Freeze–thaw processes are a key factor controlling spring surface soil salinization in areas with shallow groundwater, but the migration patterns of water, heat, and salt in soils of different textures during the freeze–thaw period remain unclear. To characterize these patterns under shallow-groundwater conditions, three lysimeters filled with sandy loam, loamy sand, and sand were established with a groundwater table depth of 1.0 m, and changes in water, heat, and salt in the 0~60 cm soil layer were monitored during the 2024-2025 freeze–thaw period. The results showed that the surface temperatures of the loamy sand and sand decreased more rapidly with falling air temperature than that of the sandy loam, whereas the sandy loam had the greatest freezing depth, reaching 44.54 cm. For all three soil textures, the 0~60 cm soil water storage first increased and then decreased, and the duration of the increase shortened as soil particle size increased. Only the sand exhibited an increase in water content by the end of the freeze–thaw period. The water-accumulation zone was located at 10~30 cm in the sandy loam and loamy sand, and at 10~20 cm in the sand. Sandy loam, loamy sand, and sand all showed a pattern of initial desalinization followed by salt accumulation, with salt-enriched layers at 0~5, 0~10 and 0~20 cm, respectively. Coarser-textured soils developed thicker salt-enriched layers, whereas finer-textured soils exhibited higher salt concentrations within the accumulation zone. For all three textures, salt storage in the 0~60 cm layer increased overall during the freeze–thaw period and was negatively correlated with water loss, and surface salinization intensified with increasing particle size. The temporal coefficients of variation of salt storage were higher than those of water storage, indicating that salt storage in the 0~60 cm profile was more strongly affected by freeze–thaw processes than water storage. Among the three soils, loamy sand showed the largest temporal variations in both water and salt storage, suggesting the strongest sensitivity to freeze–thaw action.

In order to evaluate the sustainability of water resources in Guiyang City, the three-dimensional water Ecological Footprint model was used to analyze the bearing state of water resources from 2003 to 2023, and the bearing capacity of water resources rigid constraint index was comprehensively evaluated. Then, the decoupling relationship between water Ecological Footprint and GDP, primary industry and secondary industry was analyzed by Tapio decoupling model. Finally, the decoupling catch-up model was constructed to simulate whether the water use efficiency is healthy when the city catches up with the model area from 2014 to 2023. Results show: From 2003 to 2023, the water ecological footprint of the city as a whole, per capita and thousand Yuan GDP all decreased. The per capita water ecological carrying capacity was greater than the per capita water ecological footprint, and the sustainable utilization index of water resources was greater than 0.5 (sustainable). However, from 2014 to 2023, there were different degrees of water ecological deficit in Yunyan, Nanming, Guanshanhu and other districts of the county-level administrative region. The total water use control index margin of the whole city and each county (district) fluctuated and decreased. Yunyan and Kaiyang even exceeded the total water use index. The decoupling frequency of total water Ecological Footprint and GDP is the highest (95%), followed by industrial water and secondary industry (90%), and agricultural water and primary industry (75%). By simulating the city 's catch-up to the economically developed areas in 2014-2023, the overall decoupling rate is 90%. Therefore, the overall water resources utilization efficiency of Guiyang City is gradually improved, which is sustainable; However, when it comes to county-level administrative regions, some counties (districts) have experienced water ecological deficits and exceeded total water consumption quotas, which are unsustainable. For 'main urban area, Kaiyang county', it is necessary to more strictly implement the rigid constraints of water resources, strictly control the approval of new water intake projects, continuously optimize the industrial structure and economic and social layout, improve the utilization rate of unconventional water, and accelerate the construction of water diversion and water network connectivity projects to ensure the sustainable use of water resources. The overall water use situation of Guiyang City has a good decoupling relationship with economic development. When it catches up with the model area, it can basically achieve a ' win-win ' between economic growth and water use efficiency improvement. However, the decoupling relationship between agricultural water use and primary production is general and unstable, and it is necessary to strengthen the construction and transformation of agricultural water-saving projects.

