The research on the coupling coordination of water-energy-food (WEF) system is of great significance in realizing the sustainable development of regional resources. In this paper, 24 countries were selected to construct the evaluation index system and coupling coordination degree model of the WEF system, analyze the spatio-temporal variation characteristics of the comprehensive evaluation index and coupling coordination degree from 2008 to 2020, and introduce the Moran′s index was introduced to analyze the spatial evolution characteristics of the system's coupling coordination degree. On this basis, the spatial Durbin model is used to discuss the influencing factors of coupling coordination degree. The results show that: from the perspective of time series, the comprehensive evaluation index of the system decreases first and then increases, and the coupling coordination degree fluctuates obviously, but it shows a positive trend. From the perspective of spatial distribution, the high value region of coupling coordination degree is roughly consistent with the high value region of grain comprehensive evaluation index, showing the spatial distribution characteristics of "high east and west, low middle". Although the spatial aggregation of coupling coordination degree is obvious, there are clustering or outliers, and the spatial distribution pattern is in a changing state. The results of the spatial Durbin model show that agricultural water consumption, industrial water consumption, per capita energy production, annual grain output per unit area and agricultural land area have significant effects on the coupling coordination degree, while energy consumption of the secondary industry and food import value has no significant effect on the total export value of commodities.

To explore the effect of new ecological water-retaining agent on soil microenvironment and potato yield and benefit in Lanzhou New Area, and to clarify the application effect of new ecological water-retaining agent and screen the best application amount. The new ecological water-retaining agent was used as the material (developed by Shanghai Institute of Applied Physics, Chinese Academy of Sciences). Four treatments（CK:0,B3:45 kg/hm²,B5:75 kg/hm²,B7:105 kg/hm²）were set up according to the amount of water-retaining agent to study the effects of water-retaining agent on the dynamic changes of soil moisture, soil enzyme activity, soil respiration rate and potato yield and benefit in Lanzhou New Area under drip irrigation mode. The results showed that: Compared with CK, the soil volumetric water content（5.24%~11.41%) in 0~40 cm soil layer during potato growth period was significantly increased by the application of new ecological water retaining agent. With the increase of the application amount of the new ecological water retaining agent, the soil volumetric water content in the 0-40 cm soil layer gradually increased and then stabilized, and the difference between B5 and B7 treatments was not significant. The activities of soil urease, sucrase, catalase and soil respiration rate showed a ' single peak ' curve with the growth period of potato, and reached the peak at the tuber expansion stage. Compared with CK, the activities of urease, sucrase and catalase in the 0~40 cm soil layer of the new ecological water retaining agent treatment group increased by 10.40%~24.35%, 3.98%~10.06% and 3.15%~8.11%, respectively, and the respiration rate increased by 23.32%~25.51%. There was no significant difference between B5 and B7 treatments.The application of water-retaining agent could significantly increase potato yield and commodity potato rate, and reduce the rate of small potato. Compared with CK, the potato yield of B5 and B7 treatments increased by 9.53%~10.15%, and the total output value increased by 15.23%~15.66%. Based on the application effect of new ecological water-retaining agent with different application rates in potato production in Lanzhou New Area, it is concluded that the application rate of 75 kg / hm² of ecological water-retaining agent can achieve multiple improvement of irrigation water use efficiency, soil microenvironment and potato yield benefit.

Quantitatively evaluating the status of water resources sustainable utilization in Hebei Province and its influencing factors, and to provide data support for the sustainable development of water resources utilization in the province. Using the model of matching degree between water resources utilization and economic and social development, the water resources ecological footprint model and the Logarithmic Mean Divisia Index (LMDI) method, the ecological footprint of water resources and ecological carrying capacity of Hebei Province from 2004 to 2021 were calculated. On this basis, the factors affecting the change of the ecological footprint of water resources in Hebei Province were quantitatively decomposed. The results show that: ①GDP per capita in Hebei Province shows a growing trend, water consumption per capita shows a fluctuating downward trend after a short period of growth, and the match between them shows a trend of growth followed by a downward trend. ②During the study period, water resources are all in deficit, and the deficit is serious, and the pressure of water resources utilization was excessive. It was an unsustainable utilization situation and it’s necessary to take active measures to reverse it. ③In the process of changes in the ecological footprint of water resources, the economic effect contributes the most, followed by the demographic effect, while it is inhibited by the technological effect. The structural effect either facilitated or inhibited the process in different years of the study period.

