[Objective] To comprehensively enhance the capacity for hydropower forecasting and scheduling at the scale of a river basin in China, it is imperative to accelerate the development of digital river basin systems based on the theoretical foundation of water system science, in which the “river basin simulator” plays an increasingly important role as a core supporting tool. [Methods] Based on typical application practices in the Yangtze River Basin, the research and development background, technical system, and engineering application outcomes of the “Yangtze River Simulator”(a representative river basin simulator platform) were systematically elaborated, focusing on the key value of water system science and river basin simulation technologies in hydropower scheduling management and in response to extreme hydrological events. The platform integrated core technologies including hydrological monitoring, real-time sensing, and model coupling, through which a multi-scale dynamic simulation and forecasting system for basin water systems was established, enabling simulation and prediction of complex river basin hydrological evolution processes. [Results] Practical applications showed that the river basin simulator could significantly improve the spatiotemporal resolution and the system simulation ability to reduce uncertainties through observation and multi-mode in medium-and long-term hydrological forecasting, while enhancing the scientific validity and response efficiency of multi-objective reservoir group optimized scheduling strategies. Notably, they demonstrated effective capabilities in decision support and risk prevention, especially when addressing sudden hydrological events such as extreme floods and droughts. [Conclusion] China's practical experience indicates that digital river basin development driven by river basin simulators can improve the accuracy of hydrological forecasting and the coordination efficiency of joint reservoir scheduling, and demonstrating system adaptability and operational resilience under extreme hydrological change conditions. Looking ahead, future efforts should focus on addressing challenges such as water system evolution and uncertainties driven by the constantly changing environment. The integrated development of complex “river-reservoir” system simulators should be promoted, and the system construction of multi-objective reservoir group optimized scheduling large models should be deepened. Furthermore, cross-sectoral coordination mechanisms and joint efforts in key technologies should be strengthened, and the in-depth application and capacity improvement of river basin simulators within the digital river basin system should be continuously advanced.
[Objective] In the research on hydrogeology and engineering geology, traditional mechanism-based numerical models often exhibit issues such as low modeling accuracy and high uncertainty when simulating complex physical processes, while machine learning models are limited by their substantial data demands and poor interpretability. Physics-Informed Neural Networks(PINNs), as a new computational method that combines physical laws and machine learning, can provide a feasible solution to the above-mentioned problems. [Methods] Firstly, recent literature from the past four years is systematically reviewed to summarize the current research status of mechanism-based numerical models, machine learning models, and mechanism-learning coupled models in the fields of hydrogeology and engineering geology. Secondly, an in-depth analysis of PINNs' latest applications in these fields is conducted. Finally, the existing limitations of PINNs in the fields of hydrogeology and engineering geology are expounded, and recommendations for future development are proposed. [Results] It is found that PINNs have partially addressed issues in numerical models and machine learning models, such as data scarcity, poor interpretability, and insufficient generalizability, demonstrating broad application prospects in hydrogeology and engineering geology. Future efforts should focus on resolving existing problems in robustness, adaptive weight allocation, and initial and boundary condition processing to further tap into their potential. [Conclusion] In future research, the following recommendations for further development are proposed. Generative models or reinforcement learning should be coupled to reduce the impact of data quality and noise on the model, thereby enhancing robustness. Adaptive learning algorithms and dynamic weight balancing mechanisms should be employed to balance the weights of each term in the loss function and ensure the output matrix of the PINNs model satisfies orthogonal conditions, thereby improving computational efficiency. Considering the actual situation, methods such as the activation function and constraint methods should be optimized for selection to achieve faster convergence and higher accuracy in PINN modeling.
