This thesis examines the feasibility of assimilating space borne remotely-sensed microwave data into WATClass using the ensemble Kalman filter. WATClass is a meso-scale gridded hydrological model used to track water and energy budgets of watersheds by way of real-time remotely sensed data. By incorporating remotely-sensed soil moisture estimates into the model, the model’s soil moisture estimates can be improved, thus increasing the accuracy of the entire model. Due to the differences in scale between the remotely sensed data and WATClass, and the need of ground calibration for accurate soil moisture estimation from current satellite-borne active microwave remote sensing platforms, the spatial variability of soil moisture must be determined in order to characterise the dependency between the remotely-sensed estimates and the model data and subsequently to assimilate the remotely-sensed data into the model. Two sets of data – 1996-1997 Grand River watershed data and 2002-2003 Roseau River watershed data – are used to determine the spatial variability. The results of this spatial analysis however are found to contain too much error due to the small sample size. It is therefore recommended that a larger set of data with more samples both spatially and temporally be taken. The proposed algorithm is tested with simulated data in a simulation of WATClass. Using nominal values for the estimated errors and other model parameters, the assimilation of remotely sensed data is found to reduce the absolute RMS error in soil moisture from 0.095 to approximately 0.071. The sensitivities of the improvement in soil moisture estimates by using the proposed algorithm to several different parameters are examined.

The shallow subsurface controls the partitioning of available energy between sensible and latent heat of the land surface, and the partitioning of available water among evaporation, infiltration, and runoff. It is a key component of both the hydrometeorological system and the terrestrial water cycle. A critical part of any hydrological or hydrometeorological forecast model is therefore the algorithms used to represent the shallow soil processes, which include infiltration, evaporation, runoff, and interflow. For climate models, coupled algorithms called “Land Surface Schemes” (LSSs) are developed to represent the lower boundary conditions that deal with the land-to-atmosphere energy and moisture fluxes. Similar algorithms are implemented in regional watershed models and day-to-day operational water resources forecasting models. It is the primary objective of this thesis to provide improved methods for simulating coupled land surface processes, which can be used as components of LSSs or within existing operational hydrology models. These new methods address a number of specific issues inadequately handled by current models, including the presence of shallow boundary conditions, heterogeneity in infiltration, and infiltration and interflow coupling processes. The main objective of the proposed research is to provide consistent physically-based approach for simulating near surface soil moisture processes, so as to complete the parameterization of the interflow/infiltration algorithm in a Hydrology-Land-Surface scheme MESH. The work mainly focuses on the investigation and development of more physically-based infiltration and interflow algorithms. The hope is to determine appropriate relationships between internal state variables (specifically bulk soil moisture) and system boundary fluxes, while simultaneously reducing the number of nonphysical or unknown model parameters. Fewer parameters lead to reduced calibration requirements for distributed hydrological models and consequently accelerate the transfer of such models to engineering practice. Multiple approaches were taken to provide improved relationships between infiltration and lateral drainage, fluxes and storage. These algorithms were tested by a specialized Richards' equation for sloping soils and Monte Carlo simulations. These tests demonstrated reasonable accuracy and improved representation for the hydrological processes.

