This study addresses the unclear influence of soil texture on the accuracy of hyperspectral inversion for soil salinity. From April 1 to 10, 2023, a total of 132 soil samples with different salinization degrees were collected in Shenwu irrigation area of Hetao Irrigation District, Inner Mongolia. Corresponding spectral information was collected simultaneously. The variation characteristics of spectral reflectance of soil under different salinization degree and the correlation between spectral characteristics of soil texture and soil salinity were studied. The appropriate mathematical transformation method of soil samples was discussed, and the sensitive bands were selected. A hyperspectral inversion model based on all samples and different soil textures was established. The results showed that the hyperspectral reflectance increased with the increase of soil salt content. As the soil grain size decreased, soil salinity and reflectance of different bands and their correlation coefficients exhibited an increasing trend followed by a decreasing trend. After mathematical transformation of spectral data, it is found that reciprocal logarithmic differentiation, logarithmic differentiation and square root differentiation have the best effect. Four models of multiple stepwise linear regression (BPNN), partial least squares regression (PLSR), support vector machine regression (SVM) and BP neural network (BPNN) were established to estimate the salt content under spectral transformation. The estimation accuracy of the four models was as follows: BPNN>SVM>PLSR>MLSR. Compared with the soil salt estimation results of all samples, the salt estimation accuracy of different soil textures was improved. For sand texture, the estimation accuracy R ² was increased from 0.918 to 0.962, and the RPD was increased from 3.493 to 4.313. The grain texture estimation accuracy R ² increased from 0.866 to 0.902, and the RPD increased from 2.613 to 3.310. The accuracy of clay texture estimation R ² increased from 0.876 to 0.926, and the RPD increased from 2.651 to 3.953, and the models established under the three soil texture backgrounds all reached the standard of excellent models. The results show that the hyperspectral inversion of salt content is helpful to improve the inversion accuracy when considering soil texture.

Net primary productivity (NPP) of vegetation is an important reference index for regional ecosystem protection and ecological environment governance. Aiming at the problem that the spatial and temporal variation characteristics of vegetation NPP and its response to climate change in Baicheng Basin are unknown, this study used the STARFM spatial and temporal data fusion model to estimate the vegetation NPP of 30 m spatial resolution in Baicheng Basin.At the same time, Sen slope estimation and M-K test were used to analyze the spatial and temporal variation characteristics of vegetation NPP, and the influence degree of climate factors was quantified by partial correlation coefficient method. The results showed that: Temporally, the average NPP of vegetation in the study area from 2000 to 2020 was 152.1 g C?m^-2?a^-1, showing an insignificant downward trend. Spatially, the NPP value of vegetation is high in the northern and southern regions, and low in the central valley. Out of the total area, 69.03 % of the areas showed no significant change, 11.44 % showed a significant increase trend, and 19.53 % showed a significant decrease trend. The change of vegetation NPP in the study area exhibited a positive correlation with total rainfall and total solar radiation, while they displayed a negative correlation with average temperature. Among these factors, solar radiation was the dominant factor affecting the change of vegetation NPP. The results show that the improved CASA model has good applicability to simulate the net primary productivity of vegetation in the study area, which is helpful to better reveal the variation characteristics and driving factors of NPP in Baicheng Basin, offering a new method for estimating and regularly monitoring NPP in small and medium-sized areas.

Soil moisture is an important environmental variable that connects the fields of agriculture, ecology, and hydrology. Remote sensing serves as a valuable tool for monitoring surface soil moisture. In response to the problems of insufficient spatial resolution in microwave remote sensing and the impact of cloud and rainy weather in optical remote sensing, field-scale (30 m) SSM was generated in this study based on random forest models combined with quality Landsat 8 and MODIS optical images, SMAP_L4 microwave data, and CLDAS reanalysis data, and in situ SSM measurements. The results showed that the ESTARFM algorithm could generate daily continuous normalized difference vegetation index (NDVI) image at a 30m resolution, exhibiting spatial consistency with the original NDVI image. The fused NDVI image achieved a correlation coefficient (R) of above 0.85 and a root mean square error ranging from 0.05 to 0.08, indicating a good fusion performance. The random forest model yielded the best results of soil moisture at high spatio-temporal resolution, based on the combination of multiple characteristic parameters of land surface temperature, NDVI, enhanced vegetation index, leaf area index and reanalysis of soil moisture products. The obtained soil moisture data at the field scale accurately captured its spatio-temporal variations, with a correlation coefficient of 0.82 and a root mean square error of 0.037 cm³/cm³. The research methods presented in this study can provide technical support for irrigation area identification and drought monitoring in irrigation districts.

