Search Results (13)

Pipe-jacking construction technology is favored in urban construction due to its advantages of high safety and being a non-excavation technique. However, instability of the tunnel face often occurs due to unfavorable conditions, such as pipe jacking across the river channel, shallow soil cover, and improper control of the support pressure. In this study, we made a use of the limit balance method and mud–water balance theory. At this moment of passive damage and active destruction occurring at the pipe-jacking tunnel face, the general mathematical expressions of the tunnel-face support pressure (with lower limit value P_min and upper limit value P_max) are derived. In the non-river impact area and river impact area, the optimal value P_o of support pressure at the tunnel face is thus derived. Then, based on the Y25-Y26 pipe-jacking project across the Chu River channel in Hefei North District, a numerical simulation method is used to support further discussion. The results indicate that, when the river overburden is 3 m, the ultimate support pressure calculated by means of numerical simulation is 881.786 kN, and the optimal support ratio $\mathsf{\lambda }$ is taken in the interval of 1.0~1.5. Secondly, the upper limit value P_max, lower limit value P_min, and optimum value P_o calculated using the theoretical equations are 2669.977 kN, 309.910 kN, and 1044.870 kN, respectively. These results leads us to recommend setting the support pressure of the tunnel face in a reasonable range between the upper limit value P_max and the lower limit value P_min, to ensure that the tunnel-face support pressure and resistance during pipe jacking always remain in a balanced state. The relevant research results from this study provide an important technical guarantee for the successful implementation of the examined project and, at the same time, can serve as a reference example for similar projects. Full article

Swimming is crucial to fish survival and reproduction, and is usually influenced by species, morphology, habitat environment and physiological condition. Understanding the changes in fish swimming ability and identifying the driving factors behind these changes is vital. In this study, seven endemic fish species from the Qingshui River, an important tributary of the upper Pearl River in Southwest China, were used to explore the effects of biological and environmental factors on fish swimming ability. The results indicated that the body length parameters had a minimal effect on the induced swimming speed (U_ind) but played a positive role in critical and burst swimming ability (U_crit and U_burst). Weight (W) and W/SL (the ratio of weight to standard body length) correlated more highly with swimming ability than body length parameters. Fish preferring the lotic environment exhibited higher U_crit and U_burst, and fish with a streamlined morphology had a smaller U_ind. The U_ind, U_ind/SL, U_ind/W and U_ind/(W/SL) of Discogobio yunnanensis (Regan, 1907) and Pseudocrossocheilus tridentis (Cui & Chu, 1986) were significantly higher during the spawning period. Acrossocheilus yunnanensis (Regan, 1904) performed better during the spawning period in U_crit and U_crit/SL. The U_burst of fish during the spawning period was smaller than that during the non-spawning period. Generally, the species difference had the greatest contribution to the swimming ability difference, followed by environmental conditions and fish morphology. Full article

Toponyms reflect the multifaceted relationship between humans and nature, recording and transmitting important cultural information. A toponymic cultural landscape (TCL) is the comprehensive embodiment of the cultural connotations and landscape significance carried by toponyms, reflecting various factors such as regional culture, historical memory, and social values. Wuhan, as the hinterland of Jing-Chu culture, carries a profound geo-culture and brings together numerous toponymic cultural heritages. Studying the spatial distribution characteristics of Wuhan’s toponymic cultural heritage and their association with landscape elements is of great significance in promoting the inheritance of intangible cultural heritage and realizing the orderly continuation of local culture, and it also confers deeper cultural connotations and local characteristics to the process of landscape characterization. This study analyzes 3638 toponyms in Wuhan as the research objects, utilizing geospatial analysis methods, including kernel density analysis, standard deviation ellipse analysis, and average nearest neighbor analysis, to visualize the spatial distribution of Wuhan’s TCL. It further combines these methods with the optimal parameter geographic detector (OPGD) model to explore the influence of landscape elements on the spatial distribution of different types of toponyms and their interaction effects. The results show the following: (1) The TCL of Wuhan is divided into two basic types, the natural landscape (61.16%) and the humanistic landscape (41.37%), of which hydrological-related toponyms occupy a significant proportion, reaching 35.02% of the total number of toponyms in Wuhan. (2) The distribution of Wuhan’s TCL is characterized by aggregation, mostly in the core area of the city, with the Yangtze River as the main axis, and the density of the spatial distribution of humanistic landscape toponyms varies greatly. (3) The results of a single-factor analysis show that construction land (X2) is an important influencing factor in both natural and humanistic landscape toponyms, which indicates the central role of human activities in the formation of toponyms. (4) The explanatory power of the interaction effect of two factors on the spatial differentiation of Wuhan’s TCL is stronger than that of the single factors, which suggests that the spatial differentiation characteristics of the TCL of Wuhan are formed under the joint influence of the respective variables. Full article

