Time Series Analysis of Soil Moisture Content in Loess Deposits of Hezarpich using ARIMA model

Soil moisture content (SMC) as a small part of water balance, nearly considered in all hydrological process and soil and atmosphere tradeoff. Therefor its prediction is useful in planning, designing and decision making. For this, purposeweekly SMC in 40 weeks was measured by Time Domain Reflectometry in 3 different location of wheat and rangeland in Loess deposits (West of Gorgan with 27 ha area) at 20cm intervals down to the 80cm depth. SMC in all considered depths and locations had trend for study period and the best model was selected regards to Akaike information criterion (AIC). The best prediction model in rangeland belongs to 60cm depth (R= 0.96). For all considered depths except 40cm in one location in wheat, Integrated Moving Averages (1,1) was selected as the best model. For the other location in the same land cover, the best prediction model devoted to 20cm depth (R= 0.86). Integrated Moving Averages (1,1) for all study locations had the highest priority. Considering tillage practices in crop land and following plough pan in 40cm depth, Autoregressive Integrated moving Average (1,1) selected as the best model for prediction.