In order to explore the proper buried depth of underground seep-irrigation for potato, an experiment was carried out to study the effects of different irrigation quotas (1 050,1 500,1 950 m3/hm²) and different buried depths (0,10, 20 cm) on potato growth, yield and water use efficiency. The results showed that: the maximum dry matter accumulation and yield occurred when the irrigation quota was 1 950 m3/hm² and the buried depth was 0 cm, and the second one occurred when the irrigation quota was 1 950 m³/hm² and the buried depth was 10 cm. The maximum water use efficiency occurred when the irrigation quota was 1 500 m³/hm² and the buried depth was 10 cm. In conclusion, under the climatic conditions of the Yanghuang irrigated area of Ningxia, the optimal buried depth of underground seep-irrigation was 10 cm and the corresponding irrigation quota was 1 500 m3/hm2. This study provides a reference for developing potato production under the undergroud seep-irrigation.

In view of the imperfect design of ridge and ditch cultivation measures under drip irrigation in inland arid area, the influence of different ridge and furrow specifications on the change of soil wetting peak transport is studied, which aims to provide theoretical reference value for rational design of ridge and ditch drip irrigation system. The indoor soil box simulation test was carried out, and the variation of the movement of the wetting peak was analyzed by taking the width of the bottom of the ditch and the slope of the ditch as variables and taking the planned wet layer as the constraint. With a certain slope of the ditch bottom, the greater the width of the ditch bottom, the longer the time it takes for the irrigation water to reach the planned wetting layer, and the larger the volume of the wetting body. With a certain width of the ditch bottom, the higher the slope of the ditch bottom, the shorter the time it takes for the irrigation water to reach the planned wetting layer, and the smaller the volume of the wetting body. The horizontal and vertical wetting peak migration distance has a power function relationship with the irrigation duration. The power function index b varies little with the width of the ditch bottom and the slope of the ditch bottom. The horizontal wet power function coefficient a increases with the increase of the width of the bottom of the ditch, and decreases with increase of the slope of the bottom of the ditch. The vertical wetting peak power function coefficient a decreases with the increase of the width of the bottom of the ditch, and increases with the increase of the slope of the bottom of the ditch.

In order to study the rule of transpiration water consumption of fruit trees based on apple tree trunk and stem flow and the influence of water and fertilizer and meteorological factors, an experimental study on the influence of different water and fertilizer treatments (low-fat medium water, medium-fat medium water, high-fat medium water, medium-fat high water and medium-fat low water) on apple tree stem flow was carried out in apple orchard in the dry tableland of Weibei, Shaanxi province in 2018.The results showed that the stem flow rate of apple tree increased day and decreased night in different months during the growth period; when irrigation amount was the same, the correlation between daily stem flow and meteorological factors such as daily temperature, daily radiation and daily relative humidity decreased with the increase of fertilizer application. The correlation between daily radiation, daily air temperature and surface temperature and stem flow was the highest when the fertilizer application rate was the same; The order of apple tree stem flow under different water and fertilizer treatment was: medium water > high water > low water; Medium fertilizer > high fertilizer > low fertilizer; low water and low fertilizer treatment could significantly reduce the stem flow rate of apple trees. Irrigation had a more significant effect on the stem flow rate of apple trees than fertilization. The coupling effect of water and fertilizer had a greater promoting effect on the stem flow of apple trees than single fertilizer level treatment and single water treatment.

In order to explore the influence of water and fertilizer integration on the growth of water spinach under the condition of micro-moist irrigation, six treatments, including two pressure head treatments of 100 cm (H1), 150 cm (H2) and three nitrogen (urea) application levels of 0 mg/L (N0), 500 mg/L (N1) and 1 000 mg/L (N2), were set in the experiment. Three repeated tests were conducted for each treatment to determine and analyze soil moisture content, plant height, stem diameter, fresh weight, dry matter accumulation and nitrogen agronomic efficiency under different treatments, explore the influence of different pressure water head and nitrogen application concentration on the growth of water spinach, and screen the better combination suitable for the growth of water cabbage. The results showed that under the condition of the buried depth of the micro-moistening tube 20 cm and the laying spacing 25 cm, the pressure head of 150 cm could promote the growth and development of plants, and the plant height, fresh weight，dry matter accumulation and nitrogen agronomical efficiency of water spinach with the nitrogen application concentration of 1 000 mg/L were significantly higher than those with the nitrogen application concentration of 500 mg/L.

