


































Source-to-sink agent based model for sediment transport in Ancient Lake Bonneville
The Stockton Bar is a geologic depositional landform along the coast of Ancient Lake Bonneville, located approximately 30 miles east of Salt Lake City, Utah. One method of dating the landform is using a source-to-sink agent based model for sediment transport and determining travel time of sediments to sink. The source of the boulders and gravels are the alluvial fans from the Stansbury Mountains. The sink is the Stockton Bar. The model premise is that the sediments making up the Stockton Bar were transported by high wind storm events exerting a shear stress on the lake water during the Bonneville high stand during the Last Glacial Maximum ~21,000 years ago. Sediment particles were picked up from the source area and transported in a SE direction during storm events, eventually being deposited in the Stockton Bar (sink). Model was first outlined in a pseudocode and then the code was written and compiled within NetLogo.
The simplified source-to-sink agent based model was run in NetLogo software which requires a customized script of the model input and parameters. The source and sink areas of interest were created in ArcMap and imported into NetLogo. The length of storms ranged from one to five hours. The direction of approaching storms were N, NW and S. The speed of transport, was used from the Reynolds and Hjulström equations. Sediment distance was then calculated using storm time multiplied by sediment velocity with monitors keeping track of total times and distances. All of this is modeled in an agent-based modeling environment. Because the model can be manually adjusted, a wide range of results can be found. For example, one interval resulted in a sediment travel time of 10 hours across 51 kilometers.
Skill | Description |
---|---|
Spatial Data and Algorithms | Understand methods for acquiring, evaluating, creating, manipulating, editing, and converting data and metadata in preparation for spatial analysis. Be familiar with how operations are carried out and when they are applicable. |
Model Building | Designed, created and implemented an agent-based model with appropriate data and realistic parameters and provide model results to answer objective question. |
Cartography and Graphic Design | Created successful cartographic results for report and presentation. |
Spatial Analysis | Design, implement, and report on the analysis of spatial data. Describe and test hypotheses regarding distributions of spatial datasets. |
Project Design | Overall project design implementation from beginning to end of project: defining the objective, finding the data, employing the best methodology, analyzing and write-up of results. |
Project Management | Successfully delivered NetLogo script/model and project report within the required time frame. |
Communication Skills | Project was delivered as a project report and class presentation. |
Basic Programming or Scripting | Built a customized workflow and script to find solution of sediment transport in certain geographic location. |
A mitigation perspective on three GIS case studies on post-fire debris flows along the Wasatch Front, Northern Utah
The combination of wildfire and landslide debris flow risks along the Wasatch Front in Utah are post-fire debris flows. In an effort to better understand this natural hazard and the subsequent emergency response, three Northern Utah post-fire debris flow case studies were analyzed in ArcGIS. The case studies include the wildfire/debris flow of Santaquin 2001-2001, Farmington 2003-2004 and Saratoga Springs 2012. The investigation includes the environmental circumstances surrounding the wildfire and debris flows, such as triggering rainfall amounts, slope of the burn scar and soil type. In addition, the emergency mitigation response was evaluated with a brief look at human and structural vulnerabilities.
The debris flows were caused from wildfires that occurred from months up to a year prior to the debris flow event, with acres burned ranging from 1,800-8,000. Triggering rainfall amounts were between 0.58 and 1.58 inches. The mean slope of the fire perimeter burn scars is 24.3°. All soils were loam-types. The areas were all known to have landslides hazards and mitigation efforts were treated as such. Once the wildfires took place, each area was closely monitored for potential debris flows and some underwent mitigation techniques, but damage and evacuations still occurred when intense thunderstorms hit. There were no fatalities or injuries, but there was mild to moderate property and home damage.
