State space analysis of soil water and salinity regimes in a loam soil underlain by shallow groundwater

Improved methods of irrigation scheduling are needed to reduce irrigation and drainage water volumes while not affecting yield. State space models based on mass balance principles and empirical flux laws can be used to estimate and forecast soil water and salinity regimes in the field. In this research, a state space model was developed that describes soil water and salinity dynamics and includes the effects of shallow, saline groundwater. The model was evaluated using daily time domain reflectometry (TDR) measurements of the soil water content (theta) and bulk soil electrical conductivity (ECb). Data were collected throughout the 1997 growing season in a field where cotton (Gossypium hirsutum L.) was being grown using an experimental shallow groundwater management technique that was designed to reduce both irrigation and drainage volumes. The model was tested by supposing that either weekly or biweekly profile-averaged measurements of theta and ECb, were available, and then comparing the resulting filtered model forecasts with the full data set. The results show that the measured water content was within the predicted confidence intervals of 1- or 2-wk forecasts of the profile-averaged water content, soil water EC (ECw), and EC of saturated extract (ECe), even though the performance of the model in predicting the resident salt concentration (mass of salt per volume of soil) was less satisfactory.