The development of regional flood-frequency equations is a key component of engineering infrastructure design and flood risk assessment at ungauged sites. These equations are constructed based on regression analysis techniques to study the connection between peak flow observations and different explanatory variables. However, many regions of the world remain poorly gauged or have experienced dramatic changes in land use or climate that make past observations less useful. To remedy this situation, we need to interpret and construct these regional equations based on physical principles of water movement and general knowledge of the geographic and geomorphologic setting of the upstream catchment at the location of interest. Several studies have examined these regional equations through the scaling theory of floods, making physical interpretations of the equation parameters (or scaling parameters) with respect to rainfall properties and geomorphologic variables. However, despite the advances of these previous works, the scaling theory of floods must be concerted with different, well-known problems in statistical hydrology for a proper engineering application in flood regionalization. These problems can vary from limitations in peak flow observations (sampling errors) to selection of an inadequate model structure of peak flows (epistemic errors). I present a series of studies based on hydrologic simulations and peak flow observations that illustrate several aspects related to the application and use of the scaling theory of floods, which include the following: (1) description of spatial patterns of scaling parameters; (2) inclusion of river network descriptors in flood frequency equations; and (3) evaluation of sampling errors and epistemic errors in the construction of flood frequency equations. The results presented in this dissertation contribute to the development of a more complete regional flood frequency analysis framework that leverages the physics of peak flow scaling and river network descriptors.

<p>Hydrological modeling has been a valuable tool to understand the processes governing water distribution, quantity, and quality of the planet Earth. Through models, one has been able to grasp processes such as runoff, soil moisture, soil erosion, subsurface drainage, plant growth, evapotranspiration, and effects of land use changes on hydrology at field and watershed scales. The number and diversity of water-related challenges are vast and expected to increase. As a result, current models need to be under continuous modifications to extend their application to more complex processes. Several models have been extensively developed in recent years. These models include the Soil and Water Assessment Tool (SWAT), Variable Infiltration Capacity (VIC) model, MIKE-SHE, and the Water Erosion Prediction Project (WEPP) model. The latter, although it is a well-validated model at field scales, the WEPP watershed model has been limited to small catchments, and almost no research has been introduced regarding water quality issues (only one study).</p><p>In this research, three objectives were proposed to improve the WEPP model in three areas where either the model has not been applied, or modifications can be performed to improve algorithms of the processes within the model (e.g. erosion, runoff, drainage). The enhancements impact the WEPP model by improving the current stochastic weather generation, extending its applicability to subsurface drainage estimation, and formulating a new routing model that allows future incorporation of transport of reactive solutes.</p><p>The first contribution was development of a stochastic storm generator based on 5-min time resolution and correlated non-normal Monte Carlo-based numerical simulation. The model considered the correlated and non-normal rainstorm characteristics such as time between storms, duration, and amount of precipitation, as well as the storm intensity structure. The model was tested using precipitation data from a randomly selected 5-min weather station in North Carolina. Results showed that the proposed storm generator captured the essential statistical features of rainstorms and their intensity patterns, preserving the first four moments of monthly storm events, good annual extreme event correspondence, and the correlation structure within each storm. Since the proposed model depends on statistical properties at a site, this may allow the use of synthetic storms in ungauged locations provided relevant information from a regional analysis is available.</p><p>A second development included the testing, improvement, and validation of the WEPP model to simulate subsurface flow discharges. The proposed model included the modification of the current subsurface drainage algorithm (Hooghoudt-based expression) and the WEPP model percolation routine. The modified WEPP model was tested and validated on an extensive dataset collected at four experimental sites managed by USDA-ARS within the Lake Erie Watershed. Predicted subsurface discharges show Nash-Sutcliffe Efficiency (NSE) values ranging from 0.50 to 0.70, and percent bias ranging from -30% to +15% at daily and monthly resolutions. Evidence suggests the WEPP model can be used to produce reliable estimates of subsurface flow with minimum calibration.</p><p>The last objective presented the theoretical framework for a new hillslope and channel-routing model for the Water Erosion Prediction Project (WEPP) model. The routing model (WEPP-CMT) is based on catchment geomorphology and mass transport theory for flow and transport of reactive solutes. The WEPP-CMT uses the unique functionality of WEPP to simulate hillslope responses under diverse land use and management conditions and a Lagrangian description of the carrier hydrologic runoff at hillslope and channel domains. An example of the model functionality was tested in a sub-catchment of the Upper Cedar River Watershed in the U.S. Pacific Northwest. Results showed that the proposed model provides an acceptable representation of flow at the outlet of the study catchment. Model efficiencies and percent bias for the calibration period and the validation period were NSE = 0.55 and 0.65, and PBIAS = -2.8% and 2.1%, respectively. The WEPP-CMT provides a suitable foundation for the transport of reactive solutes (e.g. nitrates) at basin scales.</p><p><br></p>

