[Objective] Severe convective weather is typically characterized by abrupt onset and localized impact. Effectively acquiring disaster information from social media can compensate for the insufficient observation density of severe convective weather and provide information support for disaster emergency management. [Methods] Chinese text segmentation and statistical analysis were performed on text data of typical severe convective weather. By integrating meteorological expert knowledge, a disaster-themed corpus tailored to severe convective weather was developed. Semantic information was incorporated into the latent Dirichlet allocation(LDA) topic model and the support vector machine(SVM) classification algorithm to construct a disaster information extraction model under severe convective weather. Taking the severe wind-hail event in Jiangsu on April 30, 2021 as an example, 16 334 original Weibo text messages were collected for simulation experiments. [Results] (1) The constructed disaster information extraction model for severe convective weather demonstrated remarkable effectiveness in identifying and classifying disaster information in Weibo texts. Through primary topic mining, five themes were extracted: weather conditions, public education on disaster prevention, disaster impact, rescue requests, and other information. The secondary classification was performed on “disaster impact” to extract six specific categories: public facilities, power and communication, vehicle traffic, agricultural facilities, casualties, and others. Cross-validation revealed an average accuracy of 92.70% for the primary classification and 90.95% for the secondary classification.(2) The development process of severe convective weather was divided into three stages: warning stage, outbreak stage, and post-disaster stage. All information categories peaked during the outbreak stage. During the outbreak stage, information on public facilities and power and communication was the most prevalent, while during the post-disaster stage, discussions about casualties were the most frequent.(3) The spatial distribution of disaster information quantity was generally consistent with the regions severely affected by the disaster. During severe convective weather events, public facilities faced a higher risk of exposure with damage being the most common. [Conclusion] The extraction model of disaster information based on Weibo for severe convective weather can effectively extract implicit disaster information in Weibo texts, reflect the variation characteristics of disaster events and the focus of public opinion, and provide valuable reference for disaster monitoring and early warning services as well as emergency response command.

[Objective] In recent years, frequent typhoon strikes on coastal areas have caused severe casualties, economic losses and environmental degradation. Therefore, it is important to explore the formation mechanism and risk assessment of the easily occurring typhoon disaster chain to provide scientific support for flood control and tide prevention in coastal cities. [Methods] Focus is paid on a typical “typhoon-storm surge-flood-dike burst”(TSFD) disaster chain event, conducting an evolution analysis of the disaster chain mechanism based on the risk transmission and response among various disasters. A risk transmission network structure is established for the TSFD disaster chain, and a risk assessment model for the TSFD disaster chain is constructed using Bayesian theory. This model is applied in Zhuhai, Zhongshan, Jiangmen, and Foshan in Guangdong Province to simulate and analyze the distribution of TSFD disaster chain risk under the three typical typhoon scenarios. [Results] The result show that coastal areas are at higher risk of TSFD disaster chain than inland regions. When a landing-type typhoon with a wind force above Category 16 occurs, the total area of “high” and “medium” risk zones in the study area accounts for 29.9% of the total, with “high” risk zones mainly concentrating in the coastal areas of Zhuhai and Zhongshan, and “medium” risk zones mainly distributing in the east-central part of Foshan and the southern part of Jiangmen. [Conclusion] The result indicate that: under different typhoon scenarios, typhoon intensity change has a greater impact on storm surge and dike burst than flood, while the impact of typhoon path change on flood and dike burst is greater than that of storm surge. Research result can provide valuable references for the disaster prevention and mitigation capacity building in the Guangdong-Hong Kong-Macao Greater Bay Area.

[Objective] Natural catchments typically have complex tributary systems. Under the influence of short-duration, intense rainfall, the process of runoff generation and concentration is intensified, leading to a surge in river discharge and rising water levels, which increases the likelihood of severe flooding. To improve the timeliness and accuracy of basin flood simulations, [Methods] the spatiotemporal flood simulation model STFS-Urban is used to analyze the spatiotemporal interaction mechanisms and characteristic parameter expressions under the integrated model. A standard dataset is constructed, and the coupling integration of the basin flood physical model with the improved Transformer deep learning algorithm is achieved. The Xiushui River Basin in Shenyang is selected as the study area, where flood process scenario simulations are conducted using monitoring data from two typical heavy rainfall events on “2022-07-06” and “2022-07-28.” The simulation result are validated through comparison with observed data from the Gongzhutun hydrological station. [Results] The results show that the difference between the predicted and observed water levels is less than 0.5 m, with an error within 1.5%. The error in the predicted peak time relative to the observed time is less than 1.85 hours. The constructed integrated basin flood model accurately predicts the inundation extent and flood evolution trends, which are consistent with the actual situation. The simulation efficiency is approximately 31 to 34 times higher than that of the physical model. [Conclusion] The results indicate that the established STFS-Urban basin flood integrated model is capable of effectively simulating the flood evolution process. While ensuring accuracy, the model significantly enhances computational efficiency and can provide a scientific basis for the prevention and control of river basin flood disasters and the formulation of countermeasures.

