Abstract

The saturated soil hydraulic conductivity (Ksat) is one of the most relevant variables in studies of water and solute movement in the soil. Its determination in the laboratory and in the field yields high dispersion results, which could be an indication that this variable has a no symmetrical distribution. Adjustment of the normal, lognormal, gamma and beta distributions were examined in order to search for a probability were density function that would more adequately describe the distribution of this variable. The experiment consisted in determining the saturated hydraulic conductivity, through the constant head permeameter method, in undisturbed samples of three soils of different textures from the central western region of the São Paulo State, Brazil, and submitting the results to the statistical tests for identification of the most adequate asymmetrical distribution to represent them. Ksat presented high variability, non normal distribution and lognormal, gamma and beta distributions fit. The lognormal probability density function was the most indicated to describe the variable, due to the verified greater agreement.

Highlights

  • The lack, or inadequacy of information on variables related to water and solute flow in soils makes the rational use of agricultural resources a difficult endeavor

  • It is possible to determine the soil hydraulic conductivity based on the saturated hydraulic conductivity (Ksat) and by using mathematical models, being able to follow water and solute movement

  • The objective of this study is to present an analysis on the characterization of the soil saturated hydraulic conductivity, based on data adjustments to fit to the gaussian, lognormal, gamma and beta density probability functions, in order to indicate the best to represent this variable measured in a given area

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Summary

Introduction

The lack, or inadequacy of information on variables related to water and solute flow in soils makes the rational use of agricultural resources a difficult endeavor. Among the variables that interfere with this flow, a very prominent one is the hydraulic conductivity (K), which represents the facility of the soil in transmitting water. The greater the hydraulic conductivity, the easier for the water to move from one site to another. Population probability curves that describe a phenomenon are unknown and they must be estimated through a sample frequency curve (Assis et al, 1996). This process will always contain errors and, the problem consists in finding a probability function that minimizes this estimation error. When frequency distributions are analyzed, quantitative results can be obtained more safely (Biggar & Nielsen, 1976)

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