Skill | Description |
---|---|
GIS Analysis | GIS analyses of average slope from DEM. |
Spatial Data and Algorithms | Migrating data sets of fire perimeters, rainfall amounts, soil type, parcel data demographic data from the Census Bureau. |
Cartography and Graphic Design | Creating several maps of results for presentation and report. |
Spatial Analysis | Spatial analysis of locations of debris flows and wildfires. |
Data Models and Structures | Minimal use of data models for feature classes and DEM. |
Database Design | Created 3 databases for each case study which all needed to be very similar to one another for examination. |
Structured Query Language (SQL) | Use of SQL with all data to discover important data amounts for conclusions. |
Project Design | Overall project design implementation from beginning to end of project: defining the objective, finding the data, employing the best methodology, analyzing and write-up of results. |
Project Management | Successfully delivered ArcGIS analysis of all case studies within the required time frame. |
Communication Skills | Project was delivered as a project report and class presentation. |
Using ArcGIS to determine the heavy metal pollution exposure from the accidental sediment release at Tibble Fork Reservoir Dam, American Fork Canyon
Historic mining sites in American Fork Canyon, in northern Utah, are a common source of environmental pollution into surface waters and soils. These heavy metal contaminants are known to cause organ failure and contain carcinogens which present a significant public health concern. Using ArcGIS, this study aims to determine the geographic exposure distribution from the toxic sediments accidentally released from Tibble Fork Reservoir, in late August 2016. This proximity model, based on spatial analysis, will show populations at risk and impacted land use areas.
The pollution exposure distribution maps were created using spatial analysis tools in ArcGIS to summarize intersecting at-risk areas within buffer regions adjacent to the American Fork River in the city of American Fork. Areas at risk include population centers, school locations and water related land use areas such as parks and irrigation. The river runs directly through the city making exposure unavoidable, therefore the exposure maps will help define the potential significance of the contamination.
Skill | Description |
---|---|
GIS Analysis | Perform core vector GIS analyses including overlay, clipping, selection and summary/summarize, multi-ring buffering. |
Spatial Data and Algorithms | Created process to best determine exposure proximity by acquiring, evaluating, creating, manipulating, editing, and converting data and metadata in preparation for spatial analysis. |
GIS Workflow | Intricate process of extracting only the data required for analysis and repeating a dozen times for results. |
Cartography and Graphic Design | Designed maps for presentation and report. |
Spatial Analysis | Design, implement, and report on the analysis of spatial distribution of heavy metal data in proximity to land use areas (schools, parks, irrigation). |
Data Models and Structures | Vector data models and schema so data could be used joined together. |
Structured Query Language (SQL) | SQL queries involving proximity to river, schools, parks, population areas and irrigation sources. |
Project Design | Overall project design implementation from beginning to end of project: defining the objective, finding the data, employing the best methodology, analyzing and write-up of results. |
Project Management | Successfully delivered ArcGIS analysis heavy metal proximity within the required time frame. |
Communication Skills | Project was delivered as a project report and class presentation. |
EIS Critique of the “Previously Issued Oil and Gas Leases in the White River National Forest Draft EIS, 2005” and how GIS aid NEPA efforts
To gain a deeper understanding of the National Environmental Policy Act by providing an in-depth critique of an Environment Impact Assessment (EIS). As part of the process, a short analysis on how GIS aids NEPA was also conducted. EIS documents can be thousands of pages long. This EIS review only covered an evaluation of Chapter 1 (Purpose and Need), Chapter 2 (Alternatives including the Proposed Action), one resource evaluation (drinking water), Chapter 3 (Affected Environment) and Chapter 4 (Environmental Consequences) of the Previously Issued Oil and Gas Leases in the White River National Forest Draft EIS (2005). The basis of the critique was in applying the Shipley Compliance Checklist for and EIS or EA.
As part of the EIS review, it was discovered that GIS helps in the resource evaluation phase of the process. In this case, GIS contained base map and boundary layers (oil and gas leases and fields, water, habitat, geologic, vegetation, hydrography systems, land cover use etc.) and also performed analysis of affected areas. The following review is for the aforementioned Draft EIS with particular attention to chapters 1-3.1, 3.5 (Volume 1) and 4.5 (Volume 2), with specific regards to Water Resources:
Overall the Draft EIS is successful in conveying the rationale behind the Proposed Action. However, many shortcomings persist, mostly within the environment impact sections, which leave many holes in the reasoning.