Simulating the processes of rainfall and runoff are at the core of hydrologic modeling. Geomorphologic features, rainfall variability, soil types, and water table depths strongly influence hydrological process in Florida ecosystems. Topographic characteristics of the terrain define the stream paths and landscape. Alteration of these characteristics as a result of urban and/or agricultural developments, for example, can highly influence wetlands and river basin response. There are two predominant landforms in Florida: wetlands, where Variable Saturated Areas form near streams causing saturation excess runoff, and uplands where runoff is mainly generated by infiltration excess. The objective of this work is to analyze the impacts of geomorphologic and hydrologic characteristics on runoff mechanisms in humid environments such as Florida. In general, most research at the hillslope scale use hypothetical values of rainfall, sometimes non-realistic values, and single slope forms to explain the geomorphic and hydrologic process on Variable Saturated Areas. In this thesis, the complexity of hillslope processes on actual Florida topography is assessed by coupling a Digital Elevation Model with a two-dimensional variable saturated-unsaturated flow model called HYDRUS-2D. Actual rainfall records and soil parameters from the Characterization Data for Selected Florida Soils, Soil Survey were used to evaluate hydrologic impacts. A commercial software package, River Tools was used to display and extract topographic information from the Digital Elevation Models. Results show that when inflitration excess runoff is dominant, infiltration and runoff are very sensitive to time resolution, especially for convective storms. When saturation excess occurs, runoff is not affected by rainfall intensity. However, saturated hydraulic conductivity, depth to the water table, slope and curvature highly influence the extent of Variable Saturated Areas. Results indicate runoff in shallow water table environments is produced mainly by subsurface storm runoff, running below the surface, except in hillslopes with concave curvature and mild slopes. Additionally, concave hillslopes generate more saturation excess runoff than straight and convex hillslopes.

Soil moisture influences the water and energy cycles of terrestrial environments, and thus plays an important climatic role. However, the behavior of soil moisture at large scales, including its impact on atmospheric processes such as precipitation, is not well characterized. Satellite remote sensing allows for indirect observation of large-scale soil moisture, but validation of these data is complicated by the difference in scales between remote sensing footprints and direct ground-based measurements. To address this problem, a method, based on information theory (specifically, mutual information), was developed to determine the useful information content of satellite soil moisture records using precipitation observations. This method was applied to three soil moisture datasets derived from Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements over the contiguous U.S., allowing for spatial identification of the algorithm with the least inferred error. Ancillary measures of biomass and topography revealed a strong dependence between algorithm performance and confounding surface properties. Next, statistical causal identification methods (i.e. Granger causality) were used to examine the link between AMSR-E soil moisture and the occurrence of next day precipitation, accounting for long term variability and autocorrelation in precipitation. The probability of precipitation occurrence was modeled using a probit regression framework, and soil moisture was added to the model in order to test for statistical significance and sign. A contrasting pattern of positive feedback in the western U.S. and negative feedback in the east was found, implying a possible amplification of drought and flood conditions in the west and damping in the east. Finally, observations and simulations were used to demonstrate the pitfalls of determining causality between soil moisture and precipitation. It is shown that ignoring long term variability and precipitation autocorrelation can result in artificial positive correlation between soil moisture and precipitation, unless explicitly accounted for in the analysis. In total, this dissertation evaluates large-scale soil moisture measurements, outlines important factors that can cloud the determination of land surface-atmosphere hydrologic feedback, and examines the causal linkage between soil moisture and precipitation at large scales.

Wetlands are important elements of watersheds that influence water storage, surface water runoff, groundwater recharge/discharge processes, and evapotranspiration. To understand the cumulative effect wetlands have on a watershed, one must have a good understanding of the water-level fluctuations and the storage characteristics associated with multiple wetlands across a region. An improved analytical method is presented to describe the storage characteristics of wetlands in the absence of detailed hydrologic and bathymetric data. Also, a probabilistic approach based on frequency analysis is developed to provide insight into surface and groundwater interactions associated with isolated wetlands. The results of the work include: 1) a power-function model based on a single fitting parameter and two physically based parameters was developed and used to represent the storage of singular or multiple wetlands and lakes with acceptable error, 2) a novel hydrologic characterization applied to 56 wetlands in west-central Florida provided new information about wetland hydroperiods which indicated standing water was present in the wetlands 62% of the time and these wetlands were groundwater recharge zones 59% of the time over the seven year study, 3) the smallest extreme value probability distribution function was identified as the best-fit model to represent the water levels of five wetland categories in west-central Florida, 4) representative probability models were developed and used to predict the water levels of specific wetland categories, averaging less than 10% error between the predicted and recorded water levels, and 5) last, based on this probability analysis, the various wetland categories were shown to exhibit similar means, extremes and ranges in water-level behavior but unique slopes in frequency distributions, a here to for new finding. These results suggest that wetland types may best be differentiated by the regular variability in water levels, not by the mean and/or extreme water levels. The methods and analytical techniques presented in this dissertation can be used to help understand and quantify wetland hydrology in different climatological or anthropogenic stress conditions. Also, the methods explored in this study can be used to develop more accurate and representative hydrologic simulation models.

