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Driven piles are used in many geological environments as a practical and convenient structural component. Hence, the determination of the drivability of piles is actually of great importance in complex geotechnical applications. Conventional methods of predicting pile drivability often rely on simplified physical models or empirical formulas, which may lack accuracy or applicability in complex geological conditions. Therefore, this study presents a practical machine learning approach, namely a Random Forest (RF) optimized by Bayesian Optimization (BO) and Particle Swarm Optimization (PSO), which not only enhances prediction accuracy but also better adapts to varying geological environments to predict the drivability parameters of piles (i.e. maximum compressive stress, maximum tensile stress, and blow per foot). In addition, support vector regression, extreme gradient boosting, k nearest neighbor, and decision tree are also used and applied for comparison purposes. In order to train and test these models, among the 4072 datasets collected with 17 model inputs, 3258 datasets were randomly selected for training, and the remaining 814 datasets were used for model testing. Lastly, the results of these models were compared and evaluated using two performance indices, i.e. the root mean square error (RMSE) and the coefficient of determination (R). The results indicate that the optimized RF model achieved lower RMSE than other prediction models in predicting the three parameters, specifically 0.044, 0.438, and 0.146; and higher R² values than other implemented techniques, specifically 0.966, 0.884, and 0.977. In addition, the sensitivity and uncertainty of the optimized RF model were analyzed using Sobol sensitivity analysis and Monte Carlo (MC) simulation. It can be concluded that the optimized RF model could be used to predict the performance of the pile, and it may provide a useful reference for solving some problems under similar engineering conditions. Graphic Abstract [ABSTRACT FROM AUTHOR]

This paper studied the characteristics of the carbon emission of an industrial wastewater treatment plant (IWWTP) and a domestic WWTP (DWWTP) located in a high-tech industrial park of Shaanxi Province, China. The results showed that the total carbon emissions of the IWWTP and DWWTP were 10.13 kg/t and 1.84 kg/t in 2020, respectively. Indirect carbon emissions play a dominant role in the total carbon emission of the IWWTP, which accounts for about 97.6% of the total amount. The direct carbon emissions of greenhouse gases (e.g., CH4, N2O) account for about 62% of the total carbon emissions in the DWWTP, followed by the indirect carbon emissions generated by electricity consumption (31.06%) and chemical consumption (6.94%). Additionally, the centralized recycling and re-utilization of the wastewater could achieve 1.06 kg/t and 1.16 kg/t of carbon emission reduction in the IWWTP and DWWTP, respectively, while the carbon emissions of the DWWTP are inversely proportional to the treatment capacity. Therefore, it is of great value to collect and utilize intensively the recycled water to achieve the goal of regional carbon emission reduction and carbon neutralization of WWTPs in industrial parks. [ABSTRACT FROM AUTHOR]

To analyze the operation risk of check dams under extreme precipitation conditions, taking Ningxia area as an example, this paper carried out a risk assessment of check dams under extreme precipitation conditions in Ningxia through data collection, hydrological statistics, numerical simulation, and other methods. The conclusions are the following: (1) By the end of 2020, about 40% of the silt reservoir capacity of check dams in various water and soil conservation zones in Ningxia has been accumulated. During 1966–2020, the extreme precipitation and frequency of extreme precipitation in Ningxia increased while the intensity of extreme precipitation decreased. The extreme precipitation in Ningxia increased year by year and lasted longer. (2) Under two future scenarios of RCP4.5 (the full name of RCP is Representative Concentration Pathway) and RCP8.5, the extreme precipitation threshold in Ningxia is gradually decreasing from south to north. Extreme precipitation in the future will bring high risk to the operation of check dams in Ningxia. The results of this paper can provide a scientific basis for the operation and management of check dams in Ningxia. [ABSTRACT FROM AUTHOR]