There are distinct variations in the distribution of moisture and temperature fields around the lined channel, and the freezing and expansion rates of the channel base soil in this range under the coupling of water and heat fields are obviously different. To investigate these differences, experimental studies on the freezing and expansion rate of the soil in different moisture and temperature conditions were carried out. The results show that: Under different sub-zero temperature conditions, the freezing expansion rate of the specimens exhibits a two-stage change process. When the temperature is reduced from 0℃ to -5℃ or so, in this stage of the freezing expansion rate accounts for about 50% to 80% of the whole freezing expansion process, showing a clear linear relationship with temperature. In the second stage, as the temperature continues to decrease, the nonlinear relationship between the two is obvious.Under the condition of no water supplement and same sub-zero temperature conditions, specimens with higher initial moisture content exhibit greater rates of freezing expansion. Initial moisture content of 25% and 35% of the specimen produced frost expansion rate is about double to more than twice the initial moisture content of 15% specimen. When the specimen is replenished with water during the freezing process, the linear relationship between the freezing expansion rate and the moisture change is evident. The larger the initial moisture content of the specimen produces a larger increment of the freezing expansion rate, the initial moisture content of 25%, 35% of the specimen freezing expansion rate increment is more than twice as much as the 15% of the specimen.The multivariate nonlinear relationship between hydrothermal coupling conditions and the freezing and expansion rate of canal subsoil was proposed, and it was in good agreement with the experimental data. A numerical simulation model was established to calculate and analyze the distribution and deformation of frost heave in different positions of lining channels. The results show that lower temperatures and higher moisture levels result in greater tangential and normal frost heave forces. And the greater the difference between water and heat, the more significant the frost heave deformation of lining channels caused by soil frost heave.

In order to explore the influence of pressure on the seepage performance of underground drip irrigation pipes, hydraulic performance test of free flow under different working pressures (0.02~0.18 MPa) were conducted. Addtionally, the infiltration test of indoor soil box under two pressure conditions were carried out for a new type of underground irrigation pipe. The variation coefficient of irrigator, flow pattern index and irrigation uniformity with pressure and the migration law of infiltration wetting front were analyzed. The results show that under the condition of free discharge, the variation coefficient of discharge is 0.01. The relation between pressure and discharge is: q = \mathrm{6.549} \text{?} \mathrm{17} \text{?} h^{\mathrm{0.521}}. The flow index, denoted as x, is 0.521, and the sensitivity of the irrigator to pressure change is higher. Irrigation uniformity coefficient is greater than 0.8. Under the same embedment depth, increasing the pressure leads to a higher migration rate of the wetting front and a larger volume of the wetted zone formed within the same timeframe. The wetting front is a power function of the distance and time of water migration in each direction.

Considering the investment and water pressure distribution of the pipe network, it is essential to design the pipe network layout and select pipe diameters in a manner that ensures both economic efficiency and system reliability for self-pressure drip irrigation systems, so that the self-pressure drip irrigation pipe network system can achieve the purpose of the lowest investment and the highest irrigation uniformity. With the goal of minimizing investment in the pipe network (pipe network economy) and minimizing the average value of the node surplus head (pipe network reliability), the multi-objective optimization mathematical models of the self-pressure drip irrigation "comb" type and "Fengzi" type field pipe network system are established. Furthermore, the methods and steps of the mixed harmony search algorithm to solve the multi-objective optimization model are proposed. Taking a self-pressure drip irrigation project in Xinjiang as an example, the field pipe network system was optimized by this method, and the total investment of the pipe network of the optimization scheme was 476,300 yuan, which was 9.86% lower than the original design scheme. The average head value of the surplus water head of the pipe network node was 8.12 m, which was 33.87% lower than the original design scheme. The optimization results obtained by this optimization design method not only yield significant cost savings, but also significantly reduce the average value of the surplus water head at the node, indicating that the pressure deviation of the pipe network system is small and the uniformity of irrigation is significantly improved. At the same time, the hybrid harmony search algorithm has stable convergence, fast calculation speed and high calculation accuracy, which has good application value in the multi-objective optimization design of self-pressure drip irrigation pipe network.