In order to comprehensively evaluate the effect of drip irrigation with brackish water on summer squash, the optimal irrigation scheme of summer squash under drip irrigation with brackish water is preferred. In this experiment, the soil moisture control threshold of the seedling stage, creeping stage and flowering and fruiting stage of summer squash and the salinity of irrigated water were used as experimental factors, and 9 treatments of summer squash under-film drip irrigation with brackish water experiment were carried out by orthogonal design in the greenhouse. The yield of summer squash, the water requirement of summer squash, the soil salt content at the end of the growing period and the utilization of brackish water were used as the evaluation indexes. The weight of the evaluation index was determined by the analytic hierarchy process. The fuzzy comprehensive evaluation converted the multi-index evaluation into the single-index evaluation, and the experimental results were obtained by orthogonal test extreme analysis method. The results showed that the factors influencing the comprehensive score of experimental treatment were ranked as follows: irrigation water salinity > seedling stage soil water > flowering and fruiting stage soil water > tendril stage soil water; The optimal irrigation scheme was as follows: the salinity of irrigation water was 3.5 g/L, the soil moisture in the seedling stage was controlled at 70%~90%θFC, the soil moisture in the creeping stage was controlled at 60%~80%θFC, and the soil moisture in the flowering and fruiting stage was controlled at 60% ~80%θFC. The results can reflect the effect of bra

In order to investigate the response law of physiological growth and yield formation of rice to different water-saving irrigation modes, four different water-saving irrigation modes, including shallow irrigation, wetting irrigation, controlled irrigation, water storage controlled irrigation, were designed. The dynamic changes of rice plant height and chlorophyll content under different water-saving irrigation modes were observed, and the total yield and its components (effective panicle number per hole, grain number per panicle, seed setting rate, 1 000-grain quality and yield per hole) of rice were analyzed. The results showed that there was no significant difference in the variation law of rice plant height under different water-saving irrigation modes. The rice plant height at harvest under water storage controlled irrigation was the highest (103.4 cm), followed by controlled irrigation. Both the linear model and the exponential model could well simulate the dynamic changes of rice plant height under different water-saving irrigation modes. The correlation coefficients were 0.978 1~0.982 4 and 0.975 6~0.982 7, respectively. The content of chlorophyll in rice reached its peak value at 76 days after transplanting, and then entered the decline period and the content of chlorophyll decreased gradually. The total chlorophyll content of rice in the middle and late stage under water storage controlled irrigation was higher than that under other treatments. Different irrigation mode had impacts on number of effective panicles per hole, grain number per panicle, seed setting rate, 1 000-grain quality and yield per hole of rice. The rice yield under water storage controlled irrigation was the highest (10 172 kg/hm2), while that under the shallow irrigation was the lowest (8 735 kg/hm2).

For the study of particle size distribution change on the Yellow River delta saline soil water characteristic curve equation parameters, laboratory simulation experiments were carried out under different sand distribution. The soil moisture content under different water suction of each treatment was measured by pressure film method. Combined with VG model and Gardner model, the applicability of the two models to the soil water characteristic curve was analyzed, as well as the influence of the change of soil particle gradation on the model parameters. The results showed that the composition of soil particles changed obviously after saline-alkali soil mixed with sand. Among them, the relative content of 0.05~0.1 mm particles increased from 3.6% to 62.02%, and the relative content of particles less than 0.002 mm decreased from 29.02% to 3.89%, indicating significant changes in soil particle gradation. Under the condition that the saline-alkali soil had a high amount of sand distribution (67.0%), the parameter n showed an increasing trend with the increase of the amount of sand distribution, while the ordinal value showed a decreasing trend with the increase of the amount of sand distribution. In the Gardner model, parameter a was only negatively correlated linearly with the treatment of sand allocation in a certain section (28.8%~45.2%), while parameter b showed an overall trend of first increasing and then decreasing with the increase of sand allocation. Both VG model and Gardner model can fit the soil water characteristic curve of clay saline soil with different sand distribution. The fitting degree of VG model to soil water characteristic curve was better than that of Gardner model, but the simulation accuracy of VG model was lower than that of Gardner model.