[Objective] With the continuous expansion of cascade hydropower systems and increasingly complex operational environments, traditional optimized scheduling method struggle to meet the complex and diverse regulation requirements of river basins, while their decision-making accuracy and computational efficiency remain limited. [Methods] To address these limitations, an optimized scheduling model was established for cascade hydropower systems that considered power generation scheduling and water resource regulation, with minimum water consumption as the primary objective. Additionally, an efficient solution method based on deep reinforcement learning(Deep Q-Network, DQN) was developed. Using the cascade hydropower system in the middle reaches of the Dadu River as a case study, three operating conditions(medium, low, and high load) were established. The model was trained using actual operational data and evaluated through water consumption and water level processes. [Results] The result showed that the DQN algorithm reduced computational time by approximately 41.37 times compared to conventional method. Furthermore, DQN effectively balanced conflicting water regulation demands(e.g., water level stability and flow control), achieving an average reduction of 0.058 m/min in the water level fluctuation index and a total water consumption decrease of 11.58 million m3 compared to pre-optimization. Notably, the proposed model exhibited good stability across diverse operating conditions. [Conclusion] The findings indicate that the DQN-based load distribution method enhances system operational stability and safety while achieving breakthroughs in both scientific scheduling and computational efficiency. By dynamically optimizing real-time power output distribution among stations, the intelligent decision-making framework significantly mitigates water level fluctuations and reduces water consumption in power generation, thereby validating the feasibility of coordinated power-water optimization. This method provides a novel technical approach for intelligent scheduling of cascade hydropower systems and their optimized regulation under complex operational scenarios in the new era.
[Objective] To investigate the current status of periphyton communities across the entire mainstream of the Yalong River and the community differences among different river sections. [Methods] Based on a sampling survey of periphyton in 29 cross-sections of the Yalong River mainstream in May 2023, combined with habitat evaluation, the variations in periphyton community structure and the ecological niches of dominant species across different river sections were analyzed. Redundancy analysis(RDA) and Pearson correlation analysis were used to examine the responses of dominant species to environmental factors. [Results] The result showed that a total of 96 species of periphyton were collected, with Bacillariophyta accounting for 89.6%. In the upper reaches, 77 species were identified, with an average cell density of 4 296.3 cells/cm2. The dominance of dominant species was relatively balanced, with niche width ranging from 1.35 to 2.05 and niche overlap at 0.628, significantly higher than those in both the better and poorer habitat sections of the middle and lower reaches. This indicated that the upper reaches, unaffected by dam construction, exhibited a more stable composition of periphyton communities, lower interspecies competition, and stronger ability to utilize environmental resources. The RDA and Pearson analysis result showed that the dominant species of periphyton were positively correlated with ammonia nitrogen, conductivity, total carbon, dissolved total silicon, and ammonium nitrate, but negatively correlated with dissolved oxygen, water temperature, and dissolved total carbon. [Conclusion] It has been demonstrated that the construction of hydropower stations in the middle and lower reaches of the Yalong River affects certain environmental factors, leading to significant differences in the characteristics of periphyton communities across different river sections. The findings provide a reference for aquatic ecological conservation and restoration in the Yalong River.
[Objective] Complex river network water quantity and quality models involve numerous parameters and high dimensionality, making parameter inversion challenging. An in-depth analysis is required to investigate how the selection of optimization objective functions and different single-parameter and multi-parameter inversion method affect the accuracy of parameter inversion. [Methods] A parameter inversion method for water quantity and quality models was proposed based on the Fast Comprehensive Learning Particle Swarm Optimization(FCLPSO). Numerical experiments for parameter inversion were designed, and the LH-OAT global sensitivity analysis method was used to optimize the objective function for seven model performance evaluation indicators. Furthermore, the inversion result using single-parameter and multi-parameter inversion method were analyzed, and the differences between different inversion method were examined. [Results] The result showed that NSE* had the highest sensitivity as the objective function. Parameters of different types achieved high accuracy, with the single-parameter inversion having a mean relative error(MRE) of 5.2% and a coefficient of variation(CV) of 7.2%. The multi-parameter inversion result had an MRE of 13.5% and a CV of 14%. In the multi-parameter inversion, the inversion result of hydrodynamic parameters were better than those of water quality parameters, and the multi-parameter “layered inversion”method outperformed the “simultaneous inversion” method. [Conclusion] The result indicate that the proposed model parameter inversion method achieves high accuracy. It can help improve the timeliness and accuracy of parameter estimation for complex river network water quantity and quality models, providing technical support for improving the accuracy of numerical simulation of complex river networks.