The carbon sequestration and emission reduction effects of biochar in paddy fields are influenced by its aging process. To this end, a two-year pot experiment was conducted in Nanjing, Jiangsu Province, to investigate the impacts of biochar aged by dry-wet cycles on greenhouse gas (CH₄ and N₂O) emissions, rice yield, and greenhouse gas intensity (GHGI). Through an indoor incubation experiment (2023), the natural dry-wet cycles of paddy fields (one cycle every 3 days, 10 cycles in total) were simulated to pre-age the biochar. Four treatments were established: fresh biochar (C0), 3-cycle aged biochar (C3), 6-cycle aged biochar (C6), and 10-cycle aged biochar (C10). Gas emissions were measured using the in-situ static chamber method, and GHGI was calculated based on yield data. The results showed that the C6 treatment yielded the optimal carbon sequestration and emission reduction effects. Compared with C0, the C6 treatment significantly reduced the fluxes and cumulative emissions of soil CH₄ and N₂O (p<0.05): cumulative CH₄ emissions decreased by 18.33% and 23.86% in 2023 and 2024, respectively, while cumulative N₂O emissions decreased by 11.03% and 15.19%, respectively. Simultaneously, the C6 treatment significantly increased rice yield (p<0.05) by 11.17% and 14.66% in the two years, respectively, and minimized GHGI, showing significant reductions of 25.40% and 32.26% compared to C0 (p<0.05). These findings indicate that biochar moderately aged through dry-wet cycles (6 cycles) can optimally achieve the synergistic goals of mitigating greenhouse gas emissions and increasing crop yield in paddy fields. This study provides new strategies and a theoretical basis for the precise application of biochar in agricultural production.

The Hetao Irrigation District in Inner Mongolia stands as one of China's three large-scale irrigation districts.The shallow groundwater within this region is subjected to varying degrees of nitrogen and phosphorus contamination, posing threats to both local drinking water security and sustainable agricultural development.This study focuses on the largest irrigation area within the Hetao Irrigation District—the Yichang Irrigation Area. In August and October 2024, a total of 76 monitoring points were established for field sampling. The spatiotemporal characteristics of nitrogen and phosphorus, as well as hydrochemical types, were analyzed. Additionally, hydrogen and oxygen isotopes combined with the Bayesian mixing model (MixSIAR) were used to identify recharge sources, while principal component analysis (PCA) and Pearson correlation were employed to reveal the main influencing factors. The results indicate that temporally the mean groundwater total nitrogen (TN) concentration was higher in October (14.7 mg/L) than in August (12.6 mg/L), while the mean total phosphorus (TP) concentration was lower in October (0.074 mg/L) compared to August (0.127 mg/L). Spatially, TN exhibited a punctate high-value distribution along the main drainage ditch, with high-concentration areas concentrated around large villages and breeding farms. High TP values were mainly found in the upstream sections of the main drainage channels and at sedimentation points where the channels bend. Hydrochemical analysis showed that groundwater is predominantly of the Cl-Na type. Hydrogen and oxygen isotopes, along with the MixSIAR model, indicated that recharge primarily originates from canal water infiltration (contribution rate > 92%). Analysis of influencing factors revealed that agricultural fertilization, livestock manure, and rural domestic wastewater discharge are the core pollution sources. Hydrogeochemical processes (such as high Cl^- competitive adsorption promoting phosphorus migration and high HCO₃ ^- facilitating phosphorus precipitation) and rainfall events collectively shape the spatiotemporal patterns of nitrogen and phosphorus pollution. These findings provide a scientific basis for groundwater pollution control and sustainable agricultural management in irrigation districts.