In order to explore the effect of water-nitrogen coupling effect of drip irrigation under plastic mulch on the quality of tomato in greenhouse and obtain the best water-nitrogen coupling mode for tomato production, the quality targets of tomato under different water and nitrogen treatments were analyzed through drip irrigation under plastic mulch testing in greenhouse. 4 irrigation treatments and 3 nitrogen treatments were designed. The water treatments included 50% reduction of full irrigation at seedling stage (W1), 50% reduction of full irrigation at seedling stage and flowering stage (W2), 50% reduction of full irrigation at the whole growth stage (W3), and full irrigation at whole growth stage (W4); Nitrogen treatments were 200 kg/hm2 (N1), 300 kg/hm2 (N2), 400 kg/hm2 (N3).The results showed that reducing irrigation amount at seedling and flowering stage could increase the content of soluble sugar, VC and nitrate, but decrease the content of organic acid. Increasing nitrogen application could increase the content of nitrate. The effects of water treatment, nitrogen application and water-nitrogen coupling on the content of soluble sugar, organic acid, VC and nitrate of tomato were reached extremely significant levels. The effect of irrigation treatment on lycopene was significant, but the effect of nitrogen treatment and water-nitrogen coupling effect on lycopene was not significant. The quality targets of tomato were comprehensively analyzed through principal component analysis, and the highest comprehensive evaluation score of water-nitrogen coupling was the treatment of W2N3.

In order to rationally formulate the optimal irrigation schedule for maize under drip irrigation under film in the semi-arid area of Jilin Province, and effectively guide the irrigation in the growing stage, so as to improve the grain yield in Jilin Province, in the semi-arid region of Jilin province, the Tongyu key irrigation test station, which is the representative of typical regions, was selected as the research subject, and the non-sufficient irrigation test data of 2018 of maize under drip irrigation under film was used to solve the five water production function models, including Jensen, Minhas, Blank, Stewart and Singh, and the sensitivity index (coefficient) of each model was obtained. Compared with other water production functions, the sensitivity index of Stewar water production function model showed a “single-peak” variation, namely smaller in early and late stages while larger in medium-term, which was 0.110 8 (seedling stage), 0.3530(jointing stage), 0.515 8 (tasseling-silking stage), 0.312 2 (filling stage) and 0.287 3 (milk stage), respectively. The sensitivity index of the tasseling-silking stage was the largest. The analysis results showed that the Stewart water production function model had good adaptability in the local area, and could be used in the formulation of optimal irrigation schedule for maize under drip irrigation under film in semi-arid area of Jilin province.

On the basis of analyzing and determining the growth period of corn, the main food crops in Anding area, the Penman-Monteith method recommended by FAO was used to calculate and determine the water requirement for the growth period of corn crops. Natural precipitation data from 1958 to 2015 were used to calculate and determine the annual distribution of precipitation at frequencies of 20%, 50% and 75%. The degree of water deficit and the main period of water deficit of maize crops in Anding area under arid habitat were analyzed. The results showed that under 50% precipitation frequency, the water deficit value of corn crops in Anding area was 126.78mm, accounting for 26.86% of the water requirement, among which the water deficit was the most serious at the seedling emergence and jointing stage, accounting for 61.76% of the water requirement, followed by the big trumpet mouth-silking stage, accounting for 41.95% of the water requirement. The study provides a very important scientific basis for guiding the dry corn crops to implement rainwater on-the-spot enrichment and utilization and rain harvesting supplementary irrigation.

The existing precision fertigation devices have similar fertilizer mixing principle, but according to different irrigation and fertilization requirements, the layout of pipeline, the types of fertilizer absorbing elements and the forms of water pumps are different. In order to speed up the research and design process of equipment, the design pipeline is simulated based on PIPENET software. The optimum design method is put forward to determine the appropriate amount of water pump, simulate the appropriate flow rate and pressure for Venturi pipe operation, and improve the efficiency and stability of fertilizer absorption equipment. The simulation results are verified by experiments. The pressure difference between the simulation results and the verification test results is less than 5.5%. Through comparison, it is proved that PIPENET software can be used in assistant design of fertilizer machine pipeline amount. Especially, the pump parameters can be determined quickly. And pipe diameter can be corrected according to flow rate. Thus, the design process can be accelerated and the reliability of the equipment can be improved.