In order to help local governments and relevant institutions make reasonable and effective decisions and promote the sustainable utilization of soil and water resources and the sustainable development of the region, this paper takes Keshan County as the research area and constructs an evaluation index system for the sustainable utilization of soil and water resources in the cold black soil area based on the DPSIR model and principal component analysis. The TOPSIS method was applied to estimate the sustainable utilization level of water and land resources in Keshan County from 2013 to 2021. The results show that: ① the subsystems exhibited fluctuating upward trends from 2013 to 2021, and the response subsystem has the highest contribution rate to the sustainable utilization level of water and land resources in Keshan County. ② The sustainable utilization level of land and water resources in Keshan County showed a fluctuating upward trend from 2013 to 2021, and the sustainable state shifted from weak sustainability to sustainability. ③ The obstacle factors restricting the sustainable utilization level of water and land resources in Keshan County are mainly waterlogging control area, dry farmland area, water conservancy expenditure, rural electricity consumption and farmland protection area. The response subsystem plays an important role in improving the sustainable utilization level of water and soil resources. Local governments can increase water conservancy expenditure, optimize waterlogging control facilities, adjust the management mode of dryland farmland and strengthen the protection of farmland, so as to further improve the sustainable utilization level of water and land resources.

The Yin Bei Irrigation Area is facing a sharp decline in the amount of water diverted from the Yellow River, while also facing problems such as low water resource utilization efficiency, insufficient scientific and reasonable irrigation water use, and serious water resource waste. Seeking suitable irrigation modes is an important way to ensure crop yield, reduce water dependence on the Yellow River, and improve water resource utilization efficiency. Using field experiments to plant rice, six different irrigation modes were set up, namely return flood irrigation (T1), Yellow River water irrigation (T2), moderate return water irrigation (T3), Yellow River water return alternating irrigation (T4), return water irrigation (T5), and conventional irrigation (T6). The effects of different irrigation modes on soil water and salt distribution, rice growth, and yield in rice fields were studied. Different irrigation modes have a significant impact on the distribution of salt in paddy fields. The phenomenon of surface soil desalination and bottom soil salt accumulation exists in different irrigation modes throughout the entire growth period. T1 treatment has the highest desalination depth, causing salt accumulation below 60 cm of soil, while the rest of the treatments accumulate below 40 cm of soil. The maximum soil desalination rate was observed in T1 treatment, which decreased by 9.58% compared to the initial soil salinity; The highest root zone desalination rate occurred in T2 treatment, at 27.36%; The maximum change in salt content in the root zone was observed in T1 treatment, and during the rice growth period, the downward migration of salt was 4.82 t/hm². The maximum rice yield was 10 029.42 kg/hm² under the treatment of flood irrigation with return water. T3 processing can save 0.56 m³/kg of Yellow River water per unit weight of rice production, and producing one season of rice can save 5 003.41 m³/hm² of Yellow River water per unit area. In summary, for the Yin Bei Irrigation Area in Ningxia, using an appropriate amount of return water for irrigation can ensure crop yield while reducing the demand for irrigation using Yellow River water.

To study the effect of water level variation amplitude and period on soil CO₂ emission rate, undisturbed soil samples were collected from the Xiaobei main stream of the Yellow River for 1161h long-term water level control monitoring. 4 groups were divided into high water level fluctuations (a), low water level fluctuations (b), drought stress (c), and reference group (d) for comparison. CO₂ emission rate, dissolved organic carbon (DOC), and DOC/DON (dissolved organic nitrogen) data from five stages were analyzed. The average CO₂ emission rates throughout the monitoring process are 0.23, 0.22, 0.16, and 0.22 μmol·cm^-2·h^-1 respectively, the overall change in water level causes changes of 0.35 times, -0.18 times, -0.11 times, and -0.24 times. Compared to the average value of the monitoring process, water level changes cause process fluctuations of -0.72~2.48 times, -0.86~1.18 times, -0.97~1.44 times and -0.85~0.70 times in groups a, b, c, and d, respectively CO₂ emission rate exhibited a characteristic of "rising-weakening-recovering". Compared to the average data of the previous stage, after the water level drops (Stage I), the abc group suggested 2.48, 1.18 and 1.44 times increase, and after 91.5 hours, there were 0.18, 0.43 and 0.27 times decrease (Stage If); The water level rise at 279.9 hours of monitoring caused a significant increase in the abc group compared to their previous stage (Stage II) while decreased after 48.5 hours (Stage IIf); The impact of the water level rise at 664 hours (stages III and III f) is similar to the previous stage. In the last 240 hours(stage IV), all 4 groups showed varying degrees of rebound compared to stage III. DOC content and DOC/DON value in soil between 0~5 cm and 5~10 cm were significantly affected by changes in water level, showing a trend of initial increase and later decrease.Water level changes have a significant and long-term impact on wetland soil CO₂ emissions, and the impact is significant and has a phased characteristic.

