The application environment for ultrasonic Doppler flow meters is quite complex. To address issues such as low and medium flow rates being affected by noise, leading to low measurement accuracy and significant errors, an innovative noise reduction model has been proposed. This model combines Variational Mode Decomposition (VMD) with Singular Value Decomposition (SVD), based on an improved dung beetle optimizer (ISEDBO), to significantly enhance the signal-to-noise ratio of the echo signals. The method first optimizes the Dung Beetle Optimizer (DBO) using crossover strategies, suboptimal guidance control strategies, and theft behavior enhancement strategies. By comparing different test functions and other algorithms, the superiority of the ISEDBO algorithm is demonstrated. Secondly, the ISEDBO algorithm optimizes the VMD parameter combination, integrating Multi-scale Sample Entropy (MSE) and spectral coefficients to distinguish Intrinsic Mode Functions (IMF). Finally, SVD is used to perform dimensionality reduction and reconstruction on the effective IMF components, further overcoming the secondary harmonic oscillation phenomenon in the mid-low frequency range. Through the processing and analysis of simulation signals and laboratory towing experiments, the feasibility of the method is verified from multiple perspectives. Additionally, the ISEDBO-VMD-SVD noise reduction effect is compared with methods such as particle swarm optimization (PSO), grey wolf optimization (GWO), and dung beetle optimizer (DBO). The results show that, compared to simulated signals, ISEDBO-VMD can effectively suppress noise interference and significantly preserve the original signal characteristics. Compared to PSO-VMD, GWO-VMD, and DBO-VMD, it achieves a signal-to-noise ratio of up to 18.78 dB and a waveform correlation coefficient of up to 0.987. In the comparative towing experiment, statistical analysis of the MSE values for multiple signal groups effectively distinguishes the original signal from background noise. When comparing detection errors at different flow rates, ISEDBO-VMD-SVD has the smallest error, ranging from 0.009~0.02 m/s, which provides a solid foundation for practical water monitoring applications.

A hydraulic coupling model for light and small-scale sprinkler fertigation systems was developed to explore the impacts of fertilizer pump operation, sprinkler configuration, and working parameters on system hydraulic performance. The model integrates a water pump performance curve, a proportional fertilizer pump suction model, and a multi-outlet pipeline hydraulic calculation model. The fertilizer pump suction model, proposed based on experimental data, uses inlet pressure, inlet flow rate, and mother liquor concentration as independent variables. A comprehensive hydrodynamic calculation framework was established for the first time by coupling all components (water pumps, fertilizer pumps, pipelines, and sprinklers) based on the back-step method. Due to the strong nonlinearity of the model, a Genetic Algorithm (GA) was employed to solve it. A case study was conducted on a system with a 50ZB-30Q water pump, 10PY₂H sprinklers, and a D8R proportional fertilizer pump to analyze the impact of factors such as fertilizer pump operation, number of sprinklers, working pressure, nozzle diameter, and mother liquor concentration on pipeline pressure distribution. Results showed that compared with clear water irrigation, integrating the fertilizer pump increased the system's average specific energy consumption by 25% under different sprinkler number configurations. Interestingly, the fertigation process (even with dilute fertilizer) reduced the overall range of pipeline pressure fluctuations compared to clear water irrigation, which may be related to the periodic operation of the fertilizer pump. An excessive number of sprinklers (>11) tended to induce abrupt pressure changes, and a low sprinkler working pressure (0.22 MPa) increased system sensitivity to hydraulic disturbance. Conversely, increasing nozzle diameter (5.5 mm) effectively mitigated these pressure variations. Additionally, increased fertilizer concentration substantially elevated pipeline pressure, especially in systems with multiple sprinklers. The strong nonlinearity of these interactions underscores the necessity of prioritizing hydraulic stability in the optimization, evaluation, and precision control of sprinkler fertigation systems.