In order to solve the problems of high power consumption, high cost and real-time accurate monitoring of soil moisture in traditional communication mode, a real-time monitoring system of soil moisture based on NB-IoT was designed. The data collected by capacitive soil moisture sensor is uploaded to the monitoring center through BC28 communication module in a prescribed format to realize remote transmission, display and query of soil moisture data. To a certain extent, the system improves the working efficiency of soil moisture monitoring, and has good prospects for popularization and economic benefits.

In order to determine the relationship between the laying length and the slope of thin-walled micro-spray belt at different slopes, the thin-walled micro-spray belt with a common fold diameter of N43 and 64mm in the market was selected. And combined with the distribution coefficient of water head in the irrigated area, take 0.55 as the distribution coefficient in lateral pipe, the allowable water head deviation of the micro-spraying belt was calculated. Based on the law of conservation of energy, the models of the relative pressure function between the head and end of the micro-spraying belt under different slope laying conditions were established, and the mathematical relationships between the allowable water head deviation of the micro-spraying belt and the relative pressure of the head and end of the micro-spraying belt was established. It was found that the relationship between the relative pressure and the laying length was a decreasing function at the adverse slope while a parabolic function at the down slope; when the laying length of the micro-spraying belt was arranged to L0, the relative pressure P（L0） get the maximum value. Finally, by using the mathematical models of three different laying lengths, the laying length of micro-spray belt was optimized and analyzed, the calculation formula for the laying length of the micro-spraying belt under different laying conditions of down slope, flat slope and adverse slope was established, and the laying length were calculated under the condition of down slope and adverse slope of 0.01,0.03 and 0.05 and flat slope, respectively, in order to provide a theoretical basis for engineering plan and design.

The factors affecting soil evaporation was complex during freeze-thaw period, and estimating the freeze-thaw soil evaporation accurately is significant for the high efficient utilization of soil water resource. Based on the field data during freeze-thaw period of 2017-2018, the solar radiation (x1), average air temperature (x2), surface soil temperature (x3), surface soil water content (x4), wind speed (x5), vapor pressure (x6), relative humidity (x7), precipitation (x8) and water surface evaporation (x9) were selected to establish the freeze-thaw soil evaporation forecast model based on the SVM optimized by PCA and PSO. The results showed that the average relative error and coefficient of determination (R2) of the freeze-thaw soil evaporation forecast model based on PCA-PSO-SVM were 9.870 4% and 0.951 3. So the PCA-PSO-SVM model can be better used for the freeze-soil evaporation forecast.

Based on the daily precipitation data of 84 meteorological stations in Guizhou province from 1961 to 2017, taking the main grain crops in Guizhou province as an example, the temporal and spatial evolution characteristics of precipitation concentration in different growing periods of rice and corn in Guizhou Province were analyzed by means of precipitation concentration index. The results showed that except the jointing- booting stage of rice, the precipitation concentration of rice and maize in each growing period increased in past 57 a. The heading-ripening period of rice and the filling-mature period of maize were the periods when precipitation concentration increased significantly. Except for transplanting-tillering stage and jointing-booting stage of rice, the precipitation concentration of rice and maize in most of Guizhou province was increased. The precipitation concentration of rice and maize at different growth stages varied in different years. The fluctuation frequency of precipitation concentration in rice is higher than that in maize.

Based on the analysis of the connotation and characteristics of the carrying capacity of water resources in the Taihu basin, this paper defined the carrying capacity of water resources in the basin by highlighting the important role of water quality and water ecology in the carrying capacity of water resources in the basin and the characteristics of water circulation and flow in the lake. Based on the four essential factors of water quantity, water quality, water ecology and water flow of water resources, a multi-level, sub-factor and capability-load evaluation index system of water resources carrying capacity was constructed, which was composed of target layer, factor layer, representation layer and index layer. The present situation of water resources carrying capacity of the Taihu basin was evaluated by single factor evaluation and comprehensive index evaluation. The evaluation results showed that the present situation of water resources in the Taihu basin could support the development of population and economy, water quality and water ecology were still serious, and the carrying capacity of population and economy in the basin was weak.