The eastern Shijin Irrigation District has long employed a conjunctive well-canal irrigation model. To investigate the impacts of irrigation activities on the spatiotemporal distribution and spatial correlation of groundwater, this study analyzed groundwater depth data from 64 monitoring wells (covering both deep and shallow aquifers) during 2018-2023 using spatial interpolation techniques. The research focused on elucidating the interannual and intra-annual evolution patterns of deep and shallow groundwater in the irrigation area, along with evaluating the influences of rainfall and irrigation practices on spatiotemporal groundwater depth variations. Key findings include: ① Ordinary Kriging with a Gaussian function demonstrated superior interpolation accuracy, establishing it as the optimal model for groundwater analysis in the eastern Shijin Irrigation District. ② Spatially, shallow groundwater depth generally exhibited lower values in the north and higher values in the south, showing a gradual increase from north outward. Deep groundwater depth displayed an opposite pattern, with lower values in the southeast and higher values in the northwest, increasing gradually from southeast to northwest. Temporally, during 2018-2023, shallow groundwater depth showed an increasing trend with an average rise of 1.36 m, while deep groundwater depth demonstrated a decreasing trend with an average reduction of 2.5 m. ③ Shallow groundwater in the study area is predominantly brackish, with its intra-annual dynamics significantly influenced by rainfall cycles, showing average fluctuations of 1.42 m in brackish zones and 18.91 m in freshwater zones. Deep groundwater consists of unconfined freshwater, with its dynamics primarily driven by pumping activities, exhibiting a maximum fluctuation of 27.58 m. Both aquifers displayed remarkable seasonal co-variation and highly synchronized patterns: groundwater levels remained relatively high under natural conditions during January-February, progressively declined to their lowest levels due to intensive pumping from March to June, recovered during July-September with rainfall recharge and reduced extraction, and stabilized from October to December. ④ Analysis of Gaussian model parameters through the nugget-to-sill ratio revealed moderate spatial correlation for both deep and shallow groundwater depths in January, February, and December, with strong spatial correlation observed during the remaining months. Deep groundwater consistently exhibited stronger spatial correlation than shallow groundwater. These spatial correlation patterns showed strong association with groundwater extraction processes, where intensified pumping correlated with enhanced spatial correlation, and vice versa.

Predicting the level of sustainable utilization of regional water resources under the impacts of climate change and human activities is of great significance for formulating reasonable water resource planning strategies and ensuring the sustainable development of social economy. By coupling the three-dimensional water ecological footprint with system dynamics, a system dynamics model of the three-dimensional water ecological footprint in Sichuan Province was established to dynamically predict the water ecological security levels under four scenarios considering the impacts of climate change and human activities. On this basis, the Tapio decoupling model and the Logarithmic Mean Divisia Index (LMDI) model were adopted to quantify the decoupling relationship between water ecological footprint and economic development, as well as the driving forces causing changes in water ecological footprint. The results show that: the water resources are in an ecological surplus state under all four scenarios; the consumption of water resource capital flow is in a relatively stable state; the decoupling effect between water ecological footprint and economic growth presents strong and relatively strong decoupling states; the economic effect and technological effect are the primary driving forces promoting and inhibiting the growth of water ecological footprint, respectively. Through comparison, the water ecological security level under scenario TS1 is the highest, which promotes the coordinated and sustainable development of water resource utilization, social and economic development, and ecological environment protection, and is suitable for the future development model of Sichuan Province.

