To investigate the effects of different climatic conditions and water management on the net CO₂ flux in rice paddies, field experiments were conducted using open-top chambers (OTC). Six treatments were established under both controlled and flooded irrigation conditions: elevated CO₂ concentration by 200×10^-6 (CCO and FCO), elevated CO₂ concentration by 200×10^-6 combined with elevated temperature by 2 °C (CCOT and FCOT), and ambient atmospheric conditions (CCK and FCK). Results showed that the variation patterns of net CO₂ flux in rice paddies were generally consistent across treatments, exhibiting an initial increase followed by a decrease, with peaks during the jointing-booting and milk-ripening stages. Compared to CCK, the CO₂ absorption rate in CCO-treated paddies increased by 10.40% to 40.78%. CCOT treatment enhanced CO₂ absorption rates during the tillering, jointing-booting, and milk stages but reduced CO₂ absorption during the heading-flowering and ripening stages. Compared to FCK, the CO₂ absorption rate in FCO-treated paddies increased by 1.19% to 52.01%, while FCOT treatment increased by 8.63% to 121.88% relative to FCK. CO treatments increased CO₂ absorption rates under both controlled and flooded irrigation conditions. However, the effect of COT treatments on net CO₂ flux varied depending on water management and rice growth stages, with flooded irrigation significantly enhancing CO₂ absorption capacity. Enhanced daily-scale net CO₂ absorption was observed in CCO and CCOT treatments on nearly every typical day. Controlled irrigation paddies over the entire growth period and flooded irrigation paddies in early growth stages exhibited the highest daily average net CO₂ absorption rates under CO treatment, while flooded irrigation paddies in later growth stages showed stronger CO₂ absorption under COT treatment. The study indicates that the impact of elevated atmospheric CO₂ concentration and temperature on net CO₂ flux in rice paddies varies by growth stage, and water-saving irrigation may dimish the positive effect of climate change on the carbon sink capacity of rice paddies.

To address the high uncertainty in domestic water use forecasting, this study introduces a KDE-IGMS interval prediction model to forecast domestic water consumption in Shaanxi Province. First, based on domestic water use data from 2002 to 2022, a similarity distance method based on water use process curves is employed to conduct cluster analysis on the time series of domestic water consumption in various cities. These sequences are categorized into three types: high-growth, slow-growth with fluctuations, and irregular fluctuation types. According to the characteristics of each type, improved grey model series (IGMS) are constructed for water use prediction and compared with prediction results from Long Short-Term Memory (LSTM) networks and Gaussian Process Regression (GPR) models. Then, non-parametric Kernel Density Estimation (KDE) is applied to fit the error distribution and calculate the prediction intervals. Finally, the KDE-IGMS model was used to forecast the interval of domestic water consumption intervals for various cities in Shaanxi Province for the year 2030.The results show that the IGMS model outperforms both the LSTM and GPR models in terms of RMSE、MAPE and R2, with particularly notable improvements in predicting high-growth water use sequences. In addition, the interval prediction results demonstrate a high coverage probability (PICP = 0.95) and a narrow interval width (PINAW = 0.040 3). By 2030, the domestic water consumption in Xi’an and Yulin is projected to increase by nearly 60% compared to 2022, while cities such as Baoji, Xianyang, and Weinan are expected to experience moderate increases of around 10% to 20%, and demand growth in Tongchuan and Shangluo is relatively limited. These findings indicate that, by classifying water use sequence types, the improved IGMS model demonstrates clear predictive advantages for short, strongly trending high-growth sequences. Furthermore, the KDE method effectively reduces prediction uncertainty. It is recommended that future efforts focus on regions with rapidly increasing water demand, such as Xi’an and Yulin, by strengthening water resource assurance, enhancing water use management, and improving water-saving practices.

