The experiment was conducted to investigate the effects of bio-organic fertilizer with chemical fertilizer technology on the growth and yield of rice under different irrigation modes using a plot test method. Two irrigation modes (F: flooded irrigation, C: controlled irrigation)and three fertilizer modes(A: full application of chemical fertilizers, B: bio-organic fertilizer with equal nitrogen replacing 15% chemical nitrogen fertilizer, C: bio-organic fertilizer with equal nitrogen replacing 30% chemical nitrogen fertilizer )were set up to study the effects of different treatments on rice growth traits and yield. The results showed that under the same irrigation mode, bio-organic fertilizer increased the number of grains per panicle and the dry matter mass of the panicle, but had little effect on rice plant height and chlorophyll. Compared with the full application of chemical fertilizer, there was no significant difference in yield and net profit of bio-organic fertilizer with equal nitrogen replacing 15% chemical nitrogen fertilizer. However, a higher proportion of bio-organic fertilizer slightly reduced rice yield and increased fertilizer input cost, resulting in a significant decline in the ratio of output to input. Under different irrigation modes, controlled irrigation suppressed unproductive tillering but reduced plant height and dry matter mass of rice. Compared with conventional flooding irrigation, yields were slightly lower by 0.5%~1.2% under controlled irrigation, but improved irrigation water use efficiency and net returns. It is concluded that the use of bio-organic fertilizer, which replaces 15% of the chemical nitrogen fertilizer under the controlled irrigation mode can avoid the excessive application of chemical nitrogen fertilizer, ensure rice production and high economic benefits under the condition of improving irrigation water utilization efficiency.

Investigating the issues of water supply and utilization efficiency in arid regions is crucial for optimizing farmland irrigation systems and improving the efficient use of water resources. This study focuses on corn in the Ningxia Qingtongxia Yellow River Irrigation Area, utilizing stable hydrogen and oxygen isotope techniques for the quantitative tracking of isotopic characteristics in atmospheric precipitation, soil water, and corn xylem water. Through the integrated use of direct comparison methods, the MixSIAR model, and transpiration separation techniques, this research deeply analyzes the main water absorption depths of corn during its growth period, the relative contribution rates at different stages, and water use efficiency (WUE) along with the influence of environmental factors. The results indicate that corn primarily absorbs water from the shallow soil layer (0~30 cm), with average contribution rates at different growth stages being 44.10% (germination), 35.44% (jointing), 41.54% (tasseling), 41.66% (grain filling), and 48.10% (maturity). Throughout the growth period, WUE exhibits a fluctuating upward trend, significantly affected by environmental factors such as the difference in saturated vapor pressure, soil temperature, and air temperature. The findings reveal the high dependency on shallow soil water during the growth and development of corn in this region and the significant increase in water use efficiency as the growth period progresses.

To investigate the impact of water, nitrogen and salt interaction on the growth and photosynthesis of the energy plant Arundo donax, identify the optimal water and nitrogen conditions for the cultivation of Arundo donax in different types of salinized soil, a three-factor and four-level orthogonal experiment was designed, soil salinity levels were categorised as follows: (S0: non-salinized soil, S1: mildly salinized soil, S2: moderately salinized soil and S3: severely salinized soil), amount of pure nitrogen applied was categorised as follows: (N0: 0, N1: 60, N2: 120 and N3: 180 kg/hm²), and irrigation quota was categorised as follows: (W0: 2 850, W1: 4 275, W2: 5 700 and W3: 7 125 m³/hm²). The results showed that individual factors of water, nitrogen and salt had significant influence on the plant height, stem diameter, leaf width, single cluster fresh weight and dry weight of Arundo donax（P<0.05）. The coupling of water and salt, as well as water and nitrogen, were found to show significant effects on the plant height, stem diameter, leaf width, single cluster fresh weight and dry weight of Arundo donax（P<0.05）. Single factors of water and salt had significant effects on the net photosynthetic rate, transpiration rate and stomatal conductance of Arundo donax（P<0.05）. When the nitrogen application rate and irrigation amount were certain, compared with the control, the characteristics such as plant height, stem diameter, leaf length, leaf width, fresh and dry weight per cluster, net photosynthetic rate, transpiration rate, and stomatal conductance of Arundo donax on mildly salinized soil did not show significant differences (P>0.05). The aforementioned characteristics exhibited notable disparities in moderately and severely salinised soils（P<0.05）. With the escalation of nitrogen application or irrigation quantities, the plant height, stem diameter, leaf length, leaf width, single cluster fresh and dry weight, net photosynthetic rate, transpiration rate and stomatal conductance of Arundo donax demonstrated a tendency to initially increase and subsequently decline. In soil with medium nitrogen and medium water treatment, the maximum values for the single cluster fresh weight and dry weight of Arundo donax were observed in treatments with non-saline soil, they were 148.45g and 45.90g, respectively. In soil with mild salinization and medium nitrogen, Arundo donax exhibited the potential to achieve high biomass accumulation and water and nitrogen use efficiency simultaneously. In soil with moderate salinity, medium nitrogen and medium water treatment, the maximum value for yield of Arundo donax was observed in a single cluster. This was accompanied by a relatively high water and nitrogen use efficiency. The growth and development of Arundo donax were clearly impeded in severely salinised soil, with water and nitrogen use efficiency also exhibiting a relatively low level. In conclusion, the regulation of water and nitrogen can facilitate the accumulation of biomass by Arundo donax on soil with elevated salt concentrations.