Autumn irrigation is a traditional practice in the Hetao Irrigation District for post-autumn salt leaching and spring soil moisture conservation, and is vital for agricultural production. Under the rigid constraints of water resources, formulating a reasonable water-saving autumn irrigation system is of great significance for improving the utilization efficiency of water resources in irrigation districts. Field trials were conducted from 2023 to 2024, with six autumn irrigation quota treatments: 1 500 m³/hm² (W1), 1 800 m³/hm² (W2), 2 100 m³/hm² (W3), 2 400 m³/hm² (W4), 2 700 m³/hm² (W5), and 3 000 m³/hm² (W6) for treatment By analyzing the variation patterns of soil water and salt after autumn irrigation and the soil water and salt conditions before spring sowing, recommended water-saving autumn irrigation quotas for wheat and corn, tailored to current plot configuration, were proposed. The results show that autumn irrigation has a significant impact on the soil moisture content of 0~60 cm. After autumn irrigation, the soil moisture content of 0~20 cm increases by more than double (145.40%~171.59%), and the salt content decreases by 12.73%~34.59%. Moreover, the variation range increases with the increase of irrigation quota. When the autumn irrigation quota is less than 2 100 m³/hm² (W3), the effective leaching depth of soil salinity is 60 cm. When the irrigation quota is greater than 2 100 m³/hm², the salt can be leached to a deeper level (below 100 cm). Overall, the 0~100 cm soil layer shows a desalination trend, with a salt leaching rate ranging from 1.37% to 15.70%. The water-increasing efficiency of the 0-100 cm soil layer before freezing was negatively correlated with the autumn irrigation quota, ranging from 47.60% to 61.77%. The water increase efficiency of wheat and corn before sowing showed a trend of first increasing and then decreasing with the autumn irrigation quota. The treatments with irrigation quotas of 1 800 m³/hm² (W2) and 2 100 m³/hm² (W3) performed the best, which were 67.79%, 72.21% and 48.96%, 53.37% respectively. The salt leaching efficiency of each treatment before freezing and before sowing of wheat and corn was positively correlated with the autumn irrigation quota. Moreover, the larger the soil salt storage before autumn irrigation, the higher the salt leaching efficiency. Taking into account the goals of water conservation, moisture retention and salt leaching comprehensively, the suitable autumn irrigation quota for wheat planting is 2 100 m³/hm², and for corn planting, it is 2 400 m³/hm².

To explore solutions to the increasingly severe soil salinization and seasonal water shortages in cotton fields of Southern Xinjiang. Taking drip irrigation under plastic mulch in the Aksu area of Southern Xinjiang as the research subject, a field experiment with a two-factor randomized block design was conducted, involving mulching methods and irrigation modes. The mulching methods included double-film mulching, thickened single-film mulching, and conventional single-film mulching. The irrigation modes consisted of 6 times of fresh water irrigation with an irrigation amount of 325 mm,6 times of fresh water plus 2 times of saltwater irrigation with an irrigation amount of 385 mm, and 8 times of fresh water irrigation with an irrigation amount of 385 mm. The study investigated the effects of double-film mulching and saltwater supplementary irrigation on soil water-salt transport, irrigation water use efficiency, and crop yield. The results showed that at the seedling stage, compared with the thickened single-film and conventional single-film mulching treatments, the double-film mulching treatment increased the average soil moisture content by 7.38% and 29.58%, and reduced the average soil electrical conductivity by 19.09% and 29.21%, respectively. At the bud stage, the double-film mulching treatment reduced the average soil electrical conductivity by 28.00% and 31.52%, respectively, compared to the thickened single-film and conventional single-film mulching treatments. At the flowering stage, the reductions were 23.77% and 31.05%, respectively, the saltwater irrigation treatment increased the average soil moisture content by 4.82% and 5.27%, respectively, compared to the 6 times of fresh water treatment, the average electrical conductivity increased by 9.76% and 13.90%, respectively, compared to the 6 times of fresh water treatment, and by 24.02% and 18.73%, respectively, compared to the 8 times of fresh water treatment. The cotton yield under the double-film mulching treatment increased by an average of 10.20% and 12.62%, respectively, compared to the thickened single-film and conventional single-film mulching treatments, while the economic benefits increased by 9.84% and 12.26%, respectively. Compared to the 6 times of fresh water treatment, the saltwater irrigation treatment increased cotton yield and economic benefits by 1.67%~14.99% and 1.20%~14.11%, respectively, but decreased them by an average of 4.00% and 4.01%, respectively, compared to the 8 times of fresh water treatment. In conclusion, under conditions of low temperature and high soil salinity during the seedling stage in Southern Xinjiang, double-film mulching can reduce surface soil salinity and promote cotton emergence, during periods of seasonal water scarcity, saltwater irrigation helps conserve soil moisture and stabilize yield.

