Earth and Environmental Sciences - Junior

COURSE #: EAES 3059 

Course Description 

Negative impacts of climate change on ecosystems, infrastructure, and people’s lives, emanating from use of energy sources, necessitate drastic changes in all sectors of the economy, but especially so in the energy sector, where transition away from fossil fuels and making energy systems green and clean to mitigate environmental harm is imperative. In this course, we will investigate the central question of “How can sustainable energy sources be harnessed and utilized to minimize or eliminate environmental impacts?”. An overview of renewable energy sources (hydropower, solar, wind, geothermal and bioenergy), energy storage and energy efficiency options as well as a discussion of conventional energy sources (coal, oil, natural gas and nuclear) provides an avenue towards assessing their environmental impacts. It is well-known that to affect transition towards sustainability, energy policy needs to phase out conventional energy and expand use of alternative options. However, much is debated about the extent to which energy policy determines the transition path and what kind of mechanisms constrain or facilitate the transition. Why is action lacking? Is it due to politics, economics or culture, or a combination of factors? During the course, we will interrogate these aspects and also deal with misconceptions about intermittency, reliability and other arguments levied at sustainable energy. Ultimately, this course seeks to provide concepts, theories and tools for describing, discussing and analyzing the issues surrounding conventional and sustainable energy options.  

Course Learning Outcomes  

At the end of this course the students will be able to:  

• Describe key concepts and theories in relation to energy forms, sources and uses. 
• Assess household energy use in terms of sustainability of energy sources and technologies. 
• Analyze country-level energy endowment, deployment, challenges and policy mechanisms that constrain or facilitate sustainable energy transformations. 

Course Assessments and Grading 

COURSE #: EAES 3052

Course Description

Environmental governance describes how societies and governments manage the relationship between human beings and the natural world, explains why they do so in certain ways, and assesses the extent to which different types of management are effective. Studying environmental governance involves interrogation of rationales, rhetoric and structures of environmental management systems, and comparison of these systems to understand why certain environmental problems are managed as they are, what approaches to environmental management are more (or less) successful, and for whom and in what ways they are (or are not) successful. Concepts and theories introduced in the course are applied in a serious of case studies that offer opportunities for analysis of each governance approach. This course seeks to provide tools for describing, discussing and analyzing the issues that underpin environmental management problems.  

Course Learning Outcomes

At the end of this course the students will be able to:

• Describe key concepts and theories of institutional analysis in relation to environmental management.
• Evaluate the effectiveness of four major governance modes (state, market, civil society, and global governance bodies) in addressing environmental problems.
• Analyze environmental management problems through the lens of an applicable governance model.

Course Assessments and Grading

COURSE #: EAES 3038

Course Description

The course offers an introduction to quantitative analysis of geomorphic processes in mountainous terrain, and examines the interaction of climate, tectonics, and surface processes in the sculpting of Earth's surface. It looks at the environments of mountains, hillslopes, glaciers, and rivers, and it explores how and why these landscapes form and change through time, with a special focus on the mechanics of surface processes in these environments. The course provides a basis for addressing geomorphic concerns affecting society and the environment while introducing techniques for analysing and predicting changes in landforms.  Students will critically examine geomorphological challenges in a scientific context at local, regional, and global scales as well as synthesize and convey scientific results by discussing them in a small group tutorial format.

Course Learning Outcomes

By the end of the course, students will be able to:

• Describe the morphology of the landscape and related processes in mountain environments.
• Discuss the key concepts and theories that have been developed to explain how the landscape has evolved.
• Analyze landforms and processes of land formation using topographic maps, remote sensing techniques, digital elevation models (DEMs), and other quantitative techniques.
• Evaluate various solutions to a wide range of geomorphological problems in mountainous environments.

Course Assignments and Grading

COURSE #: EAES 2004

Course Description

Soil determines the nature of plant ecosystems and the capacity of land to support human, animal, plant, and other organisms. This introductory soil science course is designed to provide an overview of the fundamental concepts of soil science and lead to the development of students’ understanding of the properties and processes that are basic to the use and management of soils. This course provides a professional's guide to comprehending, using, and controlling innovative soil management technologies. Students will learn about the various types of soil, their mineralogical, physical, chemical and biological properties and soil importance, type and distribution in the mountainous areas.  Surveys as well as cutting-edge soil technologies such as remote sensing, GIS, GPS, geo-statistics, and digital soil mapping (DSM) are topics to be covered. From the beginning, this course increases students' understanding of modern technological solutions for soil productivity. Students will gain an understanding of remote sensing applications in soil science and agriculture. Students will get practical experience in processing, analyzing, displaying, and debating remote sensing data for proper soil management. Finally, they will gain experience and skills in reviewing relevant literature and writing a research project proposal based on remote sensing and GIS.