To address the current situation of outdated,inefficient and non universal automatic measuring instruments for measuring crop water demand in agricultural pits,a high-precision automatic measuring instrument for measuring crop water demand (evapotranspiration) in pits has been designed and developed. The instrument operates on the principle of automatically measuring water levels using a needle at hourly intervals, featuring a separate structure for the host and sensor, and an innovatively designed water inlet detection circuit. This design resolves measurement errors caused by needle polarization and changes in water conductivity. The applyment of a wedge-designed, maintenance-free clearance screw provided guarantee for long-term stable operation of sensors. Testing results indict that the instrument has a measurement resolution of 0.01 mm, the measurement error within a range of 100 mm is under 0.01 mm, and a travel time accuracy error under 1 minute/month. The instrument has been applied in a large-scale comprehensive measurement pit at the Irrigation test station,stable and reliable for a long time, and has good promotion and application value.

In order to investigate the distribution characteristics of crop root growth and its influence on yield under wheat-to-corn intercropping and border irrigation water pattern, a comparative study was conducted between conventional intercropping and border irrigation pattern. The results showed that the root growth and development of furrow irrigation corn were stimulated under water potential gradient because of the absence of irrigation in the early stage, and the depth of rooting was obviously greater than that under furrow irrigation corn. The dry mass density of 0~60 cm vertical root under conventional border irrigation was significantly higher than that under border furrow irrigation, and the root system was more developed. In the same period, the root amount of furrow irrigation corn was significantly greater than that of border irrigation corn, and the mean root amount at 0~25 cm at jointing stage and tasseling stage was 22.76% and 16.13% higher. The horizontal root dry weight of wheat under conventional border irrigation was significantly higher than that under border furrow irrigation, and the difference decreased as the growth period of corn under furrow irrigation was prolonged. Wheat yield under border furrow irrigation was 9.92% higher than that under border furrow irrigation, influenced by the root growth of corn. The yield of corn under furrow irrigation was 13.49% higher than that under conventional border irrigation due to the root growth compensation effect.

Nitrate nitrogen (NO₃ ^--N) pollution problem in China is prominent, among which the NO₃ ^--N pollution problem of shallow groundwater in agricultural regions is particularly serious. To investigate the current status and sources of NO₃ ^--N pollution in shallow groundwater, the spatial and temporal distribution characteristics of NO₃ ^--N concentration in groundwater and its main influencing factors were analyzed in the study area of the Weishan Irrigation District, based on the water quality data of shallow groundwater from 2019 to 2021. An absolute principal component score-multiple linear regression model (APCS-MLR) was employed to identify sources of NO₃ ^--N pollution. The results showed that the groundwater NO₃ ^--N concentration in the Weishan Irrigation District presented an increasing annual trend from 2019 to 2021, with a severe exceedance rate of 21.43% in 2021. The high values of NO₃ ^--N concentration mainly appeared in the flood season (i.e., June to September) and increased with precipitation; meanwhile, the NO₃ ^--N concentration showed a tendency of gradual increase from the southwest to the northeast. Groundwater NO₃ ^--N concentration was also closely related to the groundwater depths, land use types, agricultural activities, etc. The risk of NO₃ ^--N pollution was higher in the cultivated lands of the shallow groundwater depth regions. The results of source analysis revealed that groundwater NO₃ ^--N pollution in the Weishan Irrigation District was mainly affected by three factors: agricultural activities (48.94%), leaching enrichment + faecal effluent (39.09%), and redox environment (2.61%). The results of this study can provide scientific basis for the prevention and control management of groundwater NO₃ ^--N pollution in Weishan Irrigation District.

