Geostatistical modeling of surface water balance (SWB) under variable soil moisture conditions in the Pao river basin, Venezuela

Abstract

The aim of this paper is to develop a geostatistical model for the surface water balance (SWB) under variable soil moisture conditions of the Pao river basin, Venezuela. The novelty of the research consists in identifying a statistical model that will predict the spatial variability of hydro-meteorological data in the basin. A series of meteorological data from 25 stations for the period 2015-2017 were used in connection with the ordinary kriging technique. Infiltration values were analyzed considering three different soil moisture conditions: dry, normal and wet. To represent the semi variances of the SWB variables, the function J-Bessel was used. An adequate mathematical adjustment between observed and predicted values of SWB variables has been found expressed by the correlation coefficient (R) as followes: for precipitation, 0.54-0.81; for infiltration, 0.68-0.95; for runoff, 0.68-0.92: for evapotranspiration, 0.53-0.86; and for the accumulative volume, 0.53-0.95.

Keywords

• Geostatistics modeling
• kriging
• semivariance analysis
• water balance
• infiltration
• soil moisture