[Objective] Surface water flooding is caused by heavy rainfall, which has been the main type of flooding in many cities across the world. Real urban environments are highly complex, and there are numerous parameters influencing the rainfall-runoff processes, such as road width, orientation and building coverage. The main objective is to perform a parametric study concerning the rainfall-runoff processes in complex urban environments, in order to gain a better understanding of the impact of urban characteristics on the surface runoff. [Methods] Realistic urban layouts are generated by means of procedural modelling software, which parameterises the urban configurations using 11 independent variables, including the averaged street length, street orientation, street curvature, major street width, minor street width, park coverage, etc. A shock-capturing TVD Mac Cormack shallow water equations solver is used to undertake a large number of computational simulations regarding the rainfall-runoff processes over realistic urban layouts. The dominating urban parameters that influence the time of concentration is unveiled, which characterises the timescale of the flood formation. [Results] In order to generalise the research outcomes, the obtained hydrographs at the outlet of the catchment are normalised so that they are independent of the catchment area, slope or rainfall intensity. The dimensionless time of concentration is thus only the functions of 12 independent parameters, including 11 parameters that governing the urban layouts and the Manning roughness coefficient of the ground. A sensitivity analysis, based on the multiple linear regression method, is performed on the 2, 994 simulation cases to quantify the influence of each parameter. [Conclusion] The results show that the ground roughness and the building coverage ratio are the two most important factors that influence the urban flood formation. Their influences on the dimensionless timescale of the urban catchments' response to rainfall are quantified by empirical formulae. The research findings can provide useful guidelines for the design of future flood-resilient urban environments and the improvement of existing drainage systems in cities.

[Objective] The sensitivity analysis of model parameters is conducive to enhancing the optimization efficiency of model parameters, reducing model uncertainty, and improving the model accuracy. [Methods] A residential community in Qian'an City was selected as an example, and the SWMM model was constructed. The analysis of parameter sensitivity was conducted by employing the modified Morris method and the Sobol method, with peak flow and runoff coefficient as optimization objectives under different rainfall scenarios. The advantages and disadvantages of these two methods were also evaluated. [Results] The result indicate that both the modified Morris method and Sobol method can identify high sensitivity parameters under different objective functions. For peak flow, both methods identify the roughness coefficient of the pipeline as the most sensitive parameter, with sensitivities of-0.563~-0.157 and 0.116~0.915, respectively. For runoff coefficient, the modified Morris method identifies the maximum infiltration rate as the most sensitive parameter, with sensitivities of-0.358~0. The Sobol method identifies the storage capacity of impermeable areas as the most sensitive parameter, with sensitivities of 0.238~0.961. The second-order sensitivity index calculated by the Sobol method shows that the interaction between parameters is mainly the combined effect between the two parameters. The modified Morris method can qualitatively sort the sensitivity of parameters, and the calculation is efficient and convenient. The Sobol method can comprehensively analyze the influence mechanism of parameters and their interactions. [Conclusion] The comprehensive application of qualitative and quantitative analysis method has important guiding significance for in-depth analysis of model parameter sensitivity, accurate identification of parameter calibration direction, and improvement of model reliability.