Crop growth and field moisture prediction are essential for accurate agricultural management. In order to accurately simulate the maize yield in Ningxia, based on the field observation data from 2019 to 2020, the Soil-Water-Atmosphere-Plant (SWAP) model and iterative ensemble smoother (IES) algorithm were used to construct a SWAP-IES assimilation modeling system for maize in Ningxia. The effects of assimilating leaf area index (LAI), soil water content (SW) and their combination on soil moisture content simulation and yield estimation in maize fields in Ningxia were compared. The results showed that the R ² of soil moisture content simulation increased from -0.07 to 0.71 without assimilation when assimilating LAI and SW at the same time, indicating that the simulation accuracy of soil moisture content of the model could be greatly improved by assimilating LAI and SW at the same time. However, the simultaneous assimilation of LAI and SW can better simulate the soil moisture content than the assimilation of LAI or SW alone, which indicates that the two assimilation variables are not isolated, and the coupling of the two can better improve the prediction accuracy of the model. The yield estimation accuracy was the highest when assimilating LAI and SW at the same time, and the RMSE decreased to 914.113 kg/hm², which was significantly lower than that in other scenarios. The results show that the constructed SWAP-IES maize assimilation model can accurately simulate the process of soil moisture change and crop yield under the condition of simultaneous assimilation of LAI and SW, and provides a reference for optimizing farmland irrigation and improving crop yield estimation.

In order to improve the accuracy of the APSIM-Maize model in simulating spring maize yield under drought conditions in northwest China, this study selected the suitable planting areas for spring maize in the Shiyang River Basin of Gansu Province (Yongchang County, Minqin County, Liangzhou District, Gulang County) as the research area. A total of 115 pairs of observation data from 2009 to 2022 were obtained by reviewing and researching 49 field experimental literature related to spring maize in the research area. Based on the APSIM-Maize model, sensitivity analysis was conducted on 21 model parameters such as water use efficiency and photoperiod slope using sensitivity index SI method and modified Morris method. The selected sensitive parameters were optimized and verified for each of the four suitable planting areas. The results showed, ① that there were 5 model parameters that were sensitive to spring maize yield, with sensitivity values as follows: transpiration efficiency coefficient＞accumulated temperature from emergence to elongation＞photosynthesis and radiation utilization efficiency＞accumulated temperature from flowering to beginning of grain filling＞biomass transferred from stem to grain; ② The optimization effect of parameters varies for different suitable planting areas, with Yongchang County, Liangzhou District, and Gulang County showing better results, followed by Minqin County; ③ The correlation coefficients between the measured and simulated yield values in the optimized planting area parameters for spring corn increased from 0.566 to 0.978, 0.341 to 0.809, 0.455 to 0.953, 0.537 to 0.936, and the root mean square error decreased from 1 837.10~3 088.72 kg/hm2 to 341.64~996.64 kg/hm2, respectively. The optimized parameters effectively improved the accuracy of the model's simulated yield.

To improve the prediction accuracy of soil moisture content, various numbers of predictors were selected, and the Bidirectional Long Short-Term Memory network (IPSO-BiLSTM), based on an improved particle swarm optimization and support vector machine (SVM), were used for prediction. Using the typical plots of the Shijin Irrigation District as an example, soil moisture content for the next 1~5 days was predicted using data from the preceding 15 days. The results were as follows: ①The prediction accuracy of the IPSO-BiLSTM model was higher than that of the SVM model. For the validation set and test data, the RMSE of the 1~5 day predictions made by the IPSO-BiLSTM model decreased by an average of 5.50%, MAPE decreased by 5.77%, MAE decreased by 6.56%, and the R2 determination coefficient increased by 2.96%. ②The number of predictors required to the optimal model varied across different time periods. The IPSO-BiLSTM model performed best with three predictors for 1 to 3 days ahead and four predictors for 5 days ahead. ③Regarding running time, the IPSO-BiLSTM model's running time showed no significant correlation with the number of predictors, whereas the SVM's running time increased with more predictors. For datasets of the same size, the IPSO-BiLSTM model used approximately 20% more CPU resources than the SVM model. This study provides theoretical and technical support for precision irrigation and the efficient utilization of agricultural water resources in irrigated areas.

