Variability in surface moisture content along a hillslope transect: Rattlesnake Hill, Texas

Surface soil moisture content exhibits a high degree of spatial and temporal variability. The purpose of this study was (a) to characterize variations in moisture content in the 0–5 cm surface soil layer along a hillslope transect by means of intensive sampling in both space and time; and (b) to make inferences regarding the environmental factors that influence this variability. Over a period of seven months, soil moisture content was measured (gravimetric method) on a near-daily basis at 10 m intervals along a 200 m downslope transect at the Rattlesnake Hill field site in Austin, Texas. Results indicate that significant variability in soil moisture content exists along the length of the transect; that variability decreases with decreasing transect-mean moisture content as the hillslope dries down following rain events; and that the dominant influences on moisture content variability are dependent upon the moisture conditions on the hillslope. While topographic and soil attributes operate jointly to redistribute soil water following storm events, under wet conditions, variability in surface moisture content is most strongly influenced by porosity and hydraulic conductivity, and under dry conditions, correlations are strongest to relative elevation, aspect and clay content. Consequently, the dominant influence on soil moisture variability gradually changes from soil heterogeneity to joint control by topographic and soil properties as the transect dries following significant rain events.     

Scaling characteristics of spatial patterns of soil moisture from distributed modelling

Characterizing the spatial dynamics of soil moisture fields is a key issue in hydrology, offering an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, the statistical structure of soil moisture patterns is examined using modelled soil moisture obtained from the North American Land Data Assimilation System (NLDAS) at 0.125° resolution. The study focuses on the vertically averaged soil moisture in the top 10 cm and 100 cm layers. The two variables display a weak dependence for lower values of surface soil moisture, with the strength of the relationship increasing with the water content of the top layer. In both cases, the variance of the soil moisture follows a power law decay as a function of the averaging area. The superficial layer shows a lower degree of spatial organization and higher temporal variability, which is reflected in rapid changes in time of the slope of the scaling functions of the soil moisture variance. Conversely, the soil moisture in the top 100 cm has lower variability in time and larger spatial correlation. The scaling of these patterns was found to be controlled by the changes in the soil water content. Results have implications for the downscaling of soil moisture to prevent model bias.     

Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints

Remote sensing of soil moisture effectively provides soil moisture at a large scale, but does not explain highly heterogeneous soil moisture characteristics within remote sensing footprints. In this study, field scale spatio-temporal variability of root zone soil moisture was analyzed. During the Soil Moisture Experiment 2002 (SMEX02), daily soil moisture profiles (i.e., 0–6, 5–11, 15–21, and 25–31 cm) were measured in two fields in Walnut Creek watershed, Ames, Iowa, USA. Theta probe measurements of the volumetric soil moisture profile data were used to analyze statistical moments and time stability and to validate soil moisture predicted by a simple physical model simulation. For all depths, the coefficient of variation of soil moisture is well explained by the mean soil moisture using an exponential relationship. The simple model simulated very similar variability patterns as those observed.As soil depth increases, soil moisture distributions shift from skewed to normal patterns. At the surface depth, the soil moisture during dry down is log-normally distributed, while the soil moisture is normally distributed after rainfall. At all depths below the surface, the normal distribution captures the soil moisture variability for all conditions. Time stability analyses show that spatial patterns of sampling points are preserved for all depths and that time stability of surface measurements is a good indicator of subsurface time stability. The most time stable sampling sites estimate the field average root zone soil moisture value within ±2.1% volumetric soil moisture.     

Thermal conductivity in a vadose zone: A novel spectral solution and application by the implication of significant coherence of thermal condition in the shallow soil water layer

In the context of the heterogeneity in the unsaturated or vadose zone, accurately representing the analytical mechanisms and in-situ water content within the soil layer poses a significant challenge. Particularly in shallow layers, thermal conditions exhibit rapid changes in response to evolving surface temperatures. This study proposes a hypothesis suggesting that the in situ heat mechanism may notably impact the soil water layer. The research introduces an innovative approach to theoretically uncover thermal conditions, including soil temperature, soil temperature gradients, and heat flux, within the shallow Quaternary gravel layer at various depths through spectral analysis of temporal observations. The study presents a stochastic inverse solution to estimate thermal conductivity by leveraging spectral analysis of soil heat flux and temperature gradients. The findings reveal that thermal conditions exhibit the most prominent periodic fluctuations during the diurnal process over a 24-hour cycle. The soil temperature gradients and heat flux measurements at depths of 0.1, 0.3, 0.6, and 1.2 m demonstrate their ability to capture changes in soil temperature and air temperature to a certain extent within the frequency domain. Furthermore, the analysis highlights the intrinsic uncertainty and sensitivity of estimating thermal conductivity in heterogeneous soil environments. The wide variability observed in thermal conductivity values, coupled with their dependence on soil type and environmental conditions, underscores the need for careful consideration of these factors in future studies and modeling efforts. Applying the derived inverse spectral solution allows for determining thermal conductivity throughout the soil-water system across depths ranging from 0.1 to 1.2 m. As a result, this research demonstrates the feasibility and practicality of assessing the thermal conductivity of the soil layer in conjunction with heat flux and temperature gradients through spectral analysis.     

