An integrated surface-subsurface hydrological model of Everglades National Park (ENP) was developed using MIKE SHE and MIKE 11 modeling software. The model has a resolution of 400 meters, covers approximately 1050 square miles of ENP, includes 110 miles of drainage canals with a variety of hydraulic structures, and processes hydrological information, such as evapotranspiration, precipitation, groundwater levels, canal discharges and levels, and operational schedules. Calibration was based on time series and probability of exceedance for water levels and discharges in the years 1987 through 1997. Model verification was then completed for the period of 1998 through 2005. Parameter sensitivity in uncertainty analysis showed that the model was most sensitive to the hydraulic conductivity of the regional Surficial Aquifer System, the Manning's roughness coefficient, and the leakage coefficient, which defines the canal-subsurface interaction. The model offers an enhanced predictive capability, compared to other models currently available, to simulate the flow regime in ENP and to forecast the impact of topography, water flows, and modifying operation schedules.

Groundwater is one of the main sources for drinking water and agricultural activities. Various activities of both humans and nature may lead to groundwater pollution. Very often, pollution, or contamination, of groundwater goes undetected for long periods of time until it begins to affect human health and/or the environment. Cleanup technologies used to remediate pollution can be costly and remediation processes are often protracted. A more practical and feasible way to manage groundwater contamination is to monitor and predict contamination and act as soon as there is risk to the population and the environment. Predicting groundwater contamination requires advanced numerical models of groundwater flow and solute transport. Such numerical modeling is increasingly becoming a reference criterion for water resources assessment and environmental protection. Subsurface numerical models are, however, subject to many sources of uncertainties from unknown parameters and approximate dynamics. This dissertation considers the sequential data assimilation approach and tackles the groundwater contamination problem at the port of Rotterdam in the Netherlands. Industrial concentration data are used to monitor and predict the fate of organic contaminants using a three dimensional coupled flow and reactive transport model. We propose a number of 5 novel assimilation techniques that address different challenges, including prohibitive computational burden, the nonlinearity and coupling of the subsurface dynamics, and the structural and parametric uncertainties. We also investigate the problem of optimal observational designs to optimize the location and the number of wells. The proposed new methods are based on the ensemble Kalman Filter (EnKF), which provides an efficient numerical solution to the Bayesian filtering problem. The dissertation first investigates in depth the popular joint and dual filtering formulations of the state-parameters estimation problem. New methodologies, algorithmically similar, but more efficient numerically, are then proposed based on a more consistent derivation with the Bayesian filtering approach. To reduce computational cost, I further extend the formulation of the hybrid EnKF-variational approach to the state parameter estimation problem and propose an adaptive scheme for the specification of the weights of the flow-dependent and static background covariance matrices. The new adaptive hybrid scheme is shown to provide much better results than the EnKF while using a fraction of the ensemble size. The new methods are implemented and successfully tested with a realistic coupled subsurface and transport-reaction model of the port of Rotterdam by assimilating industrial data on biodegradable chlorinated hydrocarbons. The observational design problem for placing hydrologic wells is subsequently considered and a new efficient solution is proposed that combines concepts from both information theory and data assimilation

This diploma thesis deals with design of 3D scanner for scanning problematic surfaces. The research part introduces the problem of 3D scanning and describes causes of random errors. Further, it contains a description and division of methods that leads to their elimination. The practical part of the thesis deals with design and description of hardware and software parts of the 3D scanner. The output of this work is device that is able to implement and compare quality of codification methods mainly for scanning of problematic surfaces. The functionality of equipment was verified by experimental measurement.

<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>

Subsurface tile drainage is a common management practice implemented by farmers throughout the Midwest in fields that have poorly drained soils. Tile drainage has several benefits including increased productivity, reduced erosion, and increased trafficability. However, relatively little is known about the long-term change of soil properties that may occur as a result of subsurface drainage. Careful monitoring of tile drains at the long-term experimental site at the Southeast Purdue Agricultural Center led to the observation of faster drain flow than in the past, with hydrographs of the flow showing flashier peaks, suggesting that more preferential flow paths have developed over time. The overall goal of this study was to characterize possible evolution of physical and hydraulic properties of this silt loam soil after 35 years of subsurface drainage. Bulk density and water retention were measured in May of 2018 at 0-5 cm, 5-15 cm, and 15-30 cm in all plots and again in July of 2019 in the 5 m and 40 m spacings at four different horizons down to depths of approximately 100 cm, rather than set depth increments. Bulk density results from both sets of sampling show the 5 m spacing to have a significantly lower bulk density than the 40 m spacing in the top 30 cm of soil, although the difference was small. Differences in water retention among treatments were too small to be physically meaningful. Saturated hydraulic conductivity results measured by three different methods were highly variable and no differences were detected. In soils with naturally weak structure, low organic matter, and low clay content, like the soil in this study, the processes responsible for soil aggregation, structure stabilization, and lowering bulk density are inherently slow and may require longer than 35 years of subsurface drainage to produce significant changes in the physical properties measured.

