Ground–atmosphere interaction modelling for long-term prediction of soil moisture and temperature

Abstract

Land surface and subsurface variables, such as soil moisture–suction and temperature, are among the most important components to study the behaviour of expansive soil, geothermal energy, and climate change. A more accurate and long-term series of soil moisture and temperature prediction, due to ground–atmosphere interaction, is very important for real-time drought monitoring for understanding and improving the behaviour of soil, buried structures, and climate prediction. In this study, ground–atmosphere interaction is numerically modelled using Vadose/W software for two instrumented sites in Melbourne, Australia. Soil moisture and temperature down to 2 m depth were monitored over 2 years at discrete locations and the meteorological variables including air temperature, air humidity, wind speed, precipitation, and solar radiation were measured from a weather station installed at the sites. Further, laboratory and field tests were performed to establish initial conditions and soil characteristics such as the soil-water characteristic curve (SWCC ), hydraulic conductivity, and thermal conductivity functions. The numerical model results were calibrated with the field data, indicating good agreement between numerical and field results. The calibrated numerical model was used to compute the long-term moisture and temperature variations into the immediate future using the past 20 years of weather data in Melbourne.