Factors controlling the spatial variability of surface soil moisture within revegetated‐stabilized desert ecosystems of the Tengger Desert,Northern China

The spatial structure of surface soil moisture was investigated at a grid scale with 10 × 10 m intervals on a plot of 4500 m² in a re‐vegetated desert area in Shapotou, the Tengger Desert. The site topography varies from dune crest to dune hollow, and again to dune crest. Volumetric soil moisture contents were measured 21 times over 6 months in 2006 by using Delta‐T Theta‐Probes in the 0–6 cm surface soil layer before and after rainfall. At the same time, soil texture, relative elevation, and plant coverage were measured, to examine (i) the spatial variability of surface soil moisture; (ii) the main factors controlling the spatial variability patterns; and (iii) how the importance of these factors varies with the seasonal variations in soil moisture content. The results indicated that the normal distribution of surface soil moisture was more obvious in wet conditions than in dry conditions; the spatial variability of surface soil moisture was inherent and decreased with increased soil moisture content; and precipitation increased the spatial dependence of surface soil moisture. The relative elevation of the landscape, the shrub coverage of the community, and the soil texture were the main factors influencing surface soil moisture variability, while the effect of soil texture strengthened gradually following the heavy precipitation events. The correlation between the spatial variability of surface soil moisture and the environmental factors, such as, the dry and wet conditions, the landscape coverage and the relative elevation suggests that increasing stability of the soil moisture resulted in a significant increase of soil moisture. Copyright © 2009 John Wiley & Sons, Ltd.     

Evaluation of the impact of rainfall on soil moisture variability

The impact of rainfall on the spatial-temporal soil moisture variability is investigated by using a model of the soil moisture dynamics and two rainfall models, the noise-forced diffusive precipitation model and the WGR model. The study shows that the variability of the soil moisture field is impacted during the limited time of the storm period. During the interstorm period, the variability of the soil moisture field is closely related with the soil texture, as supported by the analysis of the Washita '92 data set. As the impact of rainfall on the variability of the soil moisture field is limited to the short time period of precipitation, the role of the rainfall is simplified as a source of water to the soil moisture field without any consideration of its variability and/or organization in space. A simulation study of the soil moisture field temporal evolution also supports this result, i.e. a strong relationship between the soil moisture field and the variability of its medium. Also, larger variabilities of the loss field coefficient result in easier removal of moisture from the soil.     

Precipitation induced stream flow: An event based chemical and isotopic study of a small stream in the Great Plains region of the USA

A small stream in the Great Plains of USA was sampled to understand the streamflow components following intense precipitation and the influence of water storage structures in the drainage basin. Precipitation, stream, ponds, ground-water and soil moisture were sampled for determination of isotopic (D, ¹⁸O) and chemical (Cl, SO₄) composition before and after two intense rain events. Following the first storm event, flow at the downstream locations was generated primarily through shallow subsurface flow and runoff whereas in the headwaters region – where a pond is located in the stream channel – shallow ground-water and pond outflow contributed to the flow. The distinct isotopic signatures of precipitation and the evaporated pond water allowed separation of the event water from the other sources that contributed to the flow. Similarly, variations in the Cl and SO₄ concentrations helped identify the relative contributions of ground-water and soil moisture to the streamflow. The relationship between deuterium excess and Cl or SO₄ content reveals that the early contributions from a rain event to streamflow depend upon the antecedent climatic conditions and the position along the stream channel within the watershed. The design of this study, in which data from several locations within a watershed were collected, shows that in small streams changes in relative contributions from ground water and soil moisture complicate hydrograph separation, with surface-water bodies providing additional complexity. It also demonstrates the usefulness of combined chemical and isotopic methods in hydrologic investigations, especially the utility of the deuterium excess parameter in quantifying the relative contributions of various source components to the stream flow.     

