020, respectively, and the local indicators of spatial autocorrelation (LISA) distribution map showed that the high-high cluster was mainly distributed in the central part of the Hotan Oasis, and the low-low cluster was mainly distributed in the outer edge of the oasis. RSEI at the periphery of the oasis changes from low to high with time, with the fragmentation of RSEI distribution within the oasis increasing. Its distribution and changes are predominantly driven by anthropologic factors, including the expansion of artificial oasis into the desert, the replacement of desert ecosystems by farmland ecosystems, and the increase in the distribution of impervious surfaces. The improved RSEI can reflect the eco-environmental quality effectively of the oasis in arid area with relatively high applicability. The high efficiency exhibited with this approach makes it convenient for rapid, high frequency and macroscopic monitoring of eco-environmental quality in study area.