[Objective] Rapid urban development has exacerbated flooding and heat island effects, while green roofs can help mitigate these issues, especially as the substrate soil significantly affects stormwater management. A bilayer substrate green roof with biochar-modified soil can effectively improve rainwater management performance. [Methods] Laboratory experiments and numerical simulations were combined to investigate the hydraulic performance of bilayer substrate green roofs. The hydraulic processes under artificial rainfall conditions were observed using test columns, and the inverse solution method was used to estimate the unsaturated hydraulic parameters of the substrate soil. Numerical simulations were conducted to explore the effectiveness of biochar bilayer substrates in stormwater management. [Results] The result showed that different biochar application method exhibited different performance in delaying and reducing peak flow. Under the selected rainstorm condition, the bilayer substrate structure with 3 cm of natural soil and 12 cm of biochar-modified soil demonstrated better stormwater management performance. [Conclusion] The result indicate that modifying soil with biochar and using a bilayer substrate exhibits flexibility and efficiency in green roofs. This provides preliminary guidance for roof greening design, offers a design direction for optimizing stormwater management in green roofs, and lays the foundation for future research.
[Objective] Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development. Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events. The integration of green,grey and blue systems( GGB-integrated system) is gradually gaining recognition in the field of global flood prevention. It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction. [Methods] Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed. In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed. A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed. [Results] Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process. Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems. Additionally,optimization objective tend to prioritize environmental and economic goals, while social and ecological factors are less frequently considered. Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system. There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes. Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed. Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales. [Conclusion] Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system. Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.
[Objective] Global climate change causes frequent occurrence of extreme hydrology, threatening regional water security and ecological security. The Nenjiang River Basin is located in the middle and high latitudes and is highly sensitive to global changes. However, how hydrological extremes will evolve under future climate change remains unclear. [Methods] Selecting the Dalain Hydrological Station, a control hydrological station in the Nenjiang River Basin, changes in hydrological extremes were investigated under future climate change. The meteorological data under different SSP scenarios(SSP126, SSP245, and SSP585) of CMIP6 were used as driving climatic factors. The calibrated and validated HYDROTEL model was employed to simulate the daily runoff volume from 2025 to 2100 under future climate change. Peak flow indicators(maximum daily flow, maximum 5-day flow, and flood days) and low-flow indicators(low-flow days and consecutive dry days) were extracted to analyze the extreme hydrological evolution characteristics of the Nenjiang River Basin under future climate change. [Results] The result showed as follows:(1) Under future climate change, the variation trend of extreme hydrological risk in Nenjiang River Basin under different SSP scenarios will be divergent. There is no significant change trend in the peak discharge index under the three scenarios. In the SSP1-2.6 scenario, the low water flow index will witness a significant upward trend, while in the SSP3-7.0 scenario, the low water flow index will experience a significant downward trend. Under the SSP5-8.5 scenario, the number of consecutive drought days will witness a significant decreasing trend.(2) The change trend and fluctuation characteristics of peak flood discharge index and low water discharge index are different in different periods. In the three scenarios, the mean values of different indicators in the near term(2025—2050), the medium term(2051—2070) and the long term(2071—2090) show certain differences compared with the historical period. Particular in the scenario of SSP5-8.5, the mean values of the long-term maximum daily flow and the maximum 5 d flow will be 44.3% and 38.2% higher than during historical period respectively. [Conclusion] Under the future climate change, the intensity and frequency of floods will show a significant upward trend, while the intensity and frequency of droughts will show a certain downward trend in the Nenjiang River Basin. It can provide important references for the mitigation of agricultural drought and flood risks, water security guarantee, and comprehensive water resources management in the Nenjiang River Basin.