This study was to investigate the impact of varied bentonite application rates on soil properties, soil structure, and the agronomic performance of hot pepper in sandy soil. The findings aim to to provide reference for improving the utilization value of sandy soil, quality and yield of Hot pepper. The bentonite treatment of sandy cropland field experiment was carried out from April 2023 to October 2023 in Shanwan Village, Balagong Town, Hangjin Banner, Ordos City. Six groups of treatments were set up according to the application rate of bentonite, which were: 0(CK), 15.0 t/hm²(A1), 22.5 t/hm²(A2), 30.0 t/hm²(A3), 37.5 t/hm²(A4), 45.0 t/hm²(A5), respectively. The effects of different bentonite application rates on soil physicochemical properties and structure and the agronomic effects of hot pepper were investigated. The results showed that compared with the control group, bentonite application could significantly improve soil physicochemical properties and effectively adjust soil structure. Bentonite application increased soil water content, porosity, CO₂ flux, >0.25 mm agglomerate content, pH and conductivity during the reproductive period of hot pepper. It also reduced soil bulk weight during the reproductive period, coordinated the soil three-phase ratio, and improved the solid-liquid-gas structure of the soil, and the best effect was achieved with the A5 treatment. Application of bentonite can effectively promote the growth and development of hot pepper and increase the yield of hot pepper. The highest yield of hot pepper was achieved with A3 treatment, with a significant yield increase of 61.2% compared with the control group. Bentonite as a soil conditioner can effectively improve the physical and chemical properties of the soil, adjust the soil structure, improve the soil water holding capacity and the yield of hot pepper. Considering the comprehensive effects of different application rates on soil indicators and the yield of hot pepper, the study concluded that 30.0 t/hm² is the more appropriate application rate for the experimental area in 2023.

The alluvial plain area in the lower reaches of the Yellow River is an important grain production base and industrial agglomeration in China. The acquisition of soil hydraulic parameters in this area is crucial for ensuring water safety and guiding agricultural production.To establish the PTFs of soil water characteristic curves in the alluvial plain area of the lower Yellow River, Yanlou Township, Lankao County, Henan Province, is selected as a representative area in the alluvial plain of the lower Yellow River. Based on multiple nonlinear stepwise regression and single factor perturbation methods, the PTFs of soil water characteristic curves in the vadose zone were established, and the sensitivity of influencing factors was analyzed. The research results show that the measured soil water characteristic curves and soil physicochemical parameters exhibit strong variability. The PTFs established in this research demonstrate good accuracy, which have application and promotion value. The multiple regression results indicate that soil particle composition is the main influencing factor of PTFs in this study. The clay content is the most sensitive, followed by sand content, and the silt content is the weakest. Among the other five soil physicochemical properties, the relatively sensitive factors are pH value and fractal dimension. This study indicates that the relationship between soil physicochemical properties and soil water characteristic curve model parameters is complex. It is not a general linear or monotonic relationship. Although soil physical and chemical property parameters can improve the accuracy of PTFs, soil particle composition is the fundamental reason affecting soil water movement, and cannot be ignored as a key factor in the constructing of PTFs. In practical applications, PTFs users can determine the choice of influencing factors based on the actual situation of the data they have mastered, combined with the sensitivity of influencing factors.