Effect of spatial variability and seasonality in soil moisture on drainage thresholds and fluxes in a conceptual hydrological model

This paper uses soil moisture data from 17 recording sensors within the 50 km² Mahurangi catchment in New Zealand to determine how measured variability in soil moisture affects simulations of drainage in a typical lumped conceptual model. The data show that variability smoothes the simulated field capacity threshold such that a proportion of the catchment contributes to drainage even when mean soil moisture content is well below field capacity. Spatial variability in soil moisture controls by extension the catchment drainage behaviour: the resulting smoothed shape of the catchment‐scale drainage function is demonstrated and is also determined theoretically under simplifying assumptions. The smoothing effect increases the total simulated discharge by 130%. The analysis explains previous findings that different drainage equations are required at point scale versus catchment scale in the Mahurangi. The spatial variability and hence the emergent drainage behaviour are found to vary with season, suggesting that time‐varying parameters would be warranted to simulate drainage. Copyright © 2012 John Wiley & Sons, Ltd.     

Validation of ERS scatterometer‐derived soil moisture data in the central part of the Duero Basin,Spain

The objective of this study was to validate the soil moisture data derived from coarse‐resolution active microwave data (50 km) from the ERS scatterometer. The retrieval technique is based on a change detection method coupled with a data‐based modelling approach to account for seasonal vegetation dynamics. The technique is able to derive information about the soil moisture content corresponding to the degree of saturation of the topmost soil layer (∼5 cm). To estimate profile soil moisture contents down to 100 cm depth from the scatterometer data, a simple two‐layer water balance model is used, which generates a red noise‐like soil moisture spectrum. The retrieval technique had been successfully applied in the Ukraine in a previous study. In this paper, the performance of the model in a semi‐arid Mediterranean environment characterized by low annual precipitation (400 mm), hot dry summers and sandy soils is investigated. To this end, field measurements from the REMEDHUS soil moisture station network in the semi‐arid parts of the Duero Basin (Spain) were used. The results reveal a significant coefficient of determination (R² = 0·75) for the averaged 0–100 cm soil moisture profile and a root mean square error (RMSE) of 2·2 vol%. The spatial arrangement of the REMEDHUS soil moisture stations also allowed us to study the influence of the small‐scale variability of soil moisture within the ERS scatterometer footprint. The results show that the small‐scale variability in the study area is modest and can be explained in terms of texture fraction distribution in the soil profiles. Copyright © 2004 John Wiley & Sons, Ltd.     

Soil moisture variation in relation to topography and land use in a hillslope catchment of the Loess Plateau, China

The profile characteristics and the temporal dynamics of soil moisture variation were studied at 26 locations in Da Nangou catchment (3.5 km²) in the loess area of China. Soil moisture measurements were performed biweekly at five depths in the soil profile (0–5, 10–15, 20–25, 40–45 and 70–75 cm) from May to October 1998 using Delta-T theta probe. Soil moisture profile type and temporal variation type and their relationship to topography and land use were identified by detrended canonical correspondence analysis (DCCA) and correlation analysis. The profile distribution of time-averaged soil moisture content can be classified into three types i.e. decreasing-type, waving-type and increasing-type. The profile features of soil moisture (e.g. profile gradient and profile variability) are influenced by different environmental factors. The profile type of soil moisture is only attributed to land use while profile gradient and profile variability of soil moisture is mainly related to land use and topography (e.g. landform type and slope). The temporal dynamics of layer-averaged soil moisture content is grouped into three types including three-peak type, synchro-four-peak type and lagged-four-peak type. These types are controlled by topography rather than by land use. The temporal dynamic type of soil moisture shows significant correlation with relative elevation, slope, aspect, while temporal variance displays significant relation with slope shape. The mean soil moisture is related to both the profile and dynamics features of soil moisture and is controlled by both land use and topography (e.g. aspect, position, slope and relative elevation). The spatial variability of soil moisture across landscape varies with both soil depths and temporal evolution.     