This study aims to investigate the impact of valve opening on the hydraulic performance of oblique tee pipelines, determine the relationship between flow distribution and local loss coefficients in bifurcated pipeline systems and their influencing factors, thereby enhancing the accuracy of hydraulic calculations for pipeline systems. A bifurcated pipeline system was constructed using DN63 PVC pipes and oblique tees. System hydraulic performance tests were conducted under 25 different valve opening combinations. Pressure transmitters and ultrasonic flow meters were used to precisely measure pressure and flow rates in each pipe segment, comparing the effects of different valve openings on the diversion ratio and local head loss. Results indicate that as the valve opening increases, the total flow rate of the branched pipeline system shows an overall upward trend. The diversion ratio increases with greater valve opening in the branch pipe but decreases with greater valve opening in the main pipe. Valve opening significantly influenced the local head loss coefficients ζ??? and ζ??? in the branched pipeline. The diversion ratio exhibited a quadratic relationship with both local head loss coefficients ζ??? and ζ???. Numerical simulation results were generally consistent with experimental findings, establishing empirical formulas for ζ??? and ζ???. The study also revealed the distribution patterns and gradient changes of flow velocity under various operating conditions. This study elucidates the influence of valve opening on the diversion ratio and local head loss in bifurcated pipeline systems, demonstrating that adjusting valve opening can reduce hydraulic losses. This finding provides theoretical support for understanding the variability of hydraulic losses in bifurcated pipelines and offers feasible control measures for optimizing the design and operational management of such systems under diverse hydraulic conditions.

The purpose of this study is to explore the influence mechanism of adding a unique inner tooth structure in the flow channel of the three-way flow channel emitter on its performance, so as to optimize the performance of the emitter and improve its performance in practical applications. Methods Using the combination of numerical simulation and physical experiments, the flow field distribution, hydraulic performance and anti-clogging performance of the three-way flow channel were systematically studied by setting different internal tooth structure parameters. Results On the one hand, the inner tooth structure changed the flow path, which reduced the area of low-speed zone and expanded the range of high-speed zone in the branch channel. When the width of tooth a was 0.3 mm and the width of tooth b was 3 mm, the flow index reached the minimum value of 0.468 9, and the flow coefficient and flow index showed a downward trend after adding inner teeth. On the other hand, the anti-clogging performance test shows that the relative discharge showed a fluctuating declining trend but remained above 75%, and the sediment is mainly deposited at the front end of the branch channel. The 10 th irrigation test shows that the inner tooth structure has a negative impact on the anti-clogging performance. The CFD two-phase flow simulation shows that the trajectory of sediment particles is similar, and the vortex is concentrated at the front end of the flow splitter. Conclusion The addition of inner tooth structure can significantly improve the hydraulic performance of the three-way flow channel and optimize the flow field distribution, but it will reduce the anti-clogging performance of the three-way flow channel to a certain extent. This conclusion can provide an important reference for the design improvement of the three-way channel emitter. On this basis, the shape or size of the inner tooth structure can be further optimized to improve the anti-clogging performance while improving the hydraulic performance.

Under solar greenhouse conditions, this study investigated the effects of different types of organic water-soluble fertilizers at three application concentrations on tomato growth, fruit quality, and water–fertilizer use efficiency, using micro-irrigation technology. Four types of organic water-soluble fertilizers were evaluated: mineral-source potassium fulvic acid (T1), humic acid (T2), chitosan seaweed extract (T3), and Qicai Wogen (T4), each applied at low (C1: 150 kg/hm2), medium (C2: 225 kg/hm2), and high (C3: 300 kg/hm2) concentrations. An unfertilized treatment (CK) was used as the control. Growth parameters, quality indicators, and water–fertilizer use efficiency were measured. Ridge regression analysis was performed to assess the relationships between growth and quality indicators and tomato yield, while comprehensive evaluation was conducted using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The results showed that all levels of organic water-soluble fertilizer application promoted tomato growth and improved fruit quality compared with the control, with medium concentration treatments producing the most favorable outcomes. Under medium concentration treatments, plant height, stem diameter, leaf area, and SPAD values increased by 61.43%~99.33%、 25.47%~44.03%、 39.98%~52.39% and 15.16%~23.06%, respectively, compared with CK. Yield increased by 14.88%~39.65%, water use efficiency increased by 2.21%~39.29%, while soluble sugar, lycopene, and vitamin C contents increased by 8.17%~21.76%、 38.17%~84.47% and 106.05%~160.93%, respectively. The partial factor productivity of fertilizer in each treatment showed a decreasing trend with the increase in fertilization concentration. Ridge regression analysis indicated that stem diameter and leaf area had the strongest positive correlations with yield, whereas lycopene content showed a significant negative association. Significant differences were observed among fertilizer types and application concentrations in their effects on tomato growth and quality. The comprehensive evaluation revealed that the T4C2 treatment ranked highest in the TOPSIS analysis (score: 0.828), demonstrating superior performance in terms of fruit quality, yield, and resource use efficiency, and can be recommended as an optimal strategy for improving tomato water and fertilizer management.