Prefabricated building holds promise for quality, efficiency, and sustainability when compared to traditional techniques. However, realizing prefabricated building work hinges on strengthening supply chain resilience. This research assesses interdependent risks undermining prefab network continuity during disruption. Questionnaire data from industry experts informed a structural equation model quantifying pathways between component production, construction, information, and other uncertainties. Findings confirm that project delays can be traced to manufacturing and on-site risks, with information gaps broadly propagating impacts. Meanwhile, organizational risks have an insignificant influence, suggesting partnership networks readily reconfigure around operational contingencies. Robust information infrastructures and coordination, therefore, offer crucial leverage. Accordingly, a multidimensional resilience enhancement strategy is formulated, prioritizing supply chain transparency, digital integration, inventory buffering, contingencies planning, and transportation flexibility. Our mixed-methods approach advances the construction literature by demonstrating the applicability of structural equation modeling for diagnostic resilience analytics. Industry leaders also gain actionable, evidence-based guidance on strategic investments to stabilize project flows. This dual theoretical and practical contribution underscores the versatility of tailored statistical assessments in furthering construction innovation objectives within complex, uncertain environments. [ABSTRACT FROM AUTHOR]

Sewage treatment carbon emissions are one of the notable sources of total carbon emission in industrial parks. In order to explore the evolutionary characteristics of sewage treatment carbon emission in industrial parks and its coupling relationship with industrial economic development, based on the quarterly sewage quality monitoring data and regional economic development data of an energy and chemical industry park in Northern Shaanxi from 2016 to 2020, this paper analyzes the evolutionary characteristics of sewage treatment carbon emissions and the coupling relationship between economic development in the industrial parks by using the Intergovernmental Panel on Climate Change carbon emission accounting method and the coupling coordination degree model. The results show that the total carbon emission of sewage treatment in the industrial parks is increasing year by year, and the indirect carbon emissions occupy the dominant position. In 2020, the direct and indirect carbon emissions in the sewage treatment process accounted for 2.4% and 97.6% of the total carbon emission, respectively. It was found that the coupling and coordination relationship between sewage treatment carbon emissions and the economy has experienced the transformation process of serious imbalance—lagging economic development, lagging carbon emission and lagging economic development. In the past five years, the coordinated development degree of the two systems has increased year by year, and the benign mutual feedback mechanism between the two systems has gradually formed. However, regional economic development has lagged due to the impact of the COVID-19 epidemic, so speeding up regional economic development while protecting the environment is recommended. [ABSTRACT FROM AUTHOR]

Vegetation cover is an important indicator reflecting changes in terrestrial ecosystems and plays an important role in regulating and maintaining ecosystem stability. To investigate the spatial and temporal variations in the NDVI (normalized difference vegetation index) and their intrinsic driving influences, this paper uses trend analysis and a barycentric model to study the temporal and spatial variation characteristics of vegetation in the Jialing River Basin from 2000 to 2020, constructs PLS-SEMs (partial least squares structural equation models), analyzes the indirect and direct effects of latent and observable variables of surface, human activities, and climate on vegetation growth, and explores the driving processes of different levels of NDVI. The vegetation center gradually migrates northwards. The impact of surface factors on the NDVI is mainly direct and positive. The impact of human activities on the NDVI is mainly direct and negative. The impact of climate factors on the NDVI is mainly positive. The driving mechanisms of low and medium NDVI are relatively similar but tend to be opposite to those of high NDVI. Medium and high NDVI values are more influenced by observable variables. The research on vegetation change and its driving factors, through indirect and direct paths, illustrates the driving processes of different latent and observable variables of the NDVI in more detail and provides a theoretical basis for the implementation of ecological restoration projects and construction of ecological civilizations in the future. [ABSTRACT FROM AUTHOR]

