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Project-based design for water and wastewater treatment. Water quality, design flows and loadings, physical primary treatment, biological secondary treatment, disinfection. Drinking water laboratories.
This course will introduce topics in the environmental engineering area of water and wastewater treatment. Successful students will demonstrate an understanding of the fundamental physical, chemical, and biological processes used in water treatment, and be able to produce a process design of municipal water and wastewater treatment systems. Those working in New Zealand on drinking water and wastewater engineering have a mixture of chemical and civil engineering BE degrees, and the mixture of backgrounds of students in this course will prepare students for the mixture they will encounter in the workforce.
Analyse and solve problems in drinking water and domestic/industrial wastewater treatment using mass balances, reaction kinetics and separation process principles. (UC Attributes EIE3), Washington Accord WA1) Develop a treatment plant design from a concept to a preliminary design, evaluating the design against competing design criteria and communicating the design considerations (including site layout, site constraints and process train selection) in a variety of formats (written report, drawings)(UC Attributes EIE3), Washington Accord WA1, 3, 6, 9)Measure, through laboratory experimentation, water treatment design parameters (UC Attributes EIE3), Washington Accord WA14, WA5)Explain the function, mechanism of treatment and attributes in various drinking water and wastewater treatment process units; (UC Attributes GA2), Washington Accord WA1)Explain the importance of water from within a te ao Māori context and how this is relevant to design of treatment and disposal systems; (UC Attributes BCC7), Washington Accord WA6)
Subject to approval of the Director of Studies
ENCN481
Students must attend one activity from each section.
The course is taught as two halves; with one half being on potable water treatment and the other half being domestic wastewater treatment plant design. The course will be taught through lectures (in-person and self-study videos), design tutorial sessions, and a laboratory exercise.
Hamish Mackey
Ricardo Bello Mendoza
1. Late design or lab reports will be subject to mark reduction at 5% within the first hour, and 1% per hour thereafter.2. Students must score at least 40% in each of the mid-term test and final exam in order to pass the course. In situations where a student narrowly fails to meet this requirement, but scores very well in the other test/exam and assignments, the student may be eligible to pass at the discretion of the course coordinator.3. Design reports will be conducted in small-assigned teams of 2-3 students (depending on class size). Individual student grades will be awarded and adjusted based on degree of contribution. For pairs this will be done using a jointly signed statement of contributions and for a 3-person group using an anonymous peer evaluation.Special Considerations Any student who has been impaired by significant exceptional and/or unforeseeable circumstances that have prevented them from completing any major assessment items, or that have impaired their performance such that the results are not representative of their true level of mastery of the course material, may apply for special consideration through the formal university process. The applicability and academic remedy/action associated with the special consideration process is listed for each assessment item below. Please refer to the University Special Consideration Regulations and Special Consideration Policies and Procedures documents for more information on the acceptable grounds for special consideration and the application process. Special Consideration for AssignmentsAssignment special considerations will be handled on a case-by-case basis directly by the course coordinator. An extension may be granted for evidence-supported requests. Students seeking an extension must contact the course coordinator as soon as possible with evidence of their situation, and before the due date if it is practical to do so. In cases where the special consideration occurs early in a design project, the project team may be asked to split and reassigned to other teams. The individual requesting the special consideration may then need to complete the design assignment alone, with extended time. In the case of the laboratory assignment, a student will need to obtain the data from another student pair and perform the analysis individually. Special Consideration for Midterm Test and Final ExamThe academic remedy for a special consideration assessed at a moderate level or higher is an equivalent test or exam. The alternative exam will be held on campus during the week of July 7th. The alternative test will be arranged based on availability of instructors and those needing to take the alternative test. The mark on the alternative test/exam will replace the original test/exam mark in the course grade calculation unless a student declines or does not respond to the offer of the alternative test/exam. In such case, the original mark will be used. Students will not be advised of their original mark as