Wind transport and sublimation of snow particles are common phenomena across high altitude and latitude cold regions and play important roles in hydrological and atmospheric water and energy budgets. In spite of this, blowing snow processes have not been incorporated in many mesoscale hydrological models and land surface schemes. A physically based blowing snow model, the Prairie Blowing Snow Model (PBSM), initially developed for prairie environments was used to model snow redistribution and sublimation by wind over two sites representative of mountainous regions in Canada: Fisera Ridge in the Rocky Mountain Front Ranges in Alberta, and Granger Basin in the Yukon Territory. Two models were used to run PBSM: the object-oriented hydrological model, Cold Regions Hydrological Modelling Platform (CRHM) and Environment Canadas hydrological-land surface scheme, Modélisation Environmentale Communautaire Surface and Hydrology (MESH). PBSM was coupled with the snowcover energy and mass-balance model (SNOBAL) within CRHM. Blowing snow algorithms were also incorporated into MESH to create MESH-PBSM. CRHM, MESH and MESH-PBSM were used to simulate the evolution of snowcover in hydrological response units (HRUs) over both Fisera Ridge and Granger Basin.<p> To test the models of blowing snow redistribution and ablation over a relatively simple sequence of mountain topography, simulations were run from north to south over a linear ridge in the Canadian Rocky Mountains. Fisera Ridge snowcover simulations with CRHM were performed over two winters using two sets of wind speed forcing: (1) station observed wind speed, and (2) modelled wind speed from a widely applied empirical, terrain-based windflow model. Best results were obtained when using the site meteorological station wind speed data. The windflow model performed poorly when comparing the magnitude of modelled and observed wind speeds. Blowing snow sublimation, snowmelt and snowpack sublimation quantities were considerably overestimated when using the modelled wind speeds. As a result, end-of-winter snow accumulation was considerably underestimated on windswept HRUs. MESH and MESH-PBSM were also used to simulate snow accumulation and redistribution over these same HRUs. MESH-PBSM adequately simulated snow accumulation in the HRUs up until the spring snowmelt period. MESH without PBSM performed less well and overestimated accumulation on windward slopes and the ridge top whilst underestimating accumulation on lee slopes. Simulations in spring were degraded by a large overestimation of melt by MESH. The early and overestimated melt warrants a detailed examination that is outside the scope of this thesis.<p> To parameterize snow redistribution in a mountain alpine basin, snow redistribution and sublimation by wind were calculated for three winters over Granger Basin using CRHM. Snow transport fluxes were distributed amongst HRUs using inter-HRU snow redistribution allocation factors. Three snow redistribution schemes of varying complexity were evaluated. CRHM model results showed that end-of-winter snow accumulation can be most accurately simulated when the inter-HRU snow redistribution schemes take into account wind direction and speed and HRU aerodynamic characteristics, along with the spatial arrangement of HRUs in the catchment. As snow transport scales approximately with the fourth power of wind speed (u4), inter-HRU snow redistribution allocation factors can be established according to the predominant u4 direction over a simulation period or can change at each time step according to an input measured wind direction. MESH and MESH-PBSM were used to simulate snow accumulation and ablation over these same HRUs. MESH-PBSM provided markedly better results than MESH without blowing snow algorithms.<p> That snow redistribution by wind can be adequately simulated in computationally efficient HRUs over mountainous terrain has important implications for representing snow transport in large-scale hydrology models and land surface schemes. Snow redistribution by wind caused mountain snow accumulation to vary from 10% to 161% of seasonal snowfall within a headwater catchment in the Canadian Rocky Mountains, and blowing snow sublimation losses ranged from 10 to 37% of seasonal snowfall.

This study focuses on the relationship between hydrological and nutrient conditions in seawater surrounded by Dongsha Atoll. Dongsha Atoll is located in the northern South China Sea (NSCS), the water properties should be in coherence with the NSCS water masses. However, due to the semi-enclosed topography the water inside Dongsha Atoll is largely affected by local insolation and rainfall. Significant relationships between SiO2 or PO43- and salinity indicate that rainfall could be a major source of these nutrients. Insignificant relationship between N+N and salinity indicates that rainfall and nitrogen fixation both might affect the distribution of N+N. Temporal variations of temperature and chlorophyll a were alike, except for which occurred in July, 2011. It was probably caused by photo inhibition on phytoplankton growth. The inventory of chlorophyll a was positively correlated with both N+N and SiO2 but not with of PO43-, indicating that phytoplankton growth in Dongsha Atoll was mainly affected by N+N and SiO2. Phytoplankton growth maybe limited by N+N but not by SiO2, as the concentration of SiO2 was mostly beyond the limitation concentration for phytoplankton. According to close relationships between chlorophyll a and TSM, POC and PN, the particulate matter maybe mainly derived from biological origins. The inventory of chlorophyll a was positively correlated with both dissolved organic carbon (DOC) and dissolved organic nitrogen (DON), manifesting the importance of biological origins for DOC and DON concentration. The ratios of DOC/DON, DON/DOP and DOC/DOP within the atoll were in ranges of 7.34-303 (mean: 30.4), 3.00-142 (mean: 22.7) and 104-2546 (mean: 421), respectively. The ratios are higher than those values in NSCS and East China Sea, implying the excretion of carbon-enriched DOM by phytoplankton. The concentration of chlorophyll a, DOC and POC were higher in the Small Lagoon than in the Atoll Lagoon, implying a relatively high productivity in the Small Lagoon. The fluxes of carbonate in the atoll was more than 30 times of the flux in the NSCS, due to its unique characteristics in the coral reef habitat. The organic matter of settling particulates was mainly derived from biological sources. The metal of enrichment factor of settling particulates reveals that Fe and Al are mainly derived from crustal sources, while Cu, Zn and Pb are likely influenced by anthropogenic sources.

