Search Results (4,798)

In order to explore the applicability of the peanut growth simulation model CSM-CROPGRO-Peanut under conditions of mulched drip irrigation in Xinjiang, and to determine the optimal scenario for parameter estimation and model validation, field experiments were conducted in 2022 and 2023 on the water and nitrogen regulation of peanut. Based on the water requirements during the stages of peanut growth, three irrigation levels (low, medium, and high) and two nitrogen application levels (100% N and 50% N) were set, resulting in six treatments. An additional control treatment (CK) with a medium irrigation level and no nitrogen application was also included. In this study, four different parameter estimation and validation protocols were designed, and different parameter estimation results were obtained using the DSSAT-GLUE parameter estimation module. The results showed that the FL-SH (time between first flower and first pod), FL-SD (time between first flower and first seed), SIZLF (time between first flower and first seed), XFRT (maximum size of full leaf), and WTPSD (maximum weight per seed) parameters exhibited strong variability, with coefficients of variation of 24.33%, 22.9%, 19.78%, 14.47%, and 23.82%, respectively, and were significantly affected by environment–management interactions. Other parameters showed weaker variability, with coefficients of variation that were all less than 10%. The model outputs varied significantly among different parameter estimation protocols. Scenario 3, which used data from the adequate irrigation and adequate fertilization treatment (W3N2) environment across both years for parameter estimation and data from other treatments for validation, showed the highest model calibration and validation accuracy. The average absolute relative error (ARE) and normalized root mean square error (nRMSE) for model calibration and validation were the lowest at 9.1% and 10.1%, respectively. The CSM-CROPGRO-Peanut model effectively simulated peanut growth and development as well as soil moisture dynamics under mulched drip irrigation conditions in Xinjiang, with the highest simulation accuracy observed under full irrigation conditions. The findings provide a basis for using the CSM-CROPGRO-Peanut model to develop suitable irrigation and nitrogen application regimes for peanuts under mulched drip irrigation in Xinjiang. Full article

The ongoing changes in climate and the rapid pace of urbanization are contributing to an alarming increase in the prevalence of urban flooding, which is having a profound impact on the quality of life for residents and the smooth functioning of urban areas. The 1D–2D coupled model is an effective tool for simulating the process of urban flooding, thereby providing a scientific basis for urban planning, flood prevention, and mitigation strategies. The values of numerous parameters within the model not only influence the computational efficiency but also influence the precision of the simulation outcomes. It is of particular significance to ascertain the sensitivity of model parameters. In this study, a 1D–2D coupled model of urban flooding was constructed, and a parameter sensitivity analysis was conducted using the modified Morris method and the Sobol method in two ways, with the amount of waterlogging as the target. The findings indicate that the minimum infiltration rate is the most sensitive parameter in the local sensitivity analysis, whereas the Manning coefficient of the permeable surface area is the most sensitive in the global sensitivity analysis. The research outcomes can facilitate the optimization of the model parameters and enhance the precision and dependability of the model predictions, thereby providing more accurate data support for urban flooding early warning and emergency response. Full article

This paper presents an assessment of potential losses and damage costs to rare coastal plant species of Lake Baikal (UNESCO World Heritage Site) as a result of inundation at high water levels. The lake’s ecosystem is characterized by an exceptional diversity of rare and endemic animal and plant species. The construction of a hydroelectric power plant caused an increase in the water level of Lake Baikal, resulting in the inundation of low-lying coastal areas, the destruction of the coastline, alterations to the hydrological regime, etc. However, there are practically no works devoted to water-level modeling and the assessment of its impact on riparian vegetation, including rare species. We conducted fieldwork to determine the abundance of four vulnerable species and identified inundation zones at different high water levels on the basis of digital elevation models based on aerial photography data. The analysis revealed that at the maximum level of inundation, the number of plant species affected would total 5164, amounting to a financial loss of biodiversity estimated at 3098.4 thousand rubles. To mitigate the projected losses, it is imperative to implement measures that restrict water-level fluctuations above the 457.00 m threshold. The absence of flora as an object of state environmental monitoring, which is not specified in the regulatory legal document, must be rectified in a timely manner. Full article

The urban climate in South China is marked by high complexity and substantial precipitation, posing significant challenges to road performance. This study focuses on the importance of precise climate zoning for urban roads in South China and the application of performance grade (PG) asphalt grading technology to enhance pavement durability. Meteorological data from multiple stations across the region were analyzed to identify key climatic indicators. Using spatial interpolation methods and fuzzy c-means clustering, urban roads were classified into five distinct climate zones. Zone I has the highest temperature; Zone II experiences the lowest temperature, necessitating attention to low-temperature pavement cracking; Zone III exhibits greater temperature variability, requiring consideration of both low-temperature cracking and water stability; Zone IV demonstrates relatively stable climatic conditions; and Zone V receives the highest precipitation, demanding a focus on water stability in pavement design. Trend analysis indicates increasing precipitation across all zones except Zone II and a general rise in minimum temperatures, suggesting a diminishing influence of low-temperature conditions. By integrating the Strategic Highway Research Program temperature conversion method and PG classification technology, this study provides asphalt grade recommendations tailored to each climate zone, addressing diverse environmental challenges and optimizing pavement performance. Full article