This research aimed to analyze the relationship between deforestation (DFT) and climatic variables during the rainy (CHU+) and less-rainy (CHU−) seasons in the Tapajós River basin. Data were sourced from multiple institutions, including the Climatic Research Unit (CRU), Center for Weather Forecasts and Climate Studies (CPTEC), PRODES Program (Monitoring of Brazilian Amazon Deforestation Project), National Water Agency (ANA) and National Centers for Environmental Prediction/National Oceanic and Atmospheric Administration (NCEP/NOAA). The study assessed anomalies (ANOM) in maximum temperature (TMAX), minimum temperature (TMIN) and precipitation (PREC) over three years without the occurrence of the El Niño–Southern Oscillation (ENSO) atmospheric–oceanic phenomenon. It also examined areas with higher DFT density using the Kernel methodology and analyzed the correlation between DFT and climatic variables. Additionally, it assessed trends using the Mann–Kendall technique for both climatic and environmental data. The results revealed significant ANOM in TEMP and PREC. In PREC, the highest values of ANOM were negative in CHU+. Regarding temperature, the most significant values were positive ANOM in the south, southwest and northwestern regions of the basin. Concerning DFT density, data showed that the highest concentration was of medium density, primarily along the highways. The most significant correlations were found between DFT and TEMP during the CHU− season in the Middle and Lower Tapajós sub-basins, regions where the forest still exhibits more preserved characteristics. Furthermore, the study identified a positive trend in TEMP and a negative trend in PREC. Full article

With the rapid development of IoT, big data and artificial intelligence, the research and application of data-driven hydrological models are increasing. However, when conducting time series analysis, many prediction models are often directly based on the following assumptions: hydrologic time series are normal, homogeneous, smooth and non-trending, which are not always all true. To address the related issues, a solution for short-term hydrological forecasting is proposed. Firstly, a feature test is conducted to verify whether the hydrological time series are normal, homogeneous, smooth and non-trending; secondly, a sequence-to-sequence (seq2seq)-based short-term water level prediction model (LSTM-seq2seq) is proposed to improve the accuracy of hydrological prediction. The model uses a long short-term memory neural network (LSTM) as an encoding layer to encode the historical flow sequence into a context vector, and another LSTM as a decoding layer to decode the context vector in order to predict the target runoff, by superimposing on the attention mechanism, aiming at improving the prediction accuracy. Using the experimental data regarding the water level of the Chu River, the model is compared to other models based on the analysis of normality, smoothness, homogeneity and trending of different water level data. The results show that the prediction accuracy of the proposed model is greater than that of the data set without these characteristics for the data set with normality, smoothness, homogeneity and trend. Flow data at Runcheng, Wuzhi, Baima Temple, Longmen Town, Dongwan, Lu’s and Tongguan are used as input data sets to train and evaluate the model. Metrics RMSE and NSE are used to evaluate the prediction accuracy and convergence speed of the model. The results show that the prediction accuracy of LSTM-seq2seq and LSTM-BP models is higher than other models. Furthermore, the convergence process of the LSTM-seq2seq model is the fastest among the compared models. Full article

Lacquered wooden sculptures of fantastic hybrid beasts adorned with real deer antlers are among the most extraordinary examples of sculpture found in Chu tombs dated from the sixth through the third centuries BCE. Conventionally known as zhenmushou 镇墓兽 or “protecting tomb beasts”, the antlered sculptures have grotesque features, including bulging eyes, fangs, and protruding tongues. In the fourth century BCE, production and use of these sculptures increased and peaked in the Hanxi region of Hubei province. Although most of these figures have been found in tombs in Hanxi (west of the Han River), distinctive variations of antlered tomb sculptures are also documented in regional areas of the Chu polity, including the Nanyang Basin, the Upper Huai, Eastern Hubei, and Jiangnan. Through a systematic regional analysis of Chu antlered sculptures, this paper presents a spatial framework for analyzing this unique genre of Chu funerary sculpture. This approach provides fresh insight into the interregional networks of interaction across the Chu state and beyond, via waterways and the Suizao corridor from the sixth through the third centuries BCE. Full article