In this study, I examined the influence of hydrological seasonality on spatiotemporal variation of algal biomass and shrimp abundance on sandbanks of the Cinaruco River in southwestern Venezuela. Seasonal variations of abiotic and biotic variables in the Cinaruco were driven by the hydrological regime. During the highwater periods, river sites in the main channel and lagoon sites were similar in water physicochemical variables and algal biomass. In contrast, physicochemical variables and algal biomass differed between river and lagoon sites during the low-water period. The absence of flow in lagoons and consistently low algal biomass on river sandbanks were the most important features of the spatial variability between main-channel and lagoon sandbanks during low-water phases. Benthic algal biomass was highly uniform at small spatial scales and significantly heterogeneous at large spatial scales. In the second major part of this dissertation, I found a relatively species-rich shrimp assemblage with seven species inhabiting the sandbanks of the Cinaruco. I also observed clear patterns of temporal and spatial variation in shrimp abundance on the Cinaruco sandbanks. Abundance of shrimp on the sandbanks presented remarkable diel variation, showing almost exclusive use of this habitat at nights. Seasonally, shrimp were more abundant during rising- and falling-water periods, when rapid changes of environmental conditions occur. Shrimp abundance was high on those sandbanks with absence of troughs and presence of submerged vegetation. These environmental features presumably promote colonization/establishment and survival/persistence of shrimp in the sandbanks. In a patch-dynamic view of communities, a mobility control model seems to apply to shrimp of the sandbanks in the Cinaruco during the period of rapid changes in hydrology and habitat structure. During low-water periods, when habitat structure of sandbanks is relatively constant, low shrimp abundance appears to be heavily controlled by high fish predation. The annual flood regime of the Cinaruco, which drives the concentrations of dissolved materials, affects material interchanges between aquatic and terrestrial systems, and modifies aquatic habitat structural complexity, is responsible for creating strong patterns of seasonal and spatial variation in benthic algal crops and shrimp abundance on the sandbanks of this large floodplain river.

published_or_final_version / Civil Engineering / Master / Master of Philosophy

The shallow subsurface controls the partitioning of available energy between sensible and latent heat of the land surface, and the partitioning of available water among evaporation, infiltration, and runoff. It is a key component of both the hydrometeorological system and the terrestrial water cycle. A critical part of any hydrological or hydrometeorological forecast model is therefore the algorithms used to represent the shallow soil processes, which include infiltration, evaporation, runoff, and interflow. For climate models, coupled algorithms called “Land Surface Schemes” (LSSs) are developed to represent the lower boundary conditions that deal with the land-to-atmosphere energy and moisture fluxes. Similar algorithms are implemented in regional watershed models and day-to-day operational water resources forecasting models. It is the primary objective of this thesis to provide improved methods for simulating coupled land surface processes, which can be used as components of LSSs or within existing operational hydrology models. These new methods address a number of specific issues inadequately handled by current models, including the presence of shallow boundary conditions, heterogeneity in infiltration, and infiltration and interflow coupling processes. The main objective of the proposed research is to provide consistent physically-based approach for simulating near surface soil moisture processes, so as to complete the parameterization of the interflow/infiltration algorithm in a Hydrology-Land-Surface scheme MESH. The work mainly focuses on the investigation and development of more physically-based infiltration and interflow algorithms. The hope is to determine appropriate relationships between internal state variables (specifically bulk soil moisture) and system boundary fluxes, while simultaneously reducing the number of nonphysical or unknown model parameters. Fewer parameters lead to reduced calibration requirements for distributed hydrological models and consequently accelerate the transfer of such models to engineering practice. Multiple approaches were taken to provide improved relationships between infiltration and lateral drainage, fluxes and storage. These algorithms were tested by a specialized Richards' equation for sloping soils and Monte Carlo simulations. These tests demonstrated reasonable accuracy and improved representation for the hydrological processes.

