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This thesis explores several important hydrological modelling topics surrounding the use of continuous rainfall-runoff simulation for flood frequency estimation. A continuous simulation methodology suitable for flood frequency estimation is developed. The methodology features a rainfall-runoff model (TOPMODEL, e.g. Beven, 1997), a new profile-based stochastic rainfall model (developed in this thesis), and an uncertainty estimation procedure (Generalised Likelihood Uncertainty Estimation, or GLUE e.g. Beven and Binley, 1992). By explicitly accounting for a catchment's soil moisture conditions, allowing the direct simulation of long return period flood events (via the coupling of TOPMODEL with the stochastic rainfall model), and quantifying the uncertainty associated with the simulated flood estimates, this methodology is an attractive alternative to the more traditional statistical and event-based techniques available for flood frequency estimation. It is tested successfully using data obtained from five, gauged, UK catchments. In addition to exploring the possible consistency between flood peak and continuous flow rainfall-runoff model parameterisations, the methodology is used to examine the potential impacts of climatic change upon flood frequency. Two further issues are also addressed. These are: the choice of stochastic rainfall model (for use within continuous simulation studies), and the modification of a pulse-based stochastic rainfall model for enhanced extreme rainfall simulation.

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SUMMARY Mangrove ecosystems thrive in (sub)tropical, intertidal areas where adaptations like vivipary and the hydrochorous dispersal of propagules become an absolute necessity. As propagule dispersal and early growth allow for the replenishment of existing stands and colonization of new habitats, many authors recognize the importance of these stages in structuring mangrove populations and communities. However, when it comes to the actual propagule dispersal and recruitment mechanisms, there is an apparent lacuna in the current understanding of mangrove ecology. The period between the mature propagule falling from the parental mangrove tree and the early growth of the established seedling, under various possible circumstances, remains in the dark. In this study we focus on this particular period by investigating both the places where these propagules end up as the pathways their dispersal units follow. And we go one step further. Mangrove forests are being destroyed worldwide at a threatening pace despite their tremendous asset to coastal human communities and associated biological species. The effect of human-induced (cutting and mangrove conversion to aquaculture ponds) as well as indirectly and/or ‘naturally’ evolving disturbances (sea level rise) on propagule hydrochory occupies an important place in this study. Dispersal of water-buoyant propagules of the family Rhizophoraceae and Acanthaceae (now including the Avicenniaceae) was studied in Gazi Bay (Kenya), Galle and the Pambala-Chilaw Lagoon Complex (Sri Lanka). The study sites differ both in tidal regime and vegetation structure, covering an interesting variety of ecological settings to examine propagule dispersal. Field data and experiments ranging from micro/ mesotopographical measurements and successive propagule counts to hydrodynamic and propagule dispersal experiments were collected or executed in situ. Two main methodological approaches were employed. Firstly, the question on mechanisms of propagule recruitment was addressed by statistically investigating the effect of microtopography, top soil texture and above-ground-root complexes on the stranding and self-planting of propagules (Chapter 2&3). Afterwards, suitability maps were created using Geographical Information Systems (GIS) to assess whether a particular mangrove stand has the ability to succesfully rejuvenate. Furthermore, the effect of degradation (tree cutting) (Chapter 2&3), sea level rise (Chapter 2&4) and microtopography-altering burrowing activities of the mangrove mud lobster Thalassina anomala (Chapter 3), was incoporated in the GIS-analyses. Secondly, the combined set-up of hydrodynamic modelling and ecological dispersal modelling was developed to simulate propagule dispersal pathways influenced by dispersal vectors (tidal flow, fresh water discharge, wind), trapping agents (retention by vegetation or aerial root complexes) and seed characteristics (buoyancy, obligated dispersal period) (Chapter 5&6). This type of approach provided the possibility to explore propagule dispersal within its ecological context, but was also applied to an implication of shrimp pond area restoration (Pambala-Chilaw Lagoon Complex, Sri Lanka) (Chapter 5) and to evaluate changes in propagule dispersal when sea level rises (Gazi Bay, Kenya) (Chapter 6). The main findings regarding propagule recruitment indicate that propagules are not distributed equally or randomly within a mangrove stand, yet species-specific distribution for anchorage occurs. Characteristics of the environment (microtopography, top soil texture and above-ground root complex) influence propagule recruitment in a way that complex root systems (e.g. pencil roots and prop roots) facilitate the entanglement of dispersal units and a more compact soil texture (like clay and silt) and a predominant flat topography creates suitable areas for stranding and self-planting of propagules. This combines effects of existing vegetation and abiotic factors on mangrove propagule establishment. Since propagule dispersal is not solely determined by species-specific propagule characteristics (e.g. buoyancy, longevity, etc.), I emphasize that propagule sorting by hydrochory has to be viewed within its ecological context. Propagule retention by vegetation and wind as a dispersal vector, deserve a prominent role in studies on propagule dispersal. The significance of dense vegetation obstructing long distance dispersal (LDD in its definition of this work), mainly in inner mangrove zones, supports our main finding that propagule dispersal is largely a short distance phenomenon. ‘Largely’ is here understood as quantitatively, not excluding epic colonization events of rare but important nature. In accordance with the Tidal Sorting Hypothesis (TSH) of Rabinowitz (1978a), smaller, oval-shaped propagules were found to disperse over larger distances than bigger, torpedo-shaped propagules. We can however not fully support the TSH because (1) these differences are no longer valid when comparing between torpedoshaped propagules of different sizes and (2) propagule dispersal is not always directed towards areas more inland, but can be strongly concentrated towards the edges of lagoons and channels Anthropogenic pressure on mangrove ecosystems, more specifically clear-felling or mangrove conversion to aquaculture ponds, imposes limitations on propagule recruitment due to reduced propagule availability and a decrease in suitable stranding areas where the architecture of certain root complexes, like prop roots and pencil roots, function as propagule traps. These types of pressure appear to have more severe consequences on propagule dispersal than the effect of sea level rise on mangroves. Mangrove forests, which are not situated in an obviously vulnerable setting, can be resilient to a relative rise in sea level if a landward shift of vegetation assemblages and successful early colonization is not obstructed by human-induced pressures. Also, and this renders mangrove forests vulnerable in spite of their intrinsic resilience, when the ‘capital’ of forest is severely reduced or impoverished as happens extensively worldwide, the ‘interest’ on this capital, understood as propagule availability, delivery and trapping, will not allow them to efficiently cope with sea level rise, putting sustainability of mangrove ecosystem services and goods at risk. In a larger framework of mangrove vegetation dynamics, knowledge on propagule dispersal will benefit management strategies for the conservation of mangroves worldwide, besides its fundamental interest to fully fathom the ecology of this particular marine-terrestrial ecotone formation.

