Zuncun Yellow River Irrigation District is the largest irrigation district in Shanxi Province that uses the Yellow River as its water source, and its main irrigation method is channel irrigation. In this study, the reasonable water and fertilizer treatments under the drip irrigation with Yellow River water in Zuncun irrigation area were explored. Five treatments were set up in the experiment, namely, 60%, 80% and 100% of the fertilizer applied by local farmers under the drip irrigation with Yellow River water for treatments T1, T2 and T3, 100% of the fertilizer applied by local farmers under the drip irrigation of groundwater for treatment T4, and the drip irrigation with Yellow River water without fertilizer as CK, to study the effect of different water and fertilizer treatments on the growth and water and fertilizer utilization of winter wheat. The results showed that the plant height, leaf area index, above-ground dry matter mass and yield of winter wheat increased with the increase of fertilizer application under the drip irrigation with Yellow River water, in which the above-ground dry matter mass and yield of a single plant had the same trend, and the fitting relationship between yield and fertilizer application was in accordance with the parabolic curve, and the maximum yield was 8080.06 kg·hm^-2 when the fertilizer application was 232.28 kg·hm^-2; the leaf area index, above-ground dry matter quality and yield index of Yellow River water drip irrigation treatment were better than those of groundwater drip irrigation treatment under the same fertilizer application rate. In terms of water and fertilizer use, soil nitrogen residue, water consumption and water use efficiency increased with the increase of fertilizer application under drip irrigation with Yellow River water; under the same fertilizer application, soil nitrogen residue and water consumption of Yellow River water drip irrigation treatment were lower than those of groundwater drip irrigation treatment, and water use efficiency and nitrogen fertilizer bias productivity were higher than those of groundwater drip irrigation treatment. Considering together, the yield, water use efficiency and nitrogen fertilizer bias productivity of T2 treatment were increased by 0.62%, 5.88% and 25.79%, respectively, compared with T4 treatment; the water use efficiency of both T2 and T3 treatments was 1.98 kg·m^-3, but the nitrogen fertilizer bias productivity of T2 was increased by 21.54% compared with T3 treatment with a slight decrease in yield, and the residual amount of soil nitrogen was reduced by 32.73% compared to T3 treatment, so the best fertilizer application rate for drip irrigated winter wheat with Yellow River water in this area was 204 kg·hm^-2 to 232.28 kg·hm^-2 when combined with the yield fitting relationship.

The scale effect refers to the phenomenon that the data obtained from the remote sensing inversion of each scale are not consistent with the change of remote sensing resolution in the UAV remote sensing observation, which affects the accuracy of soil moisture monitoring by multispectral remote sensing. In order to investigate the influence of scale effect on soil moisture monitoring by UAV remote sensing, winter wheat was taken as the research object, and multispectral images were taken at different heights of 19 m, 37 m, 55 m, 74 m and 92 m (corresponding to resolutions of 10 mm, 20 mm, 30 mm, 40 mm and 50 mm) by UAV with multispectral cameras, and soil moisture content data were also collected. The multispectral images were masked by using ENVI 5.3 (64 bit), including no mask (NM), soil background removal by masking (SRM), soil and shadow background removal by masking (SSRM), and soil and shadow background removal by masking (SSRM), to obtain the texture features of winter wheat at each height. After optimizing the data by using Grey Relational Analysis (GCA), the three methods of multiple linear regression (MLR), Back PropagationNeural Network (BPNN) and random forest (RF) were used to invert the data. The results of the study showed that among the various mask treatments adopted in this paper, the unmasked method had the best inversion results. The best performing inversion model among the mask treatments is the BPNN model, which performs consistently well in most cases, demonstrating the feasibility of machine learning applications in remote sensing monitoring. The best inversion model was the 30 mm-NM-RF model for winter wheat soil moisture content. At a resolution of 40 mm, i.e. a UAV flight altitude of 74 m, the inversion of different models was the best, and the research results can be applied to determine the flight altitude for future UAV monitoring of soil moisture.