Water movement in unsaturated porous media is a focal point of concern in multiple disciplines, including hydrology, agriculture, and environmental engineering. The Richards equation, as a crucial mathematical equation for describing this phenomenon, plays an essential role in advancing our understanding of soil water movement. The equation has three distinct forms and reveals the nonlinear relationships among related variables through soil constitutive relationships. Numerical methods have emerged as the primary approach for solving the Richards equation, achieving significant advancements progress in its solution over the course of several decades. To deepen the fundamental understanding of this field and propel related research forward, this paper systematically reviews the evolution of the Richards equation and, focusing on the spatial discretization methods, temporal discretization methods, and iterative methods employed in solving this equation, along with the existing solution models and codes. Additionally, this paper also summarizes the principal problems and challenges currently encountered in solving the Richards equation and explores and anticipates future research directions and practical application prospects, aiming to foster the further advancement of this field.

The application of water-retaining agents is an important measure to effectively improve soil water retention capacity. Coal gangue and fly ash can both enhance the physical structure of soil and increase its aeration. To investigate the impact of combined application of water-retaining agents with coal gangue and fly ash on the improvement of loess soil in western Shanxi, corn was used as the research object. Field trials were conducted with four treatments: potassium polyacrylate and coal gangue (W1), potassium polyacrylate and fly ash (W2), potassium polyacrylate alone (W3), and no water-retaining agent (CK). The effects of different treatments on the hydraulic properties, aggregate stability, and corn growth in loess soil in western Shanxi were analyzed. The results showed that treatments W1 and W2 significantly improved soil water retention, with W1 increasing the water content in the 0~60 cm layer by 3.2% to 35.2% compared to CK, and the saturated hydraulic conductivity by 63.4%, reaching 7.9 cm/h. The cumulative infiltration amount over 90 minutes was the highest at 43.4 mm. Treatment W1 also promoted the formation of water-stable aggregates (>2 mm), accounting for 36.4%, which increased by 73.3% compared to CK. Although treatment W3 showed significant improvements in hydraulic properties compared to CK, its effect was less pronounced than that of W1 and W2. At the twelfth leaf stage, the height and stem diameter of corn plants under treatment W1 increased by 36.0% and 17.4%, respectively, compared to CK, with a yield of 12 018.7 kg/hm2 at maturity, representing a 73.3% increase over CK. Treatment W3 had the most significant increase in grain number per ear compared to CK, with a 29.1% improvement. The comprehensive analysis shows that the combination of potassium polyacrylate and coal gangue can significantly improve the soil structure in the loess region, and provide a feasible technical solution for high yield and stable yield of corn in arid regions.

To address severe soil salinization, water scarcity, and low corn yields in Ningxia's Yellow River irrigation districts, this study analyzed the combined effects of irrigation quotas and soil conditioners on corn growth, yield, quality, water use efficiency, and output-to-input ratio under saline drainage water irrigation conditions. The study explores optimal management strategies for drip-irrigated corn, focusing on irrigation quotas and conditioners. The experiment employed drip irrigation technology, utilizing drainage water from rice fields. Two factors were set: irrigation quota S and soil conditioner F. Three drip irrigation levels (S1=1 725 m3/hm2, S2=2 175 m3/hm2, S3=2 625 m3/hm2), three soil conditioners (oligosaccharides, desalinization agent, and sulfur fertilizer designated as F1, F2 and F3), and one control treatment (CK) without soil conditioner application. Results indicated that the interaction between irrigation quota and soil conditioner significantly affected corn growth, yield, and quality (p<0.05). The S2F2 treatment yielded the highest output at 15.1 t/hm2, achieved the highest water use efficiency at 2.52 kg/m3, and demonstrated the highest output-to-input ratio at 1.87. Based on the entropy-weighted TOPSIS comprehensive evaluation results using entropy weights, the S2F2 treatment achieved the highest proximity score and the most favorable evaluation outcome. In summary, the optimal management strategy recommended for this region is an irrigation quota of 2 175 m3/hm2 combined with the application of 150 kg/hm2 of desalinization agent.