In order to enhance the overall power generation efficiency of cascade hydropower, it is essential to conduct modelling optimization of its in-plant operation. However, existing studies have devoted minimal attention to the detailed modelling of turbine operating performance curves within the in-plant economic operation model. This represents a significant challenge to the practical application of the optimization results. This study presents a refined model of a hydraulic turbine operating performance curve, which was established by combining a particle swarm optimization (PSO) algorithm and a backpropagation (BP) neural network. The model was developed using a cascade small hydropower group as an illustrative example. On this basis, an in-plant economic operation model of a cascade small hydropower group was established, which is based on the principle of ’setting electricity by water’ and has the goal of maximizing power generation. The model was optimized using a genetic algorithm, which was employed to optimize the output of the units. In order to ascertain the efficacy of the methodology proposed in this study, typical daily operational scenarios of a cascade small hydropower group were selected for comparison. The results demonstrate that, in comparison with the actual operational strategy, the proposed model and method enhance the total output by 3.38%, 2.11%, and 3.56%, respectively, across the three typical scenarios. This method enhances the efficiency of power generation within the cascade small hydropower group and demonstrates substantial engineering application value. Full article

The global need for balance between energy generated from intermittent renewable sources and the actual demand has introduced severe operational challenges on hydropower, a steady energy source in the current context. Although it has some flexibility in operation by varying flow, head, and speed, the entirety of its operational range must be optimized to be more effective. The non-optimal conditions caused by these operational changes result in flow separation on runner blades that results in low efficiency and can be mitigated with the use of vortex generators. The vortex generators can be designed with the empirical method based on the boundary layer height, and the estimated boundary layer height for the Francis turbine runner blade in this study is 2.5 mm. The selected height of the counter-rotating rectangular vortex generators is 5 mm, and two pairs are attached close to the leading edge of the runner blade on the pressure side. The experimental analysis of the runner is conducted at all operating ranges, and efficiency is compared with the reference case. The reliable increment in efficiency obtained is 0.40% ± 0.22%, measured at a GV opening of 13 degrees (full load) and a reference speed of (333 rpm). Similarly, at the same GV opening, the increment in efficiency is obtained at a high speed (408 rpm) with a value of 1.20% ± 0.40%. However, the efficiency increment at part load and the BEP is not as significant since the values lie within the uncertainty band. Thus, these simple passive devices can be employed, and the streamwise vortices generated can be utilized to reduce the impact of flow separation on the Francis runner blades. Full article

With global urbanization on the rise, China has entered the mid-to-late urbanization stage, and the Cheng-Yu region, as a key economic zone and new urbanization model in China, has faced water environmental issues due to rapid urbanization, while systematic research on the synergy between its urbanization and water environment governance remains scarce. This study explores the spatiotemporal evolution of and optimization strategies for the coupling and coordinated development of urbanization and water environment governance in the Cheng-Yu region. A comprehensive evaluation index system was established to measure the Urbanization Development System (UDS) and Water Environment Governance System (WEGS), and a coupling coordination model was utilized to analyze the spatiotemporal relationships between the two systems from 2013 to 2021. The coupling coordination index of the two systems showed a steady upward trend from 2013 to 2021, evolving from a state of severe imbalance to high-level coordination. Initially, the UDS was relatively low, while the WEGS was higher but grew at a slower rate. After 2019, rapid urbanization caused the UDS to exceed the level of the WEGS, indicating growing environmental pressures. Moreover, there are persistent disparities among cities. Industrial cities like Chengdu, with a high UDS but low WEGS, urgently need to enhance water resource management. In contrast, cities such as Dazhou, which have a high WEGS but low UDS, should make full use of their water resources to drive sustainable urban development. For policymakers, this research provides practical guidelines, such as suggesting targeted investment in water treatment facilities in industrial cities like Chengdu and promoting water-based economic development in cities like Dazhou. It emphasizes the importance of balancing urbanization with environmental sustainability. The findings not only deepen the understanding of the dynamic interactions between urban development and water environment governance but also lay a solid foundation for optimizing future policies in the Cheng-Yu region and other similar areas. Full article