Skill | Description |
---|---|
Project Design | Overall project design implementation from beginning to end of project: defining the objective, finding the data, employing the best methodology, analyzing and write-up of results. |
Project Management | Successfully delivered EIS critique project report within the required time frame. |
Communication Skills | Project was delivered as a project report and class presentation. |
ArcGIS heavy metal exposure prototype project management plan
Create a project management plan for the creation of a prototype to measure contamination of heavy metal sediments accidentally released from a dam source. The case study will be the Tibble Fork Reservoir metal-laden release of August 2016. The plan will be comprehensive analysis including scope management, time management, cost management, quality management, human resource management and communication management.
The project was expected to cost approximately $48,000 and take 5 months to complete with a team of 6 members. Stakeholders included the water quality agency, land and dam owners and the public downstream of sediment release. Documentation that was created to support the plan included the scope statement, business case, stakeholder register, work breakdown structure, Gantt chart, cost estimate, financial analysis, QA/QC plan and checklist, and communication management plan.
Skill | Description |
---|---|
Spatial Data and Algorithms | Design management plan for acquiring, evaluating, creating, manipulating, editing, and converting data and metadata in preparation for spatial analysis. |
GIS Workflow | Develop a workflow to calculate contamination exposure levels which include selection methods and spatial analysis. |
Project Design | Overall project design implementation from beginning to end of project: defining the objective, finding the data, employing the best methodology, analyzing and write-up of results. |
Project Management | Successfully delivered project management plan within the required time frame. |
Communication Skills | Project was delivered as a project report and class presentation. |
Ancient and recent temperature evaluation using geochemical data and geostatistics in Perth Basin, Western Australia
Applying geochemical and statistical calculations to evaluate subsurface temperature changes in the Perth Basin, Western Australia, to better understand geothermal and petroleum exploration potential. The geochemical calculations included deriving ancient temperatures from Rock-Eval pyrolysis Tmax and/or vitrinite reflectance and comparing them to recent well temperatures taken from petroleum well reports. The analyzed data were first treated statistically with exploratory methods to discover any pattern of distribution. The methods used were a scatterplot, a histogram and a bubble plot. In addition, two Kriging interpolation methods were employed to predict delta temperature distribution across the region; Ordinary Kriging interpolation and Kriging with External Drift. Finally, the cross-validation error Root Mean Square Error of Prediction (RMSEP) between the two methods was calculated and compared.
The results show that Permian rock temperature change from ancient to recent, range from -207° to +6.2°C. The scatterplot revealed no correlation between delta temperature and depth. The histogram showed the delta temperatures have an asymmetrical distribution and the bubble plot conveyed the wide range of delta temperatures across the study area. RMSEP results for the Ordinary Kriging was 42.53365 and the Kriging with External Drift was 44.77281. When cross-validation methods were done on the two Kriging methods, it revealed that the depth parameter is not an important variable to consider for delta temperatures. In addition, the distribution of values is such that there must be some underlying geologic processes at work, and not just geothermal gradients that are contributing to the thermal regime in Perth Basin.
Skill | Description |
---|---|
Spatial Data | Acquired well location and geochemical data which was later edited and converted for use in R and ArcMap. |
Cartography and Graphic Design | Apply cartographic design ideas to create useful figures for final report. |
Spatial Analysis | Design, implement, and report on the analysis of spatial data. Describe and test hypotheses regarding distributions of spatial datasets. |
Project Design | Overall project design implementation from beginning to end of project: defining the objective, finding the data, employing the best methodology, analyzing and write-up of results. |
Project Management | Successfully delivered a statistical analysis within the required time frame. |
Communication Skills | Project delivered as a project report. |
Basic Programming or Scripting | Using statistical software R to build workflows or custom solutions for solving spatial analysis problems. |
Spatial database management systems
The objective was to create and design each consecutive database step for the infrastructure of a fictitious city. This was done by creating an Entity-Relationship (E-R) diagram, relational model, object-oriented model, and implementation of the geodatabase onto the ArcSDE server.