Winter wheat-summer maize rotation system is commonly used in southern Shanxi.In order to evaluate the reliability of dual-crop coefficient approach in winter wheat-summer maize rotation system, and to master the water consumption law of rotation system, in this paper, the evapotranspiration of the winter wheat-summer maize rotation system from 2016 to 2019 was simulated by the dual-crop coefficient approach. The simulated results were evaluated based on the calculation results of water balance method, and plant transpiration (T) and soil evaporation (E) were distinguished. The results showed that in the winter wheat-summer maize rotation system, the average basic crop coefficient (K_cb ) of winter wheat was 0.2, 0.59, 0.98 and 0.15 for the early, developing, middle and late stages, respectively, and that of summer maize was 0.14, 0.69, 1.24 and 0.56; The average soil evaporation coefficient (K_e ) of winter wheat was 1.24, 0.63, 0.07 and 0.42, and that of summer maize was 0.78, 0.45, 0.06, 0.46, respectively. During the whole growth period, ET_c of winter wheat was 264.18~526.22 mm, and that of summer maize was 261.76~519.67 mm; The development period was the peak of water consumption, and the proportion of evapotranspiration in the development period of winter wheat and summer maize was 31.2%~51.3% and 34.3%~58.2%, respectively; With the decrease of irrigation times, the plant evapotranspiration and plant transpiration of winter and summer maize decreased gradually, and soil evaporation reached the lowest when irrigation was the least, the E/ET_{c of the whole growth period was 27.3%~46.4% for winter wheat and 29.3%~44.2% for summer maize. At the early stage of winter wheat and summer maize growth, more than 80% of soil water was consumed by evaporation, and the proportion of soil evaporation was the lowest in the middle stage, which was 6.1%~13.4% for winter wheat and 4%~7.6% for summer maize. The simulated evapotranspiration (ETc- FAO) values of wheat and summer maize showed a good correlation with the measured values (ETc ), R ² was 0.8~0.86, RMSE was 0.5~0.6 mm/d, MAE was 0.4~0.49 mm/d. It can be seen that the dual-crop coefficient approach has high accuracy in simulating ETc of winter wheat-summer maize rotation system in southern Shanxi, which can provide a theoretical basis for accurately grasping the water consumption law of winter wheat-summer maize rotation system, and then making a reasonable irrigation plan.}

In order to reduce the effects of high light and temperature stress on the growth, physiology and yield of grapes, a combination measure of shade and micro-spray of canopy was used to design nine experimental treatments and a control treatment without shade and micro-spray of canopy in three gradients (shade gradients of 0%, 15% and 30%; micro-spray gradients of 20 L/h, 30 L/h and 40 L/h), and the duration of each micro-spray was 1 h for each treatment. The results showed that the canopy air temperature decreased with the increase of shade and micro-spray of canopy, and the air humidity increased with the increase of shade and micro-spray, and the WP2 treatment had the highest decrease of air temperature (31.57°C) and the highest increase of air humidity (70.78%) among the treatments. The amount of micro-spray had no effect on the relative chlorophyll content (SPAD) of leaves, and shade could enhance the value of leaf SPAD, among which 15% shade had the most obvious effect on leaf SPAD enhancement; the amount of micro-spray water had an inhibitory effect on leaf minimum fluorescence (Fo) and an enhancing effect on leaf maximum fluorescence (Fm), fluorescence quantum yield (Yeild), maximum light energy utilization efficiency (Fv/Fm) and PSII potential photochemical activity (Fv/Fo). The amount of water sprayed by micro-spray had an effect on branch growth, fruit volume, 100 grain weight, and expected yield of fruit spikes. The physiological growth and yield indexes were better in 15% shade compared to 30% shade and no shade measures. Among all treatments, WP1 treatment had better indexes than other treatments.

Irrigation return flow widely exists in the world and it has a large quantity, but there are relatively few researches on irrigation return flow, and the research in many aspects is not deep enough. This article identified the composition of irrigation return flow, analyzed the formation conditions of irrigation return flow, showed the mechanism of irrigation return flow, summarized the research progress of calculation method of irrigation return flow, discussed the research status and existing problems of irrigation return flow, and looked forward to the future development direction of irrigation return flow and its calculation method.

In order to reveal the water infiltration characteristics and water migration regularities of different epochs loess in loess tableland area, the infiltration and soil moisture migration characteristics of different epochs loess were analyzed through the layered vertical one-dimensional ponding infiltration test and the soil moisture migration test of loess (Q₄, Q₃, Q₂) under the conditions of natural rainfall and 800 mm surface infiltration pool in loess tableland area, and three kind of infiltration models were used to fit the infiltration process. The results showed that the infiltration capacity of Q₂ loess was the weakest, with a stable infiltration rate of 0.53 mm per minute, 44.2% and 45.4% lower than that of Q₄ and Q₃ loess respectively; the infiltration process of Q₄ loess was well fitted to Kostiakov infiltration model, and that of Q₃ and Q₂ loess were well fitted to Horton infiltration model. The maximum influence depth of natural rainfall and evaporation on soil moisture was about 1.0 m. The soil wetting front in the center of the infiltration pool moved from 2.65 m to 4.20 m from the 4th to the 83rd day after surface irrigation, and the depth of wetting front changed as a power function with time in the center of the infiltration pool.