Intelligent irrigation represents an advanced approach to agricultural management based on modern irrigation technologies. Its goal is to achieve high-yield, high-quality, water-efficient agricultural production by digitizing the assessment of water needs, enabling intelligent decision-making for water allocation, precisely controlling irrigation volumes, and managing the entire irrigation process through advanced technology. To effectively promote the application of intelligent irrigation technologies, it is essential to establish a robust evaluation framework for assessing their impact. This study develops such a framework through a combination of theoretical analysis and empirical research. The evaluation system features a three-tier index framework addressing four critical dimensions: field water use efficiency, economic impact, technological sophistication, and ecological sustainability. Weights for each index are determined using a comprehensive weighting method based on information entropy theory. The evaluation and analysis were conducted through the Dacaozhuang intelligent Sprinkler Irrigation Project and the Jintang County Drip Irrigation Project as examples, verifying the accuracy and generalizability of this evaluation system. The evaluation framework developed in this study will significantly facilitate the wider adoption and advancement of intelligent irrigation technologies.

The centrifugal pump is generally started with the valve closed when starting, that is, zero flow condition. Vertical centrifugal pumps are widely used in long-distance water transfer and large-scale irrigation projects. In order to investigate the vibration characteristics of a vertical centrifugal pump under zero flow condition, a three-direction vibration sensor is arranged on the base of the pump; an axial vibration sensor is arranged on the top of the inlet and outlet flanges of the pump; a pressure fluctuation sensor is arranged on the top of the outlet pipe of the pump. The vibration and pressure fluctuation of the pump at rated speed (1.0 nr), 1.2 nr, 0.8 nr, 0.6 nr and 0.4 nr were tested. The results show that: the inlet axial, outlet axial and base axial vibration of the vertical centrifugal pump are larger under zero flow condition. When the speed is increased to 1.2 times of the rated speed, the vibration strength of the base axis is increased to 1.6 times of that at the rated speed, and when the speed is reduced to 0.8 times of the rated speed, the vibration strength is reduced to 1/4 times of that at the rated speed. When the speed is reduced, the vibration strength of the pump can be greatly reduced. Blade frequency is the main frequency of pump inlet, outlet and base axial vibration, and pressure fluctuation is an important excitation source for vibration of vertical centrifugal pump under zero flow condition. This paper can provide reference for the design of similar large vertical centrifugal pump and the operation management of the pump station after completion.

In the operation of water transport buildings, timely detection and early warning of abnormal data and corresponding accident conditions can provide an important guarantee for the safe operation of canal and tunnel system. The purpose of this paper is to explore the hydraulic response characteristics of the canal and tunnel system under typical accident conditions, so as to provide the accident hydraulic response characteristics for the managers of the irrigation district. In this paper, based on HEC-RAS software, a generalized model is proposed for the common accident conditions of canal and tunnel system, and its effectiveness is tested according to its hydraulic response characteristics. The research shows that: ① When the flood enters the channel, the upstream and downstream water levels will rise, and the upstream flow will first decline and then stabilize to the original flow, with a maximum overflow head is 0.14 m. ② When the structural damage accident occurs, the upstream and downstream water levels and downstream flow of the channel will gradually decline. The upstream flow increases first and then decreases to the original flow, and the maximum leakage flow is 9.95 m³/s. ③ When the local collapse accident of the tunnel occurs, the water level of the upstream channel is high. The upstream flow, downstream water level and flow showed a trend of first decreasing and then gradually recovering to the original water level flow, and the maximum water level was 0.460 m. The generalized accident model can effectively reflect the dynamic change of water transport structures under accident conditions. The hydraulic response characteristics obtained in this study can provide reference for the formulation of accident emergency plan and emergency dispatch, and has significance implications for the development of safety measures in the construction of long-distance water transport systems.

