Understanding soil moisture variability and its relationship with water content at various scales is a key issue in hydrological research. In this paper we predict this relationship by stochastic analysis of the unsaturated Brooks‐Corey flow in heterogeneous soils. Using sensitivity analysis, we show that parameters of the moisture retention characteristic and their spatial variability determine to a large extent the shape of the soil moisture variance‐mean water content function. We demonstrate that soil hydraulic properties and their variability can be inversely estimated from spatially distributed measurements of soil moisture content. Predicting this relationship for eleven textural classes we found that the standard deviation of soil moisture peaked between 0.17 and 0.23 for most textural classes. It was found that the β parameter, which describes the pore‐size distribution of soils, controls the maximum value of the soil moisture standard deviation.

The dual‐probe heat‐pulse (DPHP) method is useful for measuring soil thermal properties. Measurements are made with a sensor that has two parallel cylindrical probes: one for introducing a pulse of heat into the soil (heater probe) and one for measuring change in temperature (temperature probe). We present a semianalytical solution that accounts for the finite radius and finite heat capacity of the heater and temperature probes. A closed‐form expression for the Laplace transform of the solution is obtained by considering the probes to be cylindrical perfect conductors. The Laplace‐domain solution is inverted numerically. For the case where both probes have the same radius and heat capacity, we show that their finite properties have equal influence on the heat‐pulse signal received by the temperature probe. The finite radius of the probes causes the heat‐pulse signal to arrive earlier in time. This time shift increases in magnitude as the probe radius increases. The effect of the finite heat capacity of the probes depends on the ratio of the heat capacity of the probes (C0) and the heat capacity of the soil (C). Compared with the case where C0/C = 1, the magnitude of the heat‐pulse signal decreases (i.e., smaller change in temperature) and the maximum temperature rise occurs later when C0/C > 1. When C0/C < 1, the magnitude of the signal increases and the maximum temperature rise occurs earlier. The semianalytical solution is appropriate for use in DPHP applications where the ratio of probe radius (a0) and probe spacing (L) satisfies the condition that a0/L ≤ 0.11.

Evaporation is a significant part of the water cycle in hyper‐arid environments. The subsurface of these deserts is characterized by deep groundwater with negligible recharge, whereby water flows from the water table to the surface and evaporates. We propose an analytical model to predict the evaporation rate and the position of the evaporative front. The model accounts for water table depth, atmospheric conditions, and soil hydraulic properties. We consider steady state flow, with two distinct regions separated by an evaporative front, liquid‐phase flow from the water table to the front and vapor‐phase flow from the front toward the surface. The driving forces are pressure head gradients for Darcian liquid flow, and thermal and relative humidity gradients for Fickian diffusive vapor flow. Evaporation rates are predicted for different soil types. The impact of constitutive models applied for characterizing these soils, groundwater depth, and atmospheric conditions are evaluated. Evaporation increases as groundwater levels are shallower, and as atmospheric temperatures increase and/or relative humidity values decrease. Evaporation decreases exponentially with groundwater depth, approaching a constant value of about 0.02 mm per year under typical atmospheric conditions and water table depths below 500 m. The impact of soil type and other related uncertainties are important when groundwater is shallower than 300 m. The relative portion of the liquid phase region increases compared to that of the vapor one as evaporation rates increase. The actual size of the liquid phase flow region, however, reaches its maximum when the water flux approaches zero at hydrostatic conditions.

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[1] The heat pulse probe (HPP) technique has been successfully applied for estimating water flux density (WFD)