Soil moisture is an important factor affecting vegetation growth and an important parameter for water and heat exchange between the earth surface and the atmosphere. The multi-source remote sensing data used in this study was acquired from Sentinel-1 radar and Sentinel-2 optical satellites. The test results showed that when the hidden layer reached 6 layers， the number of nodes reached 80， and the number of iterations was 450， the optimal soil moisture inversion model was obtained. The measured data were used to verify the inversion results of the model， and the correlation coefficient R ² was 0.925 2 and MSE was 0.000 8. It provides a reference for retrieving soil moisture of farmland surface from multi-source remote sensing data.

In order to reveal the effect of soil inhomogeneity coefficient on the transformation between shallow phreatic water and soil water during the freeze-thaw process, the experiments with constant freezing temperature at -10, -20 and -25 ℃ successively for 62 days and natural thawing for 10 days were carried out in the laboratory. The variation characteristics of phreatic water evaporation and phreatic water recharge of five soil columns with inhomogeneity coefficients ( C_u) of 2.00 (A), 3.70 (B), 6.36 (C), 16.18 (D) and 20.67 (E) with groundwater table depth of 0.5 m were analyzed. The results showed that in the process of freezing and thawing, the greater the inhomogeneity coefficient of soil particles, the greater the variation in temperature on the soil profile. With the increase of soil depth, the temperature difference between soil column A and soil column E at the end of freezing decreased, and the influence of inhomogeneity coefficient on soil profile temperature decreased. When frozen for 0~3 d, the phreatic water evaporation rates of soil columns A, B, C, D and E were 0.11, 0.15, 0.23, 0.27 and 0.39 mm/d, respectively. The phreatic water evaporation rate was relatively small, but the greater the inhomogeneity coefficient, the greater the phreatic water evaporation rate. At the end of freezing (freezing time is 62 d), the cumulative phreatic evaporation of soil column A, B, C, D and E were 15.17, 21.46, 28.23, 34.96 and 38.65 mm, respectively. The relationship between cumulative phreatic evaporation and soil inhomogeneity coefficient was in good agreement with the logarithmic function, and the transformation of phreatic water and soil water increased with the increase of soil particle inhomogeneity coefficient.

In order to find out the most suitable technical parameters of moistube irrigation green pepper, the entropy—TOPSIS—grey correlation model was used to evaluate the growth and development of green pepper. The growth test of moistube irrigated green pepper was carried out under the conditions of buried depth of 10 cm ( D10 ), 15 cm ( D15 ), 20 cm ( D20 ) and pressure head of 100 cm ( H100 ), 150 cm ( H150 ) and 200 cm ( H200 ). The results showed that the single indexes of green pepper treated with different pipe belt depths were D20 > D15 > D10. The plant height, stem diameter and yield after different pressure head treatments were H150 > H200 > H100, the plant height growth rate and stem diameter growth rate were H200 > H150 > H100, and the irrigation water productivity was H100 > H150 > H200. The selected indicators are different, and the optimal moistube irrigation technical parameters are also different. The entropy—TOPSIS—grey correlation model was used to analyze the effect of moistube irrigation on the growth of green pepper. When the pressure head is constant, the comprehensive closeness increases with the increase of the buried depth of the pipe belt. When the buried depth of the pipe is constant, the comprehensive closeness will increase first and then decrease with the increase of the pressure head. The most suitable technical parameters for moistube irrigation of green pepper are as follow: the pressure head is 150 cm, and the buried depth of the pipe belt is 20 cm.

Accurate solar radiation (R_S ) data are crucial for research fields and business departments such as agriculture, hydrology, meteorology, ecology, and energy in environmental evaluation. Based on the radiation data of 96 stations in China from 1967 to 2016, the accuracy of 32 (S1 ~ S32) solar radiation models was evaluated based on sunshine hours, the best general model was constructed, and its impact on calculating reference crop evapotranspiration (ET ₀) was analyzed. The results showed that the S18 ~ S32 models performed better. The average values of regression coefficient (b), determination coefficient (R² ), root mean square error (RMSE), relative root mean square error (RRMSE) and model efficiency (EF) of single site model were 0.975 ~ 0.976, 0.882 ~ 0.886, 2.368 ~ 2.412 MJ/（m²·d）, 0.171 ~ 0.175 and 0.881 ~ 0.885 for S18~ S32 models, respectively. The results of evaluating the general models for S18~S32 showed that the S18 model had higher accuracy and better model stability with only three input parameters, and the mean values of b R², RMSE, RRMSE and EF were 0.974, 0.881, 2.626 MJ/（m²·d）, 0.184 and 0.881 for S18 model. The S18 model was recommended to be a general estimation formula of daily R_S in China with or without R_S observation area. Compared with the method recommended by FAO 56, the ET ₀ results calculated based on the general S18 model reduce the mean values of RMSE and RRMSE by 12.9% and 13.9%, respectively.