[Objective] The characteristics of extreme climate change in Sichuan Province under the background of global climate change were studied, with the objective of mitigating the adverse impact on regional social economy, agricultural production, ecological environment and other aspects. [Methods] Based on the meteorological observation datasets including daily precipitation, maximum temperature and minimum temperature at 40 stations in Sichuan Province, 20 different extreme climate indices were calculated. Linear trend analysis, Local weighted regression analysis, Mann-kendall trend test, Pearson correlation analysis and ARCGIS software were used to analyzed the temporal and spatial variations of climate extremes in the mountain area of the eastern Sichuan Basin, the west Sichuan alpine plateau area and the southwest Sichuan mountain area, and the influential factors were discussed. [Results] In Sichuan Province, the extreme temperature indices were characterized by increasing trend, which were significant. The extreme precipitation indices were characterized by wetting, but the trends were not significant. [Conclusion] (1) Extreme warm(cold) events increased(decreased) in Sichuan province from 1961 to 2022, and showed the characteristics of “the rise of low temperature was more obvious than that of high temperature, the warming at night was higher than that of daytime, and the number of warm days were higher than that of cold days”. Spatially, the extreme temperature indices showed increasing trend in all regions of Sichuan province, and the increasing trend was more significant in high altitude areas such as the west Sichuan alpine plateau area and the southwest Sichuan mountain area.(2) In Sichuan province, the precipitation and the concentration of precipitation increased. Spatially, the west Sichuan alpine plateau area had a tendency of wetting, the mountain area of the eastern Sichuan Basin and the southwest Sichuan mountain area had a tendency of drying. The extreme precipitation indices showed a change characteristic of “west wetting and east drying”.(3) Most of the extreme climate indices were significantly correlated with annual mean temperature, annual precipitation, longitude and altitude, while the correlation with latitude was low. The extreme climate change in Sichuan Province mainly influenced by the Atlantic multidecadal oscillation(AMO) and the AMO had the most significant influence on the extreme climate. The analysis of the changing characteristics of extreme climate indices under the background of global warming is of great significance for flood control and drought relief in Sichuan Province.
[Objective] The lower reaches of the Jinsha River, situated in the transitional zone of Southwest China′s natural geographical boundary, serve as a significant hydropower base. Understanding the spatiotemporal variations in pan evaporation in this region is crucial. It lays the groundwork for analyzing the patterns of hydrological and climatic changes within the area. Furthermore, it provides essential support for the estimation and analysis of evaporative losses in cascade reservoirs. [Methods] Using observed and estimated data of D20 pan from 19 stations along the lower reaches of the Jinsha River from 1980 to 2022, a comparative analysis of the spatiotemporal differences in pan evaporation between the western and eastern parts of the study area is conducted and the driving factors are explored. [Results] The results indicate that the 13 stations located west of 103.5°E have higher pan evaporation(annual average of 1 997.4 mm) compared to the 6 stations in the eastern part(annual average of 1 101.4 mm). At the western stations, pan evaporation in spring(March-May) exceeds that in summer(June-August), with the peak occurring mainly in May. In contrast, at the eastern stations, summer pan evaporation is higher than in spring, with peaks occurring in July or August and a noticeable trough in June. The average pan evaporation at the western stations shows a non-monotonic change with 2000 being the turning point(first decreasing and then increasing), while the eastern stations exhibit a weak increasing trend in both periods. [Conclusion] The spatiotemporal variations of pan evaporation in the lower reaches of the Jinsha River shows a significant east-west differentiation, with 103.5°E as the boundary, impacted by of the Indian Monsoon and the East Asian Monsoon. In the context of evaporation studies in southwestern China, it is essential to account for the east-west disparity in the spatiotemporal patterns of pan evaporation and to explore the underlying driving mechanisms.