In order to accurately simulate the daily reference crop water demand of apple orchards under water storage pit irrigation according to limited meteorological data, by taking the daily meteorological data of the water storage pit irrigation orchard at the Institute of Shanxi Academy of Agricultural Sciences as input item and the daily reference water requirement as output items, on the basis of RBF neural network, a RBF neural network model based on artificial bee colony algorithm was established to predict the daily reference crop water demand of apple orchard under water storage pit irrigation. The model was validated and determined by the calculation result of the FAO-56 Penman-Monteith（FAO56-PM） formula. The results showed that the simulation results of the RBF neural network prediction model optimized by the artificial bee colony algorithm were closer to the calculation results of the standard method fao56-pm formula, which was more suitable for predicting the day reference crop water requirement of the water storage pit irrigation orchard in this area.

In order to develop and protect soil and water resources in a more reasonable way and improve the output benefit of soil and water resources, the potential of existing water diversion projects was studied and developed from the perspective of “water demand” to supply the downstream agricultural and animal husbandry production. With the aim of maximizing the output benefit, the mathematical model was established, and the optimal solution of the model was obtained by using the dynamic programming method. By optimizing the allocation and planning of the planting structure in the water distribution region, the output value of agricultural and animal husbandry land in the whole research region was greatly improved, so that the output and income of the water distribution region increased significantly after the optimized allocation of water and soil resources.

Based on CROPWAT model, the paper focused on the regional distributive laws of typical crop water requirement (CWR) in China, analyzed main crop production water footprint. The results showed that the annual average water requirements of wheat, maize and cotton in China between 1961 and 2010 were 105.64, 104.52 and 21.77 billion m³ respectively, and the green water utilization proportion of wheat, corn and cotton were higher than that of blue water. The annual average green water requirements of wheat, maize and cotton were 60.85, 75.57 and 14.96 billion m³ respectively. In terms of the spatial distribution of the growing water footprint of these crops in China, it was found that the annual average production water footprint of wheat, maize and cotton were about 1.37, 1.10 and 2.02 m³/kg. The regions with high water footprint for wheat and corn production were mainly distributed in south China and Shaanxi, Gansu, Qinghai and other provinces, with a water footprint of more than 2.0 m³/kg. The regions with high water footprint of cotton production are mainly distributed in western regions such as Beijing, Tianjin and Gansu, mostly above 2.5 m³/kg. The results can provide scientific basis for the establishment of irrigation system and the optimization and adjustment of crop industrial structure in China's main grain producing areas.

Soil organic matter is one of the most important attributes of soil. The study of the correlation between soil organic matter and soil salt parameters can provide theoretical support for the application of soil fertilization, increasing production and income, and effective utilization of resources in the ecological restoration and utilization of saline and alkaline land. In this study, 165 soil samples were collected, and the contents of plasma, soil total salt and soil organic matter in soil samples were tested. The correlation between soil organic matter and soil salt parameters and the effect of kernel function on the prediction model were studied. The results showed that there was a strong correlation between soil salinity parameters and soil organic matter. The improved BPNN-SVR model based on BP neural network and support vector regression (SVR) was used to predict soil organic matter with high reliability. After determining the optimal kernel function parameters, 120 samples data were randomly selected as training set and the remaining 45 samples data were test sets. After normalization, the decision coefficient and mean square error of the improved BPNN-SVR prediction training set were 0.938 and 0.074 2 respectively, which showed that the improved BPNN-SVR had excellent generalization ability and prediction performance, and the determination coefficient of the test set was 0.9415 and the mean square error was 0.106 5. Using the traditional BPNN model to predict soil organic matter as a contrast test, the determination coefficient of the test set was 0.870 3 and the mean square deviation was 0.116 2. The traditional BPNN model was very sensitive to the performance of initial weight and threshold, which was easy to converge locally, and often stagnates in the flat region of the error gradient surface. In addition, the improved BPNN-SVR model had updated the weights and thresholds at any time. Therefore, compared with the traditional BPNN model, the mean square deviation of the improved BPNN-SVR model was reduced by 30.99%, the determination coefficient was increased by 8.18%. Under the condition of the same training set and test set, different kernel functions also had significant influence on the improved BPNN-SVR model. The RBF kernel function was the best, with a determination coefficient of 0.790 8 and an average relative error of 5.98 and a mean square error of 0.074 6. Therefore, the improved BPNN-SVR model based on RBF kernel function could effectively predict soil organic matter content by using soil salt parameters, and had high accuracy and reliability.