In order to systematically analyze the spatial and temporal distribution and utilization efficiency of water resources in Xinjiang and promote the sustainable development of Xinjiang's economy, society and ecology, a System Dynamics (SD) model of dynamic balance between supply and demand was constructed. Four development scenarios of maintaining the status quo (S1), economic development (S2), water conservation (S3) and sustainable development (S4) were proposed through the principle of control variables, and the water demand and water supply and demand balance of Xinjiang from 2024 to 2035 were simulated and dynamically analyzed. The results show that: ① During the forecast period, the total water demand of Xinjiang showed an upward trend under the four scenarios, with the average total water demand of 71.732 3、72.071 9、60.331 1 and 60.548 6 billion m³, and the average supply-demand ratio of 0.887%、0.883%、1.054% and 1.050%, respectively. ② Under the four scenarios, if the status quo is maintained, Xinjiang will face serious water shortages after 2030. Economic development will further exacerbate the contradiction between supply and demand of water resources. The water-saving type effectively reduces the total water demand and greatly alleviates the pressure on water supply and demand, but at the same time, it will limit the rapid economic development of Xinjiang. The sustainable development type is adjusted from many aspects, which not only ensures economic development, but also ensures the sustainable use of water resources, representing the optimal strategy for Xinjiang’s societal development. The results of this study can provide a reference for the rational utilization of water resources and the sustainable development of human-water relations in Xinjiang.

This research focuses on the growth performance and physiological feedback mechanisms of crops under diverse irrigation conditions with different water quality types, aiming to develop new and efficient approaches for agricultural production practices. The aim is to identify, through rigorous experiments, the optimal irrigation water that can contribute to increased crop yields, income, and improved quality. Taking lettuce, a plant with relatively high experimental precision, as the model plant, five different water quality types (tap water, activated water, purified water, mineral water, and hydrogen-rich water) were selected to irrigate lettuce samples. The germination of lettuce seeds, fresh and dry weights of shoots and roots, photosynthetic pigment content, soluble sugar content, soluble protein content, vitamin C content, and antioxidant enzyme activity were monitored and analyzed to comprehensively explore the effects of different water quality types on the growth and development of lettuce, and further accurately identify the water quality category most suitable for lettuce growth. The research indicates that under the same cultivation conditions, the five different water quality types have different promoting effects on various indicators of lettuce. Among them, the effects of the activated water and hydrogen-rich water groups were significantly higher than those of the other groups, while the malondialdehyde content was significantly lower than that of the other groups. Through a comprehensive analysis of various indicators of lettuce, under the irrigation conditions of activated water and hydrogen-rich water, the growth and development, nutritional quality, and antioxidant system activity indicators of lettuce were optimal.

The construction and operation of electric power irrigation projects can effectively address the challenge of uneven distribution of regional water resources, which is of great significance for the rapid development of regional social economy and ecology. Developing a unified evaluation index system to quantitatively evaluate the ecological benefits of electric power irrigation projects can help improve the level of refined utilization of regional water resources and promote high-quality development. Focusing on Jingtai County, an arid area within the Yellow River Basin as the research object, this study constructs an ecological benefit evaluation system for ecological migration areas, explores the ecological contribution and influencing factors of electric power irrigation projects to the region, and systematically analyzes the impact of climate change and human activities on the ecological benefits of the study area. The results showed that: ① from 1990 to 2020, the main land use transfer mode in Jingtai County was the mutual conversion between cultivated land and low to medium coverage grassland; ② Grasslands with medium to low coverage and unused land show high levels of fragmentation; Except for the indices of landscape segmentation, sprawl, and aggregation, all other indices have shown an overall increasing trend over the past 30 years; ③ The annual mean NDVI showed a trend of first decreasing and then increasing, with an overall decrease of 7.47% over 30 years, indicating a continuous improvement from high-value areas to surrounding areas; ④ The annual average value of NPP first decreased and then increased, with a significant increase of 124.31 gc/m² from 2000 to 2020. This ecological benefit assessment in the arid areas of the Yellow River Basin can comprehensively evaluate the ecological benefits of water resource redistribution resulting from the construction of large-scale irrigation areas in the region, and provide scientific references for ecological construction.