Soil moisture (SM) is a fundamental variable in land surface processes and agricultural water management. Accurate monitoring of its spatiotemporal dynamics is crucial for water-saving irrigation and precision crop scheduling in arid and semi-arid regions. To address the sensitivity of traditional retrieval methods to vegetation interference and their limited adaptability, this study systematically evaluated the performance of three typical change detection algorithms—Short-Term (STCD), Advanced (ACD), and Long-Term Change Detection (LTCD)—across diverse underlying surfaces in the Qingtongxia Irrigation District, utilizing Sentinel-1 SAR imagery. Multi-source datasets including SMRFR (Soil Moisture via Random Forest Regression) and SMAP (Soil Moisture Active Passive) soil moisture products were integrated as prior constraints and validation, with both time-varying and fixed boundary conditions considered. Multi-year time series analysis was conducted to assess the accuracy, stability, and surface-type adaptability of each method. Results show that the ACD method achieved the best overall performance, with an average correlation coefficient (r) of 0.45 and unbiased root mean square error around 0.04 m³/m³. The STCD-V approach demonstrated strong responsiveness in cropland areas, while the LTCD-SM method exhibited high stability and reliable error control. Time-varying constraints consistently outperformed fixed boundary ones. Overall, by introducing vegetation index correction and multi-temporal information fusion, ACD effectively enhanced the applicability and accuracy of soil moisture retrieval across the irrigation districts. This study provides methodological insights for Sentinel-1–based soil moisture retrieval at the field scale and offers scientific support for precision irrigation and water resource management in arid regions.

In order to accurately understand the distribution characteristics of soil moisture in the sandy land east of the Yellow River in Ningxia, this study explores inversion models and methods for soil moisture content in sandy land, which provides theoretical support and decision-making reference for research on the spatial distribution of soil moisture. Using microwave remote sensing data from Sentinel-1 SAR combined with multispectral data from Sentinel-2, the soil moisture content at different depths (5, 10 and 20 cm) in the sandy land east of the Yellow River in Ningxia was inverted by integrating the Water Cloud Model and the Random Forest algorithm. The results showed: ① Correlation analysis between different environmental variables and soil moisture content across layers revealed significant differences. Band reflectance (B11, B12) showed a significantly negative correlation with soil moisture at all depths. The normalized difference vegetation index was positively correlated with soil moisture at 5 cm and 10 cm, while the backscattering coefficient (VV+VH) exhibited a significantly negative correlation with soil moisture at 5, 10 and 20 cm. ②Analysis of model evaluation metrics showed that the coefficient of determination between measured and validated values for soil moisture across the three layers ranged from 0.75 to 0.85, with root mean square errors between 0.02% and 0.04%, indicating that the Random Forest model achieves high accuracy in soil moisture inversion. ③ The soil water content in the study area was generally low, and the overall soil water content was less than 3.00%.　The inversion results of soil water content show strong consistency with the actual measured values. By integrating Sentinel-1/2 remote sensing data with vegetation indices and backscattering coefficients, the method demonstrates high accuracy in soil moisture inversion for this area and can effectively capture the spatial distribution characteristics of regional moisture.

Addressing the challenges of strong spatial heterogeneity in soil and the inefficiency and high cost of traditional field sampling methods in the agro-pastoral ecotone of Northwest China, which hinder large-scale dynamic monitoring and mapping of soil organic matter, this study aims to achieve rapid and high-precision estimation of soil organic matter content across the region. Landsat 8 remote sensing imagery and field-collected surface soil samples were integrated to calculate various band reflectances and spectral indices. Correlation analysis was employed to screen spectral variables significantly associated with soil organic matter content. Three machine learning models—Random Forest, Gradient Boosting Machine, and Support Vector Machine—were constructed to establish quantitative inversion relationships between spectral variables and soil organic matter content. Their estimation performances were evaluated through comparative validation. The results showed that: among single bands, green and red band reflectances exhibited the highest correlation with measured soil organic matter values; among various spectral indices, the Soil Organic Carbon Index demonstrated the most significant correlation with organic matter content; the key variable combinations selected by the three models were highly consistent, with red band, near-infrared band, Normalized Difference Soil Index, and Enhanced Vegetation Index playing major roles in estimation; the Random Forest model achieved the highest estimation accuracy, with a determination coefficient (R2) of 0.88 and a root mean square error (RMSE) of 0.75 g/kg, while also demonstrating good stability. In conclusion: the integration of multispectral remote sensing and machine learning enables efficient and large-scale quantitative inversion of soil organic matter in arid and semi-arid regions; visible light bands and specific soil and vegetation spectral indices serve as key information sources for characterizing the spatial variability of surface soil organic matter in such areas; the Random Forest model exhibits advantages in processing spectral data and complex nonlinear relationships, making it suitable for remote sensing quantitative inversion tasks of this kind; the established variable screening framework and modeling methodology can provide methodological references for remote sensing monitoring of soil properties in ecologically fragile regions with similar spectral characteristics.