Hongjiannao is the largest inland lake in China's deserts. In recent years, the water quality and area of the Hongjiannao Lake have continued to decline, which is closely associated with the economic development in the Hongjiannao basin. To explore the coupling relationship between the water quality and economic development in the Hongjiannao basin, the water quality and economic development index of the basin has been analyzed in terms of the monthly water quality and socio-economic development from 2013 to 2020. The coupling relationship and interaction mechanism between water quality and regional economic development has been studied by coupling coordination degree model. The results show that the water pollution increased and then decreased with the seasons, while the water quality was the worst in the summer. The coordinated degree between the water quality and economic development in Hongjiannao shows an upward trend from 2013 to 2020, which has transformed from the process of lagging economic development to the process of primary coordination, finally to the process of lagging water environment. The coupling relationship between water quality and economic development changed from a state of nearly un-coordination to primary coordination from 2013 to 2016, with economic development lagging behind. The coupling relationship between the two systems changed from barely coordinated to the primary coordinated from 2017 to 2018, with the rapid development of economy and slight decline in water quality. After 2018, those two systems gradually stepped into a virtuous cycle during 2019–2020, but the phenomenon of lagging water quality still existed. Therefore, in order to maintain the stable economic development of resource-based cities, it is necessary to keep improving the current situation of water environment and water shortage in Hongjiannao, which will promote the coordinated and sustainable development of water environment and economy. [ABSTRACT FROM AUTHOR]

The construction industry plays a pivotal role in energy conservation and emission reduction. Therefore, it is of great significance to conduct research on quantifying carbon emissions in this industry to accelerate the establishment of a standardized carbon emission accounting system and achieve the goals of carbon peak and carbon neutrality. In this study, the focus is on the building materialization stage, and a carbon emission accounting system is established using the carbon emission factor method. This system is applied to calculate the carbon emissions of 15 residential buildings in Shaanxi Province. Results indicate that the carbon concentration during the materialization stage ranges from 372.43 kgCO2/m2 to 525.88 kgCO2/m2, and the building material production stage accounts for 94.27% of the total emissions. Additionally, by analyzing the carbon emission composition of the sample buildings, the primary factors that influence carbon emissions during the residential building materialization stage are identified, and corresponding carbon reduction strategies are proposed. The sensitivity coefficients of carbon reduction strategies vary significantly across different stages, with the building material production stage exhibiting the highest sensitivity coefficient. Thus, it is imperative to prioritize carbon reduction strategies that target the building material production stage. [ABSTRACT FROM AUTHOR]

As the primary ecological construction measure on the Loess Plateau, check dams play an essential role in developing agricultural production, improving people's production and life, and replenishing groundwater. Soil water infiltration is the most important way to replenish groundwater in the dam land. In order to investigate the water infiltration process of check dams, an empirical model suitable for the simulation of the dam land infiltration process was selected. The soil water infiltration process of the check dam was studied by a field test and a model simulation. The results showed that there were few macropores in the dam, and the water mainly moved downwards in the form of matrix flow. Moreover, the stable infiltration rate of the dam site was low, and its infiltration process could be divided into three stages: rapid infiltration, fluctuating infiltration, and stable infiltration. In addition, the infiltration rate of a non-silted dense layer was 2.4~5 times that of a silted dense layer. The Horton model had a good fitting effect on the water infiltration process of the check dam and thus was suitable for the simulation and prediction of the water infiltration process of the dam. The results can provide a theoretical basis for efficient soil water utilization and infiltration simulation of check dam land. [ABSTRACT FROM AUTHOR]

In recent years, global warming has attracted great attention around the world. Temperature change is not only involved in global climate change but also closely linked to economic development, the ecological environment, and agricultural production. In this study, based on temperature data recorded by 756 meteorological stations in China during 1951–2013, the spatial and temporal stability characteristics of annual temperature in China and its first-level basins were investigated using the rank correlation coefficient method, the relative difference method, rescaled range (R/S) analysis, and wavelet transforms. The results showed that during 1951–2013, the spatial variation of annual temperature belonged to moderate variability in the national level. Among the first-level basins, the largest variation coefficient was 114% in the Songhuajiang basin and the smallest variation coefficient was 10% in the Huaihe basin. During 1951–2013, the spatial distribution pattern of annual temperature presented extremely strong spatial and temporal stability characteristics in the national level. The variation range of Spearman's rank correlation coefficient was 0.97–0.99, and the spatial distribution pattern of annual temperature showed an increasing trend. In the national level, the Liaohe basin, the rivers in the southwestern region, the Haihe basin, the Yellow River basin, the Yangtze River basin, the Huaihe basin, the rivers in the southeastern region, and the Pearl River basin all had representative meteorological stations for annual temperature. In the Songhuajiang basin and the rivers in the northwestern region, there was no representative meteorological station. R/S analysis, the Mann-Kendall test, and the Morlet wavelet analysis of annual temperature showed that the best representative meteorological station could reflect the variation trend and the main periodic changes of annual temperature in the region. Therefore, strong temporal stability characteristics exist for annual temperature in China and its first-level basins. It was therefore feasible to estimate the annual average temperature by the annual temperature recorded by the representative meteorological station in the region. Moreover, it was of great significance to assess average temperature changes quickly and forecast future change tendencies in the region. [ABSTRACT FROM AUTHOR]