To analyze the impact of hydrothermal factor changes on soil CO? emissions under different tillage practices in red soil sloping farmland under drought stress, aiming to provide a scientific basis for accurately evaluating the effects of drought stress on soil carbon balance and carbon sink capacity. The trial established four typical cultivation treatments for red soil slopes: Conventional tillage (CT), Plastic mulch-covered conventional tillage (PM), Ridge-tillage (RT), and Downslope tillage (DT). Relative humidity (W) was adopted as the drought indicator to simulate drought stress scenarios during maize growth through the differences in thermal insulation and water retention performance of the various tillage practices, thereby investigating the response relationship between soil CO? emissions and hydrothermal factors under drought stress. Under mild drought stress, soil temperature exhibited fluctuating characteristics across all four tillage practices, while soil moisture content continuously decreased. Under mild drought stress, the soil moisture content and temperature for RT, DT, and CT practices showed the following order: RT > DT > CT for moisture, and CT > RT > DT for temperature. PM, due to its superior water retention capacity, did not experience drought stress; its soil temperature and moisture content were significantly higher than those of the other practices (p<0.05). During drought progression, soil CO? flux ranged between 60.53 and 224.67 mg/(m2·h), showing a decreasing trend as soil moisture content declined. The cumulative CO? emission under RT was reduced by 48.42%, 40.66%, and 27.72% compared to PM, DT, and CT, respectively (p<0.05). Except for the flowering and grain-filling stage, all other maize growth stages experienced soil drought stress. Cumulative CO? emissions during the tasseling stage increased by 23.26% to 77.7% compared to those in the seedling stage (p<0.05). Drought stress exerts a significant inhibitory effect on soil CO? emissions in red soil sloping farmland. Soil moisture content is the key limiting factor for soil CO? emissions in this context.

To improve water resource utilization efficiency in irrigation districts and address the challenges of multi-objective coordination and poor adaptability of static weights in traditional water allocation methods, this study focuses on the West Main Canal of the 102nd Regiment in Wujiaqu Irrigation District. An optimization model was developed with the objectives of minimizing canal system seepage loss, water flow fluctuation, and the branch canal water shortage rate. A novel approach integrating the Whale Optimization Algorithm (WOA) with a dynamic weight strategy was proposed, which dynamically adjusts the weights of objective functions based on the real-time relationships between canal intake and crop water requirements to achieve adaptive optimization of water allocation strategies under different hydrological conditions. Simulation experiments demonstrated that WOA outperformed Differential Evolution (DE) and Particle Swarm Optimization (PSO) in convergence speed, accuracy, and stability. Case applications revealed that under high-water conditions, water distribution time was reduced by 24.90%, canal system water allocation increased by 19.05%, and seepage loss decreased by 24.74%; under water-deficit conditions, the branch canal water supply guarantee rate reached 83.76%. The proposed dynamic weight strategy effectively overcomes the limitations of fixed-weight methods, providing a reliable approach for refined water resource management in arid irrigation districts and offering significant practical implications for enhancing agricultural irrigation water use efficiency.