The application of water retainers and transpiration inhibitors is crucial in the efficient production of maize. To investigate the effects of water retainers and transpiration inhibitors on the growth and development of maize and the coupling relationship between soil water and fertilizer, a field experiment was conducted in Xiaoshiqin Village, Henan Township, Wuqian Banner, Ordos City, Inner Mongolia Autonomous Region. Four treatments were set up in the experiment, namely, irrigation rate of 30 mm and application of water conservator (C1), irrigation rate of 37.5 mm and application of water conservator (C2), irrigation rate of 45 mm and application of transpiration inhibitor (C3), and irrigation rate of 45 mm and no application of reagent (CK). The results showed that: ①Compared with CK, the average soil water content during the maize reproductive period was increased by 6.61%, 11.94% and 4.05% under C1, C2 and C3 treatments, respectively. This suggests that water retention agent and transpiration inhibitor could effectively improve soil water retention capacity. ②The highest rate of corn plant height enhancement was observed during the nodulation stage, with C1, C2 and C3 elevated by 9.40%, 17.45% and 6.04%, respectively, compared with CK. This indicates that water retaining agent and transpiration inhibitor could effectively enhance corn plant height. ③The stem thickness of maize showed a trend of rapid growth followed by slow growth and then a slight decrease with the advancement of the reproductive period, with the rapid growth period being the nodulation stage, and the average growth rate of stem thickness at the nodulation stage compared with that at the seedling stage was 60.21%. ④The application of water retainer can increase soil fertility and synergistic relationship between soil water and fertilizer. In comparison to the CK treatment, soil total nitrogen, effective phosphorus, quick-acting potassium, slow-acting potassium and organic matter content in C2 treatment increased by 37.57%, 82.76%, 88.66%, 1.31% and 37.83%, respectively. Soil water-fertilizer coupling and coupling coordination increased by 77.74% and 52.79%, respectively. In summary, the application of water retaining agents and transpiration inhibitors can effectively improve the soil moisture condition and promote the growth and development of maize, which has obvious advantages over the treatment without applying any reagents.

To investigate the applicability of the SIMdualKc model in Camellia oleifera forests located in hilly regions of south China, this study utilized two years of field-measured experimental data during the growth season of Camellia oleifera plantation to determine and validate parameters for the two-crop coefficient SIMdualKc model. The crop coefficients were determined as follows: initial crop coefficient (K _cbini) = 0.9, mid-season crop coefficient (K _cbmid) = 0.92, end-season crop coefficient (K _cbend) = 0.77. Verification results for soil moisture content showed a strong correlation (R ²: 0.918~0.979), low mean absolute error (MAE: 0.019~0.021), low root mean square error (RMSE: 0.021~0.026), and high efficiency factor (EF: 0.876~0.957). By comparing different methods of inputting leaf area index data, it was concluded that daily variation of leaf area index yielded slightly better simulation results. The reliability and applicability of leaf area index calculated using the Logistic growth function were confirmed, and simulated values of soil water content under water stress conditions for Camellia oleifolia were calibrated. At the end of summer shoot and autumn shoot stages, Camellia oleifera exhibited higher susceptibility to water stress, with water stress coefficients (K_s ) ranging between [0.478,1] in 2021 and [0.182,1] in 2022.Comparison between evapotranspiration calculated using the water balance method and simulated values showed good agreement with an R ² value ranging from (0.52~0.61). These research findings provide a theoretical basis for developing efficient water-saving irrigation systems to mitigate natural disasters such as high temperatures and drought during summer and autumn seasons in southern hilly areas.

Intercropping with legume has the advantages of improving water use efficiency of crops, optimizing soil water distribution, and promoting crop growth. Based on light energy use, nitrogen use, water consumption, water use efficiency and interspecific relationship under gramineous-legume intercropping, the characteristics and mechanism of water use under gramineous-legume intercropping were reviewed in this paper. By combining with soil improvement, different irrigation methods and intelligent detection technology, the paper analyzed the deficiency of water use under the current cropping pattern of gramineous-legume. The results showed that current studies on water use efficiency of gramineous-legume intercropping mainly focused on crop collocation, spatial layout and tillage methods, which could be combined with irrigation management and soil improvement. Intelligent detection equipment could be used to monitor crop, soil and environment factors in real time and accurately, so as to further understand the ecological and physiological processes of crops. Water migration rule and the synergistic effect of competition and complementarity between different species were used to form the water efficient management model of gramineous-legume intercropping.