[Objective] Under the context of global warming, spatio-temperal pattern of extreme heavy precipitation in the Pearl River Basin have been changing and posesgreat challenges to flood prevention and disaster mitigation. [Methods] Basd on the hourly precipitation data of 125 meteorological stations in the Pearl River Basin from 1979 to 2018, the percentile threshold method is used to define the extreme heavy precipitation events. The extreme precipitation with different durations(1~6 h short duration event, 7~12 h medium duration event, and >12 h long duration event) is identified by fuzzy identification method, and seven rainfall type is considered for classification: single-peaked extreme Ⅰ—Ⅲ means the pre-centralized, the post-centralized, and the mid-centralized type, respectively; Ⅳ is the evenly distributed precipitation; double-peaked extreme Ⅴ—Ⅶ means, with the two peaks of rainfall being located in the beginning and the ending of event, the beginning and the middle of event, and the middle and the ending of the event, respectively. Identified. Then, changes of the rainfall duration and the rainfall type are analyzed in the Pearl River Basin by applying both the linear and non-linear trend analysis method. [Results] (1) The short-, medium-, and long-duration rainfall accounts for 65%, 26%, and 9% of the total extreme precipitation in the Pearl River Basin, respectively. From 1979 to 2018,extreme precipitation with all durations has shown increasing trends, with significant risingtrend observed for short-duration extremes.(2) Short-duration extreme precipitation across the basin falls primarily to Type Ⅰ. For medium-duration extreme precipitation, Type Ⅱ dominates in the Beijiang Basin, while Type Ⅲ prevails in remaining regions. For long-duration extreme precipitation, Types Ⅰ and Ⅲ are predominant in the central Xijiang Basin, whereas Type Ⅱ is dominant in other regions.(3) Compared to the previous 20 years, short-duration precipitation for 1999—2018 in most of the basin continued to be mainly Type Ⅰ. Medium-duration precipitation showed a shift from Type Ⅲ to Type Ⅱ as the dominant type in most of the Pearl River Delta and the Dongjiang Basin. Long-duration precipitation in eastern basin mostly remained Type Ⅱ or shifted from Type Ⅱ to Type Ⅲ, while in western regions, Type Ⅲ remained predominant or shifted towards Type Ⅱ as the main type. [Conclusion] Frequency of the short-duration extreme precipitation is the highest in the Pearl River Basin, and primarily falls to the pre-centralized type has not shown obvious change in for the last 40 years. Distribution pattern of the medium-and the long-duration extreme precipitation shows clear regional differences with the mid-centralized type dominant in the western region while the post-centralized prevails in the eastern region. In the eastern part of the basin, the dominant rainfall pattern mostly remains stable or shifts from the mid-centralized type to the post-centralized, whereas in the western part, rainfall pattern either remains unchanged or shifts from the post-centralized type to the mid-centralized. For adapting flood prevention and disaster mitigation, the specific rainfall type and rainfall duration in the basin, particularly that of the long-duration events in eastern part needs to be considered fully.

[Objective] Flood simulation and risk assessment are recognized as of great significance in addressing urban flood disasters. Utilizing regional hydrological hydrodynamic models to analyze rainstorm scenarios has become a predominant approach in current research. This method aims to improve the computational accuracy of hydrological and hydrodynamic models, thereby enabling more effective multi-scenario analysis. [Methods] Jiangyin City was selected as the study area, and a nested model of the Taihu Lake area model and Jiangyin City flood model were employed to conduct multi-scenario simulations and assessment of urban flood. Considering the three typical rainfall characteristics of long-duration plum rain type, short-duration heavy rainfall, and typhoon rain, a total of 10 working conditions were established across three key scenarios: the “July 20 rainstorm in Zhengzhou, ” extremely heavy rainstorm, and water conservancy design rainfall. A flood model coupled with hydrological and hydrodynamic forces and a two-dimensional river network management network in the study area was constructed. Detailed simulations and analyses of surface waterlogging and associated risk distributions were enabled. [Results] The result indicated that under the scenario of “July 20, Zhengzhou, ” the risk area experienced a rapid rise in water level reaching high peaks, and a prolonged receding process. When subjected to the maximum rainfall magnitude, the inundated risk area within the study area accounts for 37.32%. In the case of the extremely heavy rainstorm scenario, the submerged area were jointly influenced by the total rainfall and the maximum hourly rainfall. At the maximum rainfall intensity, the total risk area accounted for 13.2%, and the submerged water depth reached 0.60 m. Under the rainfall scenario of water conservancy design, the proportion of medium-risk areas was the highest. With the increase of design rainfall, the submerged area of medium-risk and high-risk areas significantly increased. Surface waterlogging in the study area was jointly affected by local rainfall and surrounding rainfall conditions. [Conclusion] The research result revealed the adaptability of Jiangyin to encounter extreme rainstorms and predicted the risk factors under different rainfall scenarios, which can provide a decision-making basis for Jiangyin to formulate targeted countermeasures and measures, thereby enhancing the city's capacity to cope with extreme rainstorm and flood disasters.

