Andrew W. Western

Observed spatial organization of soil moisture and its relation to terrain indices

We analyze the degree of spatial organization of soil moisture and the ability of terrain attributes to predict that organization. By organization we mean systematic spatial variation or consistent spatial patterns. We use 13 observed spatial patterns of soil moisture, each based on over 500 point measurements, from the 10.5 ha Tarrawarra experimental catchment in Australia. The measured soil moisture patterns exhibit a high degree of organization during wet periods owing to surface and subsurface lateral redistribution of water. During dry periods there is little spatial organization. The shape of the distribution function of soil moisture changes seasonally and is influenced by the presence of spatial organization. Generally, it is quite different from the shape of the distribution functions of various topographic indices. A correlation analysis found that ln(a), where a is the specific upslope area, was the best univariate spatial predictor of soil moisture for wet conditions and that the potential radiation index was best during dry periods. Combinations of ln(a) or ln(a/tan(β)), where β is the surface slope, and the potential solar radiation index explain up to 61% of the spatial variation of soil moisture during wet periods and up to 22% during dry periods. These combinations explained the majority of the topographically organized component of the spatial variability of soil moisture a posteriori. A scale analysis indicated that indices that represent terrain convergence (such as ln(a) or ln(a/tan(β))) explain variability at all scales from 10 m up to the catchment scale and indices that represent the aspect of different hillslopes (such as the potential solar radiation index) explain variability at scales from 80 m to the catchment scale. The implications of these results are discussed in terms of the organizing processes and in terms of the use of terrain attributes in hydrologic modeling and scale studies. A major limitation on the predictive power of terrain indices is the degree of spatial organization present in the soil moisture pattern at the time for which the prediction is made.

Preferred states in spatial soil moisture patterns: Local and nonlocal controls

In this paper we develop a conceptual and observational case in which soil water patterns in temperate regions of Australia switch between two preferred states. The wet state is dominated by lateral water movement through both surface and subsurface paths, with catchment terrain leading to organization of wet areas along drainage lines. We denote this as nonlocal control. The dry state is dominated by vertical fluxes, with soil properties and only local terrain (areas of high convergence) influencing spatial patterns. We denote this as local control. The switch is described in terms of the dominance of lateral over vertical water fluxes and vice versa. When evapotranspiration exceeds rainfall, the soil dries to the point where hydraulic conductivity is low and any rainfall that occurs essentially wets up the soil uniformly and is evapotranspired before any significant lateral redistribution takes place. As evapotranspiration decreases and/or rainfall increases, areas of high local convergence become wet, and runoff that is generated moves downslope, rapidly wetting up the drainage lines. In the wet to dry transitional period a rapid increase in potential evapotranspiration (and possibly a decrease in rainfall) causes drying of the soil and “shutting down” of lateral flow. Vertical fluxes dominate and the “dry” pattern is established. Three data sets from two catchments are presented to support the notion of preferred states in soil moisture, and the results of a modeling exercise on catchments from a range of climatic conditions illustrate that the conclusions from the field studies may apply to other areas. The implications for hydrological modeling are discussed in relation to methods for establishing antecedent moisture conditions for event models, for distribution models, and for spatially distributing bulk estimates of catchment soil moisture using indices.

Towards areal estimation of soil water content from point measurements: time and space stability of mean response

Areal estimates of soil moisture over large areas are required for the ground truthing of remotely sensed measurements and for establishing catchment-wide antecedent conditions for runoff simulations. There is a mismatch in scale between field (point) measurements and the areal estimates from both remote sensing and simulation modelling, so attention must be focused on developing sampling strategies that are able to determine accurate areal estimates of soil moisture using present (essentially point) techniques. In this paper, we use the concepts of time stability, applied to catchments with significant relief, to investigate the existence of certain parts of the landscape which consistently exhibit mean behaviour irrespective of the overall wetness. We denote these as catchment average soil moisture monitoring (CASMM) sites. Four data sets from three catchments (Tarrawarra, R5-Chickasha and Lockyersleigh) are examined. The catchments range in size from 10.5 ha to 27 km2. Soil moisture measurements are made using time domain reflectometry (TDR) or neutron moisture meters (NMMs), over depths from 30 to 120 cm. Time-stable locations representing mean areal moisture content are found in each catchment, i.e. CASMM sites exist. Although this analysis is preliminary, it points towards the possibility of a methodology for determining a sampling regime that could provide reliable estimates of areal mean soil moisture in complex terrain from a limited number of sample locations.