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>Magister Scientiae - MSc / The research was driven by a need to increase the knowledge base concerning wetland ecological responses, as well as to identify and evaluate the factors driving the functioning of the Franschhoek Trust Wetland. An ecohydrological study was undertaken in which vegetation cover, depth to groundwater, water and soil chemistry were monitored at 14 sites along three transects for a 12 month period. The parameters used include temperature, pH, electrical conductivity (EC), sodium, potassium, magnesium, calcium, iron, chloride, bicarbonate, sulphate, total nitrogen, ammonia, nitrate, nitrite and phosphorus. T-tests and Principal Component Analysis (PCA) were used to analyze trends and to express the relationship between abiotic factors and vegetation. Results reflect the strong influence of hydrology, microtopography and nutrient availability in structuring vegetation composition in the wetland. The wetland has been classified as a palustrine valley bottom with channel wetland, which is predominantly groundwater-fed (phreatrotropic), but receives surface water inputs as well. Small scale gradients of microtopography allow for differences in flooding frequency and duration resulting in hydrologically distinct sites which differ chemically. Three zones were distinguished in the wetland. Hollows or low sites were characterized by intermittent flooding and drying and higher nutrient concentrations in soil and groundwater. High sites which were rarely or never flooded exhibited higher groundwater temperature and ammonia as well as iron in soils and groundwater. The inundated sites remained flooded throughout the year and were characterized by high nitrate and nitrite in soil as well as high EC, magnesium, bicarbonate, sulphate and phosphorus in groundwater. The limited availability of nitrogen in the wetland favoured plant types Typha capensis, Paspalum urvillei and Juncus .kraussii which are able to either fix nitrogen or store nitrogen during more favorable conditions. The main chemical concentration changes take place between summer and winter. The Principal Component Analyses suggest that sodium, chloride, potassium, ammonia and phosphorus are the dominant ions determining the chemistry of groundwater. Increased abstraction from the table mountain aquifer to supplement human demand may put the wetland at risk of degradation. Intensified agriculture and other land use in the area are likely to increase pollution loads into the wetland causing shifts in nutrient availability and vegetation composition. Continued and long term monitoring is essential to ensure effective management of the wetland and is highly recommended. Closer partnerships between wetland managers and scientists as well as community awareness and involvement through a volunteer monitoring programme should be encouraged

Surface depressions are important topographic features, which affect overland flow, infiltration, and other hydrologic processes. Specifically, depressions undergo filling-spilling-merging-splitting processes under natural rainfall conditions, featuring discontinuity in hydrologic connectivity and variability in contributing area. However, a constant and time-invariant contributing area is often assumed in traditional hydrologic modeling, and consequently, the real threshold-controlled overland flow dynamics cannot be captured. The overall goal of this dissertation research is to improve hydrologic modeling, especially for depression-dominated areas, by quantifying the hydrologic effects of depressions. The specific objectives are to analyze the hydrotopographic characteristics of depressions and identify the intrinsic relationships of hydrologic variables, develop new modeling methods to simulate the depression-oriented dynamics in overland flow and variations in contributing area, and reveal the influence of spatially distributed depressions on the surface runoff generation and propagation processes. To achieve these objectives, three studies were conducted: (1) the frequency distribution of depression storage capacities was determined and a puddle-based unit (PBU)-probability distribution model (PDM) was developed; (2) the intrinsic changing patterns of contributing area and depression storage were identified, based on which a new depression-oriented variable contributing area (D-VCA) model was developed; and (3) a modified D-VCA (MD-VCA) model was further developed by introducing a depressional time-area zone scheme and a new variable contributing area-based surface runoff routing technique to account for the spatial distribution of depressions. These three models (PBU-PDM, D-VCA, and MD-VCA) were evaluated through the applications to depression-dominated watersheds in North Dakota, and simulation results demonstrated their capabilities in simulating the variations of contributing areas and threshold-controlled overland flow dynamics. In addition, these three studies emphasized the important roles of depressions in the evolution of contributing areas as well as surface runoff generation and propagation. Without considering the spatial distribution of depressions, the formation of contributing area and the timing and quantity of runoff contributions cannot be characterized.

The Little Creek watershed was assessed to identify changes in event-based suspended sediment export and determine the factors contributing to sediment production the first year following the Lockheed Fire in 2009. The amount and volume of near-stream sediment sources were found to decrease, while an increase in hillslope sediment production was documented. High intensity, short duration rainfall (up to 87 mm/hr for 10 minute duration) initiated extensive rilling and minor channel-derived debris torrents originating from the upper south facing slopes. Rainfall simulations, hillslope erosion plots, and soil infiltration tests indicated that fire produced soil water repellency, the lack of ground cover, steep slopes, and high soil burn severity were the most influential factors contributing to hillslope erosion. Contrary to results reported in other western U.S. studies, regression analyses determined that the effect of fire significantly decreased suspended sediment concentrations with higher flows at North Fork and Upper North Fork monitoring stations. The effect of the fire did not produce increases in stormflow volumes and event sediment load, likely due to the fact near-stream sediment contribution was minimal and the majority of hillslope-derived sediment sources were not hydrologically connected. This study provides valuable information for landowners and land managers to understand how a coastal redwood dominated watershed responds to wildfire and prepare post-fire mitigation efforts following future wildfires.