Different land use types have great influence on the non-point source pollution load. To investigate the impact of land use changes on non-point source pollution loads, this paper takes the control area of Huazhou Station in Jianjiang Basin as the research object，the SWAT model is used for simulation research，the spatial and temporal distribution characteristics of nitrogen and phosphorus under three land use scenarios were revealed by simulating and analyzing the changes of nitrogen and phosphorus pollution loads. The results show that: ① The R ² values for runoff, total nitrogen and total phosphorus were greater than 0.6, NSE was greater than 0.5, and PBIAS was less than 25% ,during the calibration and validation periods, which accurately simulated the processes of runoff, total nitrogen and total phosphorus in the basin. ② Compared with other scenarios, the load intensity of total nitrogen and total phosphorus in scenario 2 is the lowest, with an average annual load of 16 451.42 t and 4 642.72 t, respectively, and the annual load intensity was closely related to rainfall, indicating that agricultural land is the key area for controlling non-point source pollution in the basin, and the rainy season is the key period for control. ③ In the future land use planning of this region, it is essential to minimize the occupation of forest land, and at the same time reduce the output of nitrogen and phosphorus from agricultural land by adjusting planting structure and implementing protective measures. This study can provide research ideas for land use and pollutant control, and provide theoretical support for protecting and improving the water environment and water quality in the basin.

To explore the reshaping effect of combined application of organic fertilizer and biochar on reshaping the fungal community structure in alkaline soils of arid regions, field experiments were conducted using high-throughput sequencing technology to investigate the influences of various levels of organic fertilizer (0, 7.5 t/hm²) and biochar (0, 2%, and 4%) on soil fungal community structure and crop yield. The results showed that, compared with the control, the combination treatment of 7.5 t/hm² organic fertilizer and 2% and 4% biochar reduced the relative abundance of Ascomycota at the phylum level, and beneficial microbiota increased, such as Basidiomycota and Glomeromycota. The Observed index and Shannon index of soil fungi increased, significantly, while the Simpson index decreased. The compound treatment improved the richness, diversity and community structure of soil fungi, which was beneficial for the growth and yield of oil sunflower. The yield of 7.5 t/hm² organic fertilizer combined with 4% biochar was the highest, reaching 2 521.5 kg/hm², an increase of 1 589.1 kg/hm² compared to the control. Therefore, compared to using a single material, the combination of organic fertilizer and biochar can further improve the structure and diversity of soil fungal communities, and increase crop yields.

Protecting water resources and the ecological environment is crucial for Yellow River governance and basin economic development. The Mu Us Sandy Land, a prime example of sand control in China, plays a pivotal role. Against the backdrop of economic reform and ecological civilization, optimizing water resource development and usage to meet rising living standards while preserving ecological gains is vital for high-quality development. Research on water resource optimization and carrying capacity in the Mu Us Sandy Land reveals that current policies fall short of balancing supply and demand, but tapping into water supply potential significantly improves outcomes. The optimal allocation plan is T14, with a carrying capacity of 3.80, approaching the "high-quality carrying" level. This plan includes achieving an advanced irrigation water use coefficient of 0.8 by 2030, ensuring that industrial water demand does not exceed 120.65 million cubic meters, moderately increasing the ecological water demand by 3% annually, and fully tapping the potential of underground water and drainage water utilization in the research area. This results in groundwater and drainage water availability reaching 432.79 million cubic meters and 247.44 million cubic meters respectively, while surface water availability remains unchanged at 31.38 million cubic meters annually.