This study aims to address the acute conflict between a 137% increase in water demand and a 58.5% decrease in supply in Zhengzhou City, against the backdrop of an average annual decline rate of 12.6% in water diversion from the Yellow River. This severe imbalance between water supply and demand has become a critical bottleneck constraining the sustainable development of megacities. To overcome the limitations of traditional single-objective optimization methods, this research constructs a three-dimensional "space-process-institution" collaborative optimization model. In the spatial dimension, water resource spatial reallocation is achieved through dynamic gate allocation and an inter-regional agricultural water transfer mechanism. In the process dimension, a multi-level water recycling system for the Jialu River—comprising "diversion, storage, purification, and irrigation"—is designed to enhance utilization efficiency. The institutional dimension introduces an interannual adjustment mechanism for water use quotas based on remote sensing monitoring to improve system adaptability. A multi-objective optimization algorithm is employed for solving the model, and a synergy index is used for evaluation. Empirical results demonstrate that the model increases the utilization rate of downstream idle projects by 41.2%, achieves a water reuse frequency of 2.3 times, improves water use efficiency by 40%, elevates the system synergy index from 0.38 to 0.82, and achieves a comprehensive utilization rate of 91.2%. The research conclusions indicate that spatial reconfiguration can effectively activate the potential of existing water conservancy infrastructure, multi-level cycling in the process can significantly expand the service function per unit of water resource, and the flexible quota system provides dynamic adaptive capacity for the system. The synergy of these three aspects offers a systematic solution for achieving multi-objective optimal allocation of water resources in highly water-scarce megacities amid water supply declines.

Vegetation and phenology, as essential components of ecosystems, directly influence the carbon cycle, hydrological processes, and regional ecological security. The ecological environment of the upper Yellow River is highly complex, encompassing grasslands, sandy areas, Yellow River irrigation districts, and forests. However, the synergistic dynamics of vegetation and phenological changes in this region remain insufficiently quantified. This study focuses on the Ningxia section of the Yellow River. Using Landsat 8 Enhanced Vegetation Index (EVI) and MODIS Gross Primary Productivity (GPP) data from 2014 to 2023, we employed the Mann-Kendall test in combination with Sen′s slope estimator and applied a double-logistic phenological model to systematically examine the spatiotemporal variations of vegetation and phenology, as well as to explore their potential effects on carbon sink functions. The results reveal that, over the past decade, EVI has shown a significant upward trend, with a mean increase of 0.033, leading to a cumulative gain of 23.7% and an overall growth rate of approximately 0.003 a?1. The most pronounced vegetation restoration occurred in the southern Liupan Mountains, the main channel of the Yellow River and its floodplains, and the northern irrigation areas. Areas with increasing EVI accounted for more than 60% of the total, whereas those with decreasing EVI comprised about 38%. The start of the growing season (SOS) advanced by an average of 1.29 days per year, the end of the growing season (EOS) was delayed by 1.11 days per year, and the length of the growing season (LOS) was extended by 2.41 days per year. These findings indicate that ecological restoration in the Yellow River Basin has been substantial. The extension of LOS suggests that climate change is continuously enhancing vegetation productivity, and together these effects are reinforcing regional carbon sink functions. Meanwhile, vegetation changes varied considerably across different ecological types, highlighting the crucial roles of land-use practices and water resource management in shaping phenological dynamics.

The Normalized Difference Vegetation Index (NDVI) serves as an effective indicator for characterizing vegetation cover dynamics，which can effectively reflect the local soil and water conservation status, ecosystem health and agricultural productivity, which is crucial for balancing ecological conservation with high-quality development. However, existing literature, predominantly investigates individual driving factors and fails to capture their interdependencies or comprehensive environmental impacts, which is insufficient to explain the complex nonlinear processes driven by multiple factors. Therefore, this study comprehensively applied the coefficient of variation method, optimal parameters-based geographical detector (OPGD), and geographically and temporally weighted regression (GTWR) to quantitatively analyze the spatial and temporal evolution of NDVI and its driving mechanisms in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2000 to 2020. The results show that: based on the coefficient of variation method, NDVI in the GBA exhibited a fluctuating upward trend over time, indicating a significant improvement in vegetation conditions. Spatially, NDVI displayed clear heterogeneity. OPGD factor detection identified population density and nighttime light intensity as the primary drivers of spatial NDVI variation. Interaction analysis revealed that combinations of key factors—particularly population density, nighttime light intensity, and temperature—substantially enhanced the explanatory power for NDVI variation. The GTWR model effectively revealed the spatiotemporal non-stationarity of driving factors. The regression coefficients for each factor showed marked spatial variability. This study provides a theoretical basis for the design of soil and water monitoring and regulation mechanisms in ecosystems within regions of high-intensity human activities, thereby effectively supporting the planning and management of soil conservation policies in the GBA.

