Dynamatic monitoring of zonal soil water-salt environment based on artificial intelligent technique

In order to forecast zonal water environment, the authors used BP neural network model of artificial intelligent technique to monitor two dimensional zonal soil water-salt environment dynamatically, simulated soil water-salt values of two experiment areas in Hetao Irrigation Zone, and obtainedisogram and tri-dimensional maps, analyzed the results of two years. Results show that the average water values among arable layer in the spring of 2002 and 2004 year are both 21% at Longsheng experimental areas, average EC values are 0.35 and 0.42 ms/cm, with a small amount of salt accumulation. The averagewater valuesare 25.8% and 21.8% at Shahaoqu experimental areas, with the decrease of water by 4%, but the salt accumulation is remarkable, it increased from 0.44 to 0.66ms/cm, salt accumulated obviously, this must be emphasized. The BP neural network technique had no requirement of parameter and distribution of raw data, not involving the question of outlier disposal. It can eliminate glabrous effect of ordinary krigingmethod, with strong nonlinear fitting function, and has no strict demands for sampling system, calculative program is easy and practical. Meanwhile it can improve conventional GS such as Kriging, and has special advantages. The BP neural network technique can be used to finish large area soil water-salt environment monitoring dynamatically.