Irrigation-induced landslides are widespread and frequent in the Loess Plateau of China, posing significant threats to rural socio-economic development and farmers' livelihoods. As an effective measure to address irrigation-induced landslides at their root, the disaster mitigation potential of water-saving agriculture largely depends on local farmers' adoption and sustained use. This study expands on the sustainable livelihood framework proposed by the UK Department for International Development, providing an in-depth exploration of the subjective and objective factors influencing farmers' adoption of technologies in the face of natural disaster risks. Using this framework, the study examines the dynamic adoption intentions of farmers towards water-saving agriculture (including drip irrigation systems and drought-resistant crops) and its underlying mechanisms, with the goal of better understanding decision-making in disaster-prone areas and offering insights for disaster prevention and mitigation. The research is conducted in Heifangtai, Yongjing County, Gansu Province, known as the “natural laboratory for modern landslides,” using data from 363 farmer surveys and a binary logistic regression model. The results show that: ① Social capital positively influences the adoption intentions of both farmers with and without landslide experience, while natural capital negatively affects those without such experience, and psychological capital has a positive effect on farmers with landslide experience. ② Self-efficacy can strengthen the influence of psychological capital on initial adoption intention; ③ Farmers' willingness to continue using water-saving agriculture is lower than their initial adoption willingness, with human capital having a significant negative impact on sustained use intentions. This study clarifies the dynamic shifts in farmers' initial and continued adoption of water-saving agriculture, identifies the key factors influencing adoption intentions, and provides insights for promoting water-saving agriculture and disaster mitigation in areas prone to irrigation-induced landslides and beyond.

As an effective way to improve the planting efficiency of farmers in the production irrigation process, water-saving technology is crucial for ensuring water and food security in China. This article is based on a survey questionnaire of grain planting farmers in the five major grain producing areas of Hebei, Henan, Shandong, Anhui, and Hubei. The SFA-Tobit model is used to study the impact of water-saving technology on grain production efficiency, and the mechanism of action is analyzed. The results indicate that: ①there are still technical inefficiencies caused by insufficient mechanical input-output in the grain production process. Overall, the adoption of water-saving technology can significantly improve the efficiency of grain production for farmers; ②The adoption of water-saving technology is conducive to further improving agricultural production efficiency by promoting large-scale farming and saving irrigation time; ③Water conservation subsidies and land transfer have a positive incentive effect on the improvement of grain production efficiency in the process of adopting water-saving technologies by farmers; ④The improvement effect of water-saving technology on grain production efficiency is limited by age and income thresholds. For high agricultural income and older farmers, the improvement effect is significant. Therefore, the government should fully play its main role in the adoption of water-saving technologies by farmers, accurately carry out agricultural water-saving subsidies, solidly promote the construction of basic irrigation facilities for agricultural water conservancy, and establish a monitoring and evaluation mechanism for technology adoption.

The analysis of sediment sources in small watersheds is of great significance for the evaluation of comprehensive watershed management and soil and water conservation measures. Using a small karst watershed as an example, starting from the sediment deposition in the check dam of the small watershed, this study examines the depth distribution characteristics of ¹³⁷Cs specific activity, bulk density, and clay content in the check dam sediment profile and its control of land use types in the watershed, in order to understand the evolution characteristics and driving factors of soil erosion in the watershed.The research results indicate that:①The specific activity of ¹³⁷Cs in the sediment of check dam varies more complex in the vertical profile, with the maximum value appearing at the bottom and top of the check dam. The specific activity range of ¹³⁷Cs is 0.99~3.58 Bq/kg, with an average value of 1.8 Bq/kg; ②There are significant differences in the distribution of ¹³⁷Cs specific activities in the surface soil of sloping farmland, grassland, and forest land in the check dam controlled watershed, with ¹³⁷Cs specific activities ranging widely, at 4.16, 2.86, and 6.36 Bq/kg, respectively; ③The sediment deposition in the check dam cycle and its control on land use types in the watershed are mainly composed of clay, medium silt, and silt particles, and their proportion of particle size components is basically consistent; ④The characteristic parameters of sediment particle size in check dam (median particle size, mode particle size, volume weighted average particle size, and fractal dimension D) vary consistently in the vertical profile, while the variation of effective particle size is more complex.The study provides an important basis for the evolution of sediment source characteristics in mountain flat ponds in karst small watersheds.