The project was completed in four steps. First, the E-R diagram was comprised of 21 entities, each with relationship cardinality, primary keys and several normalized attributes. Second, this was converted into the relational model with seven new additional attributes and worksheets for all relations and all relationships. Third, the object-oriented model was formed with another new seven attributes and added methods, access indicators, vector types and subclasses. Finally, the database design was implemented into a geodatabase with tables, point features, polygon features and line features. Additionally, geodatabase domains, subtypes, and versioning (editing, verification and creation) were implemented as well.
Skill | Description |
---|---|
Spatial Data and Algorithms | Created, manipulated, edited, and converted data in preparation for creation of spatial database. |
Data Models and Structures | Created a data model for the infrastructure of a city. |
Database Design | Implemented specific requirements for data to create EM model, object model, logical model and SDE features. |
Project Design | Implemented overall project design from beginning to end of project: defined the objective, found data, employed the best methodology, analyzed and performed a write-up of results. |
Project Management | Successfully delivered a working database plan from concept to implementation. |
Communication Skills | Project successfully delivered as a class presentation and SDE database for city features. |
Using python to automate the integration of data sets into ArcGIS
Oil and gas exploration utilizes specialized software to interpret seismic data from large subsurface regions. The seismic interpretations need to be converted and imported into a GIS, where all other project data is stored. A hydrocarbon exploration project usually interprets many subsurface geologic intervals. For each interval, a surface-grid is calculated and exported as a very large XYZ ASCII file with over 1 million points and then converted into ArcGIS feature classes. For this project, Python was used to automate this very time-consuming and tedious process.
As an additional component, I wanted to explore the Empirical Bayesian Kriging (EBK) surface interpolation method in the ArcGIS Geostatistical Analysis extension in comparison to manual contouring of the interpreted surface horizons. Therefore, one of the last element of the project was to run the EBK ArcGIS tool on the new created dataset.
A python script was written to run the following procedure
Using Python to automate the process of converting text files to a feature class saved hours of work. The automatic contouring provided a good overview of the data, which would allow for more refinements by manual interpretation.
Skill | Description |
---|---|
GIS Analysis | Perform automation of vector GIS analyses of EBK interpolation. |
Spatial Data and Algorithms | Required an in-depth understanding of the intricacies of data and workflow for acquiring, evaluating, creating, manipulating, editing, and converting data in preparation for spatial analysis. |
GIS Workflow | Fundamental knowledge of how ArcGIS imports external data before creating geodatabase features. |
Project Management | Successfully delivered a working python script and presentations within the required time frame. |
Communication Skills | Project successfully delivered as a class presentation. |
Basic Programming or Scripting | Wrote customized Pythons scripts using systems modules ArcPy, OS, CSV and GLOB for automation and interpolation solutions. |
Water Resources of Northern Utah – Web Application
This Web GIS project investigated the surface water and water consumption of Northern Utah counties and municipalities using three service types. One service will looked at rivers that are within the Great Salt Lake watershed, and their average flow accumulations for the past 30 years annually and by month. The second service provided information on how water is consumed in the same study area, by municipality. The final service analyzed a user-provided point and determined which watershed it is within.
The final web application provided three service functionalities.