Soil moisture causes dynamic adjustments to root reinforcement that reduce slope stability

In steep soil‐mantled landscapes, the initiation of shallow landslides is strongly controlled by the distribution of vegetation, whose roots reinforce the soil. The magnitude of root reinforcement depends on the number, diameter distribution, orientation and the mechanical properties of roots that cross potential failure planes. Understanding how these properties vary in space and time in forests remains a significant challenge. Here we test the hypothesis that spatio‐temporal variations in root reinforcement along a hillslope occur as a function of topographic soil moisture gradients. To test this hypothesis we compared root reinforcement measurements from relatively dry, divergent noses to relatively wet, convergent hollows in the southern Appalachian Mountains, North Carolina, USA. Our initial results showed that root reinforcement decreased in areas of higher soil moisture because the tensile strength of roots decreased. A post hoc laboratory experiment further demonstrated that root tensile strength decreased as root moisture content increased. This effect is consistent with other experiments on stem woods showing that increased water content in the cell wall decreases tensile strength. Our experimental data demonstrated that roots can adjust to changes in the external root moisture conditions within hours, suggesting that root moisture content will change over the timescale of large storm events (hours–days). We assessed the effects of the dynamic changes in root tensile strength to the magnitude of apparent cohesion within the infinite slope stability model. Slopes can be considerably less stable when precipitation‐driven increases in saturated soil depth both increase pore pressures and decrease root reinforcement. Copyright © 2016 John Wiley & Sons, Ltd.     

Spatio-temporal evolution and time-stable characteristics of soil moisture within remote sensing footprints with varying soil, slope, and vegetation

Air-borne passive microwave remote sensors measure soil moisture at the footprint scale, a scale of several hundred square meters or kilometers that encompasses different characteristic combinations of soil, topography, vegetation, and climate. Studies of within-footprint variability of soil moisture are needed to determine the factors governing hydrologic processes and their relative importance, as well as to test the efficacy of remote sensors. Gridded ground-based impedance probe water content data and aircraft-mounted Electronically Scanned Thinned Array Radiometer (ESTAR) pixel-average soil moisture data were used to investigate the spatio-temporal evolution and time-stable characteristics of soil moisture in three selected (LW03, LW13, LW21) footprints from the Southern Great Plains 1997 (SGP97) Hydrology Experiment. Better time-stable features were observed within a footprint containing sandy loam soil than within two pixels containing silty loam soil. Additionally, flat topography with split wheat/grass land cover produced the largest spatio-temporal variability and the least time stability in soil moisture patterns. A comparison of ground-based and remote sensing data showed that ESTAR footprint-average soil moisture was well calibrated for the LW03 pixel with sandy loam soil, rolling topography, and pasture land cover, but improved calibration is warranted for the LW13 (silty loam soil, rolling topography, pasture land) and LW21 (silty loam soil, flat topography, split vegetation of wheat and grass land with tillage practice) pixels. Footprint-scale variability and associated nonlinear soil moisture dynamics may prove to be critical in the regional-scale hydroclimatic models.     

Determining hydrological regimes in an agriculturally used tropical inland valley wetland in Central Uganda using soil moisture,groundwater, and digital elevation data

Inadequate knowledge exists on the distribution of soil moisture and shallow groundwater in intensively cultivated inland valley wetlands in tropical environments, which are required for determining the hydrological regime. This study investigated the spatial and temporal variability of soil moisture along 4 hydrological positions segmented as riparian zone, valley bottom, fringe, and valley slope in an agriculturally used inland valley wetland in Central Uganda. The determined hydrological regimes of the defined hydrological positions are based on soil moisture deficit calculated from the depth to the groundwater table. For that, the accuracy and reliability of satellite‐derived surface models, SRTM‐30m and TanDEM‐X‐12m, for mapping microscale topography and hydrological regimes are evaluated against a 5‐m digital elevation model (DEM) derived from field measurements. Soil moisture and depth to groundwater table were measured using frequency domain reflectometry sensors and piezometers installed along the hydrological positions, respectively. Results showed that spatial and temporal variability in soil moisture increased significantly (p < .05) towards the riparian zone; however, no significant difference was observed between the valley bottom and riparian zone. The distribution of soil hydrological regimes, saturated, near‐saturated, and nonsaturated regimes does not correlate with the hydrological positions. This is due to high spatial and temporal variability in depth to groundwater and soil moisture content across the valley. Precipitation strongly controlled the temporal variability, whereas microscale topography, soil properties, distance from the stream, anthropogenic factors, and land use controlled the spatial variability in the inland valley. TanDEM‐X DEM reasonably mapped the microscale topography and thus soil hydrological regimes relative to the Shuttle Radar Topography Mission DEM. The findings of the study contribute to improved understanding of the distribution of hydrological regimes in an inland valley wetland, which is required for a better agricultural water management planning.     

