A new model describing the relation between bulk soil electrical conductivity (ECa), volumetric content (θw) and electrical conductivity of soil water (ECw) is given along with supporting evidence for its validity. The new model distinguishes between the water and salt present in the soil in the “immobile” (fine pores) and “mobile” (large pores) phases. It provides a possible physical meaning to the transmission coefficient (T) previously used in an earlier model and eliminates a limitation of that model which existed under conditions of low salinity. New empirical relations are provided to estimate the parameters needed in the new and old models in order to utilize them for diagnosing soil salinity, in terms of the electrical conductivity of the extract of saturated soil pastes (ECe).

Realizing the full potential of drip irrigation technology requires optimizing the operational parameters that are available to irrigators, such as the frequency, rate, and duration of water application and the placement of drip tubing. Numerical simulation is a fast and inexpensive approach to studying optimal management practices. Unfortunately, little work has been done to investigate the accuracy of numerical simulations, leading some to question the usefulness of simulation as a research and design tool. In this study, we compare HYDRUS-2D simulations of drip irrigation with experimental data. A Hanford sandy loam soil was irrigated using thin-walled drip tubing installed at a depth of 6 cm. Three trials ͑20, 40, and 60 L•m Ϫ1 applied water͒ were carried out. At the end of each irrigation and approximately 24 h later, the water content distribution in the soil was determined by gravimetric sampling. The HYDRUS-2D predictions of the water content distribution are found to be in very good agreement with the data. The results support the use of HYDRUS-2D as a tool for investigating and designing drip irrigation management practices.

The Arya-Paris model is an indirect method to estimate the soil water characteristic from particle-size data. The scaling parameter, a, in the original model was assumed constant for all soil textures. In this study, a is defined as a, = (logJV//log«,-), where n, is the number of spherical particles in the ith particle-size fraction (determined by the fraction solid mass, w h and mean particle radius, R,) and /V/ is the number of spherical particles of radius R, required to trace the pore length generated by the same solid mass in a natural structure soil matrix. An estimate for log A',-was obtained by either relating log A', to log n, using a logistic growth equation or by relating log A', linearly to log (w,IR}) based on the similarity principle. For any given texture, both approaches showed that a was not constant but decreased with increasing particle size, especially for the coarse fractions. In addition, a was also calculated as a single-value average for a given textural class. The three formulations of a were evaluated on 23 soils that represented a range in particle-size distribution, bulk density, and organic matter content. The average a consistently predicted higher pressure heads in the wet range and lower pressure heads in the dry range. The formulation based on the similarity principle resulted in bias similar to that of the constant a approach, whereas no bias was observed for the logistic growth equation. The logistic growth equation implicitly accounted for bias in experimental procedures, because it was fitted to log N, values computed from experimental soil water characteristic data. The formulation based on the similarity principle is independent of bias that might be inherent in experimental data.

No abstract

No abstract