In order to study quantitative indexes and characteristics of soil erosion on the Loess Plateau, degree of complexity and stability of erosion patterns are discussed. The fractal characteristics of soil erosion spatial patterns in the Dalihe River basin were evaluated by combining them with measurements extracted from the soil erosion database of the Loess Plateau, illustrated using GIS. Results demonstrate that fractal characteristics of spatial patterns of soil erosion intensity are obvious in the Dalihe River basin. Indeed, the results show that fractal dimension reflects the degree of soil erosion complexity at certain scales of observation, is indirectly related to soil erosion degree of complexity at certain scales of observation, which indirectly corresponds to the level of difficulty to implement soil-water erosion management. In addition, the fractal characteristics of soil erosion spatial patterns in the Dalihe River basin show that patch shapes correspond with size. In other words, when the patch size is about 0.2 km², scale conversion is observed in spatial patterns of soil erosion intensity and complexity of patch shape also changes. However, at patch sizes greater than 0.2 km², the two dimensional feature was gradually enhanced for a single patch, while with the patch size less than 0.2 km², the point feature was gradually enhanced. Thus, the order of complexity in spatial patterns of soil erosion intensities in the Dalihe River basin is drastic erosion > extreme erosion > serious erosion > moderate erosion, and thus the order of priorities for the implementation of management controls on soil erosion should be moderate erosion > serious erosion > extreme erosion > drastic erosion. [ABSTRACT FROM AUTHOR]

Large-scale vegetation restoration in China's Loess Plateau has been initiated by the central government to control soil and water losses since 1999. Knowledge of the spatio-temporal distribution of soil water storage (SWS) is critical to fully understand hydrological and ecological processes. This study analysed the temporal stability of the SWS pattern during the rainy season on a hillslope covered with Chinese pine ( Pinus tabulaeformis Carr.). The soil water content in eight soil layers was obtained at 21 locations during the rainy season in 2014 and 2015. The results showed that the SWS at the 21 locations followed a normal distribution, which indicated moderate variability with the coefficients of variation ranging from 14 to 33%. The mean SWS was lowest in the middle slope. The spatial pattern of SWS displayed strong temporal stability, and the Spearman correlation coefficient ranged from 0.42 to 0.99 ( p < 0.05). There were significant differences in the temporal stability of SWS among different soil layers ( p < 0.01). The spatial patterns of SWS distribution showed small differences in different periods. The best representative locations of SWS were found at different soil depths. The maximum RMSE and MAE at 0-1.6 m soil depth for the rainy season were 4.27 and 3.54 mm, respectively. The best representative locations determined during a short period (13 days) can be used to estimate the mean SWS well for the same rainy season, but not for the next rainy season. Samples of SWS collected over a fortnight during the rainy season were able to capture the spatial patterns of soil moisture. Roots were the main factor affecting the temporal stability of SWS. Rainfall increased the temporal stability of the soil water distribution pattern. In conclusion, the SWS during the rainy season had a strong temporal stability on the forestland hillslope. [ABSTRACT FROM AUTHOR]