A new surface runoff parameterization with subgrid-scale soil heterogeneity for land surface models

Soil heterogeneity plays an important role in determining surface runoff generation mechanisms. At the spatial scales represented by land surface models used in regional climate model and/or global general circulation models (GCMs) for numerical weather prediction and climate studies, both infiltration excess (Horton) and saturation excess (Dunne) runoff may be present within a studied area or a model grid cell. Proper modeling of surface runoff is essential to a reasonable representation of feedbacks in the land–atmosphere system. In this paper, a new surface runoff parameterization that dynamically represents both Horton and Dunne runoff generation mechanisms within a model grid cell is presented. The new parameterization takes into account of effects of soil heterogeneity on Horton and Dunne runoff. A series of numerical experiments are conducted to study the effects of soil heterogeneity on Horton and Dunne runoff and on soil moisture storage under different soil and precipitation conditions. The new parameterization is implemented into the current version of the hydrologically based variable infiltration capacity (VIC) land surface model and tested over three watersheds in Pennsylvania. Results show that the new parameterization plays a very important role in partitioning the water budget between surface runoff and soil moisture in the atmosphere–land coupling system. Significant underestimation of the surface runoff and overestimation of subsurface runoff and soil moisture could be resulted if the Horton runoff mechanism were not taken into account. Also, the results show that the Horton runoff mechanism should be considered within the context of subgrid-scale spatial variability of soil properties and precipitation. An assumption of time-invariant spatial distribution of potential infiltration rate may result in large errors in surface runoff and soil moisture. In addition, the total surface runoff from the new parameterization is less sensitive to the choice of the soil moisture shape parameter of the distribution.     

Spatial Variability of Surface Soil Moisture in a Depression Area of Karst Region

An understanding of soil moisture variability is necessary to characterize the linkages between a region's hydrology, ecology, and physiography. In subtropical karst region, the spatial variability of surface soil moisture is still unclear for the rocky ecological environment and intensive land uses. The purpose of this study was to characterize the variation and patterns of soil moisture content at depth of 0–16 cm and to investigate their influencing factors in a karst depression area of southwest China. Soil moisture content was measured at 20 m intervals by intensive sampling on March 11 (dry season) and August 30 (rainy season) in 2005, respectively. Surface soil moisture presented a moderate variability in the depression area at the sampling times. The variability was relatively higher in dry season with lower mean soil moisture, but lower in rainy season with higher mean soil moisture after heavy rain event. Similar results were also obtained from the mosaic patterns of soil moisture generated by ordinary Kriging interpolation with low standard deviations. This suggested that more soil samples might be required and the sampling interval should be shortened in dry season compared with rainy season. The dominant influencing factors on the variability of surface soil moisture were rainfall and land use types. However, altitude, bare‐rock ratio, and soil organic carbon were also important factors, and exerted jointly to control and redistribute the surface soil moisture either in dry or rainy season in the depression area. Such information provided some insights for the study on eco‐hydrological processes of vegetation restoration in the karst degraded ecosystem of southwest China.     

Characterization of Ethiopian mega hydrogeological regimes using GRACE,TRMM and GLDAS datasets

Understanding the spatio-temporal characteristics of water storage changes is crucial for Ethiopia, a country that is facing a range of challenges in water management caused by anthropogenic impacts as well as climate variability. In addition to this, the scarcity of in situ measurements of soil moisture and groundwater, combined with intrinsic “scale limitations” of traditional methods used in hydrological characterization are further limiting the ability to assess water resource distribution in the region. The primary objective of this study is therefore to apply remotely sensed and model data over Ethiopia in order to (i) test the performance of models and remotely sensed data in modeling water resources distribution in un-gauged arid regions of Ethiopia, (ii) analyze the inter-annual and seasonal variability as well as changes in total water storage (TWS) over Ethiopia, (iii) understand the relationship between TWS changes, rainfall, and soil moisture anomalies over the study region, and (iv) identify the relationship between the characteristics of aquifers and TWS changes. The data used in this study includes; monthly gravity field data from the Gravity Recovery And Climate Experiment (GRACE) mission, rainfall data from the Tropical Rainfall Measuring Mission (TRMM), and soil moisture from the Global Land Data Assimilation System (GLDAS) model. Our investigation covers a period of 8 years from 2003 to 2011. The results of the study show that the western part and the north-eastern lowlands of Ethiopia experienced decrease in TWS water between 2003–2011, whereas all the other regions gained water during the study period. The impact of rainfall seasonality was also seen in the TWS changes. Applying the statistical method of Principal Component Analysis (PCA) to TWS, soil moisture and rainfall variations indentified the dominant annual water variability in the western, north-western, northern, and central regions, and the dominant seasonal variability in the western, north-western, and the eastern regions. A correlation analysis between TWS and rainfall indicated a minimum time lag of zero to a maximum of six months, whereas no lag is noticeable between soil moisture anomalies and TWS changes. The delay response and correlation coefficient between rainfall and TWS appears to be related to recharge mechanisms, revealing that most regions of Ethiopia receive indirect recharge. Our results also show that the magnitude of TWS changes is higher in the western region and lower in the north-eastern region, and that the elevation influences soil moisture as well as TWS.     

