Modeling Soil Water Movement under Low Head Ponding and Gravity Infiltration Using Data Determined with Different Methods

Abstract

The aim of this work is to analyze differences in experimental and calculated model study of the processes of movement of soil water under low head ponding and gravity infiltration. In the forecast of the water regime two kinds of hydrological information were used – experimental and pedotransfer functions (PTFs). The experimental information: the hydraulic conductivities (HC) in saturated conditions were determined in the field conditions, unsaturated conductivity function was calculated (van Genuchten-Mualem model) using HC and water retention curves (WRC), WRC were investigated in laboratory condition with the help of capillarimeters, sand-kaolin boxes and by the centrifuge method. PTFs included: regional PTF, based on the data of the original database for the soil hydrological properties of the study area relying on the soil density and soil organic content, PTF based on particle size distribution, based on field capacity and wilting point as a predictors, and PTFs based on physico-mechanical properties, specifically Atterberg limits. The spatial distribution of moisture indicates that after infiltration under low head ponding, the soil water content variation is rather high (at depths of 50 and 60cm the quartiles were about 2-3 and 6-12%), but in the case of gravity infiltration the quartiles were about 2 and 5%. This points to the presence of preferential flows. The best forecast of the real-mode soil water regime gave experimental hydrological information: no systematic errors in the high min-max range of modeling errors. Among PTFs the modeling results were placed in the following order: regional PTFs work better (>) than PTFs based on the field capacity and wilting point >PTFs based on Atterberg limits> PTF based on particle size distribution. The statistical analysis of the modeling errors by Williams-Klute nonparametric statistical criteria is evidence that models describe best gravity filtration.