Surface microtopography affects fundamental hydrologic processes including infiltration and soil-water percolation at different scales. By means of studying the unsaturated flow, this thesis research is aimed to evaluate the effects of surface microtopography on wetting front moving patterns for rough soil surfaces through both experimental study and HYDRUS modeling. Additional influential factors such as rainfall intensity and soil type are also considered. Laboratory-scale infiltration and unsaturated flow experiments were conducted for different microtopographic surfaces, rainfall intensities, and types of soil; and two- and three-dimensional numerical modeling was conducted under the same conditions. The simulated and observed wetting front distributions were compared in this combined experimental and modeling study. It was found that a uniformly distributed wetting front was eventually achieved although soil surfaces had dissimilar topographic characteristics. However, the timing to reach the uniform flat wetting front varied, depending on surface microtopography, soil hydraulic properties, and boundary conditions. / Department of Civil Engineering, North Dakota State University / National Science Foundation (Grant No.EAR-0907588)

Microtopography is an important factor in hydrologic processes. The purpose of this research was to study the effects of microtopography on runoff generation. Specifically, this was performed through an array of physical experimentation comparing “rough” and “smooth” surfaces under natural and simulated rainfall. Utilizing these types of rainfalls required experimentation to take place in both field and laboratory settings. The range of control factors in this study varied from surface microtopography to soil type, rainfall intensity/pattern, and ambient moisture content. The recorded results of the laboratory study were further compared with the output of a puddle-to-puddle (P2P) overland flow model. The physical experiments showed a trend initially favoring neither the rough nor smooth surface in runoff production. However, in subsequent experiments the rough surface appeared to substantially increase runoff production relative to the smooth surface. Additionally, good agreement was found between the results of the physical experimentation and the model.

Surface microtopography affects a series of complex and dynamic hydrologic and environmental processes that are associated with both surface and subsurface systems, such as overland flow generation, infiltration, soil erosion, and sediment transport. Due to the influence of surface depressions, overland flow essentially features a series of progressive puddle-to-puddle (P2P) filling, spilling, merging, and splitting processes; and hydrologic systems often exhibit threshold behaviors in hydrologic connectivity and the associated overland flow generation process. It is inherently difficult to realistically simulate the discontinuous overland flow on irregular topographic surfaces and quantify the spatio-temporal variations in dynamic behaviors of topography-dominated hydrologic systems. This dissertation research aims to develop a hydrologic model to simulate the discontinuous, dynamic P2P overland flow processes under the control of surface microtopography for various rainfall and soil conditions, and propose new approaches to quantify hydrologic connectivity. In the developed P2P overland flow model, the depressions of a topographic surface are explicitly incorporated into a well-delineated, cascaded P2P drainage system as individual objects to facilitate the simulation of their dynamic behaviors and interactions. Overland flow is simulated by using diffusion wave equations for a DEM-derived flow drainage network for each puddle-dominated area. In addition, a P2P hydrologic connectivity concept is proposed to characterize runoff generation processes and the related spatio-temporal dynamics. Two modified hydrologic connectivity indices, time-varying connectivity function and connectivity length of the connected areas and ponded areas, are proposed to quantitatively describe the intrinsic spatio-temporal variations in hydrologic connectivity associated with overland flow generation. In addition, the effects of DEM resolution, surface topography, rainfall distribution, and surface slope on hydrologic connectivity are also evaluated in this dissertation research. The developed model can be applied to examine the spatio-temporally varying P2P dynamics for hydrologic systems. This model provides a means to investigate the effects of the spatial organization/heterogeneity of surface microtopography, rainfall, and soil on overland flow generation and infiltration processes. In addition, the two proposed hydrologic connectivity indices are able to bridge the gap between the structural and functional hydrologic connectivity and effectively reveal the variability and the threshold behaviors of overland flow generation. / National Science Foundation under Grant No. EAR-0907588 / Department of Civil and Environmental Engineering, North Dakota State University / North Dakota Water Resources Research Institute

Spatial characterization of surface microtopography is important in understanding the overland flow generation and the spatial distribution of surface runoff. In this study, fractal parameters (i.e., fractal dimension D and crossover length l) and three hydrotopographic parameters, random roughness (RR) index, maximum depression storage (MDS), and the number of connected areas (NCA), have been applied to characterize the spatial complexity of microtopography. Clear and meaningful relationships have been established between these parameters. The RR was calculated as the standard deviation of the processed elevation, and the fractal parameters were calculated with the semivariogram method. The puddle delineation program was applied in this study to spatially delineate soil surface and to accurately determine MDS and NCA. It has been found that fractal parameters can better characterize surface microtopography. More importantly, fractal and anisotropic analyses can help to better understand the overland flow generation process.