To explore an optimal integrated water-biogas deficit irrigation model for greenhouse tomatoes, a two-season experiment was conducted in March-July 2021 and September-December 2021 in a greenhouse in Lanzhou City, Gansu Province, China. Three irrigation and fertilization levels: high water and low fertilizer (full irrigation), medium water and medium fertilizer (mild deficit irrigation), and low water and high fertilizer (moderate deficit irrigation) were set at three growth stages (seedling, fruiting, and fruit ripening) of tomatoes to analyze the effects of different treatments on tomato yield, water use efficiency, and quality. A hierarchical model of tomato integrated quality was constructed, and an approximate ideal solution (the TOPSIS method) was applied to obtain the tomato integrated quality evaluation value. At the same time, the yield, water use efficiency, and comprehensive quality of tomato were taken as the evaluation indexes of comprehensive benefit of tomato. A combined evaluation method was applied to obtain the evaluation value of comprehensive benefit of tomato under different water and fertilization treatments. The results showed that: T8 treatment (using medium water and fertilizer in all three growth stages) had the highest yield of 5.612 kg (spring 2021) and 5.032 kg (autumn 2021); T9 treatment (using low water and high fertilizer in all three fertility stages) had the optimal tomato water use efficiency of 0.173 kg/L (spring 2021) and 0.171 kg/L (autumn 2021). The highest fruit shape ratio, sugar-acid ratio, soluble solids, vitamin C, soluble proteins, and fruit water content were found in the T8 treatment. The highest values of soluble sugars, titratable acids, and hardness were found in the T9, T4 (medium-water fertilizer at seedling stage, plus low water and high fertilizer at flowering and fruit setting stages, and high water and low fertilizer at fruit setting stages), and T3 (medium-water fertilizer at seedling stage, high water and low fertilizer at flowering and fruit setting stages, and high water and low fertilizer at fruit setting stages), respectively. The best comprehensive quality evaluation and comprehensive benefits of tomato in the two-season trial were obtained in the T8 treatment.

As a revolutionary technical project to increase agricultural production and income in arid oasis irrigation, drip irrigation engineering has a profound impact on agricultural production and the ecological environment. To effectively evaluate the impact of drip irrigation engineering on agricultural productivity, this study took Shaya County as the research area, and analyzed the spatiotemporal changes of NDVI and cultivated land area in the county during the construction and operation period of drip irrigation engineering (2014-2022) by using Normalized Difference Vegetation Index (NDVI) datasets, meteorological datasets and Land Use/Cover Change (LUCC) datasets. The results show that: ①From 2014 to 2022, the cultivated land area of the county increases by 83.83 km², with drip irrigation engineering accounting for 71.22% of this expansion. ②The average growth rate of NDVI in the drip irrigation area is 0.44%/a, while the average growth rate of NDVI in the non-drip irrigation area is only 0.30%/a. The change of NDVI in the drip irrigation area is obvious. ③After the implementation of drip irrigation project, the annual precipitation decreases by 42.48%, but NDVI of the county shows a characteristic pattern of "increase - gentle - increase", with an average growth rate of 0.27%/a and an average increase of 11.53%. Agricultural productivity increased rather than decreased. The implementation of drip irrigation engineering not only promoted land transfer and large-scale management, reduced plot fragmentation, it also significantly expanded the effective cultivated land area. Moreover, the county agricultural productivity (NDVI) and water saving and drought resistance ability are significantly improved, and the overall agricultural production capacity of Shaya County is improved. Therefore, drip irrigation projects hold significant importance in improving agricultural productivity and ecological environment in arid areas.

To analyze the applicability of different reference crop evapotranspiration estimation methods in the Huaibei Plain, based on the meteorological observation data of Wudaogou Experimental Station from 2009 to 2022, this paper takes the calculation results of FAO56 Penman-Monteith (FAO56PM) method as the standard and select six statistical indicators for comprehensively analysis from daily and monthly scales. The results showed that the FAO24 Penman (FAO24PM) method, 1996 KiM-Berly Penman (K-P) method and Pristley-Taylor (P-T) method were the best at the daily scale, and the FAO24 PM method, P-T method and Debruin-Keijman (D-K) method were the best at the monthly scale. The comprehensive method shows the highest performance, followed by the radiation-based method, the mass transfer-based method and the temperature-based method. The FAO24 PM method is the best in the comprehensive method. The P-T method is the best in the radiation-based method. The FAO24 BC method is the best in the temperature-based method. The Mahringer method is the best in the mass transfer-based method at the daily scale, while the Trabert method is the best at the monthly scale. Therefore, the FAO24PM method is recommended when the data are sufficient, and the P-T method, FAO24BC method, Mahringer method (daily scale) or Trabert method (monthly scale) are recommended when data are insufficient.

