Analysis of soil Infiltration Estimation Methods in Irrigated lands with Zabol Municipal Treated wastewater

Water quality is one of the most affective factors on soil infiltration. The widespread use of wastewater in recent years caused the accurate estimation of soil infiltration to be essential for achieving proper irrigation management. Therefore, Philip, Kostiakov, Kostiakov-Lewis, Green-Ampt,Horton, SCS and linear regression models for soil infiltration estimation were evaluated. Infiltration experiments were carried out in an area of 190 ha of agricultural lands under wheat cultivation, around the Zabol refinery of municipal waste water for six soil texture classes include silty clay, clay loam, sandy loam, loam, loamy sand, silty clay loam. These lands are irrigated with treated wastewater for over 10 years. The study area was divided into pixels with 150mÍ150m size. The cumulative infiltration was determined using double ring experiment. Some physicochemical soil properties were determined in soil samples taken from the center of each pixel. Despite of significant relation between soil infiltration and EC, sand, clay and silt percentage, exchangeable sodium and bulk density, transfer functions didn’t led to satisfactory results for cumulated infiltration. Kostiakov and Horton models were the best profitable models for silty clay soils. Whereas, the others were the best for cumulative infiltration estimation in silty clay loam soils. Green-Ampt and Kostiakov models were the best fitted on the observed cumulative infiltration data with root mean square, mean bias error and efficient coefficient of 0.16 and 0.15 cm, -0.03 and 0.04 cm, and 0.74 and 0.78 cm, respectively. The considerable reduction in soil infiltration due to over accumulation of salt and sodium in the surface soil layers through long term application of waste water in the study area.