Associate Professor Patricia Saco

© 2015 Elsevier B.V. The impact of leaf area index (LAI) seasonality on three-year (2005-2007) daily soil moisture predictions was investigated for two different land surface models (IBIS and HYDRUS) at the Stanley semi-arid grassland field site. Three daily LAI time series derived from different empirical NDVI-LAI relationships using the MODIS NDVI data were used in the analysis. Calibration results from both models consistently suggested that an average LAI over time, rather than a time varying daily LAI, was sufficient to reproduce daily soil moisture at our site. We did, however, find that the sensitivity of the impact of LAI time variability on soil moisture estimation was a function of soil parameters. The influence of LAI time variation on the soil moisture simulations is controlled by the sensitivity of modelled soil moisture to the average LAI values over that period, and soil parameters affected the sensitivity of the model to LAI. Those parameter sets that were most sensitive to the long-term mean LAI were also those that were the most sensitive to the time variability. In our case, model calibrations using a constant LAI adjusted the soil parameters to reduce the impact of LAI variability. Results also suggested that the LAI variability could be significant if the varying LAI approached a very low level (i.e. LAI. <. 1) for a significant proportion of the simulation period. This is most likely to be the case for short grasses in grasslands.

Nonlinear interactions between physical and biological factors give rise to the emergence of remarkable landform-vegetation patterns. Patterns of vegetation and resource redistribution are linked to productivity and carrying capacity of the land. As a consequence, growing concern over ecosystem resilience to perturbations that could lead to irreversible land degradation imposes a pressing need for understanding the processes, nonlinear interactions, and feedbacks, leading to the coevolution of these patterns. For arid and semiarid regions, causes for concern have increased at a rapid pace during the last few decades due to growing anthropic and climatic pressures that have resulted in the degradation of numerous areas worldwide. This paper aims at improving our understanding of the ecogeomorphic evolution of landscape patterns in semiarid areas with a sparse biomass cover through a modeling approach. A coupled vegetation-pattern formation and landform evolution model is used to study the coevolution of vegetation and topography over centennial timescales. Results show that self-organized vegetation patterns strongly depend on feedbacks with coevolving landforms. The resulting patterns depend on the erosion rate and mechanism (dominance of either fluvial or diffusive processes), which are affected by biotic factors. Moreover, results show that ecohydrologic processes leading to banded pattern formation, when coupled with landform processes, can also lead to completely different patterns (stripes of vegetation along drainage lines) that are equally common in semiarid areas. These findings reinforce the importance of analyzing the coevolution of landforms and vegetation to improve our understanding of the patterns and structures found in nature. ©2012. American Geophysical Union. All Rights Reserved.

Motivated by the need to understand large-scale hydrologic response, significant research has been directed toward the identification of coherent regions using characteristics of streamflow variability. Typically, these regions are delineated using principal component analysis on streamflow. This method does not account for differences in temporal scales of fluctuations embedded in the time series. To capture this, we use wavelet spectral analysis. Wavelet spectra from the specific stream flow series are obtained for outflow binned at 3°-length segments along the border of the conterminous United States. Rotated principal component analysis is performed on the wavelet spectra to obtain clusters of segments that exhibit similar distribution of variability across scales. Three physically distinct modes explain over 89% of the variability. Two of the modes identified are associated with high variability at seasonal scales, and the third is associated with high variability at small timescales. The runoff generation mechanisms underlying the observed modes of multiscale variability of various regions are also discussed. Each of these coherent modes of multiscale variability indicate the existence of regions with similar scales of fluctuations that are located geographically apart, as well as regions located geographically close with dissimilar scales of fluctuations.

© 2015, Engineers Australia. All rights reserved. The configuration of the Macquarie Marshes is a mosaic-like collection of swamps, marshes and lagoons. The Macquarie Marshes is also one of the most ecologically important wetland systems in Australia. It contains unique plant communities that serve as a sanctuary for many species of waterbirds and other fauna such as frogs and mammals. A significant deterioration of the ecological features of the Macquarie Marshes has been recorded in the past decades. This fact is mostly attributed to reductions of the input discharges to the marshes due to water allocations for industrial, agricultural and domestic usage. Reduction of water supply translates into changes of the hydraulic regime which has a direct impact on the flood dependent vegetation species of the marshes. The complexity of the system and its ecological significance requires the use of an adequate computational tool that would allow for a realistic assessment of the site. In this paper we present initial work regarding the development of a vegetation dynamics model that can integrate vegetation establishment with time aggregated characteristics of the flow. We simulate floods on a fictional wetland by implementing a quasi-2D hydrodynamic model (VHHMM 1.0) over a rectangular cell grid. This same grid constitutes the basis for a cellular vegetation model that can calculate changes in the vegetation for each element inside the domain. The work presented here for a fictional site was developed in order to test the capability of our model to recreate consistent vegetation gradients by using deterministic transitional rules. These rules relate time aggregated characteristics of the flow such as flood period and depth of water to water requirements of different vegetation communities. We found that a well calibrated set of deterministic transitional rules based on water preferences can recreate consistent vegetation distributions; however, succession and critical conditions for succession rules will have to be defined for a specific site application. Further development of this model will result in a strategic tool for managing environmental water allocations and water sharing plans in the Macquarie Marshes.

Pool-riffle sequences are one of the most common geomorphological features in many streams and provide important habitat diversity both in terms of flow and substrate. The conditions for their formation and self-maintenance are still the subject of active research, but it has become clear in later years that a combination of three mechanisms: 1) stage-dependent flow conditions, 2) three-dimensional flow patterns and 3) selective sediment transport over a mobile bed, can explain the resilience and ubiquity of pool-riffle sequences observed in the field. In this paper, we analyze the importance of these three mechanisms using different combinations of stage-dependent three-dimensional flow patterns in pool-riffle sequences and sediment size distributions obtained in both pools and riffles. Self-maintenance mechanisms are identified by evaluating erosional or depositional tendencies in pools and riffles for different flow conditions using local values of bed shear stress and their corresponding fractional sediment transport volumes. Self-maintenance is directly linked to episodes of pool erosion and riffle deposition and we use the term sediment transport reversal rates to indicate this situation, rather than velocity reversal or shear stress reversal that only consider flow variables. This approach allows us to compare, for the first time, the relative importance of each of the mechanisms and their role in the self-maintenance of these bedforms, which can vary from site to site. Computations are performed using existing field, laboratory and numerical simulation data from several study sites. We discuss the limitations of our approach and the extensions to more complex field cases.

This work presents preliminary results of implementing a quasi-2D hydrodynamic module (VMMHH 1.0) to simulate flows and flooding patterns throughout the Macquarie Marshes, south east Australia, in order to assess habitat requirements. The model uses an interconnected cell scheme that solves mass conservation and uses simplified versions of the momentum equations to represent flow between cells. This model has been used before to assess geomorphological changes in large river floodplains and vegetation evolution in estuarine wetlands, showing results consistent with cases of gradual floodplain inundation following overbank flow. The simplified characteristics of the quasi-2D model allow for an adequate representation of hydrodynamic processes with similar performance of other higher dimensional models. Model results and computational times are compared with outputs from a conventional 1D/2D model (MIKE FLOOD) applied to the same domain showing that the VMMHH 1.0 is adequate for representation of floods in the Macquarie Marshes.