In order to clarify the effect of biochar application under deficit regulation at critical fertility stage on N fertilizer utilization and yield in winter wheat, three water treatments were set up in the field: full irrigation at full fertility stage [W1, 70%~80% field water holding capacity (θ _f)], medium deficit regulation at nodulation stage (W2, 50%~60% θ _f) and medium deficit regulation at filling stage (W3, 50%~60% θ _f), and three types of charcoal application: no charcoal application ( C1), low-moderate charcoal (C2, 15 t/hm²) and high charcoal (C3, 30 t/hm²), soil water content (SWC), soil nitrogen distribution, nitrogen leaching, nitrogen fertilizer destination and winter wheat yield were studied. Results showed that the application of biochar under deficit adjustment at nodulation or irrigating stage could increase the contents of SWC, nitrate nitrogen and ammonium nitrogen in the 0~40 cm soil layer, and reduce the nitrate nitrogen and ammonium nitrogen loss. The water-holding and nitrogen-retaining effects of biochar were more pronounced at th high application rate. Compared with the fully irrigated treatment, the proportion of nitrogen fertilizer uptake (N _dff), nitrogen fertilizer utilization and yield of wheat organs were slightly higher in the irrigated stage deficit adjustment treatment, while lower in the nodulation stage deficit adjustment treatment. Nitrogen fertilizer utilization, N _dff, yield and water use efficiency were increased by 1.89%, 7.86%, 10.05% and 9.22%, respectively, and N _dff loss rate was reduced by 16.05% under W3C3 treatment compared with W3C1 treatment. The highest N _dff and yield were recorded in the W3C3 treatment, which was 34.16% and 6 220.1 kg/hm², respectively, and the lowest loss rate was 20.58%. In conclusion, the high carbon treatment (50%~60% θ _f, 30 t/hm²) could achieve higher N fertilizer utilization and wheat yield during the filling period.

To construct the AquaCrop model for root zone irrigation and optimize winter wheat irrigation regimes under this system, this study performed two-year field experiments from 2022-2024 in Yuncheng, Shanxi Province. Two root zone irrigation patterns were established: T1 with drip irrigation pipes buried 40 cm underground, and T2 with drip irrigation pipes both at the surface and 40 cm underground (with a surface-to-underground water ratio of 3∶7). Field data were used to calibrate AquaCrop model parameters, and irrigation regimes were optimized based on comprehensive analysis of yield and water use efficiency across different hydrological conditions. Results showed that: ① The calibrated AquaCrop model demonstrated high simulation accuracy for winter wheat growth under root zone irrigation with R2 for canopy cover of 0.99, CVRMSE of 1.4%~4.0%, and d of 0.97~1.0; biomass simulation R2 of 0.93~0.95, CVRMSE of 19.3%~23.8%, and d of 0.93~0.94; soil moisture simulation R2 of 0.78~0.93, CVRMSE of 11.0%~20.8%, and d of 0.87~0.93; ② Root zone irrigation improved water use efficiency, reaching 2.44 kg/m3 under normal water year conditions; ③ For extremely dry and moderately dry years, T1 treatment performed best with four irrigations recommended (67.5 mm each during overwintering, jointing, heading, and grain filling stages); for normal water years, T2 treatment was slightly superior with three irrigations recommended (67.5 mm each during overwintering, jointing, and heading stages); for wet years, both treatments performed similarly. Two irrigations (67.5 mm each during overwintering and jointing stages) yielding optimal results.

At present, most research on Pennisetum giganteum focused on the variety introduction, feeding value, protein nutrition, effect on soil microorganism and cultivation technology. However, there is no relevant research on the evapotranspiration characteristics and irrigation schedule of the Pennisetum giganteum. This study investigated the evapotranspiration characteristics of the Pennisetum giganteum in arid and semi-arid areas were studied, and determined the optimal irrigation time, irrigation quota, irrigation times and irrigation quota were mastered. Based on field experiments, water balance theory and CROPWAT model, the evapotranspiration characteristics of Pennisetum giganteum in arid and semi-arid areas were analyzed, and suitable irrigation schedules were developed for different hydrological years based on high-yield targets. The results showed that, the E/ET ratio was the highest (0.86) during the fast-growing period and the lowest (0.28) during the harvest period. The evapotranspiration of Pennisetum giganteum was as follows: rapid growth stage>jointing stage>tillering stage>turning green stage>harvest stage. From the analysis of the coupling degree between evapotranspiration and effective rainfall, it can be seen that the coupling degree of the extremely dry year from May to August is low, and the coupling degree of the dry year and the normal year in June is low, and the irrigation level needs to be increased during this period. For wet years, the coupling degree in different periods is between 0.92 and 0.99, and only an appropriate amount of supplementary irrigation is needed. Combined with the CROPWAT model, the optimal irrigation system of Pennisetum giganteum in wet year, normal year, dry year and special dry year was obtained as follows: irrigation frequency of 7~14 times, irrigation quota 13.7~53.3 mm, total irrigation quota 285.3~492.7 mm.