[Objective] In the context of global climate change, various disasters caused by extreme weather have become more frequent, recurrent, and severe. Understanding the variations of extreme temperature events and their population exposure holds great practical value for protecting people's lives and health, as well as for promoting economic and social development. [Methods] Using daily temperature observations, the spatiotemporal characteristics of extreme temperature events in Shandong Province from 1986 to 2022 were analyzed by using method including linear trend estimation, Mann-Kendall test, sliding t-test, and wavelet analysis. Combined with the national census data, the variation patterns of population exposure to extreme temperature at the county level in Shandong Province were revealed. [Results] (1) Temporally, the annual average number of high-temperature days in Shandong Province increased from 5.93 d to 12.49 d, with an increasing rate of 2.0 d/10 a(P<0.01), while the annual average number of frozen days showed a slight downward trend at a rate of 0.1 d/10 a.(2) Spatially, the annual average number of high-temperature days in Shandong Province gradually increased from east to west, and the annual average number of frozen days showed a distribution pattern of being higher in the north and lower in the south. Compared with the period from 1986 to 1995, the number of counties with an annual average number of high-temperature days exceeding 8 d increased by 227% during the period from 2013 to 2022, while no significant spatial changes were observed in the annual average number of frozen days.(3) From 1986 to 2022, the population exposure to extreme high temperature in Shandong Province increased continuously, with the annual average population exposure rising from 5.25 million people·d during the Fourth National Population Census to 12.57 million people·d during the Seventh National Population Census. Areas with high values were located in the southwestern and central Shandong. The population exposure to extreme low temperature first increased and then decreased, with high-value areas mainly distributed in the eastern Shandong Peninsula. [Conclusion] Both the frequency and influence range of extreme high-temperature events in Shandong Province have shown significant upward trends. Combined with changes in population size, the exposure to extreme high temperature increases rapidly, while extreme low-temperature events and their population exposure first increase and then decrease, with relatively small overall variations.
[Objective] The upper reaches of the Yellow River contribute approximately two-thirds of the water volume of the entire river basin and four-fifths of its reservoir storage capacity, serving as the major water-producing area and interannual runoff regulation area for the river basin. However, the significant interannual variation of runoff and its difficulties in accurate prediction have constrained the effectiveness of reservoirs in the upper reaches in “storing water in wet years to compensate for dry years” and undermined the security of water resources. [Methods] To further enhance the understanding of runoff, naturalized runoff data at major cross-sections along the Yellow River's mainstream from 1956 to 2022(Tangnaihai, Lanzhou, Lijin) and archaeological runoff data from 1736 to 1911(Qingtongxia) were collected. Multivariate statistical method such as Copula function and non-consistency tests were employed to explore the contribution of the upper reaches to the runoff of the entire river basin, interannual variation patterns of runoff in the upper reaches, and statistical characteristics of wet and dry years. [Results] The synchronous probability of wet, normal, and dry years of runoff at the Lanzhou cross-section and the entire river basin was 71.5%, with the probabilities of coincident dry or wet years being 32.2% and 20.3%, respectively. The probabilities of single dry or wet year at the Lanzhou cross-section were 43.3% and 26.9%, respectively. Specifically, the probability of an extremely wet year was 7.5%, with no extremely dry year observed during the study period. The probabilities of two consecutive dry or wet years were 19.7% and 12.1%, respectively, while three consecutive dry or wet years showed probabilities of 7.7% and 4.6%, respectively. The probability of transition between wet and dry years was 16.7%. [Conclusion] To effectively cope with the adverse effects of extremely wet or dry years, as well as consecutive wet or dry years, it is imperative to improve the long-term runoff prediction capabilities while fully leveraging the interannual regulation capacity of the Longyangxia Reservoir, and to accelerate the construction of the “one-route and seven-reservoir” water network system in the Yellow River Basin.