part of this process. All communication associated with special considerations will be conducted using official UC email accounts. The offer to sit an alternative assessment will come with a date and time. Students will have a clearly specified timeframe to respond to the offer. Failure to respond within the deadline will be interpreted as a declined offer. If a student has applied for special consideration but the application has not yet been approved, they may be permitted to sit the alternative test/exam, but the mark will not be applied until the special consideration application has been approved. Statement on Generative AI use in ENGR409Generative AI (e.g., ChatGPT, CoPilot, DeepSeek etc) is a new technology with clear implications for civil and natural resource engineering practice. In this course, the use of generative AI is permitted providing it adheres to the guidelines of responsible practice described below.Information gathering: AI can be used to find, gather and summarize knowledge on a subject that is outside your expertise. For this course, where you will face design constraints that do not necessarily fit the basic theory taught, this is an excellent use of AI to gain improved understanding and identify considerations beyond your initial conceptions. However, it is important that you verify any information produced by AI. AI output can be convincingly wrong on technical matters. AI output can be incomplete, potentially omitting alternative hypotheses or views. AI output can be contradictory, offering concluding statements that are incoherent with arguments given earlier. Thus, it is important to verify AI-generated output. This includes checking source material, asking or reprompting an AI for alternative views, and challenging it to justify its statements. Verification may only possible when you are a subject matter expert, i.e., a competent engineer, and you will be responsible for any material used in your reports.Writing: Generative AI can be used to improve your writing and provide editing feedback. It is not permitted to use AI to generate original text. Rather, you should place yourself in the role of author, providing the skeleton text and ideas, so that the AI in the role of editor, only improving the communication of your original ideas. When using AI to alter your writing, it is important to check that the substantive message of the text has not been altered. It is recommended that your prompt end with “…and explain the changes that you made” so that you can gain feedback to improve your own writing. A word of warning – AI editing tends to have distinctive traits that do not necessarily fit with the expectations of a professional engineering report. It is advised to further edit and review the AI output and be aware that marks for writing style may be deducted if the writing does not fit the stylistic expectations for engineering. Calculations and design: AI is not to be used to undertake design or engineering calculations. As indicated in most AI tools, the output of generative AI is not always correct, and an engineer must be competent to check and validate outputs from AI where it is used in industry. An AI is not a substitute for a creative, problem-solving engineer. It cannot match the complex reasoning or emotional intelligence of a human. Relying on an AI to solve problems for you may prevent you from achieving course Learning Outcomes. Being unable to demonstrate your mastery of Learning Outcomes during an invigilated assessment (test or exam) when AI is unavailable could lead to you failing the course. If you decide to use AI to complete a course assessment, then it is important that you are transparent about this use, including a statement to this effect at the beginning of your reports. Use of AI that falls within the permissible guidelines described here will not result in a penalty. Consequences of misuse of AI:Students suspected of using AI outside the specifications of this document will be reported to the department Academic Integrity Officer. Evidence of misuse may include (but is not limited to) vastly out-of-context material, calculation errors that are reproducible in an AI model; or significantly reduced performance and knowledge demonstration in the invigilated tests/exams than in the un-invigilated reports submissions. As part of their investigation, students may be invited to attend an interview, during which they may be asked to describe how the report was completed or to demonstrate their knowledge of the subject. If it is determined that a student is likely to have misused AI, i.e. and is unable to complete the assignment without its assistance, then disciplinary action may be taken, including partial or full denial of credit for an assignment or course, X-mark on transcript denoting breach of academic integrity, suspension, fines and expulsion. Further reading: Academic Integrity at the University of Canterbury. https://www.canterbury.ac.nz/about-uc/what-we-do/teaching/academic-integrity Engineering NZ guidelines on ethical use of Generative AI. https://www.engineeringnz.org/programmes/engineering-and-ai/appropriate-safe-and-ethical-use/
Domestic fee $1,122.00
International fee $6,238.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Civil and Natural Resources Engineering .