- Title
- Climate – soil – vegetation interactions: eco-hydro-geomorphic inferences from landscape evolution models
- Creator
- Srivastava, Ankur
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2021
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Landscapes evolve through nonlinear interactions between landform, soil, vegetation, and water fluxes (including the various components of the hydrologic cycle). Solar radiation, which regulates water availability, plays a key role in determining the amount of vegetation cover, particularly in semi-arid ecosystems which are often characterised by the constrasting density of vegetation cover in opposing north-facing slopes (NFS) and south-facing slopes (SFS). These aspect-controlled vegetation differences are linked to variations in water-stress patterns across the slopes. Due to the significant effect of vegetation on the movement of water, and as a consequence, on geomorphic processes and landform evolution, the inclusion of dynamic vegetation in landscape evolution models (LEMs) is of critical importance. The use of a physically-based model which represents the topography-vegetation-climate interactions for landscape evolution can greatly improve our understanding on this matter. To explore the ecohydro-geomorphic coevolution of semi-arid landform-vegetation ecosystems, the Channel-Hillslope Integrated Landscape Development (CHILD) landscape evolution model LEM), coupled with the vegetation dynamics Bucket Grassland Model (BGM; which explicitly tracks above- and below-ground biomass) was used for this research. This thesis begins with the analysis conducted on the spatial and temporal soil moisture variability (SMV) in semi-arid ecosystems with distinct landform shapes characterised by fluvial dominated and diffusion dominated erosion processes. SMV is controlled by several factors such as non-uniform precipitation, incoming solar radiation, and soil and vegetation properties. Simulations driven by a stochastically generated 100-year climate time series were conducted to understand the effect of the various soil moisture controlling factors on the spatiotemporal SMV. Results from the simulations showed that fluvial dominated landscapes promote higher spatial variability in soil moisture than diffusion dominated landscapes. The analysis of spatial SMV is more sensitive to changes in topography and climate (radiation, latitude, and precipitation variability than to soil and vegetation controlling factors (anisotropy, porosity, infiltration capacity, and root zone depth). The next aim was to investigate the effect of SMV and vegetation variability on coevolving landform factors. Unlike the previous aim, simulations were performed using dynamic geomorphic processes, which enable the response of landform shapes to soil moisture and vegetation dynamics. Strong feedback between the different geomorphic factors (hillslope diffusion and uplift rate) and soil moisture and vegetation were observed through slope-area relationships. As a result of this strong feedback, landform shapes differ with the coevolution and interaction of soil moisture and vegetation, which was explored using a complexity index. The complexity index analysis showed the differences in the final landscape morphologies obtained for each factor. Constituting the factors which produced the highest variation in the complexity index were uplift, hillslope diffusion, latitude, and MAP. The CHILD LEM, coupled with BGM, was then used to better understand the role of orographic precipitation on the coevolution of landforms and aspect-controlled vegetation in semi-arid ecosystems. To do this, simulations using different precipitation settings (i.e., uniform, elevation control, and orographic precipitation) were combined with uniform and spatially-varied solar radiation settings to assess their corresponding effects on coevolving patterns of vegetation cover and landforms. Results from the simulations showed that drainage network, aspect, and elevation are key drivers of vegetation patterns. A complex pattern was observed in the simulations driven by orographic precipitation combined with spatially-varied solar radiation due to the competition between the effects of slope-controlled solar radiation and orographic precipitation. The combination of orographic precipitation and spatially-varied solar radiation created the highest divide migration due to the gentler windward side slopes than the leeward side of the domain. Our results suggest that the erosive power of increasing runoff under orographic precipitation dominates the effect of vegetation protection on erosion on the windward side of the domain. The last part of the thesis focuses on the data analysis of global net radiation components between climatological and geographical variables. To conduct this analysis, 313 flux stations from the Ameriflux, Fluxnet, and Ozflux networks were used. An analysis of the albedo data for 0900 to 1500 hours was performed to limit the uncertainties associated with low solar elevation angles. An empirical global atmospheric transmissivity model was developed by identifying the two major factors (i.e., aridity index and cloud cover) found to have a significant influence on atmospheric transmissivity. Results for different climatic zones showed that warm temperate regions outperformed arid and equatorial climatic regions due to their underlying higher correlation between atmospheric transmissivity and cloud cover. The findings from the current research provide key insights towards understanding soil moisture and vegetation-landform feedback, as well as advance current knowledge on the long-term spatiotemporal ecohydro-geomorphological interactions in semi-arid ecosystems.
- Subject
- ecohydrology; landscape evolution; ecogeomorphology; solar radiation; orographic precipitation; vegeatation; soil moisture
- Identifier
- http://hdl.handle.net/1959.13/1513996
- Identifier
- uon:56798
- Rights
- Copyright 2021 Ankur Srivastava
- Language
- eng
- Full Text
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