[Objective] To explore the spatiotemporal characteristics of groundwater drought and its dynamic response to meteorological drought in Qingdao plain areas, [Methods] the standardized groundwater index(SGI) and standardized precipitation index(SPI) at the multi-scale were calculated using monthly groundwater level data from 20 monitoring wells and monthly precipitation data from Pingdu Station from 2000 to 2020. The evolution and trend characteristics of groundwater drought and meteorological drought were analyzed, and Kendall's rank correlation coefficient was used to quantitatively identify the dynamic response relationship between groundwater drought and meteorological drought. [Results] The result indicate that both groundwater and precipitation in the study area tend to become wet first and then dry, and the occurrence time of groundwater drought is later than that of meteorological drought. The response time of groundwater drought to meteorological drought is 30~56 months, and the overall response degree is strong. The maximum correlation coefficients between SGI and SPI-n(n=1, 2,… 48) in spring, summer, autumn, and winter were 0.42, 0.84, 0.65, and 0.57, respectively. The response degree of groundwater drought to meteorological drought was significantly stronger in summer and autumn than in spring and winter. The correlation coefficient between SGI and SPI-n in the southwest is significantly lower than in other regions. [Conclusion] The result reveal that there is spatiotemporal heterogeneity in groundwater drought and its response to meteorological drought in the study area, influenced by factors such as precipitation, lithology of the aquifer, and groundwater exploitation. The propagation from meteorological drought to groundwater drought is a slowly evolving implicit process. Understanding the spatiotemporal response relationship between groundwater drought and meteorological drought can provide reference for the early warning and prevention of groundwater drought.

[Objective] Thermal stratification is an important characteristic of lake and reservoir water ecosystems, affecting mixing, convection, nutrient cycling of water bodies, and the vertical distribution of dissolved oxygen(DO). Therefore, understanding the stratification patterns and their key influencing factors is essential. [Methods] Based on the high-frequency profile data collected over one year from Nuozhadu Reservoir, the temporal variations of temperature profiles, thermal stratification parameters, and thermal stability were analyzed on a daily scale. The driving factors of thermal stratification during different stratification periods were explored, and the impact of climate warming on thermal stratification and the water ecological environment was examined. [Results] The water column of Nuozhadu Reservoir showed clear stratification, with significant seasonal variations in the vertical distribution of water temperature and DO. The temperature difference between the surface and the bottom layers ranged from 2.8 to 12.3 ℃, with a minimum DO concentration of 0.59 mg/L occurring in the oxycline. The maximum thermocline thickness reached 14.85 m, while the relative water column stability(RWCS) peaked at 359.9 during the same period. [Conclusion] The daily variations in thermal stratification parameters reveal the formation, stabilization, and weakening phases of thermal stratification. Surface water temperature is identified as the main factor affecting thermal stratification. Additionally, climate warming may lead to more stable thermal stratification, extending the duration of stratification, changing DO concentration profiles and distributions, and causing other environmental issues. The findings provide scientific evidence for understanding the seasonal stratification and water chemistry characteristics of Nuozhadu Reservoir and the impacts of climate warming. The result are significant for reservoir water quality management and ecological environment protection.

[Objective] Accurately monitoring the main objective and changes of river and lake shorelines is crucial for river and lake shorelines management. Exploring the use of high spatiotemporal remote sensing data to achieve dynamic monitoring of river and lake shorelines is of great significance. [Methods] Sentinel-2 images from different periods of Tiangang Lake were selected. The post classification change detection method was proposed to monitor the dynamic changes of Tiangang lake shorelines. Firstly, the accuracy of land use classification using maximum likelihood method, random forest method, and object-based image classification method was evaluated. Then, the transitional graphic of land use was calculated to analyze the dynamic changes in the shoreline of Tiangang Lake. Finally, the accuracy and spatiotemporal changes of photovoltaics were compared. [Results] The result showed that among the three selected land use classification method, object-based image classification method had the best classification accuracy, with an average overall classification accuracy and Kappa coefficient of 92.7% and 0.91, followed by random forest method and maximum likelihood method. From 2019 to 2023, the photovoltaic area of Tiangang lake shorelines in Jiangsu Province was rapidly increased, and the land use change rate of water bodies converted to photovoltaics was the highest. The average IOU of photovoltaic recognition using object-based image classification method was 91.4%, and Sentinel-2 images can accurately monitor the dynamic changes of photovoltaics in different periods. [Conclusion] The use of object-based image classification method can accurately identify and monitor the main targets and their spatiotemporal changes along the water shoreline, providing reference for dynamic supervision of rivers and lakes.

