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Abounia Omran, BehzadApplication of Data Mining and Big Data Analytics in the Construction Industry
Doctor of Philosophy, The Ohio State University, 2016, Food, Agricultural and Biological Engineering
In recent years, the digital world has experienced an explosion in the magnitude of data being captured and recorded in various industry fields. Accordingly, big data management has emerged to analyze and extract value out of the collected data. The traditional construction industry is also experiencing an increase in data generation and storage. However, its potential and ability for adopting big data techniques have not been adequately studied. This research investigates the trends of utilizing big data techniques in the construction research community, which eventually will impact construction practice. For this purpose, the application of 26 popular big data analysis techniques in six different construction research areas (represented by 30 prestigious construction journals) was reviewed. Trends, applications, and their associations in each of the six research areas were analyzed. Then, a more in-depth analysis was performed for two of the research areas including construction project management and computation and analytics in construction to map the associations and trends between different construction research subjects and selected analytical techniques. In the next step, the results from trend and subject analysis were used to identify a promising technique, Artificial Neural Network (ANN), for studying two construction-related subjects, including prediction of concrete properties and prediction of soil erosion quantity in highway slopes. This research also compared the performance and applicability of ANN against eight predictive modeling techniques commonly used by other industries in predicting the compressive strength of environmentally friendly concrete. The results of this research provide a comprehensive analysis of the current status of applying big data analytics techniques in construction research, including trends, frequencies, and usage distribution in six different construction-related research areas, and demonstrate the applicability and performance level of selected data analytics techniques with an emphasis on ANN in construction-related studies. The main purpose of this dissertation was to help practitioners and researchers identify a suitable and applicable data analytics technique for their specific construction/research issue(s) or to provide insights into potential research directions.

Committee:

Qian Chen, Dr. (Advisor)

Subjects:

Civil Engineering; Comparative Literature; Computer Science

Keywords:

Construction Industry; Big Data; Data Analytics; Data mining; Artificial Neural Network; ANN; Compressive Strength; Environmentally Friendly Concrete; Soil Erosion; Highway Slope; Predictive Modeling; Comparative Analysis

Nabaee-Tabriz, SaeedAn economic analysis of soil conservation limitations on the intensity of cropland use in Ohio /
Doctor of Philosophy, The Ohio State University, 1985, Graduate School

Committee:

Not Provided (Other)

Subjects:

Economics

Keywords:

Soil erosion;Land use

Van der Poel, Petrus W.Plunge pool erosion in cohesive channels below a free overfall /
Doctor of Philosophy, The Ohio State University, 1985, Graduate School

Committee:

Not Provided (Other)

Subjects:

Engineering

Keywords:

Soil erosion;Arroyos;Erosion

Bejranonda, SomskaowAn assessment of the soil erosion impacts on lakeside property values in Ohio: a hedonic pricing method (HPM) application /
Doctor of Philosophy, The Ohio State University, 1996, Graduate School

Committee:

Not Provided (Other)

Subjects:

Agriculture

Keywords:

Soil erosion

Zhou, HongIntegration of Analytical Models for Estimating Sediment Supply and Evaluation of Channel Stability
Doctor of Philosophy (PhD), Ohio University, 2016, Civil Engineering (Engineering and Technology)
Sedimentation is one of the important factors affecting stream channel stability. The estimation of sediment supply, assessment of channel stability, and potential influencing factors are of interest in this study. A proposed model was developed by the integration of Revised Universal Soil Loss Equation (RUSLE) model and Watershed Assessment of River Stability and Sediment Supply (WARSSS), aiming to estimate the sediment load and evaluate the channel stability of a man-made channel. The proposed model was applied to the channelized Hocking River near Athens, Ohio. It was estimated that the annual gross erosion from the watershed was 728,733,738 kg, 97% of which was from the surface erosion, while only 3% resulted from streambank erosion. The total sediment yield in the channelized Hocking River was indirectly estimated by the addition of suspended sediments and bedload sediments, which were directly measured in the channel. The total annual sediment yield was 80,991,718 kg, in which 98% was estimated from suspended sediments and 2% from bedload sediments. This resulted in a sediment delivery ratio of 11%, which was consistent with those of the watersheds having similar size in the studied region. The total sediment transport capacity was estimated by the proposed model to be 17,161,761 kg/yr. Compared with the total sediment yield of 80,991,718 kg, 21% of which was transported by the river flow. The majority of sediments deposited in the channel due to the insufficient transport capacity. The amount of sediment accumulated was indirectly verified by the annual dredging project conducted by the Hocking Conservancy District (HCD). The channel stability of the Hocking River near Athens, Ohio was assessed by the characteristics of soil erosion for each monitored reach. Based on the four categories of stability determinations, most of the studied reaches were unstable in the lateral direction and all the reaches had excess deposition except one of the downstream reaches. There was a moderate tendency of channel enlargement for the studied reaches. The sediment loads at all the six studied reaches were relatively high, which indicated highly unstable channel reaches. The proposed model has quantitatively simplified the complex soil erosion and sedimentation process into three major components, the gross erosion from watershed, the sediment yield in the channel, and the sediment transport. Based on the results, I believe that the proposed model can estimate the sediment load reasonably well and assess the channel stability in the studied man-made portion of the Hocking River.

Committee:

Tiao Chang (Advisor); Wei Lin (Committee Member); Kurt Rhoads (Committee Member); Teruhisa Masada (Committee Member); Deborah McAvoy (Committee Member)

Subjects:

Civil Engineering; Water Resource Management

Keywords:

soil erosion; sediment supply; Sediment Delivery Ratio; SDR; channel stability; Watershed Assessment of River Stability and Sediment Supply; WARSSS; Revised Universal Soil Loss Equation; RUSLE

Safwat, Amr MStochastic Multimedia Modelling of Watershed-Scale Microbial Transport in Surface Water
PhD, University of Cincinnati, 2014, Engineering and Applied Science: Environmental Engineering
Events of rainfall have been reported to result in increased concentrations of biological and chemical contaminants transported through streams and channels. The heterogeneous distribution of the contaminants in time and space presents interesting modeling challenges. Incorporating and pinpointing sources of increased microbial contribution to our water bodies would effectively help in the decision making process. There are many factors and unknown processes that we still do not fully understand and are not able to describe using deterministic approaches and methods. One way to account for these uncertainties is by utilizing well established stochastic based models to be able to predict the risks that might result from increased microbial influx to our recreational water systems. The goal of this work was to develop a new, GIS-integrated stochastic framework to model the fate and transport of microbial pollutants in surface waters. The resulting tool is intended for assessment of the spatial and temporal distribution of microbial water contamination risk during and following individual storm events on the watershed scale. As part of the work, a new data management system (DMS) was developed and tested. The DMS focuses primarily on standardizing hydrological data for easy access to facilitate sharing. All steps that were taken to setup and populate the Observations Data Model are described. After completion of the DMS, a framework that enables modeling and prediction of microbial concentrations and behaviors during individual rainfall events was developed based on a ArcGIS tool called the Schematic Processor. This framework was developed to include both a stochastic model and a soil erosion model to provide a more accurate picture of concentrations in time and space. The resulting new model contains expanded capabilities that incorporate contaminant interactions with suspended sediments in hillslopes and channels, thus providing time series of concentrations at any given position in a subwatershed. Finally, a second model was developed to bridge the microscopic dynamics of individual microorganisms to macroscopic behavior of microbial ensembles. The distribution of microbes in the watershed was described as a non-homogeneous Poisson random field. Derivation of parameters of this field allowed for computation of water contamination risk in space and in time. Built on the recently published report on the developed and tested data management system, the two new microbial transport models are complementary in that they provide information both on the dominant processes that govern microbial transport and on risk of water contamination in space and in time. Both frameworks were successfully applied and tested with two different microbes E. coli and Enterococci for two individual rainfall events that took place in 2005 in the Shepherd Creek watershed in Cincinnati, OH. The two models were calibrated and simulated the spatial and temporal distribution of E. coli and Enterococci. The results showed high risk of microbial exceedance of EPA recommendation for recreational water use in the first hours following the rainfall events. Decision makers will be able to use the developed models for future microbial risk predictions.