This thesis develops a methodology for mesoscale model verification and validation that is founded on the rigorous constraint imposed by the need to conserve both water mass and isotopes simultaneously. The isoWATFLOOD model simulates δⁱ⁸O in streamflow, which effectively reduces and constrains errors associated with equifinality in streamflow generation by improving internal parameterizations. The WATFLOOD model is a conceptually-based distributed hydrological model used for simulating streamflow on mesoscale watersheds. Given the model’s intended application to mesoscale hydrology, it remains crucial to ensure conceptualizations are physically representative of the hydrologic cycle and the natural environment. Stable water isotopes because of their natural abundance and systematic fractionation have the ability to preserve information on water cycling across large domains. Several coordinated research projects have recently focused on integrating stable water isotopes into global and regional circulation models, which now provides the opportunity to isotopically force land-surface and hydrological models. Where traditionally streamflows are the primary validation criteria in hydrological modelling, problems arise in remote and ungauged basins, or large watersheds where streamflows may not be well monitored. By streamflow validation alone, no insight is obtained on the internal apportioning and physical representation of sub-processes contributing to streamflow. The primary goal of this research is to develop alternative measures to parameterize mesoscale hydrological models in a physically-based manner, and to validate such models over large domains. This research develops improved model parameterizations that facilitate realistic runoff generation process contributions. The examination of runoff generation processes and the subsequent δⁱ⁸O of these processes are performed for two mesoscale watersheds: Fort Simpson, NWT and the Grand River Basin, ON. The isoWATFLOOD model is shown to reliably predict streamflow and δⁱ⁸O of streamflow, and simulates mesoscale isotopic fractionation associated with evaporation. In doing so, a more physically meaningful, robust modelling tool is developed that is practical for operational use. This research also contributes the first continuous record of δⁱ⁸O in streamflow that enables the visualization of spatial and temporal variability and dominant hydrologic controls within mesoscale watersheds.