Course Learning Outcomes

Upon successful completion, students will be able to:

• Explain the importance of the soil in the environment, its impact on agricultural and non-agricultural practices, and the process of soil formation.
• Explain the basic chemical, physical, mineralogical, and biological properties of soil; their interactions; and their impact on plant growth, soil behavior, and soil management.
• Explain the significance of soils in the hydrologic and carbon cycles and evaluate various quantitative models for digital soil mapping.
• Understand the chemical properties of soil such as pH, salinity, acidity, and the role of organisms that live in the soil.
• Explain the value of the SCORPAN model and other models in soil surveys and the usage of satellite images for soil surveys.
• Describe the geostatistical modeling process using GIS and GPS technology.
• Explain spatial prediction models and discuss how the process of diffuse reflectance works via various VisNIR-DRS equipment.

Course Assessments and Grading

COURSE #: EAES2011

Course description 

This course introduces students to physical processes and ways of thinking quantitatively about the world around us, to understand every day and specific physical phenomena related to Earth and Environmental Sciences. The course includes introductions to mechanics and gravity (how objects move, potential field gravity field, principles of Newtonian mechanics, stress and strain), fluids and material properties (how solids, liquids and gases behave, buoyancy forces, gases rules, model of ideal gases, thermal physics (how heat moves, latent constant, thermodynamics laws), and waves (e.g., light and sound). Throughout the course, we’ll develop skills of asking physics questions and making scientific estimates. 

Course learning outcomes 

After finishing this course students will be able to:

• recognize fundamental concepts throughout physics (e.g., conservation of energy).
• recognize that EES phenomena as combination of multiple physical processes
• interpret physical concepts quantitatively
• derive the most important physics concepts and equations for EES

Assessments and Grading 

COURSE #: EAES 3045

Course description 

Geophysics is an interdisciplinary and applied science which involves geology and physics. This course introduces students to various subdisciplines of geophysics (geodesy, gravity, geomagnetism, seismology, and geochronology) and their applications in study of the interior and crust of the Earth and applications in prospecting for water, oil and mineral resources. The course presents a broad overview of size and shape of the earth; seismology and the interior of the earth; heat flow in the earth and geothermics; gravity and variation of density; geomagnetic field and paleomagnetism; electrical properties of the Earth; geochronology and absolute age, and application of the physical properties for exploration purposes.

Course learning outcomes 

Upon the completion of the course, students will be able to: 

• understand physical behavior of earth and its different layers, including atmosphere and lithosphere
• interpret geophysical data, including seismic waves and earthquake data, thermal data and gravity anomalies
• use mathematical skills to explain geophysical behaviors and processes
• apply geophysical quantitative methods to wide geological problems.

Assessments and Grading 

COURSE #: DMNS 2035

Course Description

This is an introduction to statistics for students in earth and environmental sciences. It assumes zero    to little prior experience in statistics but does assume a good background and understanding of single variable calculus. This course will cover elementary probability including introducing random variables, discrete and continuous probability distributions so that students are able to use the language of probability in statistics. The second part of the course will cover inferential statistics wherein students will learn how to draw conclusions about a population based on a random sample.

Course Learning Outcomes

At the end of this course the students will be able to:

• apply a variety of methods for explaining, summarising and presenting data and interpreting results clearly using appropriate diagrams, titles and labels when required
• summarise the ideas of randomness and variability, and the way in which these link to probability theory to allow the systematic and logical collection of statistical techniques of great practical importance in many applied areas
• have a grounding in probability theory
• perform inference to test the significance of common measures such as means and proportions
• use simple linear regression and correlation analysis and know when it is appropriate to do so.

Course Assessments and Grading

COURSE #: EAES 4751

Course Description

Programming in Python is an introductory course that covers programming techniques and tools to manipulate, manage, and analyze relevant data. The course focuses on the Python programming language that students will use to solve statistical analysis problems, apply Machine Learning and Deep Learning techniques, and create a website using Django. The tasks will be accomplished by identifying and using existing Python packages as well as appropriate open-source software extensions. The course introduces basic to advanced statistical functions, data visualization, and data manipulation techniques. The relevant functions in data science are explained. The main goal of this course is to give students an understanding of the breadth of different programming applications. In particular, students will be taught how to design and write effective code using Python to perform routine and specialized data manipulation, management, statistical analysis, and web application development tasks. The tasks will be accomplished by identifying and using existing Python packages as well as appropriate open-source software extensions.