Understanding the potential impact of the Three Gorges Reservoir (TGR) on regional extreme precipitation and its mechanisms is critical for the safe operation of the reservoir and the efficient management of regional water resources. This study uses the regional climate model RegCM4 to conduct a double-nested simulation experiment (50 km to 10 km) from 1989 to 2012, evaluated against the CN5.1 observation dataset. Sensitivity experiments with three different lake area ratios (0%, 20% and 100%) were performed using the sub-grid partitioning method in the Community Land Model Version 4.5 to analyze the spatiotemporal distribution, intensity, and frequency of precipitation under varying TGR water areas. The results show that with a 20% lake area ratio, precipitation slightly decreases, but the impact on extreme precipitation indices is not statistically significant. However, with a 100% lake area ratio, significant decreases in both total and extreme precipitation indices occur. The reduction is primarily driven by the formation of anomalous mountain-valley circulation between the TGR and surrounding mountains, which leads to atmospheric subsidence and reduced convective activity. These findings indicate that while the TGR has a negligible impact on extreme precipitation under its current configuration, the exaggerated sensitivity experiments reveal potential mechanisms and localized effects. This research enhances the understanding of the TGR’s influence on regional extreme precipitation and provides valuable insights for water resource management and reservoir operation. Full article

The gas relay is a common non-electric protection device inside transformers, installed on the connecting pipeline between the transformer oil tank and the oil conservator. When the transformer malfunctions and the oil flow value reaches the heavy gas setting value of the gas relay, a heavy gas alarm is triggered. Therefore, accurately analyzing the heavy gas action characteristics and the setting value of the gas relay directly affects the accuracy of the heavy gas alarm. The BF(Bi-Float) type double float ball gas relay uses steady-state oil flow to calibrate the setting values of heavy gas action. In reality, transformer faults cause transient oil flow. To explore the relationship between the oil flow state and gas relay flow velocity setting values, a dynamic model of the heavy gas action process of BF type double float ball gas relay was first established, and the influence of the oil flow state on the gas relay baffle action process was analyzed. Then, a transient oil flow impact test bench was developed to experimentally study the heavy gas action characteristics of gas relays under different intensities of transient oil flow impact. Theoretical and experimental research results indicate that different oil flow impact states have a significant effect on the flow velocity setting values of gas relays. The flow velocity setting value of the BF type double float ball gas relay used in this study under transient oil flow impact is 0.8 m/s, which is lower than its factory flow velocity setting value of 1 m/s. These research results have positive significance for optimizing the performance of gas relays and improving the operational reliability of power transformers. Full article

The global energy transition is pivotal in mitigating climate change. In Chile, the energy system that includes hydropower faces challenges from prolonged megadroughts, necessitating diversification toward renewable energy sources like solar and wind energy. However, research gaps persist in understanding how these sources can optimally address climate-induced vulnerabilities. This study conducts a bibliometric analysis to identify global research trends on renewable energy strategies under extreme drought conditions, distinguishing it from systematic or narrative reviews. A bibliometric analysis was conducted using Scopus, incorporating 82 selected documents analyzed via Bibliometrix and VOSviewer to map co-authorship networks, keywords, and publications. Results revealed a significant increase in research on solar energy (26.83%) and renewable energy (25.61%) within the study period (2005–2024), with the most notable growth occurring in the last six years. Key findings include the predominance of studies on energy optimization, with solar and wind technologies emerging as pivotal for enhancing resilience in water-scarce regions. These insights underscore the strategic role of renewable energies in addressing climate vulnerabilities while supporting sustainable energy transitions. The implications of this work lie in guiding future research and policy frameworks to enhance energy security and environmental sustainability. Full article

Increasing water use efficiency (WUE) is a key way to produce high crop yield under water resources deficit regions. North China produces approximately 60% of the total Chinese wheat while suffering great water shortages. Therefore, this paper aims to find out the main factors and their mechanisms that affect the WUE of winter wheat in North China. In this study, we analyzed the yield and the WUE of winter wheat and the influencing factors based on mega data from published papers. We found that climate conditions, irrigation and fertilization management, and tillage measures are the three main factors that greatly influence wheat yield production. Aiming for high yield and WUE in North China, the optimal average annual temperature is 10–15 °C, and seasonal precipitation is 150–200 mm. The recommended optimal irrigation water amount is 160–240 mm and the suitable irrigation methods are drip and sprinkler irrigation. The optimal application amount of both nitrogen and phosphorous (equivalent to P₂O₅) is 150–200 kg·ha⁻¹. Both deep loosening tillage and rotary tillage can produce higher yield and WUE. Ridge and flat cultivation produce similar wheat yield and WUE, and flat cultivation is recommended due to its’ ease of machine working. The results of this study can help farmers and agricultural extension specialists select appropriate methods to enhance wheat yield and WUE and may help develop a sustainable agriculture system for high wheat production in North China. Full article