There is a lack of measured, long-term, reliable, and well-distributed hydrological variables in Canada. These hydrological variables include, but are not limited to: temperature, precipitation, ground runoff, evapotranspiration, soil moisture, and snow water equivalent. The objective of this thesis was to establish the best possible distributed estimates of these hydrological variables for Canada over the period of 1961-2000. The first step was to interpolate measured temperature and precipitation across the country. These interpolated values were then used to calculate the other hydrological variables using the Waterloo Flood Forecasting Model (WATFLOOD). The Waterloo Mapping technique (WATMAP) was developed to use topographic and land cover databases to automatically and systematically derive the information needed to create the drainage database. WATFLOOD was calibrated with the Dynamically Dimensioned Search (DDS) algorithm using the difference between the measured and simulated streamflow as the objective function. After a final calibration of 100 separate DDS runs, distributed time series for the hydrological variables were created. A simple assessment was made for the predictive uncertainty in the simulated streamflow results based on the results of the final calibration. As well, the implications of various climate change scenarios were examined in the context of how they would change the hydrological variables. The major recommendations for future study included: finding other gridded datasets that could be used to verify the ones that were created in this study and examining further the magnitudes of the different kinds of predictive uncertainty (data, model, and parameter). The results of this thesis fit in well with the goals of the study on Predictions in Ungauged Basins. This thesis was organized along the principle of “design the process, not the product”. As such, although a set of final products are presented at the end, the most important part of the thesis was the process that achieved these products. Thus it is not assumed that every technique designed in this thesis will be applicable to every other researcher, but it hoped that most researchers in the field will be able to use at least some parts of the techniques developed here.

Distributed hydrological models have been used for decades to calculate and predict the movement of water and energy within watersheds. These models have evolved from relatively simple empirical applications into complex spatially distributed and physically-based programs. However, the evolution of distributed hydrological models has not involved the improvement of the numerical methods used to calculate the redistribution of water and energy in the watershed. Because of this, many models still use numerical methods that are potentially inaccurate. In order to simulate the transport of water and energy in a hydrological model, typical numerical methods employ an operator splitting approach. Operator splitting (OS) essentially breaks down the set of coupled ordinary differential equations (ODEs) that define a hydrological model into separate ODEs that can be solved individually. The dominant operator splitting method in surface water models is the ordered series approach. Because the ordered series approach treats parallel hydrological processes as if they happen in series, it is prone to errors that can significantly reduce the accuracy of model results. The impact that operator splitting errors have upon hydrologic model results is, to date, unknown. Using a new distributed hydrological model, Raven, the impact of operator splitting errors is investigated. Understanding these errors will lead to better numerical methods for reducing errors in models and to shed light on the shortcomings of hydrological models with respect to numerical method choice. Alternative numerical methods - the explicit Euler and the implicit iterative Heun methods - are implemented and assessed in their ability to minimize errors and produce more accurate distributed hydrological models.