Subsurface drainage (SSD) has been used to remove excess water from fields in the United States upper Midwest for more than a century, but only since the last decade in the Red River Basin of the North in North Dakota (ND). The water leaving from a SSD system can affect both the quality and quantity of water that flows to a surface water system. Therefore, determination of the water balance components is the first step to study the impact of SSD on water quantity, while evapotranspiration (ET), one of the most important components in the water balance, needs to be accurately measured for SSD field. A field experiment was conducted to study the water balance in SSD and undrained (having no artificial drainage system) fields in southeast ND. The field had three different water management systems: 22 ha undrained (UD), 11 ha subsurface drained, and the remaining 11 ha subsurface drained and subsurface irrigated. The ET rates were measured directly using an eddy covariance (EC) system for the SSD and UD fields. The changes in water table were monitored in 8 wells installed in both fields. Rainfall, SSD drainage volume, and soil moisture at six different depths at two locations were measured in both fields. The measurements were conducted in the growing seasons of 2009 and 2010. The ET rates were calculated for two different field crops: Com (Zea Mays) in 2009 and soybean (Glycine Max) in 2010. Crop coefficient (Kc) value was also developed using the ET measured by the EC system and the reference ET (ETref) estimated using the American Society of Civil Engineers Environmental and Water Resources Institute (ASCE-EWRI, alfalfa) method. The ETref was also estimated using the ASCE-EWRI grass and the Jensen Haise (JH) methods. The results indicated that the water table in the SSD field was lower during spring and fall than that in the UD field. The shallow water table and high soil moisture content in the spring and fall have resulted in higher ET rates in the UD field. In the summer, SSD field has favorable soil moisture at the root zone depth; the ET in the SSD field was 30% and 13% higher than that in UD field in summer 2009 and 2010, respectively. For the entire growing season, the ET in the SSD field was 15% higher compared to UD field and the difference was minimal in 2010. Though there were differences in the ET values, they were not statistically different. However, difference in magnitude of ET during summer 2009 yielded a statistical difference. During the peak growing season in July and August, the Kc values were greater in the SSD field due to healthy crops. / USDA (Grants CSREES NRI 2008-35102-19253) / USDA NRCS / North Dakota Agricultural Experiment Station / North Dakota State Water Commission / North Dakota Water Resource Research Institute / North Dakota Department of Health

The adsorption of oxygen on Rh(110) was investigated by thermal desorption spectroscopy (TDS), X-ray photoelectron spectroscopy (XPS) and scanning tunnelling microscopy (STM). The desorption of chemisorbed oxygen was observed at 700 K to 1200 K. Above 1400 K exists another desorption peak which is attributed to subsurface oxygen. The content of subsurface oxygen in Rh(110) influences the chemisorption states on the surface, so that the desorbing character of the surface oxygen species is changed. The subsurface-state needs high preparation temperature and has not any reaction with residual gas or added hydrogen in the chamber, which clarifies its spatial isolation. The XPS result showed that the binding energy of subsurface species is higher than the one of surface oxygen. This confirms the TDS observation. The subsurface-oxygen containing surface showed in STM oxygen induced hillock-like structures.

The aim of the San Andreas Fault Observatory at Depth (SAFOD) project, a component of the NSF Earthscope Initiative, is to directly observe active fault processes at seismogenic depths through the drilling of a 3 km deep (true vertical depth) inclined borehole across San Andreas fault. Preliminary subsurface models based on surface mapping and geophysical data predicted different lithologies than were actually encountered. At 1920 meters measured depth (mmd), a sequence of well-indurated, interbedded arkosic conglomerates, sandstones, and siltstones was encountered. We present a detailed lithologic and structural characterization as a step toward understanding the complex geologic history of this fault-bounded block of arkosic sedimentary rocks. We divide the arkosic section into three lithologic units with different compositional, structural, and sedimentary features: the upper arkose, 1920-2530 mmd, the clay-rich zone, 2530-2680 Illtlld, and the lower arkose, 2680-3150 mmd. We interpret the section to have been deposited in a Salinian transtensional basin, in either a subaqueous or subaerial fan setting. We suggest four different possibly equivalent sedimentary units to the SAFOD arkoses, the locations of which are dependent on how the San Andreas fault system has evolved over time in the vicinity of the SAFOD site. Detailed analysis of three subsidiary faults encountered in the arkosic section at 1920 mmd, 2530 mmd, and 3060 mmd, shows that subsurface faults have similar microstructures and composition as exhumed faults at the surface, with less evidence of alteration from extensive fluid flow.

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