Study On The Model Of Soil Moisture Forecast System In Farmland

Soil moisture is mainly used to reflect two aspects of water content: the first is the soil moisture content of the farming layer;the two is the amount of soil moisture absorbed by crops.Soil moisture has a direct impact on the root growth of crops,and is an important factor.However,from the current situation,most of the soil moisture detection and prediction methods are time-consuming and time-consuming,and the time limitation is poor,it is difficult to reflect the soil moisture changes in time.With the rapid development of Internet and information technology,if more information technology is used in soil moisture forecast,it can effectively improve the efficiency of soil moisture data processing,and finally strengthen the efficiency of agricultural water use in China,and become an important decision basis for the drought resistant department.So this study takes the construction of the prediction model of farmland soil moisture as the object,and makes in-depth research on the following contents.(1)data collection of soil moisture is the first step,so first of all,the design of soil moisture data acquisition related mobile terminal is designed.This design is ASW-4mobile terminal.This type of mobile terminal can quickly measure the water content in soil samples,and these data can also be sent back to the data using GPRS.The heart also has the function of GPS,which can locate the relevant information of the coordinates of the sampling points.ASW-4 mobile terminal is relatively low in cost,and is very simple in operation.It is generally not restricted by geographical location,and has high flexibility.In the case of a fixed monitoring station,it can be able to achieve uniform and comprehensive coverage in the area.(2)the design and development of farmland soil moisture information system is based on GIS technology.The system can receive the data transmitted by the ASW-4 mobile terminal,while the extended interface is reserved,and the data of the fixed monitoring station can be received accordingly.In function,not only data acquisition,but also data management,data storage,data display and data transmission functions,the change in soil water content of sampling points can be monitored and predicted in real time,and displayed in a graphic way.The system combines soil moisture and crop growth period,and can make a more accurate analysis of soil moisture,and then master the overall trend of soil moisture in the monitoring area.(3)the data collection point of BP neural network learning samples for this study isthe fixed soil moisture monitoring station of Yuan Wu Town,Yuanyang County of Xinxiang City,and the soil moisture forecast system model is constructed by BP neural network technology.Through the related analysis,the input variables of the forecast model are three layers of soil sample water content,precipitation in the study area,average temperature,air humidity and sunshine time,while the output variable is the water content of the second layers of soil samples in the next day,and the construction of soil soil moisture forecast model is realized through the process.The BP neural network is optimized by genetic algorithm.The purpose is to improve the accuracy of information prediction for the prediction model.The research results have been popularized in Weibin,Makino,Huojia,Yuanyang County and Yanjin County in Xinxiang.According to the practical application,the system can run steadily,improve the efficiency of monitoring and forecast,and ensure the local agricultural production.