This thesis develops a methodology for mesoscale model verification and validation that is founded on the rigorous constraint imposed by the need to conserve both water mass and isotopes simultaneously. The isoWATFLOOD model simulates δⁱ⁸O in streamflow, which effectively reduces and constrains errors associated with equifinality in streamflow generation by improving internal parameterizations. The WATFLOOD model is a conceptually-based distributed hydrological model used for simulating streamflow on mesoscale watersheds. Given the model’s intended application to mesoscale hydrology, it remains crucial to ensure conceptualizations are physically representative of the hydrologic cycle and the natural environment. Stable water isotopes because of their natural abundance and systematic fractionation have the ability to preserve information on water cycling across large domains. Several coordinated research projects have recently focused on integrating stable water isotopes into global and regional circulation models, which now provides the opportunity to isotopically force land-surface and hydrological models. Where traditionally streamflows are the primary validation criteria in hydrological modelling, problems arise in remote and ungauged basins, or large watersheds where streamflows may not be well monitored. By streamflow validation alone, no insight is obtained on the internal apportioning and physical representation of sub-processes contributing to streamflow. The primary goal of this research is to develop alternative measures to parameterize mesoscale hydrological models in a physically-based manner, and to validate such models over large domains. This research develops improved model parameterizations that facilitate realistic runoff generation process contributions. The examination of runoff generation processes and the subsequent δⁱ⁸O of these processes are performed for two mesoscale watersheds: Fort Simpson, NWT and the Grand River Basin, ON. The isoWATFLOOD model is shown to reliably predict streamflow and δⁱ⁸O of streamflow, and simulates mesoscale isotopic fractionation associated with evaporation. In doing so, a more physically meaningful, robust modelling tool is developed that is practical for operational use. This research also contributes the first continuous record of δⁱ⁸O in streamflow that enables the visualization of spatial and temporal variability and dominant hydrologic controls within mesoscale watersheds.

There is a lack of measured, long-term, reliable, and well-distributed hydrological variables in Canada. These hydrological variables include, but are not limited to: temperature, precipitation, ground runoff, evapotranspiration, soil moisture, and snow water equivalent. The objective of this thesis was to establish the best possible distributed estimates of these hydrological variables for Canada over the period of 1961-2000. The first step was to interpolate measured temperature and precipitation across the country. These interpolated values were then used to calculate the other hydrological variables using the Waterloo Flood Forecasting Model (WATFLOOD). The Waterloo Mapping technique (WATMAP) was developed to use topographic and land cover databases to automatically and systematically derive the information needed to create the drainage database. WATFLOOD was calibrated with the Dynamically Dimensioned Search (DDS) algorithm using the difference between the measured and simulated streamflow as the objective function. After a final calibration of 100 separate DDS runs, distributed time series for the hydrological variables were created. A simple assessment was made for the predictive uncertainty in the simulated streamflow results based on the results of the final calibration. As well, the implications of various climate change scenarios were examined in the context of how they would change the hydrological variables. The major recommendations for future study included: finding other gridded datasets that could be used to verify the ones that were created in this study and examining further the magnitudes of the different kinds of predictive uncertainty (data, model, and parameter). The results of this thesis fit in well with the goals of the study on Predictions in Ungauged Basins. This thesis was organized along the principle of “design the process, not the product”. As such, although a set of final products are presented at the end, the most important part of the thesis was the process that achieved these products. Thus it is not assumed that every technique designed in this thesis will be applicable to every other researcher, but it hoped that most researchers in the field will be able to use at least some parts of the techniques developed here.

Distributed hydrological models have been used for decades to calculate and predict the movement of water and energy within watersheds. These models have evolved from relatively simple empirical applications into complex spatially distributed and physically-based programs. However, the evolution of distributed hydrological models has not involved the improvement of the numerical methods used to calculate the redistribution of water and energy in the watershed. Because of this, many models still use numerical methods that are potentially inaccurate. In order to simulate the transport of water and energy in a hydrological model, typical numerical methods employ an operator splitting approach. Operator splitting (OS) essentially breaks down the set of coupled ordinary differential equations (ODEs) that define a hydrological model into separate ODEs that can be solved individually. The dominant operator splitting method in surface water models is the ordered series approach. Because the ordered series approach treats parallel hydrological processes as if they happen in series, it is prone to errors that can significantly reduce the accuracy of model results. The impact that operator splitting errors have upon hydrologic model results is, to date, unknown. Using a new distributed hydrological model, Raven, the impact of operator splitting errors is investigated. Understanding these errors will lead to better numerical methods for reducing errors in models and to shed light on the shortcomings of hydrological models with respect to numerical method choice. Alternative numerical methods - the explicit Euler and the implicit iterative Heun methods - are implemented and assessed in their ability to minimize errors and produce more accurate distributed hydrological models.