Infrastructure Engineering - Research Publications
Permanent URI for this collection
Search Results
1 - 10 of 346
-
ItemThe behavior of stratified pools in the Wimmera River, Australia(AMER GEOPHYSICAL UNION, 1996-10-01)Numerous inland Australian streams contain density‐stratified or saline pools, which are usually located on channel bends. Saline pools consist of a layer of saline water underlying a layer of fresh water. Saline pools generally form as a result of saline groundwater seeping into the stream and collecting in scour depressions during periods of low flow. Inflows of saline river water can also collect in scour depressions. Field and laboratory investigations of saline pool mixing by overflowing fresh water reveal that mixing depends on a balance between interfacial shear and buoyancy forces acting on a thin dense layer flowing up the downstream slope of the scour depression, and on the bend sharpness. Convection associated with surface cooling also causes mixing. A model for saline pools formed by groundwater inflows and mixed by fresh overflows is proposed and applied to several saline pools in the Wimmera River.
-
ItemPreferred states in spatial soil moisture patterns: Local and nonlocal controls(AMER GEOPHYSICAL UNION, 1997-12-01)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.
-
ItemThe Tarrawarra data set: Soil moisture patterns, soil characteristics, and hydrological flux measurements(AMER GEOPHYSICAL UNION, 1998-10-01)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/).
-
ItemObserved spatial organization of soil moisture and its relation to terrain indices(AMER GEOPHYSICAL UNION, 1999-03-01)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.
-
ItemToward capturing hydrologically significant connectivity in spatial patterns(AMER GEOPHYSICAL UNION, 2001-01-01)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.
-
ItemOn the computation of the quasi-dynamic wetness index with multiple-flow-direction algorithms(AMER GEOPHYSICAL UNION, 2003-05-06)The quasi-dynamic wetness index, in its original development, was computed by calculating the travel time along all the possible upslope flow paths on a contour-based terrain network. In more recent applications the same approach has been extended to gridded digital elevation models with single-flow- direction algorithms. Multiple-flow-direction algorithms, although more effective in representing flow paths, have not been used because they are not practicable with the established methodology. We propose an alternative method for computing the quasi-dynamic wetness index based on the numerical integration of the linear-kinematic wave equation. This method can be applied to any of the terrain-based flow-direction algorithms currently published. The method is robust and efficient.
-
ItemCharacteristic space scales and timescales in hydrology(AMER GEOPHYSICAL UNION, 2003-10-30)We analyzed spatial and temporal variograms of precipitation, runoff, and groundwater levels in Austria to examine whether characteristic scales exist and, if so, how big they are. In time, precipitation and runoff are stationary with characteristic scales on the order of a day and a month, respectively, while groundwater levels are nonstationary. In space, precipitation is almost fractal, so no characteristic scales exist. Runoff is nonstationary but not a fractal as it exhibits a break in the variograms. An analysis of the variograms of catchment precipitation indicates that this break is due to aggregation effects imposed by the catchment area. A spatial variogram of hypothetical point runoff back calculated from runoff variograms of three catchment size classes using aggregation statistics (regularization) is almost stationary and exhibits shorter characteristic space scales than catchment runoff. Groundwater levels are nonstationary in space, exhibiting shorter‐scale variability than precipitation and runoff, but are also not fractal as there is a break in the variogram. We suggest that the decrease of spatial characteristic scales from catchment precipitation to runoff and to groundwater is the result of a superposition of small‐scale variability of catchment and aquifer properties on the rainfall forcing. For comparison, TDR soil moisture data from a comprehensive Australian data set were examined. These data suggest that in time, soil moisture is close to stationary with characteristic scales of the order of 2 weeks while in space soil moisture is nonstationary and close to fractal over the extent sampled. Space‐time traces of characteristic scales fit well into a conceptual diagram of Blöschl and Sivapalan [1995]. The scaling exponents z in T ∼ Lz (where T is time and L is space) are of the order of 0.5 for precipitation, 0.8 for runoff from small catchments, 1.2 for runoff from large catchments, 0.8 for groundwater levels, and 0.5 for soil moisture.
