Predictive modelling provides an efficient means to analyse the coastal environment and generate knowledge for long term urban planning. In this study, the numerical models SWAN and XBeach were incorporated into the ESRI ArcGIS interface by means of the BeachMMtool. This was applied to the Greater Christchurch coastal environment to simulate geomorphological evolution through hydrodynamic forcing. Simulations were performed using the recent sea level rise predictions by the Intergovernmental Panel on Climate Change (2013) to determine whether the statutory requirements outlined in the New Zealand Coastal Policy Statement 2010 are consistent with central, regional and district designations. Our results indicate that current land use zoning in Greater Christchurch is not consistent with these predictions. This is because coastal hazard risk has not been thoroughly quantified during the process of installing the Canterbury Earthquake Recovery Authority residential red zone. However, the Christchurch City Council’s flood management area does provide an extent to which managed coastal retreat is a real option. The results of this research suggest that progradation will continue to occur along the Christchurch foreshore due to the net sediment flux retaining an onshore direction and the current hydrodynamic activity not being strong enough to move sediment offshore. However, inundation during periods of storm surge poses a risk to human habitation on low lying areas around the Avon-Heathcote Estuary and the Brooklands lagoon.
Prognostic modelling provides an efficient means to analyse the coastal environment and provide effective knowledge for long term urban planning. This paper outlines how the use of SWAN and Xbeach numerical models within the ESRI ArcGIS interface can simulate geomorphological evolution through hydrodynamic forcing for the Greater Christchurch coastal environment. This research followed the data integration techniques of Silva and Taborda (2012) and utilises their beach morphological modelling tool (BeachMM tool). The statutory requirements outlined in the New Zealand Coastal Policy Statement 2010 were examined to determine whether these requirements are currently being complied with when applying the recent sea level rise predictions by the Intergovernmental Panel on Climate Change (2013), and it would appear that it does not meet those requirements. This is because coastal hazard risk has not been thoroughly quantified by the installation of the Canterbury Earthquake Recovery Authority (CERA) residential red zone. However, the Christchurch City Council’s (CCC) flood management area does provide an extent to which managed coastal retreat is a real option. This research assessed the effectiveness of the prognostic models, forecasted a coastline for 100 years from now, and simulated the physical effects of extreme events such as storm surge given these future predictions. The results of this research suggest that progradation will continue to occur along the Christchurch foreshore due to the net sediment flux retaining an onshore direction and the current hydrodynamic activity not being strong enough to move sediment offshore. However, inundation during periods of storm surge poses a risk to human habitation on low lying areas around the Avon-Heathcote Estuary and the Brooklands lagoon similar to the CCC’s flood management area. There are complex interactions at the Waimakariri River mouth with very high rates of accretion and erosion within a small spatial scale due to the river discharge. There is domination of the marine environment over the river system determined by the lack of generation of a distinct river delta, and river channel has not formed within the intertidal zone clearly. The Avon-Heathcote ebb tidal delta aggrades on the innner fan and erodes on the outer fan due to wave domination. The BeachMM tool facilitates the role of spatial and temporal analysis effectively and the efficiency of that performance is determined by the computational operating system.