To investigate the effects of deep plowing in arid regions combined with subsurface drainage on the improvement of saline-alkali soils, experiments were conducted in the Yanqi Basin. The study examined the changes in soil water-salt content and physical properties under spring irrigation conditions, focusing on two factors: plowing depth [0 (D0) and 70 cm (D70)]and subsurface drainage pipe spacing [20 (H20), 30 (H30), and 40 m (H40)]. Soil moisture content showed a significant relationship with plowing depth and subsurface drainage pipe spacing. After spring irrigation, the average moisture content of the surface layer (0~20 cm) in the D70H20 treatment increased from 24.17% to 27.54%; After spring irrigation, at soil depths of 0~80 cm, the average soil desalination rate showed a significant relationship with pipe spacing and plowing depth (p<0.05), and an extremely significant relationship under synergistic effects (p<0.01). At the same plowing depth: the soil desalination rate showed a negative linear relationship with pipe spacing; at the same spacing: when the plowing depth was 70 cm, the soil desalination rate reached its highest value of 27.13%. After spring irrigation, the soil desalination rate was optimal in the area 0.2 m from the sub-surface drain, and the soil desalination rate showed a negative correlation with the horizontal distance from the sub-surface drain. Under the synergistic effect of deep plowing and spacing, the soil bulk density in the 0~70 cm soil layer significantly decreased by 15.38%, and porosity increased by 24.10%. Among all treatments, D70H20 was the optimal. In summary, the suitable parameters for the study area are a plowing depth of 70 cm and a spacing of 20 m. These research results can provide reference for subsurface drainage technology for saline-alkali land remediation in arid regions.

Deep micro-moistening irrigation is a type of mid-to-deep continuous irrigation suitable for orchards. To explore the dynamic characteristics of soil moisture in deep micro-irrigation, a three-dimensional soil moisture movement model for deep micro-irrigation in orchards under adaptive flux boundary conditions was constructed based on the principles of soil hydrodynamics, considering factors such as irrigation, rainfall, surface evaporation, and root water uptake. The model was solved using COMSOL Multiphysics software and validated using experimental data. The soil moisture movement characteristics of deep micro-irrigation in orchards were systematically analyzed. The results show that the model can accurately simulate the spatiotemporal dynamics of soil moisture under deep micro-irrigation, with simulation errors of soil moisture content and various water processes all below 6%, indicating high accuracy and reliability; The use of adaptive flux boundaries enables a more accurate description of soil moisture dynamics. The micro-irrigation system forms an ellipsoid wetting body centered on the micro-irrigation pipe in the soil. The soil moisture content in the root layer (20~80 cm) remains stable at 70%~90% of the field capacity, while the soil moisture content in the deep soil layer (80~200 cm) is maintained between 50% and 70%, showing significant vertical stratification of soil moisture. The system also has the ability to adaptively adjust based on soil water potential feedback, with irrigation rates dynamically changing according to soil wetness. The fruit swelling period is a critical period for water consumption, with transpiration ratio reaching its peak. The transpiration ratio of T2 treatment (buried at 20 cm) was higher than that of T1 treatment (buried at 10 cm) throughout the growth period, with a reduction of 5%~8% in evaporation and an increase of 6%~10% in transpiration ratio. Reasonably increasing the burial depth can significantly optimize the crop water consumption ratio and improve the transpiration ratio of crops.