[Objective] Plain river network cities in the middle and lower reaches of the Yangtze River are located in flat and open terrain with crisscrossed river networks. During flood seasons, higher water levels combined with lower urban elevation often lead to poor drainage, making these areas highly susceptible to flooding. Dike merging has proven to be an effective method for addressing flood issues within dike areas. [Methods] Taking Xinchengnanwei in Wuhu City as an example, the effect of dike merging measures on flood control and drainage was systematically evaluated. A refined flood-inundation coupled model was developed, incorporating engineering infrastructure, rainfall, and external river water levels. Seven scenarios were designed to simulate changes in flood risks before and after the implementation of dike merging measures. [Results] The result showed that, under different rainfall conditions and external river flood return periods, the inundation area in the study area decreased compared to before the implementation of dike merging measures. Specifically, when the return period was 10 years, the reduction in inundation area in high-risk zones was the most significant, reaching 18.40%. As the design storm and flood return periods increased, the effectiveness of these measures gradually diminished. After implementing the dike merging measures, the main drainage infrastructure in the dike area, such as the Jingfang Pump Station and Zhugang Pump Station, was able to meet the urban drainage needs. However, for rainfall events exceeding a 20-year return period, it was necessary to pre-lower the water level of the Jingshan River by activating pump stations in advance to ensure their proper operation. [Conclusion] Dike merging measures can effectively reduce the flood and inundation risks in plain river network cities. Combined with drainage engineering projects, pre-lowering internal river water levels enhances the city's flood control and drainage capacity. The refined flood-inundation coupled model can comprehensively simulate the interaction between floods and urban inundation. Technical support can be provided for flood control and drainage planning, as well as water engineering scheduling in plain river network cities, along with theoretical guidance for establishing refined flood-inundation coupled models in similar dike areas.

[Objective] The rapid formation and movement of cumulus clouds are the main meteorological factors causing fluctuations in photovoltaic(PV) power output, and their shading effects on solar irradiance significantly affect the operational stability of PV systems and the accuracy of power prediction. However, traditional cumulus cloud modeling method based on 2D images fail to reflect the structural variation of clouds in the vertical direction and lack effective expression of key physical parameters such as cloud base height, cloud thickness, and internal particle distribution, making it difficult to meet the modeling requirements for high resolution, real-time performance, and physical consistency in PV applications. [Methods] To address this, a 3D voxel-based cumulus cloud modeling method using ground-based cloud images was proposed. The geographic positioning of cumulus regions was achieved through image preprocessing and spatial registration. An automatic extraction method for cloud base height and cloud thickness for cumulus clouds was proposed, and a cloud particle density parameter was introduced to construct a voxel expression model with physical constraints. Combined with a GPU rendering pipeline, efficient modeling and visualization of cumulus cloud morphology and internal characteristics were realized. [Results] The experimental result showed that the calculated cloud base height had a relative error within 5% compared to remote sensing inversion result. The cloud particle density distribution was consistent with CloudSat profile observations. The GPU-based method outperformed traditional method in modeling efficiency and rendering performance, maintaining stable frame rates in 3D scene interaction. [Conclusion] The findings demonstrate that this method can achieve rapid reconstruction and efficient visualization of cumulus clouds, verifying the feasibility and accuracy of extracting key parameters based on ground-based cloud images and providing an effective model and data support for PV power prediction.

[Objective] In a changing environment, the wet-dry encounter relationships between adjacent regions may undergo significant changes, profoundly affecting the implementation and operation of regional water diversion projects. However, the spatiotemporal evolution characteristics of wet-dry encounters and their potential effects on water network layout remain unclear, necessitating in-depth research. [Methods] Taking the three major regions of Northern, Central, and Southern Shaanxi as the study areas, a two-dimensional joint distribution model was established based on the Copula function to quantify the occurrence probabilities of wet-dry encounter events. The main factors driving dynamic changes were investigated, and the future evolution trends of wet-dry encounters under a moderate emission scenario were projected. Furthermore, the potential effects on water network layout were assessed, and optimization recommendations were provided. [Results] The result showed that:(1) the probability of synchronous wet-dry encounters was highest between Central and Southern Shaanxi at 60.71%, while it was lowest between Northern and Southern Shaanxi at 44.93%. In terms of water diversion, the probability of favorable water diversion conditions in the three joint regions(Central-Southern Shaanxi, Northern-Central Shaanxi, and Northern-Southern Shaanxi) was approximately 45%.(2) The Arctic Oscillation was the dominant teleconnection factor driving the changes in wet-dry encounters between Central-Northern Shaanxi and Northern-Southern Shaanxi, followed by the Pacific Decadal Oscillation.(3) Under the future moderate emission scenario, the probability of favorable water diversion conditions in Central-Southern Shaanxi and Northern-Central Shaanxi was projected to increase by 7.31% and 2.58%, respectively, while the probability of simultaneous drought was expected to decrease by 3.08% and 1.32%, respectively. [Conclusion] Significant spatiotemporal variations are observed in the wet-dry encounter relationships among Central, Northern, and Southern Shaanxi under changing environmental conditions. Under the future moderate emission scenario, the suitability for water diversion from Southern to Central Shaanxi is expected to improve, which can help alleviate water shortages in Central Shaanxi to some extent. However, simultaneous drought conditions may exacerbate regional water resource pressure. To achieve more efficient water resource allocation, it is essential to strengthen water replenishment capacity in Southern Shaanxi while improving water diversion from the Yellow River, backup water sources, and strategic reserve facilities in Central and Northern Shaanxi to cope with the uncertainties and challenges posed by future climate change.

