http://nova.newcastle.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:12263 A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen–Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts–Strogatz model, a gene network during the progression of Alzheimer’s disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution. 2012-12-17T04:50:04.393Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:10817 This study explores temporal changes in the dynamics of the Holocene ENSO proxy record of the Laguna Pallcacocha sedimentary data using two entropy quantifiers. In particular, we analyze the possible connections between changes in entropy and epochs of rapid climate change (RCC). Our results indicate that the dynamics of the ENSO proxy record during the RCC interval 9000–8000 BP displays very low entropy (high predictability) that is remarkably different from that of the other RCCs of the Holocene. Both entropy quantifiers point out to the existence of cycles with a period close to 2000 years during the mid-to-late Holocene. Within these cycles, we find a tendency for entropy to increase (predictability to decrease) during the two longer RCC periods (6000–5000 and 3500–2500 BP) which might be associated with the reported increased aridity of the low tropics. 2012-05-21T02:07:58.915Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9601 Recent research aiming at the distinction between deterministic or stochastic behavior in observational time series has looked into the properties of the “ordinal patterns”. In particular, new insight has been obtained considering the emergence of the so-called “forbidden ordinal patterns". It was shown that deterministic one-dimensional maps always have forbidden ordinal patterns, in contrast with time series generated by an unconstrained stochastic process in which all the patterns appear with probability one. Techniques based on the comparison of this property in an observational time series and in white Gaussian noise were implemented. However, the comparison with correlated stochastic processes was not considered. In this paper we used the concept of “missing ordinal patterns” to study their decay rate as a function of the time series length in three stochastic processes with different degrees of correlation: fractional Brownian motion, fractional Gaussian noise and, noises with f⁻ᵏ power spectrum. We show that the decay rate of “missing ordinal patterns” in these processes depend on their correlation structures. We finally discuss the implications of the present results for the use of these properties as a tool for distinguishing deterministic from stochastic processes. 2011-12-06T00:50:10.671Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:6676 This chapter attempts to bring together and summarize the results from recent research analysing the role of hillslope, channel and network processes on the hydrologic response of basins. In doing so, particular emphasis is placed on understanding how different processes act at various scales, from individual channels to the network scale, to produce the dispersive, or 'spreading', effects that shape the basin's hydrologic response. These processes not only have an impact on the hydrograph's shape by determining the waywater is routed to the outlet but also on the way sediments, nutrients, chemicals, aquatic organisms, seeds, bacteria and a number of other substances are redistributed along the basin and/or transported to the outlet by the flow. Consequently, the advances presented in this chapter are relevant not only for hydrology and other fields like fluvial geomorphology and ecology but also for interdisciplinary research in a number of emerging fields, like ecohydrology hydroecology and ecogeomorphology. 2010-09-10T04:00:03.090Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:6465 The objective of this work is to determine the relative effects of hydrodynamic and geomorphologic dispersion on the hydrological response of the Illinois River Basin (IRB) as scale increases. The specific hypothesis that was tested is that as basin size increases, the river network structure, as compared to channel hydrodynamic properties, plays an increasingly dominant role in determining the hydrologic response. The analysis was performed on eight of the major watersheds in the IRB in order to provide an adequate representation of basins that contain streams of order six or greater. The basins studied include the Des Plaines, Mackinaw, Vermilion, Fox, La Moine, Spoon, Kankakee, and the Sangamon, and have magnitudes ranging from order six to order eight. The geometric and hydrodynamic properties were derived from the analysis of digital elevation model data and from the hydraulic geometry equations for various subcatchments of the IRB put forth by Stall and Fok [Univ. of Ill. Water Res. Center Res. Rep. 15, 1968]. The hydrodynamic and geomorphologic dispersion coefficients were determined for each order stream of the eight basins and for constant flow frequencies, then compared. The results contradict the original hypothesis, for at small scales, geomorphologic dispersion tends to dominate, the extent of which depends upon the flow frequency, and at large scales, geomorphologic dispersion is less dominant. This occurs because of the behavior of the path lengths of a stream network, which geomorphologic dispersion depends upon. In addition, at high flow frequencies the geomorphologic dispersion dominates, and at low frequencies the hydrodynamic dispersion begins to play an increasingly important role, although the geomorphologic dispersion still dominates. This dominance suggests that the geomorphologic parameters of a watershed could be more important in characterizing the hydrologic response of a river basin than hydrodynamic parameters. 2010-06-11T01:40:01.198Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:867 The evolution of soil depths is investigated by modeling the interaction between soil production and surface erosion within a landform evolution model. An enhanced version of the landform evolution model SIBERIA that incorporates a soil evolution module is used to simulate evolving landforms and soils depths over geologic timescales. The spatial and temporal evolution of soil depths are examined at the hillslope scale. Though it is widely accepted among the geomorphology community that soil water enhances chemical, physical and biological weathering processes, its effect has not been explicitly included in published models of soil production. The main scientific questions that we address are (1) what are the implications of incorporating soil moisture dependency in the soil production function and (2) what type of soil production dynamics is needed to generate a bedrock topography that has a different spatial pattern from that of the ground surface. A range of physics for the soil production model is explored. The effect of soil moisture is included using the wetness index obtained from drainage analysis of either surface elevations or the bedrock topography. The results show that the various soil production functions that incorporate either a wetness index or subsurface flow depth based on the bedrock topography give rise to soils that self-organize with well-defined spatial patterns and bedrock elevations with spatial organization significantly different from that of the surface. The model that incorporates the influence of subsurface water on soil production is able to naturally generate a soil production rate with a maximum value for a nonzero soil depth and overcomes an inconsistency of previously published “humped” soil production models. 2010-04-27T06:23:11.562Z ]]>