Ren, Z.; Feng Z.; Li, P.; Wang, D.; Cheng, S., and Gong J., 2017. Response of runoff and sediment yield from climate change in the Yanhe watershed, China. In: Zhi, Y. and Guido Aldana, P.A. (eds.), Sustainability of Water Resources and the Development of Coastal Environments: Select Proceedings from the 2016 International Conference on Water Resource and Environment (WRE2016). Journal of Coastal Research, Special Issue No. 80, pp. 30-35. Coconut Creek (Florida), ISSN 0749-0208. Changes in temperature and precipitation in the Loess Plateau, China have been studied for many years. The runoff and sediment yield in the Loess Plateau are sensitive to global climate change. Understanding the characteristics of runoff and sediment will be of great importance in the future. The Soil and Water Assessment Tool (SWAT) was used to simulate the runoff and the sediment yield in the Yanhe watershed, a typical water basin with soil erosion in the Loess Plateau. The resulting statistics of the SWAT simulation of the runoff and sediment yield were acceptable. The rainfall for the period from 2010 to 2099, as predicted by the Statistical Down Scaling Model (SDSM), was used to simulate the runoff and sediment yield in the future, using SWAT. Compared with the period from the 1980 to 2000, the annual precipitation increased by 9.2% to 16.4%. Under simulated future climate change, the annual runoff of the Yanhe watershed changes averaged −2.6% to 52.7%, compared with the baseline period. In the context of future climate change, in general, the runoff distribution was more even within the year when it increased significantly from March to May and decreased from July to August. The variations of the sediment yield for the watershed were −31.3% to 62.5% compare with the period from the 1980 to 2000. Overall, the trends of the sediment yield for the watershed were consistent with the runoff. [ABSTRACT FROM AUTHOR]

Soil salinization is currently a constraint on agriculture development in irrigated areas throughout the world. This study was conducted to examine the temporal stability and periodicity of groundwater electrical conductivity (EC) in irrigation districts. To accomplish this, 51 observation wells were selected for analysis of groundwater EC. Relative difference analysis and the non-parametric Spearman rank correlation test were used to check EC temporal stability, while the Morlet wavelet analysis was applied to measure the periodic variation of groundwater EC and groundwater level of high and low salinity wells. The mean groundwater EC of the 51 wells did not show an increasing trend over the entire measurement period, but demonstrated a moderate spatial variability, with coefficient of variation values ranging from 61 to 72%. The groundwater EC exhibited a strong temporal stability with Spearman correlation coefficients ranging from 0.81 to 0.98. The mean EC representative location in the study area was well 2, showing a good relationship between groundwater EC and groundwater level. Changes in groundwater EC were mainly affected by lateral groundwater recharge sources in small time scales. However, the groundwater EC and groundwater level always showed an obviously inverse phase with a large time scale due to precipitation effects. In conclusion, the groundwater EC, lateral recharge sources, and irrigation time should be fully considered in irrigation to avoid soil salinization. [ABSTRACT FROM AUTHOR]

Phosphorus is an essential and common limiting element for plants. Phosphorus losses from agricultural production systems are known to contribute to accelerated eutrophication of natural waters. In this study, soil available phosphorus (SAP) content and SAP density were estimated based on a soil survey of a small watershed in the Dan River, China, and the spatial heterogeneity of SAP distribution and the impacts of land-use types, elevation, slope and aspect on SAP were assessed. Field sampling was carried out based on a 100 m × 100 m grid system overlaid on the topographic map of the study area, and samples were collected in three soil layers to a depth of 40 cm. A total of 190 sites were sampled, and 539 soil samples were collected. The results showed that classical kriging could successfully interpolate SAP content in the watershed. SAP content showed a downward trend with the increase in soil depth and the extent of SAP variability in the three soil layer is moderate. There were significant differences among the three soil layers ( P < 0.01). The land use had a great impact on the SAP content. ANOVA indicated that the spatial variation of SAP contents under different land-use types was significant ( P < 0.01). The SAP density of different land-use types followed the order of cropland > forestland > grassland. The mean SAP density of cropland, forestland and grassland at a depth of 0-40 cm was 4.28, 3.74 and 2.81 g/m, respectively. SAP and topographic factors showed that SAP content increased with decreasing altitude and slope gradient. The soil bulk density played a very important role in the assessment of SAP density. In conclusion, the soils in the source area of the middle Dan River would reduce SAP with conversions from cropland to forest or grassland. [ABSTRACT FROM AUTHOR]