[Objective] The Preissmann slot method is widely used in numerical simulation of free-surface-pressurized flow. However, it cannot directly simulate negative pressure. Based on the analysis of existing method, the Preissmann slot method is improved to enable the simulation of free-surface-pressurized flow process involving negative pressure. [Methods] The model was used to determine the different flow patterns based on the initial state of water head and aeration conditions. If the initial water head was lower than the top of the pipeline and the pipeline was not connected to the atmosphere, the flow was determined as negative pressure flow. For negative pressure flow, the flow cross-sectional area was treated as a frozen full-pipe flow. The Preissmann slot method was still used to solve the equation, but the water level in the equation was converted to water head. Subsequently, the calculation method for open channel flow, pressurized flow, and negative pressure flow were described, along with the unified controlling equations. The Preissmann four-point implicit scheme was used for discrete solution, so as to establish an improved one-dimensional free-surface-pressurized flow model. [Results] Multiple classic cases and numerical simulations of the tailwater transition section of a multi-stage cascade hydropower station were used for comparison and validation. The result showed that the improved Preissmann slot method could effectively simulate the transition processes of open channel flow, pressurized flow, negative pressure flow, and free-surface-pressurized flow, with no significant impact on calculation efficiency. For a specific real-world case, the calculation time was only 0.243 s longer. [Conclusion] The research indicates that in the traditional Preissmann slot method, the water head and water level remain consistent. However, for negative pressure flow, the water head and water level should be separated. In the improved Preissmann slot method, the flow cross-sectional area is treated as a frozen full-pipe flow for negative pressure conditions, and the equation solving remains consistent with the traditional method. The only modification required is converting the water level in the equation to water head, thus enabling the simulation of negative pressure flow.

[Objective] The Heihe River Basin(HRB) is the second-largest inland river basin in the arid to semi-arid region of northwest China. Existing studies have mostly focused on its ecological environment, while research on surface deformation related to groundwater extraction for dryland agriculture and mineral resource exploitation remains insufficient. [Methods] In response to the need for surface stability monitoring in the HRB, an improved IPTA-InSAR technique was employed to process a total of 101 Sentinel-1 SAR images from two orbital tracks covering the study area from 2019 to 2020, generating a time series of surface deformation. The reliability of the result was verified using independently processed data from overlapping adjacent tracks. Furthermore, high-resolution optical remote sensing data were integrated to comprehensively analyze deformation characteristics. [Results] The result showed that the root mean square error between adjacent track result was 0.2 mm/year, and six significant deformation zones were identified within the basin. The maximum annual average subsidence rate reached 56 mm/year, and the maximum seasonal subsidence and uplift along the satellite line of sight were-70 mm and 60 mm, respectively. [Conclusion] The spatiotemporal distribution characteristics indicate significant heterogeneity in deformation mechanisms:(1) periodic subsidence due to seasonal over-extraction of groundwater in midstream oasis irrigation areas;(2) seasonal rebound influenced by groundwater rise during the rainy season in the saline-alkali lands along the Great Wall in eastern Jiuquan; and(3) continuous subsidence caused by mining activities in the Jinchang open-pit mine and Shandan coal mining areas. The findings of this study can provide a scientific basis for the optimized allocation of water resources in river basins, dynamic regulation of mining operations in mining areas, and protection of ecologically vulnerable zones, and offer important references for the coordinated development of human-land systems in the inland river basins of Northwest China.