To determine the representative period of soil respiration within the daily variation dynamic range of the extremely arid ecological migrantion area, and to investigate the effects of abiotic factors soil temperature and soil moisture on soil respiration rate, can improve the accuracy and reliability of soil respiration data to reflect the real level, and lay a solid foundation for the subsequent accurate assessment of carbon emissions in the area. Four typical landforms were selected in the southern margin of the Tengger Desert for long-term measurements of soil respiration by using the LI-COR 8100 soil respiration observation system, and the representative time periods of the daily variation of soil respiration in different land use types were investigated, which can be effectively applied to the daily variation of soil respiration rate to the estimation of the total soil carbon emission at the monthly scale. By comparing the rate difference of different time periods, the 2-hour representative period of each land use type was determined. The 2-hour characteristic period of the grassland and the original landform is 7∶00-9∶00 in the morning, 17∶00-19∶00 in the afternoon, and 18∶00-20∶00 in the original landform. The morning time of lime stick forest and cultivated land is from 8∶00 to 10∶00, the afternoon time of cultivated land is from 16∶00 to 18∶00 (the earliest of the four land use types), and caragana forest is from 18∶00 to 20∶00. Regarding the relationship between soil respiration rate and environmental factors, soil temperature was the main influencing factor, which was significantly positively correlated with the respiration rate and increases exponentially, explaining 75%~85% of the variation in soil respiration, and the calculated Q ₁₀ values showed that the original landform had the highest sensitivity to temperature, and cultivated land had the lowest. Soil respiration rate was also significantly and positively correlated with soil moisture at 10 cm depth. A linear fit showed that changes in soil moisture explained 43%~69% of the variation in soil respiration rate. A quadratic fit showed that it explained 62%-79% of the variation, and the respiration rate increased with the increase of moisture. Sobol sensitivity analysis showed that the sensitivity of soil respiration to soil water change was higher than that of soil temperature. Considering the arid climate of the study area with low annual precipitation and high evapotranspiration, soil temperature is the main influencing factor for the variation of soil respiration rate.

Precise simulation of rice growth is of great significance for guiding field management and increasing crop yields. The ORYZA Version 3 (ORYZA_V3) model has been widely used to simulate rice growth in farmland systems. However, few studies have investigated the simulation performance of this model for rice growth in Chongqing. Based on the field experiment data from rice trials at the Irrigation Experiment Station in Chongqing, this study evaluates the simulation accuracy of the model for six rice growth variables. The results showed that: ① The ORYZA_V3 model could accurately simulate rice phenology, leaf area index, total above-ground biomass, and yield, with WIA ranging from 0.72 to 0.97, RRMSE from 5.13% to 14.47%, and R2 from 0.91 to 0.97; ② The simulation accuracy of the model for leaf nitrogen content was lower than that for the aforementioned four variables, but it was still within an acceptable range, with WIA from 0.96 to 0.97, RRMSE from 16.14% to 18.50%, and R2 from 0.91 to 0.92; ③ However, the simulation accuracy of the model for panicle nitrogen content was poor, with WIA from 0.43 to 0.45, RRMSE from 67.26% to 110.19%, and R2 from 0.41 to 0.48. In future research, the simulation accuracy of the model for panicle nitrogen content can be improved by optimizing the module about nitrogen migration and transformation among rice organs. In conclusion, this study demonstrates that the ORYZA_V3 model can provide modeling support for rice growth simulation and paddy field management in Chongqing.

The scientific maintenance of ecological restoration of high and steep slopes in slag fields has become one of the urgent problems to be solved in production practice. To guide the design and application of the drip irrigation system for reconstructed soil on steep slopes, an indoor soil box experiment was conducted to simulate the soil moisture movement under drip irrigation on reconstructed soil slopes. The movement of the wetting front and the distribution of soil moisture were studied under different slopes (15°、30°、45°), emitter flow rates (1、1.5、2 L/h), and irrigation volumes (3、5、7 L). The results showed that with the increase of slope, the wetting front movement distance in the down-slope direction (R ₊) and the infiltration depth under the emitter (H) and the maximum infiltration depth (H _max) increased, while the movement distances in the up-slope direction (R _-) and cross-slope direction (R), as well as the maximum wetting front distance in the cross-slope direction (R _max), decrease. With larger emitter flow rates, R ₊ increases, while R _-、R、R _max、H and H _max all decrease. R ₊、R _-、R、R _max、H and H _max all exhibited a significant power function relationship with irrigation time (irrigation volume) (R ² > 0.95). At the end of irrigation, the soil moisture content within the wetting body decreases with increasing distance from the emitter. At points equidistant from the emitter at the same depth, the moisture content in the down-slope direction is higher than in the up-slope direction. In the profiles of the up-slope and cross-slope directions, the moisture content decreases as the slope and emitter flow rate increase. In the down-slope direction profile, the soil moisture content at different depths responds differently to slope and emitter flow rate. The greater the slope and emitter flow rate, the higher the average moisture content in the 0 and 5 cm layers, while the lower the slope and emitter flow rate, the higher the average moisture content at the 10 and 15 cm layers.