Soil parameters are important factors for simulating and calculating state data such as soil moisture content and are of great significance for agricultural management and research. However, due to the variable saturation and nonlinear characteristics of the soil system, existing data assimilation methods still face challenges when estimating soil parameters. The parameter estimation method based on deep learning (Parameter Estimator with Deep Learning, PEDL) is employed to estimate soil parameters through inversion. The effectiveness of PEDL in estimating soil parameters was validated using two ideal numerical cases, and a systematic comparison was conducted with the Ensemble Smoother with Multiple Data Assimilation (ESMDA). The research results show that PEDL can successfully identify the nonlinear relationship between observed data and parameters to be estimated and can approach the true value of soil parameters without iteration; the posterior distribution range of parameters obtained by PEDL is significantly narrowed compared to ESMDA. Compared with the ESMDA method with five iterations, the PEDL estimation results exhibit lower uncertainty and require fewer total model runs. This study helps improve the accuracy of soil parameter estimation and can effectively enhance the prediction reliability of soil states and related agricultural models.

As climate change intensifies and human activities increase, vegetation change has become a key indicator of environmental response and a focus of scientific research. This study used MODIS data to analyze the Kernel Normalized Difference Vegetation Index (kNDVI) in the Hetao irrigation area from 2000 to 2022. By calculating slope, LOWESS smoothing, centroid shift models, and the Hurst index, and combining surface temperature and precipitation data, a multiple regression residual analysis was performed to assess the contributions of climate change and human activities. The results show: ① The kNDVI in the Hetao irrigation area exhibited a steady increase, with an average annual growth rate of 1.51% (p < 0.001). The overall centroid shifted to the southwest, and 93.42% of the area showed a strong persistence in kNDVI change trends. ② The combined contribution of climate change and human activities to kNDVI changes reached 88.75%, with joint greening as the dominant driving factor, accounting for 80.25% of the total. ③ The individual contribution rates of climate change and human activities were approximately 0.21 and 0.76, respectively. This study provides new insights into the spatiotemporal evolution of kNDVI and its driving forces in the Hetao irrigation area, offering scientific evidence for regional ecological management and policy-making.

In order to better capture the nonlinear characteristics and effective influencing factors of reference crop evapotranspiration (ET ₀) data, and to achieve accurate ET ₀ prediction when meteorological information is lacking, an ET ₀ prediction method based on the fusion modeling idea of a combination of Random Forest Feature Selection and Pelican Optimization Algorithm (POA) optimized Long Short Term Memory Neural Network (LSTM) is proposed. First, Random forest feature selection was used to evaluate the importance of the features and filter the effective weather factors as model inputs; subsequently, the optimal hyperparameter combinations are searched by POA for optimizing the LSTM model; finally, the ET ₀ prediction was performed based on the LSTM model under the optimal hyperparameters.The results show that the POA-LSTM model outperformed the other models, among which POA-LSTM1 (u ₂、N、R_H 、T_mean ) has the highest prediction accuracy, with the test set R ², RMSE and MAE of 0.927, 0.778, and 0.400 mm/d, respectively; POA-LSTM4 (u ₂、N) also demonstrated good performance in estimating ET ₀ with fewer meteorological inputs, with the test set R ², RMSE and MAE of 0.881、0.995 and 0.510 mm/d, with higher prediction accuracy and stability compared to other methods.

A capacitive-based surface soil moisture sensor is designed to address the issues of slow speed and low efficiency in surface soil moisture measurement. Unlike traditional insertion-based measurement methods, a co-planar inter-digitated capacitive probe is designed and fabricated to achieve rapid measurement of surface soil moisture. Sandy loam soil from the Langfang area of Hebei Province was used as the experimental soil sample. The sensor output values were calibrated using polynomial fitting, achieving a determination coefficient of 0.981 77. The dynamic response, stability, and sensitivity tests of the sensor meet the monitoring requirements. The impact of environmental temperature changes on the sensor output is analyzed, and a linear fit between the sensor output and temperature was determined with a determination coefficient of 0.984 57. Furthermore, the sensitive measurement area of the sensor is determined through experimental testing, and its longitudinal influence range is found to be 4 cm. Comparative experiments with the TRIME-PICO64 insertion type soil moisture sensor show that the performance of the designed sensor is comparable to that of similar foreign products but has a higher cost-effectiveness. Finally, through comparative experiments and analysis, the designed soil moisture sensor is concluded to enable rapid measurement of surface soil moisture and effectively solve the problem of low efficiency in measuring flowing water in surface soil.