[Objective] Numerous springs emerge in the Laiwu region, yet no systematic research has been conducted. To clarify the spring characteristics, spring systems, and their formation mechanisms in this region, and to support spring protection efforts, a systematic investigation was conducted based on the spring survey in Laiwu. [Methods] Method including data utilization analysis, hydrogeological surveys, geological drilling, and water quality analysis were employed to analyze the hydrogeological conditions for spring development. The distribution, hydrochemical, and quality characteristics of the springs were summarized. The spring systems were classified, and the formation mechanisms and controlling factors were examined. [Results] The result showed that the springs were mainly distributed at the margins of Laiwu Basin and in river valleys. Based on aquifer lithology, they could be classified into karst springs and fissure springs, with descending springs being dominant and a few ascending ones. The main hydrochemical types included HCO3-Ca, HCO3-Ca·Mg, and HCO3·SO3-Ca, with major ions primarily derived from water-rock interactions. 82% of the springs met or exceeded the Class III groundwater quality standards, with some being strontium-type or metasilicic acid-type natural mineral water. Spring formation was controlled by geological factors such as topography, stratum lithology, and fault structures, mainly featuring shallow circulation with rapid water cycling. [Conclusion] The spatial distribution of springs in the Laiwu Region is significantly affected by topographic variations. The springs show overall good water quality with rapid circulation. The spring discharge shows strong correlation with precipitation, making it susceptible to human activities. The systematic analysis of the spring systems in Laiwu provides technical support for the coordinated development of spring protection and urban planning in the region.
[Objective] Shallow instability of expansive soil water conveyance channel is easy to occur under the action of dry and wet freeze-thaw cycles in cold and arid regions, which is the key problem for the safe operation of expansive soil water conveyance channel. [Methods] Taking the expansive soil of the North bank of the Ili River in northern Xinjiang as the research object, the simulation of wet-dry freeze-thaw cycle effect and low stress direct shear test were carried out on the sample. The crack parameters of the expansive soil during the test were analyzed, and the changing rules of the crack parameters and the strength characteristics of the expansive soil were discussed. The influence of crack parameters on the strength characteristics of the expansive soil was studied. [Results] The result show that the fracture parameters and cohesion decay rate of the expanded soil sample will increase with the decrease of wet-dry freeze-thaw effect and the density degree, and the mechanical properties will further deteriorate. Under the wet-dry freeze-thaw cycle effect, the crack structure of expansive soil experienced rapid cracking, steady expansion and steady development, corresponding to the rapid decay, slow decay and steady decay stages of cohesion, indicating that the shear strength has a certain correlation with the fracture parameters, and the change trend of the connectivity coefficient is most closely related to the decay of cohesion. [Conclusion] The correlation degree ranges from 0.730 to 0.878 and the weight ranges from 0.260 to 0.300, which can quantitatively characterize the fracture development characteristics and strength attenuation rule of expansive soil under the effect of wet-dry freeze-thaw cycle.
[Objective] During the low-head start-up of pumped-storage units, units are prone to entering the unstable reverse-S zone of the full characteristic curve, which can lead to failure in grid connection and severely affect the safe and stable operation of the units. [Methods] A three-dimensional numerical simulation was conducted to study the low-head start-up process of the full-flow system in a pumped-storage hydropower plant's pump-turbine units, focusing on analyzing pressure pulsations in the volute and guide vane impeller regions, as well as internal flow characteristics. [Results] The simulation result showed that during the low-head start-up process of the pumped-storage units, in the stage of guide vane opening, vortices and blocked flow paths at the impeller inlet and within the impeller blades reduced the flow, generating a water hammer effect that rapidly increased the upstream pressure of the impeller. As the high pressure caused by the water hammer dissipated, the flow increased rapidly, followed by a slight negative water hammer that caused the pressure to drop. After the guide vanes stopped moving, the distribution of vortex structures at the impeller inlet and outlet decreased. As the impeller torque continued to decrease, the units entered the reverse-S zone and approached the no-load operating condition, with pressure pulsations starting to intensify. Unstable vortex structures reappeared at the leading and trailing edges of the impeller blades, and the increased water flow velocity at the impeller outlet caused the vortex belt in the tailwater pipe to extend downstream, forming a double-layer vortex structure at the center and near the wall. [Conclusion] Some vortex structures are the main cause of the instability of the units' external characteristic parameters at the beginning of the start-up process. As the process continues, pressure pulsations begin to increase, and unstable vortex structures reappear within the impeller flow passages, [Results] ing in the unstable hydraulic characteristics of the pump turbine under no-load conditions. The analysis of pressure pulsations and internal flow characteristics in the volute and guide vane impeller regions aims to provide a reference for achieving stable low-head start-up of the pumped-storage units.