To facilitate the integrated development of the mountain-water-forest-farmland-lake-grass-sand system and ensure the sustainable utilization of water resources alongside the dynamic equilibrium of ecosystems, it is imperative to establish a comprehensive impact assessment framework for water security in the Yellow River. This study focuses on the Ordos section of the Yellow River, utilizing expert consultation, frequency statistical methods, and theoretical analysis, alongside a weighted average approach. It identifies 24 indicators, including climate aridity, sandstorm frequency, sedimentation dam effectiveness, soil and water conservation rates, land salinization levels, and water-sediment coordination, to develop a comprehensive evaluation system for assessing the impact on Yellow River water security. This system encompasses four criterion layers: Kubuqi Desert, Ten Major Tributaries, the South Bank of the Yellow River Forest-Grassland System, and the Yellow River Main Stream. The findings indicate that the wind-sand mitigation efficacy of the South Bank Forest-Grassland System is substantial, and the water quality of the Yellow River Main Stream is predominantly healthy. Furthermore, metrics such as desert vegetation coverage, soil and water conservation rates, the efficacy of ice flood ecological management, and the adherence of the flood control system to standards show strong performance in the overall assessment, while other indicators showed relatively poor performance. This assessment framework establishes a scientific foundation for the restoration and development of water security in the Yellow River, facilitating the sustainable utilization of water resources and the holistic restoration of the natural environment in the Ordos region.

To investigate the application potential of the Runner Irrigator in water-saving afforestation in desert regions, this study selected three desert plants species, lemon stripe, sand abraded jujube and four-winged quinoa, as the targets, and carried out field experiments at Minqin Comprehensive Experimental Station for Sand Control in Wuwei City, Gansu Province. Treatments included an experimental group (irrigated by the Runner Irrigator), a control group (conventional watering), and a water-adding group (secondary watering), to systematically evaluate its effects on plant transplanting survival rate, growth indexes, and soil. Results indicated that the wet irrigator significantly improved the survival rates of the three plants, which was 64%, 70% and 20% higher than that of the control group, and the survival rate of the second watering group reached 100%. Plant height and crown width in the experimental group were significantly greater than those in the control group, and the growth performance of the water-adding group was particularly outstanding. In addition, the soil water content of all soil layers (0~80 cm) was higher than that of the control group, especially in the soil layer of 20~60 cm, the effect of moisture conservation was significant. This study demonstrated that the Runner Irrigator, through precise water supply, can reduce evaporation losses, effectively improve root-zone water conditions, enhance the survival rate of desert plants and promote their growth. These findings provide technical support for water-saving afforestation and ecological restoration in arid areas.

Aiming at the large area of high-standard farmland in Xinjiang, the problem of unstable pipeline pressure and uneven drip irrigation caused by too long distance of water delivery in the process of automatic drip irrigation is designed a drip irrigation terminal system based on LoRa communication. The system features an STM32WLE5CBU6 microcontroller as its core control unit, is solar-powered, and employs LoRa star networking technology for in-field information communication. By collecting battery power and valve opening information, the drip irrigation terminal can feedback the operating status. Combined with the electric valve and pressure feedback, the outlet pressure of the drip irrigation terminal can be stabilized through the infinity-free adjustment of valve opening. In addition, a remote-control platform was designed to enable terminal management and remote operation. Field test results show that the system has highly reliable communication performance and pressure regulation ability, which can meet the demand of high standard farmland for the uniformity and stability of drip irrigation, and has certain practical value.