The drought is a natural disasters that affect social and economic development. The exploration of temporal and spatial characteristics of drought is crucial to drought prevention and strategy formulation. The spatial-temporal aspect of drought in China was analyzed under different time scales (1-month, 3-month, 6-month, and 12-month) by the frequency and intensity indexes of drought. The study used the Mann-Kendall test (MMK) method and the sliding time window method based on the standard precipitation Evapotranspiration Index (SPEI) grid data of seven regions in China from 1979 to 2020. The results show that the drought degree is more prominent in the Qinghai-Tibet Plateau, Inner Mongolia grassland, Northwest desert, and Northeast humid and semi-humid temperate regions. The drought frequency decreased with the increase of the SPEI time scale and the increase of drought level for the SPEI index on 3-month, 6-month, and 12-month time scales. The spatial trend of China shows that the desert region of Northwest China, the Qinghai-Tibet Plateau, the grassland region of Inner Mongolia, the northern part of the humid subtropical region of South China, the southern part of the humid and semi-humid warm temperate region of North China, and the humid and semi-humid temperate region of Northeast China have a significant aridification trend. There were distinct differences between dry and wet in the Qinghai-Tibet Plateau and the humid and sub-humid temperate regions of Northeast China. Regarding time scale, the drought degree calculated by the SPEI index is greater in the northwest desert area on 1-month, 3-month,6-month, and 12-month time scales, in the Qinghai-Tibet Plateau on 1-month, 3-month, 6-month, and 12-month, in the Inner Mongolia grassland area on 1-month, 3-month, 6-month, and 12-month time scales, in the humid and semi-humid temperate area of Northeast China on 6-month, and 12-month time scales, and in the humid and semi-humid temperate area of Central and South China on 1-month, 3-month and 12-month time scales. The results can provide some reference for drought prevention and impact assessment in China.

The objective of this study was to investigate the effects of different application rates of phytonutrients (compound oligosaccharides) and irrigation quotas on the growth, yield, quality and soil enzyme activity of greenhouse-grown tomatoes. “Jiahong 100” was planted in a greenhouse, and three irrigation quotas were set up: 5 550 m³·hm^-2 (W1)、6 375m³·hm^-2 (W2)、7 200 m³·hm^-2 (W3). Additionally, three compound oligosaccharide application rates: 168 g·hm^-2 (P1), 336 g·hm^-2 (P2) and 504 g·hm^-2 (P3), and CK treatment was used as the control group. A total of 10 treatments were used. The effects of different treatments on the growth, yield, quality and related enzyme activities in fruit tomato soil at maturity stage were determined and analyzed. The results show, Irrigation quotas and compound oligosaccharides had a certain effect on the growth of fruit tomatoes. The yield and irrigation water use efficiency of fruit tomato increased with the increase of irrigation quota and compound oligosaccharides. High irrigation quota would lead to the decrease of quality. Under the experimental conditions, when the irrigation quota is constant, the more complex oligosaccharides are applied, the more beneficial it is to improve the yield and quality. For urease in soil, higher dosage of complex oligosaccharides will increase its enzyme activity, with the p3 dosage of compound oligosaccharides has the best effect. However, too much irrigation quota will reduce its activity. For sucrase, the sucrase activity of W2P1 treatment was the highest, and the enzyme activity initially increased and then decreased with the increase of irrigation quota. In summary, W2P3 (irrigation quota 6 375 m³·hm^-2, compound oligosaccharide 504 g·hm^-2) was recommended as the water-phytonutrient coupling mode for greenhouse fruit tomato cultivation in Wuzhong area, Ningxia Province.