Structure in fluctuations of large-scale soil moisture climate due to external random forcing and internal feedbacks

Large-scale fields of soil moisture are forced by atmospheric precipitation and radiative forcing. When these forcing factors are themselves influenced by surface and soil moisture processes, the result is a nonlinear land-atmosphere system with inherent feedback mechanisms that may strongly modulate variability in climate. Given such feedbacks, simple randomness in the forcing factors may be manifested as a complex statistical signature in the surface hydrology. In this paper, we investigate the impacts of non-Gaussian and colored-noise on the probability distribution of soil moisture resulting from the statistical-dynamical land-atmosphere interaction model of Rodriguez-Iturbe et al. (1991). Persistence of hydroclimatologic anomalies as characterized by the correlation time scale of soil moisture is discussed.     

Structure in fluctuations of large-scale soil moisture climate due to external random forcing and internal feedbacks

Large-scale fields of soil moisture are forced by atmospheric precipitation and radiative forcing. When these forcing factors are themselves influenced by surface and soil moisture processes, the result is a nonlinear land-atmosphere system with inherent feedback mechanisms that may strongly modulate variability in climate. Given such feedbacks, simple randomness in the forcing factors may be manifested as a complex statistical signature in the surface hydrology. In this paper, we investigate the impacts of non-Gaussian and colored-noise on the probability distribution of soil moisture resulting from the statistical-dynamical land-atmosphere interaction model of Rodriguez-Iturbe et al. (1991). Persistence of hydroclimatologic anomalies as characterized by the correlation time scale of soil moisture is discussed.     

The role of overland flow and subsurface flow on the spatial distribution of soil moisture in the topsoil

Many investigations show relationships between topographical factors and the spatial distribution of soil moisture in catchments. However, few quantitative analyses have been carried out to elucidate the role of different hydrological processes in the spatial distribution of topsoil moisture in catchments. A spatially distributed rainfall—runoff model was used to investigate contributions of subsurface matric flow, macropore flow and surface runoff to the spatial distribution of soil moisture in a cultivated catchment. The model results show that lateral subsurface flow in the soil matrix or in macropores has a minor effect on the spatial distribution of soil moisture. Only when a perched groundwater table is maintained long enough, which is only possible if the subsurface is completely impermeable, may a spatial distribution in moisture content occur along the slope. Surface runoff, producing accumulations of soil moisture in flat flow paths of agricultural origin (field boundaries), was demonstrated to cause significant spatial variations in soil moisture within a short period after rainfall (<2 days). When significant amounts of surface runoff are produced, wetter moisture conditions will be generated at locations with larger upstream contributing areas. Copyright © 2001 John Wiley & Sons, Ltd.     

An analysis of infiltration with moisture content distribution in a two‐dimensional discretized water content domain

On the basis of unsaturated Darcy's law, the Talbot–Ogden method provides a fast unconditional mass conservative algorithm to simulate groundwater infiltration in various unsaturated soil textures. Unlike advanced reservoir modelling methods that compute unsaturated flow in space, it only discretizes the moisture content domain into a suitable number of bins so that the vertical water movement is estimated piecewise in each bin. The dimensionality of the moisture content domain is extended from one dimensional to two dimensional in this study, which allows us to distinguish pore shapes within the same moisture content range. The vertical movement of water in the extended model imitates the infiltration phase in the Talbot–Ogden method. However, the difference in this extension is the directional redistribution, which represents the horizontal inter‐bin flow and causes the water content distribution to have an effect on infiltration. Using this extension, we mathematically analyse the general relationship between infiltration and the moisture content distribution associated with wetting front depths in different bins. We show that a more negatively skewed moisture content distribution can produce a longer ponding time, whereas a higher overall flux cannot be guaranteed in this situation. It is proven on the basis of the water content probability distribution independent of soil textures. To illustrate this analysis, we also present numerical examples for both fine and coarse soil textures. Copyright © 2014 John Wiley & Sons, Ltd.