Course Learning Outcomes

Upon completion of this course, every student will be able to:

• Explain the theoretical concepts of different data types
• Conceptualize and create loops and if/else statements in Python
• Create specialized functions in Python to handle results
• Manipulate data for descriptive statistical analysis in Python
• Use Django framework for development of different types of websites, in particular, a highly customizable app, such as an internet magazine website
• Use special packages, such as panda, to create graphs and convert plain text to formatted text.
• Use the packages NumPy, Matplotlib, Pandas and Skikit-Learn for various mathematical calculations, data manipulation, graphing and creating machine learning algorithms.

Course Assignments and Grading

COURSE #: DMNS 2012

Course Description

Linear Algebra is a foundational course at UCA. It can be applied in business, economics, sociology, ecology, demography, engineering, and other areas. In this course, students will study mathematics that deals with the system of linear equations and their applications, operations with matrices, applications of Markov chains, applications of determinants, eigenvalues and eigenvectors and their applications.

Course Learning Outcomes

Upon successful completion of this course, students should be able to:

• Set up and solve a system of equations to fit a polynomial function to a set of data points.
• Use matrices and Gaussian and Gauss – Jordan eliminations to solve a system of linear equations.
• Do operations with matrices
• Find the inverse of a matrix.
• Use a stochastic matrix to find the nth state matrix of a Markov chain.
• Find steady state matrices of absorbing Markov chain.
• Use matrix algebra to analyze an economic system (Leontief input- output model).
• Find the least square regressions line for a set of data.
• Use Cramer’s rules to solve a system of n linear equations in n variables.
• Model population growth using an age transition matrix and an age distribution vector.

Course Assessments and Grading

COURSE #: ECON 1001

Course Description

Introduction to Microeconomics deals with the interactions between individual households and business. The course helps in explaining the mechanism behind determination of prices of different commodities. It also explains about the prices of the factors of production. It helps in understanding the working of the free-market economy and it introduces students to some of the basic concepts used in economics. The course introduces the students to the various basic concepts necessary to understand economic policies and their effect on society and shows which policies can enhance productive efficiency that may result in greater social welfare. In brief, the course will introduce some explanation about the working of a capitalist economy.

Course Learning Outcome

Upon successfully completing this course, students should be able to:

• Define basic microeconomic concepts.
• Explain how markets optimally allocate scarce resources faced with unlimited wants.
• Describe models of goods’ markets with competitive, oligopolistic and monopolistic setups.
• Determine models to solve microeconomic problems as well as assess the power and limitations of these models.
• Relate the "language" of formal mathematical models and the "language" of graphs, to the microeconomic concepts under review.

Course Assessments and Grading

COURSE: # ECON 2006

Course Description

This course focuses on ways to manage personal finances effectively in order to increase savings and reach financial goals and examines ways of how financial reporting is prepared and communicated by businesses. The course enables students to develop their knowledge and understanding of principles and purposes of accounting for individuals, businesses and non-for-profit organization.

Course Learning Outcomes

After completion of the course, students should be able to:

• Define the basic accounting vocabulary, accounting principles, and concepts
• Explain ways to prepare a personal and family budget to reach financial goals
• Discuss ways to increase personal savings
• Perform accounting tasks for non-current assets, inventory, receivables, non-current liabilities, current liabilities, and equity
• Prepare a multiple-step income statement, statement of financial position, and cash flow statement of a company
• Explain the interactions between the financial statements and the way they are used by investors, creditors, regulators, and managers
• Record business transactions using accounting software
• Analyze the financial statements of a company.

Course Assessment and Grading

COURSE #: DMNS 4180 

Course Description 

Linear programming is one of the most versatile and powerful mathematical programming techniques that can be employed for efficiently solving a stylized class of decision problems. 

Linear programming has been used with marked success to solve optimization problems in areas such as economics (including banking and finance), business administration and management, agriculture and energy, contract bidding, nutrition (diet) planning, health care, public decision making, facility location, transportation, strategic planning, and so on.  

In this course, students will study mathematics that deals with various real-world situations which leads to mathematical models involving linear optimization problems, geometrical solution of two-variable problem, simplex algorithm, dual problems and transportation problem. 

Course Learning Outcomes 

Upon successful completion of this course, students should be able to: 

• Formulate a mathematical model of real life problem. 
• Solve the formulated mathematical problem with the use of different 
• Translate the results back into the context of the original problem.  

Course Assessments and Grading