Toward capturing hydrologically significant connectivity in spatial patterns

Many spatial fields exhibit connectivity features that have an important influence on hydrologic behavior. Examples include high-conductivity preferred flow paths in aquifers and saturated source areas in drainage lines. Connected features can be considered as arbitrarily shaped bands or pathways of connected pixels having similar (e.g., high) values. Connectivity is a property that is not captured by standard geostatistical approaches, which assume that spatial variation occurs in the most random possible way that is consistent with the spatial correlation, nor is it captured by indicator geostatistics. An alternative approach is to use connectivity functions. In this paper we apply connectivity functions to 13 observed soil moisture patterns from the Tarrawarra catchment and two synthetic aquifer conductivity patterns. It is shown that the connectivity functions are able to distinguish between connected and disconnected patterns. The importance of the connectivity in determining hydrologic behavior is explored using rainfall-runoff simulations and groundwater transport simulations. We propose the integral connectivity scale as a measure of the presence of hydrologic connectivity. Links between the connectivity functions and integral connectivity scale and simulated hydrologic behavior are demonstrated and explained from a hydrologic process perspective. Connectivity functions and the integral connectivity scale provide promising means for characterizing features that exist in observed spatial fields and that have an important influence on hydrologic behavior. Previously, this has not been possible within a statistical framework.

Geostatistical characterisation of soil moisture patterns in the Tarrawarra catchment

Abstract Spatial soil moisture patterns have been measured in the 10.5 ha Tarrawarra catchment in temperate south-eastern Australia on 13 occasions using time domain reflectometry (TDR). Measurements are made on regular grids of between 500 and 2000 points for each occasion. The spatial correlation structure of these soil moisture patterns is analysed. Sample variograms are found to have a clear sill and a nugget. Exponential variogram models, including a nugget, fit the sample variograms closely. The geostatistical structure is found to evolve seasonally. High sills (15–25 (%v/v) 2 ) and low correlation lengths (35–50 m) are observed during the wet winter period. During the dry summer period sills are smaller (5–15 (%v/v) 2 ) and correlation lengths are longer (50–60 m). This seasonal evolution is explained on the basis of the importance of lateral redistribution of moisture during different seasons. Both a nugget effect due to measurement error and variability at small scales contribute to the variability at the 10 m scale, which is the smallest scale in most of the data sets. For one occasion four soil moisture patterns containing 514 samples were collected on 10 × 20 m grids. These patterns are offset by 2 m in an easterly and/or a northerly direction. Variograms for these four patterns are similar which indicates that variograms used for the structural analysis are highly reliable. An analysis based on transects subsampled from typical summer and winter soil moisture patterns indicates that a substantial number of data points (more than about 300) are needed to obtain meaningful sample variograms.

The Tarrawarra Data Set: Soil moisture patterns, soil characteristics, and hydrological flux measurements

Experiments investigating the spatial variability of soil moisture conducted in the 10.5 ha Tarrawarra catchment, southeastern Australia, are described. The resulting data include high-resolution soil moisture maps (over 10,000 point measurements at up to 2060 sites), information from 125 soil cores, over 1000 soil moisture profiles from 20 sites, 2500 water level measurements from 74 piezometers, surface roughness and vegetation measurements, meteorological and hydrological flux measurements, and topographic survey data. These experiments required a major commitment of resources including 250 person days in the field, with a further 100 person days in the laboratory preparing for field trips and checking and collating data. These data are available on the World Wide Web (http://www.civag.unimelb.edu.au/data/).

Advances in the use of observed spatial patterns of catchment hydrological response

Over the past two decades there have been repeated calls for the collection of new data for use in developing hydrological science. The last few years have begun to bear fruit from the seeds sown by these calls, through increases in the availability and utility of remote sensing data, as well as the execution of campaigns in research catchments aimed at providing new data for advancing hydrological understanding and predictive capability. In this paper we discuss some philosophical considerations related to model complexity, data availability and predictive performance, highlighting the potential of observed patterns in moving the science and practice of catchment hydrology forward. We then review advances that have arisen from recent work on spatial patterns, including in the characterisation of spatial structure and heterogeneity, and the use of patterns for developing, calibrating and testing distributed hydrological models. We illustrate progress via examples using observed patterns of snow cover, runoff occurrence and soil moisture. Methods for the comparison of patterns are presented, illustrating how they can be used to assess hydrologically important characteristics of model performance. These methods include point-to-point comparisons, spatial relationships between errors and landscape parameters, transects, and optimal local alignment. It is argued that the progress made to date augers well for future developments, but there is scope for improvements in several areas. These include better quantitative methods for pattern comparisons, better use of pattern information in data assimilation and modelling, and a call for improved archiving of data from field studies to assist in comparative studies for generalising results and developing fundamental understanding.