The impact of sediment on reservoir operation is a problem that cannot be ignored in reservoir operation and management. Sedimentation causes reservoir capacity loss and affect the functions of water supply, ecology and power generation. Sediment management needs to take into account the multi-dimensional objectives of siltation and power generation, ecology, water supply and flood control. Therefore, the multidimensional benefit analysis of sediment regulation is crucial to maximize the comprehensive benefits of reservoirs. This paper takes the backbone hub group of the main tributaries of the Yellow River as an example, proposes the multidimensional benefit indexes, establishes the multidimensional benefit evaluation model of sediment dynamic regulation of reservoir group based on the energy-value theory and economic method, and uses the model to calculate the benefits of flood control, sedimentation reduction, water supply, power generation, and ecological environment under different regulation schemes in a long series of years and typical years. The results show that over a long-term series, the operation of Guxian and Dongzhuang reservoirs can enhance the comprehensive benefits of the basin, and under different water and sand conditions in different typical years, the schemes of commissioning Guxian or Dongzhuang reservoirs are the optimal operation schemes.

In response to the low efficiency and insufficient automation of traditional open channel flow measurement, a multi-resolution grid-based automatic flow measurement method is proposed in this paper. Using rectangular open channels as the study subject, drawing on concepts from image resolution and channel geometry, and the cross-section is divided into a grid according to the channel width and water depth. The precise positioning of the velocity sensor in the direction of horizontal and vertical axis is realized through the coordinated control of single-chip microcomputer and stepper motor. After measuring the flow rate at the center point of the flow measuring unit, the flow rate area method is used to calculate the flow rate. The results show that under the same water depth, the relative error increases linearly with the area of the measuring unit, and decreases as a power function with the resolution n (n is the number of measuring units in the vertical direction). The flow measurement duration increases linearly with n. When the area of the measuring unit is 5 to 100 cm², the relative error is within 5%. This method breaks through the limitation of single point measurement, realizes the fine sampling of flow velocity field, and has the advantages of automatic, accurate and portable.

Canopy cover is an important parameter for calculating crop water requirements. This study aims to address the problems encountered in traditional UAV-based maize canopy extraction caused by uneven illumination, uncertain threshold selection, and an excessive reliance on large-scale labeled data. An iterative self-training recognition framework based on RGB imagery is proposed. First, raw images are enhanced using median filtering, adaptive histogram equalization (CLAHE-SV), and Retinex illumination correction. This enhancement improves contrast, highlights maize plant details, and reduces noise. Next, a multidimensional feature vector including the Excess Green Index (EXG) is constructed, and pseudo-labels for maize canopy cover are generated using an unsupervised Gaussian Mixture Model (GMM) clustering method. Finally, the DeepLab v3+ deep learning model is iteratively retrained using the pseudo-labels and a small set of manually labeled data (45 images, accounting for approximately 3.7% of the total sample) to gradually improve recognition accuracy. The results showed that, after multiple iterations, overall accuracy increased from 87.05% to 94.24%, and the Kappa coefficient improved from 73.26% to 87.97%. The proposed method effectively reduces the dependence on large-scale labeled data, providing an efficient and automated solution for UAV?based maize canopy cover remote sensing.

The development of saline soil in coastal areas is an important way to expand land resources, and due to the increasing shortage of freshwater resources, the improvement of saline soil by using local brackish water has become a key issue. In this paper, the indoor soil column infiltration experiments of brackish water (Ca²⁺/Na⁺=1∶0,2∶1,1∶2,0∶1) and organic materials (straw powder, organic fertilizer, biochar) with different ionic compositions were carried out to study the effects of brackish water irrigation and organic material addition with different ionic compositions on the water and salt transport process in coastal saline soil. The results showed that the ionic composition of brackish water was the main influencing factor of water movement in coastal saline soil, and the irrigation of brackish water with low Ca²⁺/Na⁺ was not conducive to soil water infiltration and soil moisture content. Organic materials promoted water movement under brackish water irrigation, increasing the infiltration rate increased by 8.00%-22.22% within the same period. Straw powder treatment was more effective in improving water infiltration. The lower the Ca²⁺/Na⁺, the higher the soil salt content, the lower the desalination rate and desalination depth coefficient. The desalination rate and desalination depth coefficient increased by 26.72%-64.75% and 79.43%-91.85%, respectively, and the calcium ion content was increased, which promoted sodium ion leaching, and the straw powder had the best effect, while the salt leaching effect of organic fertilizer and biochar was lower than that of straw powder treatment. The results showed that the application of organic materials could effectively promote the infiltration performance and water-holding capacity of coastal saline soil under brackish water irrigation. This practice also improves salt distribution, and reduces the risks of high-sodium brackish water, offering valuable insights for saline soil management in this region.