Committee:

Lilit Yeghiazarian, Ph.D. (Committee Chair); William D Shuster, Ph.D. (Committee Member); Timothy L Whiteaker, Ph.D. (Committee Member); Margaret Kupferle, Ph.D. P.E. (Committee Member); George Sorial, Ph.D. (Committee Member)

Subjects:

Environmental Engineering

Keywords:

Stochastic Multimedia Modelling;Environmental data management system;Hillslope scale;Soil erosion;Non-homogeneous Poisson random field;Microbial risk predictions

Mulumba, Lukman NagayaLand use effects on soil quality and productitivity in the Lake Victoria Basin of Uganda
Doctor of Philosophy, The Ohio State University, 2004, Soil Science

Soil quality indices are useful tools for assessing agronomic/ biomass productivity and ascertaining temporal changes in soil properties in relation to land use and management. This study was conducted in the Lake Victoria region in Masaka, Uganda to: (a) identify key soil properties that impact soil quality and agronomic productivity; (b) evaluate soil quality-management inter-relationships; (c) evaluate the use of soil reflectance as a soil quality indicator, and (d) determine the cost and returns of different cropping systems.

Bulk and core soil samples were collected from the 0-20 and 20 – 50 cm depths, from the farmers’ fields, in order to determine soil organic carbon, nitrogen, calcium, phosphorous, magnesium, pH, _13C, _15N, coarse fragments, soil bulk density and soil texture. Saturated hydraulic conductivity (Ks) was determined in the field using a tension infiltrometer and soil depth using an auger. The soil degradation rating was assessed by assigning parametric values to levels of SOC, soil bulk density, Ks, soil texture, soil pH, soil depth and the proportion of coarse fragments in the top soil and these parameters were utilized to develop a single index. Air dry samples were scanned using a spectrometer and the first derivative of the spectral data was calibrated against the measured soil properties. Results indicated that soil quality was affected by SOC, soil depth and Ks. No direct effects of management on soil quality were discerned. Good predictions of several soil properties were obtained using the spectral data. Although a majority of farmers planted bananas as the first choice crop, the highest net returns were obtained from coffee while the highest costs were measured for bananas implying that food self sufficiency was the major determinant of the choice of crop to be grown. It was recommended that grasslands must not be converted to agricultural land use because of their high susceptibility to soil degradation and that farmers be sensitized to think beyond food-self sufficiency, a goal that could also be achieved through strategies which increase farm income.

Committee:

Rattan Lal (Advisor)

Keywords:

Soil quality; Land use; Lake Victoria; Spectroscopy; Tension infiltrometer; Soil degradation; Spectral calibration; Soil organic carbon; Delta 13 carbon; soil erosion; Bananas; Grasslands; Coffee; Masaka

Albright, Amy N.An Analysis of Slope Erosion and Surface Changes on Off-Road Vehicle Trails in Southeastern Ohio
Master of Arts (MA), Ohio University, 2010, Geography (Arts and Sciences)

Few studies have researched the effects of off-road vehicles (ORVs) on trail surfaces in humid regions, particularly the ability of soil models to estimate erosion, the geomorphic change in the trail surface, or the effectiveness of grade reversals in reducing erosion. This research examines cross-trail profile measurements of 11 ORV trail segments in southeastern Ohio over a six month period in order to calculate the erosion occurring in both the ORV riding season and the off season. Field measurements are compared to the output of two soil erosion models, WEPP and WEPP:Road. Spatial patterns of erosion, compaction, and soil texture, and the geomorphic change in the trail surface are also analyzed.

Results show that both WEPP and WEPP:Road models grossly underestimate the amount of soil erosion measured on the studied trail segments. The highest measured erosion rate totaled 116 kg/m2/yr. Significant geomorphic changes in cross-trail profiles were not detected during the six month study. Spatial patterns reveal the dominance of erosion over the study period for upslope and mid-slope locations, and a tendency for deposition at segment-bottom locations just upslope from grade reversals, proving the effectiveness of some of the grade reversals. Statistically significant higher compaction values were found in the tire ruts and along the inside strip of the trail, compared to the outside edges. Surface materials at the slope bottoms were significantly sandier and contained clay than surface materials at the midslopes or the top of the slopes. Results of this study demonstrate spatial patterns of soil erosion and compaction on the ORV trail surfaces and the need for improved models for predicting soil erosion from ORV trails.