Thanks to the large scope, high spatial resolution, and increasing data records, satellite-based precipitation products are playing an increasingly important role in drought monitoring. First, based on the data from ground sites, the long-term Multi-Source Weighted-Ensemble Precipitation (MSWEP) precipitation product was evaluated in respect to drought monitoring. Then, based on the MSWEP product, the drought trends and the spatiotemporal characteristics of the drought events in four major basins (Amu Darya Basin, Syr Darya Basin, Chu-Talas River Basin, and Ili River Basin) in Central Asia, which have relatively dense gauge sites, were studied. The Standardized Precipitation Index (SPI) and the run theory were used to identify drought events and describe their characteristics. The results showed that MSWEP can effectively capture drought events and their basic characteristics. In the past 40 years, the study area experienced 27 drought events, among which the severest one (DS = 15.66) occurred from June 2007 to September 2008. The drought event that occurred from June 1984 to October 1984 had a drought peak value of 3.39, with the largest drought area (99.2%). Since 1881, there appeared a drying trend and a wetting trend in the Amu Darya River basin and the Ili River basin, respectively. No obvious wetting or drying trend was found in both the Chu-Talas River basin and the Syr Darya basin. Since 2016, the drought area has been on the increase. Full article

The literary representation of China’s great rivers has repeatedly been transformed by changes in religious belief and ritual. In the Book of Songs, rivers figure primarily as political boundaries and figures of separation. Though they may already play a role in religious rites, their geographical identity is paramount. However, in the “Nine Songs” of the Elegies of Chu, they appear in a new guise as sites of divine encounter and shamanistic flight. Their treatment in later works may be regarded as a peculiar synthesis of these two traditions. Once the Four Waterways were designated as the object of state ritual in the Western Han, their divine status was widely accepted, along with explicitly political ramifications. For instance, the god of the Yellow River was honored as a participant in flood control and imperial governance writ large. Meanwhile, the tradition of the epideictic fu also celebrates the awesome scale of China’s waterways, reaching a culmination not long after the fall of the Han in Guo Pu’s (286–324) “Rhapsody on the Yangzi River”. However, it is noteworthy how often the fu tradition eschews material description of rivers in favor of celebrating their numinous powers and divine inhabitants. Because of this turn towards the divine in the medieval literary tradition, it is no accident that one of the most prominent subjects of fluvial verse in the Tang is not body of water at all but rather the Sky River, or Milky Way. Full article

The frequency of glacier lake outbursts floods (GLOFs) is likely to increase with the ongoing glacier retreat, which produces new glacial lakes and enlarges existing ones. Here, we simulate the outburst of a potentially dangerous glacial lake in Bhutan by applying hydrodynamic modelling. Although the lake volume is known, several parameters connected to the dam breach and the routing of the flood are rough estimates or assumptions, which introduce uncertainties in the results. For this reason, we create an ensemble of nine outburst scenarios. The simulation of magnitude and timing of possible inundation depths is an important asset to prepare emergency action plans. For our case study in the Mo Chu River Basin, the results show that, even under the worst case scenario, little damage to residential buildings can be expected. However, such an outburst flood would probably destroy infrastructure and farmland and might even affect the operation of a hydroelectric powerplant more than 120 km downstream the lake. Our simulation efforts revealed that, by using a 30-m elevation model instead of a 5-m raster, flood magnitude and inundation areas are overestimated significantly, which highly suggests the use of high-resolution terrain data. These results may be a valuable input for risk mitigation efforts. Full article

In contrast to other fields, environmental protection (e.g., habitat protection) often fails to include quantitative evaluation as part of the existing environmental impact assessment (EIA) process, and therefore the EIA is often a poor forecasting tool, which makes selecting a reasonable plan of action difficult. In this study, we used the Habitat Evaluation Procedure (HEP) to quantify the long-term effects of a road construction project on an ecosystem. The water deer (Hydropotes inermis) was selected as the species of study since it uses an optimum habitat; water deer habitat data were collected on vegetation cover, stream water density, geographic contour, land use class, and road networks. The Habitat Suitability Index (HSI) and Cumulative Habitat Unit (CHU) values for the water deer were estimated to investigate the major land cover classes, the national river systems, and vegetation cover. Results showed that the environmental impact in the road construction project area would result in a net ecological loss value of 1211 without installation of an eco-corridor, which reduced to 662 with an eco-corridor, providing a 55% increase in the net value after 50 years of the mitigation plan. Comparing the 13 proposed ecological mitigation corridors, the corridor that would result in the highest net increase (with an increase of 69.5), was corridor #4, which was regarded as the most appropriate corridor to properly connect water deer habitat. In sum, the study derived the net increase in quantitative values corresponding with different mitigation methods over time for a road construction project; this procedure can be effectively utilized in the future to select the location of ecological corridors while considering the costs of constructing them. Full article