Mitigating the cascade of environmental damage caused by the movement of excess reactive nitrogen (N) from land to sea is currently limited by difficulties in precisely and accurately measuring N fluxes due to variable rates of attenuation (denitrification) during transport. This thesis develops the use of the natural abundance isotopic composition of nitrate (δ15N and δ18O of NO₃-) to integrate the spatialtemporal variability inherent to denitrification, creating an empirical framework for evaluating attenuation during land to water NO₃- transfers. This technique is based on the knowledge that denitrifiers kinetically discriminate against 'heavy' forms of both N and oxygen (O), creating a parallel enrichment in isotopes of both species as the reaction progresses. This discrimination can be quantitatively related to NO₃- attenuation by isotopic enrichment factors (εdenit). However, while these principles are understood, use of NO₃- isotopes to quantify denitrification fluxes in non-marine environments has been limited by, 1) poor understanding of εdenit variability, and, 2) difficulty in distinguishing the extent of mixing of isotopically distinct sources from the imprint of denitrification. Through a combination of critical literature analysis, mathematical modelling, mesocosm to field scale experiments, and empirical studies on two river systems over distance and time, these short comings are parametrised and a template for future NO₃- isotope based attenuation measurements outlined. Published εdenit values (n = 169) are collated in the literature analysis presented in Chapter 2. By evaluating these values in the context of known controllers on the denitrification process, it is found that the magnitude of εdenit, for both δ15N and δ18O, is controlled by, 1) biology, 2) mode of transport through the denitrifying zone (diffusion v. advection), and, 3) nitrification (spatial-temporal distance between nitrification and denitrification). Based on the outcomes of this synthesis, the impact of the three factors identified as controlling εdenit are quantified in the context of freshwater systems by combining simple mathematical modelling and lab incubation studies (comparison of natural variation in biological versus physical expression). Biologically-defined εdenit, measured in sediments collected from four sites along a temperate stream and from three tropical submerged paddy fields, varied from -3‰ to -28‰ depending on the site’s antecedent carbon content. Following diffusive transport to aerobic surface water, εdenit was found to become more homogeneous, but also lower, with the strength of the effect controlled primarily by diffusive distance and the rate of denitrification in the sediments. I conclude that, given the variability in fractionation dynamics at all levels, applying a range of εdenit from -2‰ to -10‰ provides more accurate measurements of attenuation than attempting to establish a site-specific value. Applying this understanding of denitrification's fractionation dynamics, four field studies were conducted to measure denitrification/ NO₃- attenuation across diverse terrestrial → freshwater systems. The development of NO₃- isotopic signatures (i.e., the impact of nitrification, biological N fixation, and ammonia volatilisation on the isotopic 'imprint' of denitrification) were evaluated within two key agricultural regions: New Zealand grazed pastures (Chapter 4) and Philippine lowland submerged rice production (Chapter 5). By measuring the isotopic composition of soil ammonium, NO₃- and volatilised ammonia following the bovine urine deposition, it was determined that the isotopic composition of NO₃ - leached from grazed pastures is defined by the balance between nitrification and denitrification, not ammonia volatilisation. Consequently, NO₃- created within pasture systems was predicted to range from +10‰ (δ15N)and -0.9‰ (δ18O) for non-fertilised fields (N limited) to -3‰ (δ15N) and +2‰ (δ18O) for grazed fertilised fields (N saturated). Denitrification was also the dominant determinant of NO₃- signatures in the Philippine rice paddy. Using a site-specific εdenit for the paddy, N inputs versus attenuation were able to be calculated, revealing that >50% of available N in the top 10 cm of soil was denitrified during land preparation, and >80% of available N by two weeks post-transplanting. Intriguingly, this denitrification was driven by rapid NO₃- production via nitrification of newly mineralised N during land preparation activities. Building on the relevant range of εdenit established in Chapters 2 and 3, as well as the soil-zone confirmation that denitrification was the primary determinant of NO₃- isotopic composition, two long-term longitudinal river studies were conducted to assess attenuation during transport. In Chapter 6, impact and recovery dynamics in an urban stream were assessed over six months along a longitudinal impact gradient using measurements of NO₃- dual isotopes, biological populations, and stream chemistry. Within 10 days of the catastrophic Christchurch earthquake, dissolved oxygen in the lowest reaches was <1 mg l⁻¹, in-stream denitrification accelerated (attenuating 40-80% of sewage N), microbial biofilm communities changed, and several benthic invertebrate taxa disappeared. To test the strength of this method for tackling the diffuse, chronic N loading of streams in agricultural regions, two years of longitudinal measurements of NO₃- isotopes were collected. Attenuation was negatively correlated with NO₃- concentration, and was highly dependent on rainfall: 93% of calculated attenuation (20 kg NO₃--N ha⁻¹ y⁻¹) occurred within 48 h of rainfall. The results of these studies demonstrate the power of intense measurements of NO₃- stable isotope for distinguishing temporal and spatial trends in NO₃ - loss pathways, and potentially allow for improved catchment-scale management of agricultural intensification. Overall this work now provides a more cohesive understanding for expanding the use of NO₃- isotopes measurements to generate accurate understandings of the controls on N losses. This information is becoming increasingly important to predict ecosystem response to future changes, such the increasing agricultural intensity needed to meet global food demand, which is occurring synergistically with unpredictable global climate change.