The Irrigation Water Effective Utilization Coefficient (IWEUC) is a key indicator for measuring the efficiency of farmland irrigation water use. This study analyzes the variation trend and influencing factors of the IWEUC in Ningxia from 2015 to 2024 (a recent 10-year period). The results showed that: the area of high-efficiency water-saving irrigation maintained a significant and continuous growth trend; the planting proportion of rice decreased by 77.48% compared with 2015, while that of corn increased year by year with an increase of 42.55% compared to 2015, and the planting proportion of wheat fluctuated significantly; the irrigation area in Ningxia's irrigation districts increased year by year, yet the total water consumption showed a yearly downward trend; the IWEUC values from 2015 to 2024 were 0.501, 0.511, 0.524, 0.535, 0.543, 0.551, 0.561, 0.570, 0.579, and 0.586, respectively. The IWEUC can be estimated using four indicators: water consumption per hectare, irrigation area, high-efficiency water-saving area, and total water consumption of the region. Moreover, rational regulation of these four indicators within a certain range can better improve the IWEUC. The research results can provide scientific guidance for analyzing the variation and influencing factors of the IWEUC in Ningxia's farmland, and further propose effective approaches to enhance this coefficient.

Farmers' economic affordability is a critical constraint in determining water rights trading prices. Conducting in-depth research on the dynamic changes and influencing factors of farmers' affordability regarding irrigation water rights trading prices holds significant theoretical and practical value for improving China's water rights trading pricing mechanism and optimizing water resource allocation efficiency in irrigation areas. This study focuses on rural regions of Shijiazhuang City, Hebei Province as the research area. Leveraging data from 2016 to 2022, the Extended Linear Expenditure System Model (ELES) combined with the water fee affordability index was employed to dynamically determine the upper limit of irrigation water rights trading price affordability. On this basis, Tobit regression analysis was used to explore the key influencing factors of the fluctuation of farmers' water rights trading price affordability. The results show that the upper limit of affordability for irrigation water users fluctuated significantly from 2016 to 2022. Per capita water resources, per capita income of farmers, the proportion of irrigation water use and the proportion of effective irrigation area all had a positive impact on it, the water rights trading price determined by market forces can be adjusted from the demand side based on these insights. The research further points out that the government needs to formulate corresponding policies and dynamically adjust the water rights trading price in combination with market supply and demand and farmers' ability to pay.

In order to address issues such as low efficiency, strong subjectivity, and delayed hazard identification in manual inspection for safety monitoring of large-scale irrigation district projects, this study takes the first phase project of Tingzikou Irrigation District as the research object, and designs and constructs a multi-scenario safety monitoring system based on machine vision. A training set is built through on-site camera video collection, organization of existing data in the project department, and crawling of publicly available online data, and the GridMask image enhancement technology is introduced to optimize the training set. The YOLOv8 model improved with a small target detection branch and an SE attention mechanism module, along with the ByteTrack algorithm, is adopted to realize the functions of safety helmet detection, personnel tracking, machinery type identification, and human-machine collision early warning. The project verification results show that: ① the accuracy of this multi-scenario safety monitoring system reaches 82%; ② each algorithm model exhibits good robustness and accuracy in different designated construction areas, among which the accuracy of the safety helmet detection algorithm reaches 89%, and compared with the original baseline YOLOv8 model, the key indicators of the improved model, such as accuracy, recall rate, and mAP50(B), are all improved; ③ the accuracy of the dynamic collision early warning model between humans and machines as well as between machines reaches 75%, which compensates for the problem of deviation in collision distance judgment in traditional manual empirical inspection. The practical application and verification of this study in the project have effectively improved the intelligent level of safety management of the Tingzikou Irrigation District Project, and can provide a scientific reference for the intelligent development of safety monitoring in large-scale irrigation district projects.