To address the issue of the effects of different irrigation lower limits on photosynthetic parameters and yield of cotton leaves, this study was conducted through a field experiment, using local conventional drip irrigation as the control (CK) to set two irrigation lower limits at the bud stage: 60%~65% field capacity and 70%~75% field capacity, and three irrigation lower limits at the boll stage: 55%~60% field capacity, 60%~65% field capacity，and 70%~75% field capacity, respectively. A total of six different irrigation lower limit treatments were designed to analyze their effects on photosynthetic characteristics and yield at different fertility stages of cotton, and the correlations between soil weight water content and photosynthetic parameters were explored. The results showed that soil weight water content was significantly positively correlated with net photosynthetic rate, transpiration rate and stomatal conductance of cotton, and negatively correlated with leaf water use efficiency. Considering the differences in cotton irrigation amount, photosynthetic characteristics and yield, and using the TOPSIS entropy weighting method for comprehensive benefit evaluation, it is recommended that the lower limit of irrigation at both bud stage and bolling stage be set at 70%~75% field capacity, at which time the irrigation quota for the whole life cycle was reduced by 26.32% compared with that of CK, and the yield was 6 946.65 kg/hm², which was increased by 26.46% compared with that of the CK treatment, which realized the cotton irrigation quota's substantial reduction and significant increase in yield (P<0.05).

Predicting agricultural water usage is a key element in regional water resource planning, essential for ensuring the rational development of water resources and ensuring food security. However, existing models for predicting agricultural water usage often suffer from issues such as redundant input parameters and insufficient accuracy, hindering effective water resource management and optimal decision-making. Therefore, this study selects the Hetao irrigation district in Inner Mongolia as the research area. Firstly, principal component analysis (PCA) is conducted on the driving factors related to agricultural water usage to identify the key factors influencing water usage in the irrigation district. Secondly, various machine learning-based models were constructed for predicting agricultural water usage. Finally, the SHapley Additive exPlanations (SHAP) method is used to validate the applicability of the optimal model and to deeply explore the contribution of each feature to agricultural water usage. The results show that the Multilayer Perceptron (MLP) neural network model effectively predicts agricultural water usage, with an R2 evaluation index of 0.84, performing better than five other machine learning models: Least Absolute Shrinkage and Selection Operator Regression (Lasso), Ridge Regression (Ridge), Decision Tree (DT), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). Using the SHAP method to quantitatively analyze the input parameters of the MLP model reveals that the total output value of the primary industry and grain yield have higher absolute mean SHAP values, with slight differences in SHAP value contributions among different irrigation regions. Constructing an agricultural water usage prediction and screening model can accurately predict water usage, thereby achieving precise irrigation in the irrigation district and improving water resource utilization efficiency. This has significant practical implications for alleviating future water resource supply and demand conflicts in the Hetao irrigation district.

Hargreaves formula provides an effective method for calculating reference crop evapotranspiration (ET ₀) when meteorological data are limited, but its applicability and deviations need to be evaluated in different climate zones. In order to explore the applicability of Hargreaves formula in Dongting Lake district of Hunan Province, this study analysed the deviations from annual, monthly and daily time scales compared with Penman-Monteith method, using daily meteorological data of Anxiang from 2001 to 2017. The causes of deviations between the two methods were explained and the monthly empirical coefficient of Hargreaves formula were adjusted in this study. The results showed that the variation trend of the two methods was consistent. Hargreaves method annual ET ₀ was larger, the perennial average absolute deviation and relative deviation were 79 mm and 8% respectively. The deviations were obvious on the monthly time scale. The perennial monthly ET ₀ of Hargreaves method was larger except for July and August. The perennial average relative deviation of monthly ET ₀ ranged from 9% to 16%. Smaller sunshine duration and higher relative humidity were the main reasons for causing the deviations. The daily relative deviation fluctuated significantly and the deviations in winter were greater than those in summer. About 44 percent of the daily relative deviation was greater than 20%. After monthly empirical coefficient adjusting, the perennial average absolute deviation and the annual maximum deviation were 28 mm and 68 mm respectively. The perennial average relative deviation was 3%, and the maximum annual relative deviation was 7%. The monthly perennial average absolute deviation was within 5 mm, and the average relative deviation was within 10%. It is shown that the adjusted Hargreaves formula can be applied to ET ₀ calculation in Dongting Lake region of Hunan Province on monthly scale.