Abstract:

Soil water content is an important factor affecting crop growth, and the accurate prediction of water resources is an important guiding on their reasonable utilization and management. An artificial neural network model was established, with rainfall, evaporation, relative humidity and groundwater table as the input factors, and soil moisture as the output factors and its prediction accuracy was evaluated in this paper. The results showed that the maximum error of predicting soil moisture for BP neural network model was 8.66%, average error was 4.27%, and prediction accuracy of 0.989. BP neural network model had higher prediction accuracy for the prediction of soil moisture. The results can be used for the allocation of irrigation water resources.