Technological and methodological advances of the past few decades have provided hydrologists with advanced and increasingly complex hydrological models. These models improve our ability to simulate hydrological systems, but they also require a lot of detailed input data and, therefore, have a limited applicability in locations with poor data availability. From a case study of Big Creek watershed, a 186.4 km2 urbanizing watershed in Atlanta, GA, for which continuous flow data are available since 1960, this project investigates the relationship between model complexity, data availability and predictive performance in order to provide reliability factors for the use of reduced complexity models in areas with limited data availability, such as small ungaged watersheds in similar environments. My hope is to identify ways to increase model efficiency without sacrificing significant model reliability that will be transferable to ungaged watersheds.

Ephemeral streams are small headwater streams that only experience streamflow in response to a precipitation event. Due to their highly complex and dynamic spatial and temporal nature, ephemeral streams have been difficult to monitor and are in general poorly understood. This research implemented an extensive network of recently developed electrical resistance sensors to monitor ephemeral streamflow in a Southern Ontario watershed, located in Guelph, Ontario. From this data, patterns of stream network expansion and contraction were determined. Further analysis examined a series of spatial and temporal variables that were monitored to explain the occurrence of ephemeral channel activity through binary logistic regression. The results suggest that the most common patterns of network expansion and contraction at the study site are incomplete coalescence and disintegration, respectively. Analysis of the primary controls on ephemeral streamflow showed only weak relationships, suggesting that there are more complex processes at work in these ephemeral streams. This research has implications for improving ephemeral streamflow monitoring in the future, which will be important for developing and implementing meaningful conservation and management strategies.

The potential impact of sea level rise on Lake Ellesmere - Te Wiahora and the subsequent effect on the efficiency and performance of the L2 Drainage network was investigated in relation to the operation of the L2 Drainage scheme. Lake Ellesmere is currently manually opened for drainage to the sea when the lake levels reach 1.05 m above mean sea level (asl) in summer and 1.13 m asl in winter. With a rise in sea level, the lake opening levels for both summer and winter would have to increase in order to maintain the current hydraulic gradient. Higher lake levels would impact drainage schemes such as the L2 drainage network. An integral research approach was used to study this potential impact, including fieldwork, analysis of data, hydrologic and hydraulic modelling. Both the hydrologic and hydraulic response of the L2 catchment and river were reproduced with reasonable accuracy by the use of computational models. Simulations of 2, 10 and 20 year annual recurrence intervals (ARI) rainstorm events coupled with higher lake levels show increase flooding along the length of the river. An increase in the lake opening levels, coupled with south-easterly wind was shown to have increased the degree of flooding on adjacent farmlands, but only a 3.50 per cent increase of water level (for all conditions simulated) 3.5 km upstream of the L2 River. The study clearly shows that weed growth within the L2 River plays an important part in controlling the water level within the channel. Results show it was responsible for an observed water level rise of 0.30 m from the winter to summer season. The combined use of hydraulic and hydrological models provides an effective tool to study future impacts on the drainage efficiency and performance of the L2 drainage scheme and other similar systems. The potential for both models to be used as a predictive tool for improving the operation of the L2 scheme and Lake Ellesmere was only limited by the difficulty in estimating model parameters especially for the hydrologic model.