Seasonal and event dynamics of spatial soil moisture patterns at the small catchment scale

[1] Our understanding of short- and long-term dynamics of spatial soil moisture patterns is limited due to measurement constraints. Using new highly detailed data, this research aims to examine seasonal and event-scale spatial soil moisture dynamics in the topsoil and subsoil of the small spruce-covered Wustebach catchment, Germany. To accomplish this, univariate and geo-statistical analyses were performed for a 1 year long 4-D data set obtained with the wireless sensor network SoilNet. We found large variations in spatial soil moisture patterns in the topsoil, mostly related to meteorological forcing. In the subsoil, temporal dynamics were diminished due to soil water redistribution processes and root water uptake. Topsoil range generally increased with decreasing soil moisture. The relationship between the spatial standard deviation of the topsoil soil moisture (SD� ) and mean water content (� ) showed a convex shape, as has often been found in humid temperate climate conditions. Observed scatter in topsoil SD� (� ) was explained by seasonal and event-scale SD� (� ) dynamics, possibly involving hysteresis at both time scales. Clockwise hysteretic SD� (� ) dynamics at the event scale were generated under moderate soil moisture conditions only for intense precipitation that rapidly wetted the topsoil and increased soil moisture variability controlled by spruce throughfall patterns. This hysteretic effect increased with increasing precipitation, reduced root water uptake, and high groundwater

Hydropedology: Synergistic integration of pedology and hydrology

This paper presents a vision that advocates hydropedology as an advantageous integration of pedology and hydrology for studying the intimate relationships between soil, landscape, and hydrology. Landscape water flux is suggested as a unifying precept for hydropedology, through which pedologic and hydrologic expertise can be better integrated. Landscape water flux here encompasses the source, storage, flux, pathway, residence time, availability, and spatiotemporal distribution of water in the root and deep vadose zones within the landscape. After illustrating multiple knowledge gaps that can be addressed by the synergistic integration of pedology and hydrology, we suggest five scientific hypotheses that are critical to advancing hydropedology and enhancing the prediction of landscape water flux. We then present interlinked strategies for achieving the stated vision. It is our hope that by working together, hydrologists and pedologists, along with scientists in related disciplines, can better guide data acquisition, knowledge integration, and model-based prediction so as to advance the hydrologic sciences in the next decade and beyond.

The Tarrawarra project: high resolution spatial measurement, modelling and analysis of soil moisture and hydrological response

Detailed spatial patterns of soil moisture were measured for 13 dates at the 10.5 ha Tarrawarra catchment in southern Victoria, Australia. Several analyses of the data are summarized. These include: hydrological behaviour, including preferred states, spatial organization and the performance of terrain indices; geostatistical properties of the soil moisture patterns; and remote sensing of the soil moisture patterns. In the second part of the paper, the patterns along with surface runoff and meteorological data are used in applications of the Thales and VIC models at Tarrawarra. Thales is a process-based distributed parameter hydrological model which explicitly simulates the spatio-temporal patterns of soil moisture, while VIC uses a lumped statistical distribution approach to model the spatial variability of soil moisture storage. Both models simulate saturation excess runoff and are forced by rainfall and potential evapotranspiration. VIC was calibrated to observed runoff at the catchment outlet. Limited manual calibration of Thales to runoff and the soil moisture patterns was performed. Internal testing was achieved by comparison of predicted and observed spatial soil moisture patterns for the Thales model and of predicted and observed cumulative distributions of active soil moisture storage for the VIC model. With limited calibration effort, Thales was able to to simulate the seasonal changes in characteristics of the spatial soil moisture patterns. Detailed examination of the errors in the simulated patterns allowed identification of structural problems in the model, including problems with simulating lateral redistribution as the catchment wets in autumn. For the VIC model, time-series of spatially averaged internal state variables (total storage) were consistent with observations. However, the statistical distribution of soil moisture storage assumed in the model differed from that observed. The collection of detailed spatial data for soil moisture patterns provided a basis for testing the internal states relevant to each model formulation (spatially distributed for Thales and statistically lumped for VIC), as well as improving the identification of the dominant runoff processes.