-
ItemA rational function approach for estimating mean annual evapotranspiration(AMER GEOPHYSICAL UNION, 2004-02-05)Mean annual evapotranspiration from a catchment is determined largely by precipitation and potential evapotranspiration; characteristics of the catchment (e.g., soil, topography, etc.) play only a secondary role. It has been shown that the ratio of mean annual potential evapotranspiration to precipitation (referred as the index of dryness) can be used to estimate mean annual evapotranspiration by using one additional parameter. This study evaluates the effects of climatic and catchment characteristics on the partitioning of mean annual precipitation into evapotranspiration using a rational function approach, which was developed based on phenomenological considerations. Over 470 catchments worldwide with long-term records of precipitation, potential evapotranspiration, and runoff were considered, and results show that model estimates of mean annual evapotranspiration agree well with observed evapotranspiration taken as the difference between precipitation and runoff. The mean absolute error between modeled and observed evapotranspiration was 54 mm, and the model was able to explain 89% of the variance with a slope of 1.00 through the origin. This indicates that the index of dryness is the most significant variable in determining mean annual evapotranspiration. Results also suggest that forested catchments tend to show higher evapotranspiration than grassed catchments and their evapotranspiration ratio (evapotranspiration divided by precipitation) is most sensitive to changes in catchment characteristics for regions with the index of dryness around 1.0. Additionally, a stepwise regression analysis was performed for over 270 Australian catchments where detailed information of vegetation cover, precipitation characteristics, catchment slopes, and plant available water capacity was available. It is shown that apart from the index of dryness, average storm depth, plant available water capacity, and storm arrival rate are also significant.
-
ItemIdentifying and quantifying sources of variability in temporal and spatial soil moisture observations(American Geophysical Union, 2004-02-20)Soil moisture is an important component of the hydrological cycle. It is a control in the partitioning of energy and water related to evapotranspiration and runoff and thereby influences the hydrological response of an area. Characterizing the temporal and spatial distribution of soil moisture has important hydrologic applications, yet soil moisture varies in response to many processes acting over a variety of scales; the relative importance of different temporal and spatial controls on soil moisture is still poorly understood. In this paper we analyze both temporal and spatial soil moisture data empirically for two catchments in Australia and a further three in New Zealand. Hydrological conditions at these field sites covered a wide range over a 2 year period. The ground-based soil moisture data set is unique in its temporal and, in particular, its spatial coverage. Analyses attempt to isolate and quantify different deterministic sources of variability, measurement error, and a remaining unexplained component of variability. Because of limited data (especially relating to soils) we take a pragmatic approach of removing patterns that we can define in time and space (namely, seasonality and terrain) and then analyzing the unexplained variation. We then look for consistent patterns in this unexplained variability and argue that these are related to meteorological conditions, especially precipitation events, in the temporal case, and a combination of soils and vegetation in the spatial case. We were able to explain most of the observed variance in time and space, and the temporal variance was typically 5 times larger than spatial variance. Seasonality is the dominant source of temporal variability at our sites, although this conclusion obviously depends on climate and does not hold where soil water storage is limited. Most importantly, in controlling the distribution of soil moisture in space, the spatial distribution of soils and vegetation seems to be of similar importance to that of topography, a fact often ignored in hydrological modeling, or else surrogate soils patterns are used, but these are often not well correlated to the actual patterns [Grayson and Blöschl, 2000]. Better methods for defining the spatial properties of soils and vegetation as they affect soil moisture patterns are a key challenge.
-
ItemScaling from process timescales to daily time steps: A distribution function approach(American Geophysical Union, 2005-02)A new temporal scaling method applicable to many rainfall-runoff-erosion models is presented. The method is based on the probability distribution approach used in a number of spatial hydrological models, and it uses statistical distributions of rainfall intensity to represent subdaily intensity variations in a daily time step model. This allows the effect of short timescale nonlinear processes to be captured while modeling at a daily time step, which is often attractive due to the wide availability of total daily rainfall data. The approach relies on characterizing the rainfall intensity variation within a day using a probability distribution function (pdf). This pdf is then modified by various linear and nonlinear processes typically represented in hydrological and erosion models. The statistical description of subdaily variability is thus propagated through the model, allowing the effects of variability to be captured in the simulations. This results in pdfs of various fluxes, the integration of which over a day gives respective daily totals. The method is tested using 42 plot years of daily runoff and erosion plot data from field studies in different environments from Australia and Nepal. Significant improvements in the simulation of surface runoff and erosion are achieved, compared with a similar model using average daily rainfall intensities. The probability-based model compares well with a subhourly (2 and 6 min) model using similar process descriptions. This suggests that the probability-based approach captures the important effects of sub–time step variability while utilizing commonly available information. It is also found that the model parameters are more robustly defined using the probability-based approach compared with the daily effective parameter model. This suggests that the probability-based approach may offer improved model transferability spatially (to other areas) and temporally (to other periods).