Skill | Description |
---|---|
GIS Analysis | Perform core vector and raster GIS analyses including overlay, interpolation, map algebra, terrain modeling, network analysis, and multi-criteria analysis. |
Spatial Data and Algorithms | Understand methods for acquiring, evaluating, creating, manipulating, editing, and converting data and metadata in preparation for spatial analysis. Be familiar with how operations are carried out and when they are applicable. |
GIS Workflow | Understand the importance of workflow in GIS and how to develop a workflow to perform GIS operations and spatial analysis. |
Model Building | Be able to interpret existing geoprocessing models, create new models, add tools and data to a model, and string tools together to form an analysis workflow. Be able to choose appropriate models for modeling static and dynamic geographic processes. Be able to document a model so that others can understand its purpose and how it works. |
Cartography and Graphic Design | Be able to design maps for different purposes, mediums, and audiences, and demonstrate cartographic design principles including color and symbology theory. |
Spatial Analysis | Design, implement, and report on the analysis of spatial data. Describe and test hypotheses regarding distributions of spatial datasets. |
Data Models and Structures | Be able to explore the data models within a database, and understand its structure. |
Database Design | Given specific requirements for data, be able to design appropriate data models. Be familiar with database design tools. |
Structured Query Language (SQL) | Query NDHPlus rivers database for river inclusions of web application. |
Project Design | Overall project design implementation from beginning to end of project: defining the objective, finding the data, employing the best methodology, analyzing and write-up of results. |
Project Management | Successfully delivered working Web Application within the required time frame. |
Communication Skills | Project was delivered as a class presentation. |
Basic Programming or Scripting | Scripting of HTML, CSS and JavaScript. Using AGOL map services. |
Regression analysis of an aerial photography imagery service
The objective was to perform geo-analytics on the Automated Geographic Reference Center’s (AGRC) Discover server which hosts Google’s licensed high resolution (6 inch pixels) aerial photography imagery service. This was accomplished by using statistical analysis tools in ArcGIS to build a regression model, which helped to determined where people in Utah looked at this imagery at scales at or below 1:2000 during 2016, and reveal other spatial relationships. The results would be a predictive model that could be used to help determine areas for future purchase updates. If it is known where the high resolution base map views are most often occurring, it would help drive budgets and mitigate costs.
For the regression model, the dependent variable are the base map views of the high resolution aerial photography of Utah. There were many choices for the independent variables, but the following were eventually chosen for this model:
The statistical analysis included exploratory data methods, Ordinary Least Squares (OLS) and Random Forest Regression (RFR). Exploratory data methods were fundamental to choosing an appropriate regression method. Scatterplots and histograms were invaluable throughout the entire process in understanding data distribution and possible variable correlations. OLS was performed to understand the overarching relationships of the independent and dependent variables. Because the data is not well distributed Random Forest Regression method was used. The final step was to transform the base map views before the RFR. Analysis were performed with R and ArcGIS.
Skill | Description |
---|---|
GIS Analysis | Applied Euclidian distance tool on independent variable vector data. Converted those raster results into integer raster’s so that they could be converted back to square mile polygons which could be spatially joined to the dependent variable for regression analysis. |
GIS Workflow | Acquired data, prepared GIS data, join spatial datasets, apply regression methods, and interpret results. Repeat as necessary to build the best regression model. |
Model Building | Constructed tens of regression models and parameter testing: Ordinary Least Squares, Moran’s I Spatial Autocorrelation, Geographic Weighted Regression and Random Forest Regression. |
Cartography and Graphic Design | Created many maps to convey project ideas for several Power Point presentations, and a poster for the UGIC conference. |
Spatial Analysis | Ran Moran’s I to determine spatial autocorrelation on variance residuals. |
Structured Query Language (SQL) | Used many SQL queries to select the most appropriate fields for the independent and dependent variables. |
Project Design | Created several progress reports which included time and budget considerations as well as issues encountered and project workflow. |
Project Management | Work was accomplished individually and collaboratively with the AGRC. Successfully deliver a model regression solution within the required time frame. |
Communication Skills | Project was delivered as a project report and multiple class presentations. |
Basic Programming or Scripting | Built a custom python iteration script to generate the final distance maps for the regression. |
The aim of this project is to measure the height of the trees on the University of Utah (UU) campus. A previous study (Kuhns, 2011) documented the locations and type of 61 trees on campus. This will be the guide of which trees will be included in the field work. How tall are these trees and is their height above/below average for their species? Are there any other contributing factors to these heights, such as elevation, aspect of Utah’s climate?
METHODOLOGY/RESEARCH STRATEGY: The GPS locations and tree type of campus trees have already been documented. Using the University of Utah Tree Database (Kuhns, 2011) as a guide, do the following steps for each of the 61 trees (figure below from Henry, 2011):
These two measurements will be used in the Pythagorean Theorem to calculate tree height. These heights will be loaded into ArcGIS where further analysis will be spatially investigated. A projected coordinate system will be necessary because of the measurement, therefore WGS84 UTM11 will suffice. Anticipated results include average tree height for all trees where the climate of Utah is the species native climate. In addition, tree height might be below average where their location is getting limited sun exposure, northward for example.