[Objective] The flood control optimization scheduling of reservoir clusters plays a crucial role in flood management during heavy rain and flooding events. However, existing studies on improving the PSO algorithm often lack constraints and adjustments on the distance between particles and the optimal solution during the iteration process. Additionally, they fail to comprehensively consider both the downstream flood control targets and the safety of the reservoirs themselves during the optimization scheduling. [Methods] To better address the flood control optimization scheduling problem of reservoir clusters, an optimization model is established with the objective of maximizing peak shaving and minimizing the highest water level. The model focuses on four reservoirs in the Fei River Basin of Feixian County, Shandong: Longwangkou, Shangye, Xujiaya, and Shilan. The inertia weight and learning factors of the PSO algorithm are dynamically adjusted during the optimization process using trigonometric functions and Beta distributions. Additionally, the Central Limit Theorem is introduced to impose real-time constraints and regulation on the iterative process, further improving the PSO algorithm. The input conditions are the inflow of design floods with a recurrence interval of 100 years and 1000 years, and the optimization scheduling model is evaluated by considering flood control constraints and flood evolution. [Results] The result demonstrate that the larger the reservoir capacity, the more significant the peak shaving effect. Under the input conditions of a 100-year flood, the maximum discharge flow from the Xujiaya Reservoir was reduced by 559.62 m³/s compared to conventional scheduling, and by 279.81 m³/s compared to the standard PSO-optimized scheduling, achieving a peak shaving rate of 10.4%. The reservoir capacity was reduced by 6.4% compared to conventional scheduling and by 5.3% compared to the standard PSO optimization. Under the input conditions of a 1000-year flood, the maximum discharge flow from the Xujiaya Reservoir was reduced by 701.79 m³/s compared to conventional scheduling, and by 350.90 m³/s compared to PSO-optimized scheduling, achieving a peak shaving rate of 12.1%. The reservoir capacity was reduced by 9.2% compared to conventional scheduling and by 4.8% compared to PSO-optimized scheduling. [Conclusion] The result indicate that the proposed optimization scheduling model shows significant effects in achieving maximum peak shaving and minimizing water levels. The algorithm ensures effective precision and stability during the optimization process, demonstrating strong optimization performance and substantial practical application value.

[Objective] The aim of the study is to address the issue of inadequate representation of entity models during the transition of natural resource management from traditional economic utilization to ecological protection and sustainable development. [Methods] The concepts and connotations of “entity” and “geographical entity” were analyzed, and the concept of “natural resource entity” was defined. A multidimensional conceptual model of natural resource entities integrating business and ecological associations was established through an “event-rule-response” integration mechanism. Business activities were abstracted as “events”, which dynamically triggered the “responses” in the ecological association network among entities through preset “rules”. A modeling process for natural resource entities based on existing data was proposed. Taking mining areas as an example of natural resource entities, a mining entity model and its multidimensional association network diagram were constructed. [Results] (1) A composite natural resource entity comprising various land types such as mining land, forest land, and dry land was successfully constructed.(2) The model not only clearly expressed the mining entity and its core attributes but also effectively represented the spatial, temporal, semantic, business, and ecological associations of the mining entity.(3) Through the event of mining rights changes, the model demonstrated the ecological responses of adjacent mining areas, surrounding forest land, and groundwater to business adjustments. [Conclusion] The natural resource entity model integrating business and ecological associations can more accurately reflect the complexity of resource management and utilization. It addresses the issue that existing models struggle to represent ecological interactions between natural resource entities and the ecological impact of business activities, providing a scientific basis for the coordinated development of ecological civilization construction and rational utilization of natural resources.

