A field study was conducted on 2 hectare area at Al- Rashid district, south of Baghdad to analyze the spatial variability of saturated hydraulic conductivity (Ks), initial infiltration rate (IR), Porosity (F) and bulk density (BD). Based on measured BD values Rosetta software was used in this study to estimate water retention parameters, water content at θ33 and θ1500 kPa and unsaturated hydraulic conductivity at 33 kPa(k33), 100 kPa(k100) and  1500 kPa(k1500) according to Van Genuchten-Mualem model.  Measured and predicted data were analyzed both statistically and geostatistically and, the results showed a strong to moderate spatial dependence for the studied characteristics. The spatial correlation values (r2) were obtained with a spherical model for Ks, θ33, θ1500, k33, k100   and k1500, an exponential model for IR, and a Gaussian model for F and BD. Ks increased significantly with increasing of IR (r2 = 0.49**) and decreased with increasing of F and BD, IR increased with decreasing of BD (r2 = -0.326*) and BD increased with increasing of F (r2 = 0.989 **). In general the spatial distribution was moderately skewed (-0.5 to 0.5) for the studied characteristics with pronounced kurtosis (>2.5). The limit distance for the search radius to estimating spatial dependency varied from 29.9 m for BD to 105 m for IR.

The purpose of this study was to develop the best transfer functions for estimating the soil water retention curve (SWRC) for Iraqi soils using multiple regression methods. Soil samples were collected from 30 different sites in Iraq at two depths (0-0.3 m and 0.3-0.6 m) to create a database for the development of predictive transfer functions. The database included information on soil particle size distribution, carbonate minerals, mass density, particle density, organic matter, saturated hydraulic conductivity, capillary height, and available water limits. Explanatory variables (EV) were the measured characteristics, while response variables (RV) were the volumetric water content measured at different potentials (0, 5, 10, 33, 500, 1000, 1500 kPa). Two methods were used to develop predictive transfer functions: the logit model and beta model. Prediction accuracy was assessed using mean bias error (MBE), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The results showed that the variables included in the derivation of the two models for predicting θ(Ψ) were similar, except at θ(0). The variables w1 (w1 = 2P sand° − P silt° − P caly° − P carbonate ), capillary height, available water, and porosity were found to be included in most of the logit and beta models. Additionally, there were no statistically significant differences between the MAE, RMSE, and R2 values of the two models. However, the beta model performed better in terms of MBE compared to the logit model. The models also demonstrated highly significant R 2 values (0.9819-1.00) for a linear relationship between the measured and predicted water content values.

cum ETwere algorithmed in this study. Irrigation water was applied to three different depths 30, 30-60 and 60 cm at three different depletion rates 50, 70 and 90% from plant available water. Wheat ET ranged from 428.49 to 522.12 mm. Contributions to ET from applied irrigation water ranged from 334.20 to 496.50 mm and increased with increasing irrigation depth. Contributions to ET from upward flux capillarity ranged from 25.61 to 96.59 mm and decreased with increasing irrigation depth. Contributions to ET from applied irrigation water decreased with increasing depletion rate whilst contributions to ET from upward flux capillarity increased with increasing depletion rates. Daily rate contribution to evapotranspiration from irrigation water ranged from 2.15 to 3.20 mm.d-1 and from capillary flux ranged from 0.16 to 0.61 mm.d-1.