Committee:

Dorothy Sack (Committee Chair); James Lein (Committee Member); Geoffrey Buckley (Committee Member)

Subjects:

Geography

Keywords:

off-road vehicles; ORVs; soil erosion; compaction; trails

Amba, Etim AnwanaEffects of rainfall characteristics, tillage systems and soil physioichemical properties on sediment and runoff losses from micro-erosion plots /
Doctor of Philosophy, The Ohio State University, 1983, Graduate School

Committee:

Not Provided (Other)

Subjects:

Agriculture

Keywords:

Rain and rainfall;Tillage;Soil erosion

Das, Arunachal P.Nonpoint Source Modeling of Indian Run Watershed
Master of Science in Engineering, Youngstown State University, 1999, Department of Chemical, Civil and Environmental Engineering
The problem of soil erosion and sediment runoff in the Indian Run watershed (area 11,277 acres), a major tributary to Mill Creek, is of serious concern to the Mill Creek Metroparks management and the Youngstown metropolitan area community. Mill Creek is primarily responsible for sediment deposition in Lake Newport that continues at an alarming rate. A nonpoint source simulation was performed for the Indian Run watershed using the Agricultural Nonpoint Source Pollution Model (AGNPS) water quality model with a focus on the problems of soil erosion and sediment yield. Four hypothetical storm conditions were simulated: (i) 3 in. precipitation of 6 hour duration, (ii) 2 in. precipitation of 4 hour duration, (iii) 1 in. precipitation of 1 hour duration, and (iv) 1 in. precipitation of 12 hour duration. Sensitivity of the results to changes in P, C, and K factors in the Universal Soil Loss Equation was evaluated. Using the model results, the mean flow, erosion and sediment yield for the watershed outlet on a yearly basis were estimated to be on the order of 0.944 cfs/sq. miles, 13.4 tons/acre, and 1100 tons, respectively, which compare favorably with the field measurements. The AGNPS simulation identifies five cells (each 179 acres in area) that are primarily responsible for the problems of soil erosion, and sediment deposition in the entire Indian Run watershed. The sediment deposition and the flow rate predictions are within 10% of the measurements reported [MBR-HER, 1994]. The AGNPS simulation of the watershed provides information that could be of considerable help in formulating management decisions to address the problem of sediment deposition in Lake Newport.

Committee:

Scott Martin (Advisor)

Subjects:

Engineering, Environmental

Keywords:

soil erosion; Mill Creek

Mossaad, Mostafa El-SayedA stochastic model for soil erosion.
Doctor of Philosophy, The Ohio State University, 1981, Graduate School

Committee:

Not Provided (Other)

Subjects:

Engineering

Keywords:

Soil erosion--Mathematical models;Stochastic processes

Tomashefski, David JAn Erodibility Assessment of Central Ohio Cropland Soils
Master of Science, The Ohio State University, 2016, Environment and Natural Resources
Soil erosion due to human activity impairs agricultural productivity and puts valuable wildlife habitat at risk for conversion into cropland. The present study sought to gain insight into the mechanisms of erosion through evaluating the erodibility of central Ohio soils under management regimes of contrasting intensity. Erodibility was examined at 2 adjacent agricultural fields managed for at least 10 years under respective regimes of no-tillage and conventional tillage (i.e., chiseling in the fall and disk harrowing in the spring). Measured soil properties included texture, organic carbon content, bulk density, wet aggregate stability, water-holding capacity, saturated hydraulic conductivity, residue coverage, and permanganate-oxidizable carbon content (POXC). Due to the temporal variability of many of these properties, measurements were carried out in both the spring and fall of 2014. In order to better isolate the impact of management regime on soil properties, both study fields were sampled according to landscape position (e.g., upland, lowland, and terrace), and comparisons between fields were performed primarily among samples matched in terms of both landscape position and season. Correlations among measures were also examined, and each field was additionally evaluated using 3 erosion assessment tools: the Universal Soil Loss Equation (USLE), the Revised Universal Soil Loss Equation 2 (RUSLE2), and a systems-engineering framework described by Karlen and Stott (1994). Significant differences (p < 0.05) between fields were found for most soil properties sampled within the same landscape position and season, and differences were most pronounced for aggregate stability and residue coverage. Correlations among properties revealed that organic carbon was well correlated with bulk density, water-holding capacity, and POXC, and weakly correlated with aggregate stability. POXC was slightly better correlated with aggregate stability than was organic carbon, but it still could only minimally account for the observed variation in wet-aggregate stability. It therefore appears that other factors are influencing aggregation, and it is hypothesized that one destabilizing factor may be heterogeneity of aeration on the aggregate scale, which is potentially increased through tillage. In poorly-drained tilled soils, such as the tilled lowland of the present study, aeration heterogeneity may work to segment larger aggregates by focusing oxidation upon discrete points along otherwise protected organic fragments. This hypothesis merits further investigation. Annual soil losses predicted for the tilled field by the USLE and RUSLE2 were 10.6 and 8.9 tons per acre, respectively. These values are far in excess of the tolerable soil loss, or “T-value,” which these tools identify to be 3.0 tons per acre. Soil losses predicted by the USLE and RUSLE2 for the no-till field, by contrast, were 1.3 and 1.7 tons per acre, annually. In keeping with these values, the systems-engineering framework rated the erosion resistance of the no-till and tilled fields to be 0.55 and 0.21, respectively. These findings support the notion that tillage disrupts soil structure and leads to heightened erosional losses. Due to the ability of percent residue coverage and wet-aggregate stability to discriminate between land areas of contrasting erodibility, it is recommended that future erodibility assessments include these two measurements.

Committee:

Brian Slater, PhD (Advisor); Edward McCoy, PhD (Committee Member); Steven Culman, PhD (Committee Member)

Subjects:

Agriculture; Agronomy; Environmental Science; Soil Sciences

Keywords:

soil erosion, tillage, organic carbon, POXC, aggregate stability, Ksat, residue, bulk density, water-holding capacity, aeration heterogeneity, oxygenation, RUSLE2, USLE, occluded, mucilage, particulate

Aina, Patrick OladipoThe effects of rainfall, soil and management factors on soil erosion of Nigerian tropical soils /
Doctor of Philosophy, The Ohio State University, 1977, Graduate School

Committee:

Not Provided (Other)

Subjects:

Agriculture

Keywords:

Soil erosion;Rain and rainfall;Nigeria

Lucas, Andrew K.Soil Erosion Analysis of Watersheds in Series
Master of Science (MS), Ohio University, 2012, Civil Engineering (Engineering and Technology)
The objective of this study is to determine the relationship between soil erosion and sedimentation within Wills Creek, Senecaville Lake, and Salt Fork watersheds of Ohio. Both Senecaville Lake and Salt Fork Lake watersheds are entirely located within the watershed of Wills Creek Lake. Experimental results using the Revised Universal Soil Loss Equation and a sediment delivery equation in conjunction with Geographic Information Systems are compared to sedimentation reports prepared by the United States Army Corps of Engineers. Results of this comparison show that the type of land cover has the highest impact on the amount of soil erosion, specifically the lands associated with cultivated crops. Furthermore, the sediment yield of a watershed is not accurately calculated based on average annual sedimentation and present RUSLE erosion potential.

Committee:

Tiao Chang, PhD (Advisor); Teruhisa Masada, PhD (Committee Member); Lloyd Herman, PhD (Committee Member); James Dyer, PhD (Committee Member)

Subjects:

Civil Engineering

Keywords:

RUSLE; GIS; sedimentation, soil; erosion; sediment delivery

Abraham, Girmai,Crop production, soil erosion, and the environment in the Maumee River Basin : a modelling approach /
Doctor of Philosophy, The Ohio State University, 1981, Graduate School

Committee:

Not Provided (Other)

Subjects:

Economics

Keywords:

Crops and soils--Maumee River Basin;Soil erosion--Maumee River Basin;Environmental policy--Maumee River Basin