The Chu River is one of the most important rivers in arid Central Asia. Its discharge is affected by climate change. Here, we establish a tree-ring chronology for the upper Chu River Basin and analyze the relationships between radial growth, climate, and discharge. The results show that the radial growth of Schrenk spruce (Picea schrenkiana Fisch. et Mey.) is controlled by moisture. We also reconstruct a 175-year standardized precipitation-evapotranspiration index (SPEI) for the Chu River Basin. A comparison of the reconstructed and observed indices reveal that 39.5% of the variance occurred during the calibration period of 1952–2014. The SPEI reconstruction and discharge variability of the Chu River show consistent long-term change. They also show that the Chu River Basin became increasingly dry between the 1840s and the 1960s, with a significant drought during the 1970s. A long and rapid wetting period occurred between the 1970s and the 2000s, and was followed by increasing drought since 2004. The change in the SPEI in the Chu River Basin is consistent with records of long-term precipitation, SPEI and Palmer Drought Severity Indices (PDSI) in other proximate regions of the western Tianshan Mountains. The hydroclimatic change of the Chu River Basin may be associated with westerly wind. This study is helpful for disaster prevention and water resource management in arid central Asia. Full article

Snowmelt from the Tianshan Mountains (TS) is a major contributor to the water resources of the Central Asian region. Thus, changes in snow phenology over the TS have significant implications for regional water supplies and ecosystem services. However, the characteristics of changes in snow phenology and their influences on the climate are poorly understood throughout the entire TS due to the lack of in situ observations, limitations of optical remote sensing due to clouds, and decentralized political landscapes. Using passive microwave remote sensing snow data from 1979 to 2016 across the TS, this study investigates the spatiotemporal variations of snow phenology and their attributes and implications. The results show that the mean snow onset day (D_o), snow end day (D_e), snow cover duration days (D_d), and maximum snow depth (SD_max) from 1979 to 2016 were the 78.2nd day of hydrological year (DOY), 222.4th DOY, 146.2 days, and 16.1 cm over the TS, respectively. D_d exhibited a spatial distribution of days with a temperature of <0 °C derived from meteorological station observations. Anomalies of snow phenology displayed the regional diversities over the TS, with shortened D_d in high-altitude regions and the Fergana Valley but increased D_d in the Ili Valley and upper reaches of the Chu and Aksu Rivers. Increased SD_max was exhibited in the central part of the TS, and decreased SD_max was observed in the western and eastern parts of the TS. Changes in D_d were dominated by earlier D_e, which was caused by increased melt-season temperatures (T_m). Earlier D_e with increased accumulation of seasonal precipitation (P_a) influenced the hydrological processes in the snowmelt recharge basin, increasing runoff and earlier peak runoff in the spring, which intensified the regional water crisis. Full article

Sound water resources planning and management requires adequate data with sufficient spatial and temporal resolution. This is especially true in the context of irrigated agriculture, which is one of the main consumptive users of the world’s freshwater resources. Existing remote sensing methods for the management of irrigated agricultural systems are often based on empirical cropland data that are difficult to obtain, and that put into question the transferability of mapping algorithms in space and time. Here we implement an automatic irrigation mapping procedure in Google Earth Engine that uses surface reflectance satellite imagery from different sensors. The method is based on unsupervised training of a pixel-by-pixel classification algorithm within image regions identified through unsupervised object-based segmentation, followed by multi-temporal image analysis to distinguish productive irrigated fields from non-productive and non-irrigated areas. Ground-based data are not required. The final output of the mapping algorithm are monthly and annual irrigation maps (30 m resolution). The novel method is applied to the Central Asian Chu and Talas River Basins that are shared between upstream Kyrgyzstan and downstream Kazakhstan. We calculate the development of irrigated areas from 2000 to 2017 and assess the classification results in terms of robustness and accuracy. Based on seven available validation scenes (in total more than 2.5 million pixels) the classification accuracy is 77–96%. We show that on the Kyrgyz side of the Talas basin, the identified increasing trends over the years are highly significant (23% area increase between 2000 and 2017). In the Kazakh parts of the basins the irrigated acreages are relatively stable over time, but the average irrigation frequency within Soviet-era irrigation perimeters is very low, which points to a poor physical condition of the irrigation infrastructure and inadequate water supply. Full article