To effectively address the impact of meteorological disasters on the Golden Fruit industry, risk indices for key growth stages were constructed, with disaster characteristics analyzed to ensure stable development. Based on daily meteorological data (2005-2024) from the Jianzha and Tongren national stations, along with Golden Fruit phenological data from 2025, two indices were developed using the information entropy weight method: the Low-Temperature Frost Index during the flowering period and the Continuous Rainy Weather Index during the maturity and harvest period. Disaster severity levels were classified using the natural breaks method. Results indicate that the main disaster-causing factors for low-temperature frost during the flowering period include accumulated negative temperature, extreme daily minimum temperature, and cumulative sunshine duration 1~3 days before the event. For continuous rainy weather during the maturity and harvest period, the primary factors are the cumulative rainy days and total precipitation. From 2005 to 2024, a decreasing trend was observed both in low-temperature frost during the flowering period and in continuous rainy weather during the maturity and harvest period of golden fruit. While the risk of low-temperature frost was found to be higher in Jianzha, large-scale cultivation was considered more suitable in Tongren. Future work should focus on standardizing phenological and meteorological disaster observations, progressively refining the meteorological disaster risk indices, and evaluating their applicability. These efforts aim to support precise risk warnings for key growth stages of Golden Fruit.

The Hankou-Hukou reach in the middle reaches of the Yangtze River is one of the core areas within the Yangtze River system, characterized by complex natural evolution and intensive human activities, and is also a key region for flood control. Channel topographic evolution holds significant importance for flood control safety and the ecological environment. Current understanding of the channel erosion and deposition patterns under conditions of rapid shifts from high to low flow in the Yangtze River Basin remains insufficient. This study focuses on the rapid high-to-low flow shift event occurring in the middle and lower Yangtze reaches in 2024. Based on channel topographic survey data, the erosion and deposition characteristics of the Hankou-Hukou reach were analyzed. The results indicate that this reach transitioned from erosion to deposition. The bankfull channel from Hankou to Hukou experienced a total deposition of 4.42 million m3, while the low-water channel scoured 6.30 million m3, collectively exhibiting a pattern of "deposition on bars and scour in channels." Significant deposition occurred notably at the heads of mid-channel bars, within branching secondary channels, and in expanding reaches downstream of nodal points. Combined with water and sediment data from key control stations on the mainstem, the causes of deposition in the Hankou-Hukou reach were analyzed. The analysis shows that the rapid high-to-low flow shift exacerbated channel morphological adjustments by weakening flow dynamics, reducing water surface slopes, and diminishing sediment transport capacity. This research provides a scientific basis for the joint operation of reservoir groups and channel regulation under extreme climatic conditions.

U-shaped channels are widely utilized in irrigation systems due to their high water conveyance efficiency, excellent anti-seepage performance, and strong frost resistance. To improve the accuracy of flow measurement in U-shaped channels while minimizing head loss, it is of great significance to investigate the outflow characteristics of structurally simple plate gates and establish reliable flow calculation methods. This study systematically examines the influence of channel bottom slope (i), upstream water depth (H), and gate opening (e) on the hydraulic characteristics of a plate gate in a U-shaped channel through experimental modeling and numerical simulation. Based on the sluice gate flow theory, a discharge calculation formula for flat-plate gates in U-shaped channels under free outflow conditions was developed. The results indicate that the upstream Froude number decreases with increasing upstream water depth but increases with larger gate openings. Furthermore, the flow downstream of the gate forms diamond-shaped waves accompanied by significant head loss, which diminishes as both the gate opening and channel slope increase. The backwater height rises with steeper slopes and greater upstream water depths, however, as the gate opening increases, the flow-blocking effect of the gate weakens, leading to a reduction in backwater height. Based on the sluice gate outflow theory, a comprehensive discharge coefficient ( {\mu }_s) related to the channel slope (i) and relative opening (e/H) is introduced, leading to an empirical formula for estimating free flow discharge under such conditions. With the channel bottom slope fixed at 0.003, the proposed formula was validated. The maximum relative error between the calculated and measured flow rates is 3.92%, demonstrating the high accuracy of the proposed formula for flow measurement.