Soil phosphorus is a major determinant and indicator of soil fertility and quality, and is also a source of nonpoint-source pollution. In order to control soil and water loss in the Loess Plateau, a series of soil and water conservation measures have been taken, resulting in changes in land use and differences in spatial distribution. It is necessary to study soil available phosphorus (SAP) to evaluate land productivity and environmental quality. In this study, the spatial distribution of SAP in different land uses was investigated in a small catchment area of Loess Plateau, and the field-influencing factors were determined on five layers with soil depth of 20 cm. The results show the minimum and maximum SAP content occurred at 20–40 cm and 80–100 cm soil depth and reach a value of 27.26 mg/kg and 29.37 mg/kg at catchment scale, respectively. There is significant difference among the SAP of the five soil layers (p < 0.01). The SAP of different land uses is, in order: forestland < slope farmland < dam farmland < terrace < grassland. Different land uses' topographies make a difference to the spatial distribution of SAP. Slope and soil texture are the domain factors influencing the SAP concentration at the catchment. [ABSTRACT FROM AUTHOR]

The construction of terraces and vegetation restoration in the hillslope are major soil and water conservation measures on the Chinese Loess Plateau and contributed to the distribution patterns of soil organic carbon (SOC) and soil total nitrogen (STN). Topography influences soil erosion and changes SOC and STN contents. However, little information is available regarding the effects of ecological construction and topography on SOC and STN. A study was undertaken in the Loess Plateau, to evaluate the effects of land use conversion and topographic factors on the topsoil SOC and STN content at three hillslope positions (upper, middle, and foot slopes) under four land uses types: artificial forest, grassland, terraced fields, and sloping cropland. The results showed that land use conversion from sloping cropland to artificial forest and grassland improved the SOC and STN content. Slope position was an important topographic factor governing the SOC and STN distribution at the slope scale in artificial forest, grassland, and sloping cropland, with the foot slope having the highest SOC and STN content, followed by the upper slope, while the middle slope had the lowest values. SOC and STN showed positive correlation with Caesium-137 (137Cs) content. Land use types, slope position, and soil erosion had significant relationships with SON and STN. The results suggested that vegetation restoration of sloping cropland will contribute to soil carbon (C) and nitrogen (N) sequestration in the loess hilly region. The quantitative estimation of land use change and topography effects on SOC and STN could improve the accuracy of SOC and STN predictions in the region with a complex topography. [ABSTRACT FROM AUTHOR]

Soil properties are influenced by freeze-thaw, which in turn influences soil erosion. Despite this, only a few studies have investigated the impacts on soil hydrodynamic processes. The objective of this study was to evaluate the impact of soil freezing conditions on runoff, its energy consumption, and soil erosion. A total of 27 laboratory-concentrated meltwater flow experiments were performed to investigate the soil erosion rate, the runoff energy consumption, and the relationship between the soil erosion rate and runoff energy consumption by concentrated flow under combinations of three flow rates (1, 2, and 4 L/min) and three soil conditions (unfrozen, shallow-thawed, and frozen). The individual and combined effects of soil condition, flow rate, and runoff energy consumption on the soil erosion rate were analyzed. For the same flow rate, the shallow-thawed and frozen slope produced mean values of 3.08 and 4.53 times the average soil erosion rates compared to the unfrozen slope, respectively. The number of rills in the unfrozen soil slope were 4, 3, and 2 under the flow rate of 1, 2, and 4 L/min, respectively. The number of rills in the thawed-shallow and frozen soil slope were all 1 under the flow rate of 1, 2, and 4 L/min. The rill displayed disconnected distribution patterns on the unfrozen slope, but a connected rill occurred on the shallow-thawed and frozen slopes. The average rill width on unfrozen, thawed-shallow, and frozen soil slopes increased by 1.87 cm, 4.38 cm, and 1.68 cm as the flow rate increased from 1 L/min to 4 L/min. There was no significant difference in the rill length on the frozen slope under different flow rates (p > 0.05). The runoff energy consumption ranged from unfrozen > shallow-thawed > frozen slopes at the same flow rate. The soil erosion rate had a linear relationship with runoff energy consumption. The spatial distribution of the runoff energy implied that soil erosion was mainly sourced from the unfrozen down slope, shallow-thawed upper slope, and frozen full slope. [ABSTRACT FROM AUTHOR]