Soil moisture content refers to the content of water in the soil and the degree of utilization of the crop, and can be described by a series of indicators such as soil moisture content, relative soil moisture, total soil moisture storage, and effective soil moisture.

Soil moisture monitoring is the basic work for the study of the law of water circulation, irrigation for agriculture and animal husbandry, rational use of water resources, and basic information collection for drought relief. For a long time, soil moisture information has become the most important element of soil moisture content monitoring stations. As a result, soil water content information is in short supply. At present, the city's soil moisture data are exclusively owned by the meteorological department, and the moisture content, drought conditions, and development trends are the same as the meteorological conditions. Soil, soil moisture status, crop species and their growth and development are closely related, so it can be considered that the meteorological conditions, soil physical properties, soil moisture status, crop species and growth and development status are the four major factors in the monitoring of drought and drought conditions.

Foreign research

The research on soil moisture forecast in foreign countries was relatively early. In the 1970s, some scholars began to study the soil moisture forecast. Through the measured data of wheat, the empirical model of soil moisture prediction was obtained. The development of soil moisture forecast in the late 1980s was more rapid. Based on the study of crown temperature, Jackson et al. proposed the concept of Crop Water Stress Index (CWSI), which is the canopy temperature measured by an infrared thermometer. It can be used to estimate dry and wet temperatures and net radiation in the energy balance equation. Calculate CWSI. According to the heat balance equation, the concept of crop water deficit index was put forward, and it was proved that there was a good correlation between water deficit index and soil moisture content. Others have established prediction models for soil moisture at different depths.

After the 1990s, the soil moisture forecast research has been further developed, and a detailed comparative study has been conducted on soil moisture measurements and the use of various measurement tools. Mahmood and Hubbard established a soil moisture forecasting model based on the principle of water balance. Mahmood used this model to predict the soil moisture content of three different land uses and achieved good results. Tamir Kamai et al. made a new improvement to the measurement of soil moisture by a thermal pulse detector. A 6 mm radius heating ring and a thermistor were placed on a 6 mm thick, 16 mm diameter plastic disc in place of the original probe. This button-type thermal pulse detector measures soil moisture and performs data analysis. The improved instrument is more sensitive to soil moisture. Moisture Reflectors In adverse climates, such as lightning, measurement results can be affected. In response to this phenomenon, John et al. established a conceptual model to modify the data under the influence of lightning. Martinez et al. performed a four-week survey of the temporal and spatial distribution of soil moisture in the surface layer (0-50mm) and the root layer (0-300mm) of the catchment. The data from the limited observation points can provide accurate estimates of the temporal and spatial distribution of surface moisture in the surface layer and the root layer, and also have a certain role in revealing the moisture content of deep soil.

Domestic research

In the early stage of the understanding of soil moisture, the monitoring of soil moisture content often only monitored soil moisture content, neglected the collection of crop information and other important information, resulting in a large number of soil moisture monitoring stations and irrigation test stations basically remained only Provide relevant departments with real-time monitoring of raw data such as precipitation and soil moisture content.

In the initial monitoring study, most of the focus was on the monitoring of soil moisture. Based on the assumption that the rate of change of soil moisture is directly proportional to the water storage capacity, the exponential regression of soil moisture is obtained. On this basis, an empirical recursive model for forecasting soil moisture in winter wheat growth period was established, and the model was tested at the Yongledian Experimental Station of the Beijing Institute of Water Resources, which showed that the model had a good forecast effect.

The model is characterized by simple model and few parameters. The main characteristic of the model is that the regression coefficient of soil moisture in the model has strong regional and temporal characteristics. At the same time, in the same area, they used the soil moisture test data of winter wheat after the greening of the test station to establish a BP and network model of soil moisture forecast. The model also considered the influence of multiple factors on soil water storage. Using some measured data to train the network, and then predicting soil water storage under different irrigation treatments in 2a, and achieved good results. Jiang Honggen et al. used the plain hydrology model to refer to the characteristics of evapotranspiration at different growing stages of crops, and the relationship between soil structure and soil water storage capacity and soil moisture content, and constructed a regional soil moisture model.

The model was tested using measured soil moisture data from Hongdong County, Shanxi Province. The results showed that the physical concept of the model was clear, and the soil moisture content could be continuously simulated or forecasted, and the forecast accuracy was high. Li Fanghua et al. adopted the /3S0 technology, computer technology and communication technology integration, with the monitoring of remote sensing model and soil moisture retreat 30% evapotranspiration model as the core, comprehensive use of polar orbit meteorological satellites remote sensing data sources and multi-point ground monitoring moisture, meteorological observations Data, developed the Heilongjiang Provincial Public Information Management System.

At present, the measurement of soil moisture mainly starts from three aspects. One is the actual measurement of the ground; the second is the estimation through remote sensing; and the third is the estimation of the simulation model. The factors affecting the changes in soil moisture are very complicated, and existing technical means have some defects. The known models have the disadvantages of narrow application scope, poor practicality, and complicated operation. At the same time, high-precision measuring instruments are expensive, low-cost instruments have inaccurate measurement data, take a long time, and are complicated to operate. Therefore, whether it is a public opinion forecasting model or a low-cost, accurate and rapid method for measuring soil moisture, there is a wide research space; the water-saving irrigation instruction obtained by combining the soil moisture model with the measured humidity value of the instrument is a subject with a wide range of application prospects. . The research and development of the Soil Moisture Meter solves the above difficulties. The price is reasonable and the functions are complete. The instrument not only records the soil moisture, but also records the change of rainfall, and can see the curve of soil moisture as the rainfall increases or decreases. At the same time, it has been praised by professionals.

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