[Objective] When traditional droop control is adopted for multiple distributed generators(DG) in the DC microgrid, there are challenges of achieving the control objective of accurate load distribution of multi-DG, stabilizing bus voltage, and ensuring safe operation considering DG capacity. A distributed control strategy for voltage regulation and power distribution in an islanded DC microgrid is thus proposed. [Methods] First, through theoretical derivation, bus voltage drop deviation and current correction deviation were analyzed, and a unified controller was designed, which compensated for the bus voltage drop caused by the traditional droop control while achieving accurate distribution of load power. A current limiting element was introduced to ensure that the output current of each DG did not exceed the limit. The stability analysis of the microgrid system was also carried out in conjunction with the proposed control strategy. Finally, a simulation model was built using MATLAB/Simulink software for verification. [Results] The result show that the proposed single-controller strategy can ensure that the bus voltage is continuously stabilized at the rated value, achieve a high-precision distribution of load power, and remain unaffected by load power fluctuation. The current limiting element can set the maximum limiting current to ensure that the output current of the DG does not exceed the limit. Stability analysis shows that the system is stable and unaffected by the change of the droop coefficient and the cut-off frequency. [Conclusion] The result indicate that the proposed unified controller strategy for bus voltage compensation and load power distribution can effectively achieve multiple control objective, reduce the system communication pressure, decrease the operation complexity, and realize efficient and stable operation of the microgrid.
[Objective] To optimize water quality monitoring and early warning systems and promote the sustainable development of river ecosystems. [Methods] Using daily water quality monitoring data from 19 monitoring stations around Taihu Lake from 2021 to 2023 and daily meteorological data from 7 meteorological stations, the water quality conditions were quantitatively evaluated using the comprehensive water quality index(WQI) method. Meteorological data spatially consistent with water quality monitoring stations were obtained through Kriging interpolation. Meteorological input variables were selected by comprehensively considering the influencing mechanisms of meteorological factors on water quality parameters and the result of Spearman correlation analysis. Predictions of the comprehensive WQI were conducted using Long Short-Term Memory(LSTM), Gated Recurrent Units(GRU), Backpropagation(BP) neural network, and a parallel GRU-LSTM model. [Results] The result showed that in the water quality prediction model, model accuracy was affected by the input step length. The parallel GRU-LSTM model using a 14-day input step length achieved the best performance, with a prediction accuracy of R2=0.98. [Conclusion] The deep learning-based prediction model provides a new technical approach for long-term monitoring and prediction of river water quality. Water quality prediction combined with meteorological data can help relevant authorities to warn water quality changes in advance in practical applications, optimize water resources scheduling and management strategies, and improve the sustainable management of water environment.
[Objective] Soft soil landslides, due to their complex plastic deformation and rheological properties, have failure mechanisms distinct from ordinary landslides in hard rock and soil. Traditional method of landslide research are ineffective at capturing the nonlinear and uncertain characteristics of their movement. [Methods] To quantitatively evaluate the movement characteristics of soft soil landslides, a viscoplastic fluid assumption of soft soil was adopted, using ideal viscoplastic material Carbopol as the test material in physical model experiments. Thickness and velocity at a specified distance were chosen as representative parameters, and a prediction model was built by training the experimental data with the random forest algorithm. [Results] The results show that the determination coefficients of the thickness training and testing data were 0.941 and 0.923, respectively, while those of the velocity training and testing data were 0.936 and 0.917, respectively. The residuals for thickness and velocity were mainly distributed within the ranges of(-0.02, 0.02) and(-0.1, 0.075), respectively, and showed a normal distribution. Furthermore, an analysis of feature importance indicated that yield stress had the most significant impact on the model, with an importance value of 0.35. [Conclusion] The results demonstrate that the model has high predictive accuracy and good generalization ability, and it performs well in handling high-dimensional data and complex nonlinear relationships in the dynamics of soft soil landslides. This provides a scientific basis for the prevention and control of soft soil landslide disasters.
