Study on the Dynamic Low Limit of Irrigation for Winter Wheat

International audienceThe concept of dynamic irrigation low limit (DILL) was proposed and the determination method of DILL was given based on crop-water model. The parameters of the crop-water model were calibrated with winter wheat experimental data of 2008 and 2009. The optimal irrigation scheduling of five typical years under different irrigation water supply were determined, which resulted in 58 groups of data on the average soil moisture content of main root zone (0–60 cm) before an irrigation, the corresponding irrigation time, and water supply. The results showed that, the crop yield under the irrigation times of 3 and 2 increased by 7.42% and 5.62% averaged from 2009 to 2013, and the economic benefit increased by 7.64% and 7.24% than those under the empirical irrigation practices, respectively. The irrigation forecast based on DILL provides an important method to implement and dynamically correct optimal irrigation scheduling under limited water supply

Research on Irrigation System of Limited Water Supply for Soybean Crops in Shanxi Province

International audienceThe limited water supply irrigation system for soybean crops in Shanxi Province was studied. The irrigation data of Limin experimental station in Linfen City, Shanxi Province had been selected. Frequency calculation of rainfall data of Limin was made, choosing 2010, 1993 and 1997 respectively as the sample year of plain water year (50%), water year dry year (75%) and special drought year (95%) of Limin. The Jensen model as the basis for calculation was selected, calculating the actual yield value of crop according to the actual crop water requirement, crop maximum water demand, sensitive index value and maximum crop yield at each stage. Through the selection of the number of days of irrigation, the optimization model of irrigation times was established. The limiting condition is the maximum actual yield. The quota irrigation system of soybean crops in different hydrological years was determined. According to calculation results, each target year was three times, with the highest amount of water

Monitoring of soil moisture and irrigation forecast under the condition of drip irrigation in greenhouse

The accurate prediction of the soil moisture in greenhouse can improve the accuracy of irrigation forecast, thus saving water and increasing production. In this paper, the monitoring data were obtained from the greenhouse in Agricultural Demonstration Park of Northland Spring, Wuqing District, Tianjin. The soil moisture was predicted based on the GM (1,1) model, and the effect of water-saving and increased production was tested with the results of the economic irrigation research in the same area. The results show that the GM (1,1) model has a higher accuracy of soil moisture prediction. The correlation coefficient (R2) of the predicted value and the measured value is higher than 0.9; the small error probability P is 1; the mean relative prediction errors are all less than 0.1. Therefore, the GM (1,1) model can be used to predict soil moisture content

Research on Economic Irrigation Scheduling of Crops for Drip Irrigation in Greenhouse

Aiming at the problem of water waste in the traditional greenhouse vegetable irrigation, economic irrigation schedule of three kinds of vegetables (tomato, cucumber and eggplant) were studied. The experiment was carried out in the North Country Spring Agricultural Demonstration Park in Wuqing District, Tianjin, from April 2018 to December 2018. Three vegetables were tested in 100% (no drought) and 50% (drought) irrigation. The water balance method was used to simulate the change of soil moisture content under greenhouse drip irrigation. The crop coefficient parameters, the temperature stress index, water stress index and dry matter conversion factor were determined using the measured data. The results show that the parameters have good applicability and can be used to describe the effects of water and temperature stress on crop growth and yield. Based on the objective of maximum economic benefit per unit area, the economic irrigation schedule of crops was determined. The analysis showed that the use of the economic irrigation schedule can save the irrigation water and increase production

Spatial Variability Analysis of Farmland Soil Infiltration Based on Model Parameters

Research on the variation of soil infiltration is helpful to analyze the mechanism of soil water movement in farmland. At the same time, soil infiltration characteristics affect the surface irrigation. Based on the field test data, this study simulated and analyzed the soil infiltration with three soil infiltration models (Kostiakov-Lewis model, Philip model and Horton model). The infiltration uncertainty of farmland soil are investigated, and proposed by using two random simulation methods (direct method and parameter mean method) of infiltration. The evaluated indicators are the interval size and its stability of cumulative infiltration amount changed with 95% confidence. The effects of different random simulations methods and three models on the infiltration process are compared and analyzed. Finally, the model and stochastic simulation method suitable for the infiltration characteristics of the farmland are determined. The results show that the correlation coefficients of the three models are all above 0.98, and there is no significant difference in fitting accuracy. In terms of the degree of spatial uncertainty (determined by standard deviation): direct method > parameter mean method, in which the combination of the Kostiakov-Lewis model and the parameter mean method have less uncertainty, and the combined simulation effect is better, it is more suitable for the simulation of soil infiltration at farmland scale

The determination of reasonable number of soil infiltration test in farmland

At the experimental base of Tianjin Agricultural University, the infiltration process of water was measured by double - ring infiltration instrument at six points. Horton，Philip and Kostiakov-lewis (K-l) infiltration models were fitted with the infiltration data measured and the parameters were correspondingly obtained. Six sets of parameters of the corresponding infiltration model were obtained, and six sets of parameters were used for statistical analysis. The reasonable number of points of the corresponding model was obtained. Then, the statistical analysis of the cumulative infiltration amount was used to obtain the variation of the number of reasonable points in the three models with time. The results show that the imitative effect of accumulative infiltration water and time in K-l model is the best, and the curve of reasonable test points determined by K-l model with time is located under the other two models; The reasonable number of points determined by the parameter K in the K-l model is the least and most reasonable. In view of this, the number of reasonable points was determined by using the parameter K in the K-l model

Calculation of Effective Rainfall in the Spring Maize Growing Period

International audienceEffective rainfall accurate determination can promote the technology development of planning crop irrigation, irrigation water management, irrigation and drainage design and highly efficient use of water resources. However, the effective rainfall will be affected by many factors, such as the characteristics of rainfall, characteristic of the crop’s type and crop water consumption, soil characteristics and the way farming farmland management. In addition, geographical location, climatic conditions and other factors will also affect the calculation of effective rainfall. Thus, a reasonable calculation method of effective rainfall should be determined based on the specific conditions of the region. In this paper, based on the meteorological data of Changzhi in Shanxi, the effective rainfall in the spring maize growing period was calculated by the method of water balance, under different hydrological conditions and different irrigation. And then this paper applied this method to analyze the effective rainfall of spring maize and simulate daily soil water content. The results show that: with the increase of rainfall, effective rainfall decreases. With the increase of irrigation amount, effective rainfall gradually reduced. With the increase of crop water requirements, effective rainfall gradually increased. Therefore, this paper analyzes the relationship between effective rainfall and rainfall, irrigation and crop water requirement. The correlation coefficient is 0.802. It is closely related. The simulated and measured values of the growing period of spring maize daily soil moisture better fit, weather in the irrigation or non-irrigation conditions. This verified the calculation method of the effective rainfall