[Objective] The deterioration mechanisms, influencing factors, and preventive measures of concrete performance under freeze-thaw cycles are core issues in the field of civil engineering materials science and have long been international research hotspots. Since the 1930 s, extensive research on the deterioration response mechanisms of concrete to freeze-thaw cycles has provided a solid theoretical basis for the durability design of concrete structures. [Methods] Through literature review and engineering practice experience, the primary theoretical hypotheses of concrete performance deterioration under freeze-thaw cycles are systematically summarized, including hydrostatic pressure hypothesis, osmotic pressure hypothesis, thermodynamic hypothesis, and critical water saturation theory. The influence of freeze-thaw cycles on the mechanical properties, chloride diffusion performance, and constitutive relationships of concrete is analyzed. Additionally, a theoretical framework and knowledge map are constructed based on relevant research findings. [Results] Extensive research indicates that freeze-thaw cycles damage the microstructure of concrete through multiple mechanisms including hydrostatic pressure, osmotic pressure, and thermodynamic effects, leading to increased porosity, microcrack propagation, and ultimately macroscopic performance deterioration. Regarding mechanical properties, freeze-thaw cycles reduce mechanical indicators such as strength and elastic modulus, with flexural strength exhibiting the highest sensitivity. In terms of chloride diffusion, freeze-thaw cycles accelerate chloride ion transport within concrete, increasing both the internal chloride concentration and diffusion coefficient. Additionally, freeze-thaw cycles alter the constitutive relationship of concrete, exhibiting the typical characteristics of “reduced peak stress and increased peak strain”. Based on the systematic review, future research trends in the freeze-thaw damage of concrete are discussed, and key issues requiring in-depth investigation are proposed. [Conclusion] The research progress on chloride ion erosion and performance deterioration of concrete under freeze-thaw cycles is systematically reviewed, and corresponding preventive measures such as optimization of concrete material parameters and physicochemical surface treatments of concrete are summarized. These efforts are essential to promote development in concrete research and improve the design level of concrete materials.

[Objective] Under climate change scenarios, high temperature and waterlogging stresses have emerged as critical constraints for wheat production. Elucidating the molecular mechanisms of stresses resistance in wheat, with particular emphasis on identifying key metabolic pathways and regulatory networks underlying these stresses tolerance, will provide theoretical basis for molecular breeding.[Methods] 24 hours' single high temperature(30 ℃), single waterlogging and compound stress treatments were conducted on the wheat variety Emai 007 at the three-leaf one-center stage. Basing on RNA-seq, transcriptome analysis on leaves of Emai 007 under the three treatments was performed, and differentially expressed genes(DEGs) were analyzed by DESeq2, and GO and KEGG pathway enrichment analysis were performed. [Results] Transcriptome profiling identified 30 648 DEGs, including 3 088, 13 291, and 11 269 DEGs responsive to waterlogging, high temperature, and combined stress, respectively. Notably, 902 core DEGs were consistently regulated across all the stress treatments. GO and KEGG enrichment analysis revealed that these core DEGs were predominantly enriched in nicotinamide metabolism and sulfur-containing amino acid(cysteine and methionine) metabolic pathways. [Conclusion] It was demonstrated that the combined stress synergistically exacerbates oxidative damage through coordinated suppression of nicotinamide and sulfur metabolic pathways, leading to disrupted iron homeostasis and compromised antioxidant capacity. The identification of these conserved stress-responsive pathways provides novel insights into adaptation mechanisms of wheat to concurrent abiotic stresses. Furthermore, this study offers valuable theoretical foundations for developing climate-resilient wheat varieties through molecular breeding approaches.

[Objective] Accurate prediction and analysis of soil temperature in the tillage layer of farmland is of great practical significance for agricultural production, in order to effectively and accurately analyze the characteristics of soil temperature change in the farmland of conservation tillage of black soil lacking in real measurement conditions. [Methods] Based on the Extreme Limit Training Machine(ELM) algorithm, the Self-Encoder Algorithm(AE) was introduced to form the Depth Extreme Limit Training Machine(DELM), which was improved by using the Sparrow Search Algorithm(SSA), and a hybrid SSA-DELM model was constructed to predict soil temperatures at different depths under two types of no-tillage no-straw cover(NT0) and no-tillage full straw cover(NTS) tillage conditions by utilizing the data of meteorological factors, and then predict soil temperatures at different depths under no-tillage no-straw cover(NTS). Soil temperature was predicted and compared with ELM, RF and SSA-RF models. [Results] The results showed that the coefficient of determination(R²) of the SSA-DELM model was 0.996 and 0.998, the mean absolute error(MAE) was 0.16 and 0.1, the root mean square error(RMSE) was 0.29 and 0.16, and the coefficients of Nash′s efficiency(NSE) were 0.999 and 0.999 for the prediction of soil temperatures under two types of tillage conditions, respectively. Performance Index(PI) was 0.051 and 0.056, the maximum residual error(MaxE) was less than 0.25, and the average running time was 17.2 s and 17.6 s, respectively. [Conclusion] Compared with other models, the prediction accuracy, generalization ability and prediction efficiency of SSA-DELM model were better than other models, and the prediction error was very low, and it could satisfy the two different tillage conditions under the soil temperature prediction needs, has good stability and anti-interference ability, and can provide certain data support for agricultural production decision-making.