From 2020 to 2022, hydrological extremes such as severe floods and droughts occurred successively in Jiujiang city, Poyang Lake Basin, posing a threat to regional water quality safety. The chlorophyll-a (Chl-a) concentration is a key indicator of river eutrophication. Until now, there has been a lack of empirical research exploring the Chl-a trend in inland water in Jiujiang in the context of hydrological extremes. In this study, Sentinel-2 satellite remote sensing data sourced from the Google Earth Engine (GEE) cloud platform, along with hourly water quality data collected from monitoring stations in Jiujiang city, Jiangxi Province, China, are utilized to develop a quantitative inversion model for the Chl-a concentration. The Chl-a concentrations for various inland water types were estimated for each quarter from 2020 to 2022, and the spatiotemporal distribution was analyzed. The main findings are as follows: (1) the quantitative inversion model for the Chl-a concentration was validated via in situ measurements, with a coefficient of determination of 0.563; (2) the spatial estimates of the Chl-a concentration revealed a slight increasing trend, increasing by 0.1193 μg/L from 2020 to 2022, closely aligning with the monitoring-station data; (3) an extreme drought in 2022 led to less water in inland water bodies, and consequently, the Chl-a concentration displayed a significant upward trend, especially in Poyang Lake, where the mean Chl-a concentration increased by approximately 1 μg/L from Q1 to Q2 in 2022. These findings revealed the seasonal changes in the Chl-a concentrations in inland waters in the context of extreme hydrological events, thus providing valuable information for the sustainable management of water quality in Jiujiang city. Full article

Inspired by earthworm peristalsis, a novel modular robot suitable for narrow spaces is proposed, capable of elongation, contraction, deflection and crawling. Unlike motor-driven robots, the earthworm-inspired robot achieves extension and deflection in each module through “on–off” control of the SMA springs, utilizing the cooperation of mechanical skeletons and gears to avoid posture redundancy. The return to the initial posture and the maintenance of the posture are achieved through tension and torsion springs. To study the extension and deflection characteristics, we established a model through kinematic and force analysis to estimate the relationship between the length change and tensile characteristics of the SMA on both sides and the robot’s extension length and deflection angle. Through model verification and experiments, the robot’s extension, deflection and movement characteristics in narrow spaces and varying curvature narrow spaces were comprehensively studied. The results show that the earthworm-inspired robot, as predicted by the model, possesses accurate extension and deflection performance, and can perform inspection tasks in complex and narrow space environments. Additionally, compared to motor-driven robots, the robot designed in this study does not require insulation in low-temperature environments, and the cold conditions can improve its movement efficiency. This new configuration design and the extension and deflection characteristics provide valuable insights for the development of new modular robots and robot drive designs for extremely cold environments. Full article

This study presents part of a pilot work for the structural health monitoring of a large tied-arch reinforced concrete aqueduct in eastern China. Based on field-monitored data for over a year, it mainly focuses on the effect of air temperature and water load variations on the static behavior of a typical span of the aqueduct through field monitoring and 3D FE model analysis. It is found that the longitudinal deformation of the composite tied-arch shows a good linear relationship with the air temperature during the non-operation period and also has a good bilinear correlation with the air temperature and water level during operation. However, isolation of the air temperature effect from the second bilinear correlation using the first linear relationship results in a poor correlation between the longitudinal deformation and water level due to the dominance of the temperature effect. Therefore, it is recommended to use the bilinear regression to predict the longitudinal deformation of the tied-arch during operation. The vertical deformation of the tied-arch is insignificantly affected by air temperature, whereas it shows a fair bilinear correlation with the air temperature and water level during operation, which can be used to provide a reasonable estimation of the vertical deformation of the tied-arch. The strain measurements of the tied-arch using vibrating-string gauges are more complicated due to the notable influence of the ambient temperature and solar radiation, but the relatively consistent bilinear regression of the strains versus the air temperature and water level can still give fair predictions for the strains of the bottom tension rods during operation. The 3D FE model can provide a fair estimation for the vertical deformation of the tied-arch under water load, but its predictions for longitudinal deformation and strains are less satisfactory when compared to monitored data excluding temperature effects. Full article

In the context of global climate change, understanding cryosphere degradation and its impact on water resources in alpine regions is crucial for sustainable development. This study investigates the relationship between permafrost degradation and runoff variations in the Source Region of the Yangtze River (SRYR), a critical water tower for sustainable water supply in Asia. We propose a novel method for assessing permafrost sensitivity, which establishes the correlation between cryosphere changes and hydrological responses, contributing to sustainable water resource management. Our research quantifies key uncertainties in runoff change attribution, providing essential data for sustainable decision making. Results show that changes in watershed characteristics account for up to 20% of runoff variation, with permafrost degradation (−0.02 sensitivity) demonstrating a greater influence than NDVI variations. The findings offer critical insights for the development of sustainable adaptation strategies, particularly in maintaining ecosystem services and ensuring long-term water security under changing climate conditions. This study offers a scientific basis for climate-resilient water management policies in high-altitude regions. Full article