[Objective] In order to study the effect of axial loading and unloading on the deformation properties of Guiyang red clay, [Methods] the loading and unloading tests of soil samples under different axial stress ratios and cyclic numbers were designed, supplemented by low-field nuclear magnetic resonance technology and SEM electron microscope scanning. The evolution laws of macro-deformation and inner pore structure of soil samples during the whole cycle loading-unloading process were discussed to reveal the damage mechanism of soil samples. [Results] The result show that the internal structure of Guiyang red clay underwent a process from compaction to deterioration due to cyclic loading and unloading. With the increase of cycle number and stress ratio, the stress-strain curve of Guiyang red clay gradually changed from strain hardening type to strain softening type. The T2 spectrum curve of pore distribution was developing from “mountain peak type” to “hilly type”, and the pore size range and peak spectrum of the sample were gradually decreasing. The number of large-medium pores gradually decreased, while the number of small-micro pores gradually increased. The clay particles around the pores were mostly in the form of closely cemented mineral particles, and the surface contact between the particles was changed into the form of line and point contact. The damage coefficient was defined by the change of unloading modulus and plastic deformation, indicating that the more the number of cycles and stress ratio, the more serious the damage of the soil sample, which was consistent with the law of pore change. [Conclusion] The result can provide theoretical guidance for the compaction and stability evaluation of red clay subgrade during construction period.
[Objective] Storing CO2 in goafs is a feasible technical approach for addressing the issue of reusing underground spaces in abandoned coal mines in China and achieving the “dual carbon” goals, with promising application prospects. However, it currently faces numerous challenges. To enhance the safety and efficiency of CO2 storage in goafs, it is necessary to establish control pressure indicators and their calculation method for the entire CO2 storage process. [Methods] Taking the optimization of CO2 storage control pressure in the goaf of Changcun Coal Mine in Shanxi Province as a case study, the physical properties of CO2 were first analyzed under different temperature and pressure conditions. Based on the climatic temperatures in Shanxi and the burial depth conditions of abandoned coal mines, the CO2 injection process was determined, and its storage characteristics in the goaf were analyzed. Subsequently, based on the storage principles of CO2 in the caprock and the requirement for preventing groundwater infiltration, the concepts of upper and lower pressure limits for CO2 storage in goafs were proposed, along with corresponding calculation method and analyses of major influencing factors. Finally, integrating the specific geological conditions of the goaf in Changcun Coal Mine, the approximate range of CO2 storage control pressure in this goaf was derived. [Results] The annual average temperature in Shanxi was 15 ℃, and the burial depths of abandoned coal mines generally ranged from 100 to 300 m. Under these temperature and pressure conditions, CO2 exhibited liquid-gas two-phase storage characteristics in the goaf. The available goaf space capacity in Changcun Coal Mine was 1.509 2 million m3, with maximum control pressure for CO2 storage recommended to be 8~10 MPa and the minimum control pressure recommended to be 4~6 MPa, indicating significant storage potential in the region. The goafs of abandoned coal mines in Shanxi had large capacities, moderate temperature and pressure conditions, and low hydraulic head of groundwater, indicating their potential for large-scale CO2 storage. [Conclusion] The lower limit of storage pressure is relatively small, while the upper limit of control pressure primarily depends on the breakthrough pressure and fracture pressure of the caprock. Based on the sealing capacity of the caprock, if sealing the goaf is required to utilize the enclosed space for CO2 storage, it is necessary to comprehensively consider sealing costs, implementation method, and the re-establishment of mechanical models. The investigation of calculation method for CO2 storage control pressure in goafs in Shanxi provides valuable references for the application and development of large-scale CO2 storage technology in abandoned coal mines.