ENVX3003: Semester 2, 2022

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Units ENVX3003 Semester 2 2022 [Normal day]

Unit of study_

ENVX3003: Hydrological Monitoring and Modelling

Semester 2, 2022 [Normal day] - Camperdown/Darlington, Sydney

Overview

Globally, and in Australia in particular, water quantity and quality problems are growing due to increasing human use and a changing climate. In this unit, you will engage with field-based and quantitative problems related to water quantity and quality. This includes a multi-day field trip to regional NSW to collect samples and engage with field-based activities. During these activities, you will develop field-based skills for collection of hydrological data. The data will be used later in the unit to analyse and map the water quantity and quality issues in the catchment, relating this to landscape, management and climate. The second part of the unit focusses on developing an insight into model building, model calibration, validation and sensitivity analysis. It links back to the field experience by using long-term data collected by previous student cohorts and focussing on the identified landscape issues. This part of the study will allow you to directly engage with numerical approaches in prediction and forecasting in landscape hydrological models. The unit of study is specifically designed to extend your field hydrological knowledge and to strengthen your analytical and numerical skills in this area.

Unit details and rules

Unit code	ENVX3003
Academic unit	Life and Environmental Sciences Academic Operations
Credit points	6
Prohibitions ?	LWSC3007
Prerequisites ?	Completion of 72 credit points of units of study
Corequisites ?	None
Assumed knowledge ?	SOIL2005 or GEOS2116 or ENVI1003 or GEOS1001 or ENSC2001
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Julieta Rossi, julieta.rossi@sydney.edu.au
Lecturer(s)	Floris Van Ogtrop, floris.vanogtrop@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Record+)	Final exam Final exam Record + (AI invigilation)	50%	Formal exam period	2 hours
Outcomes assessed:
Small test	Assignment 1 Online quiz	10%	Week 04	1 hour
Outcomes assessed:
Assignment	Assignment 2 Written assignment	10%	Week 07 Due date: 18 Sep 2022 at 23:59	1000 words
Outcomes assessed:
Assignment	Practical report Report	15%	Week 12	3000 word
Outcomes assessed:
Presentation	Group presentation and diary Presentation and diary	15%	Week 12	1000 words
Outcomes assessed:
= group assignment ? = Type B final exam ?

Assessment summary

Final Exam: If a second replacement exam is required, this exam may be delivered via an alternative assessment method, such as a viva voce (oral exam). The alternative assessment will meet the same learning outcomes as the original exam. The format of the alternative assessment will be determined by the unit coordinator.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	1. How do we know what water is where and how much?; 2. Overview of the unit topics and review of SOIL2005	Lecture (2 hr)
Week 02	Rainfall-runoff processes in a changing world	Lecture (2 hr)
Week 03	1. Using models to manage water resources; 2. Distributed models and lumped models	Lecture (2 hr)
Week 04	1. Basic model calibration and evaluation 2. Novel data for models using remote sensing	Lecture (2 hr)
Week 05	Models as digital twins	Lecture (2 hr)
Week 06	Using models to analyse scenarios of change: pitfalls and opportunities	Lecture (2 hr)
Week 07	Water quality and management	Lecture (2 hr)
Week 08	Water quality and management	Lecture (2 hr)
Week 09	Water quality and management	Lecture (2 hr)
Week 10	Water quality and management	Lecture (2 hr)
Week 11	Water quality and management	Lecture (2 hr)
Week 12	Review of the unit	Lecture (2 hr)
Weekly	Weekly practical. Analysing data, developing modelling skills, working with field data	Computer laboratory (30 hr)

Attendance and class requirements

Due to the exceptional circumstances caused by the COVID-19 pandemic, attendance requirements for this unit of study have been amended. Where online tutorials/workshops/virtual laboratories have been scheduled, students should make every effort to attend and participate at the scheduled time. Penalties will not be applied if technical issues, etc. prevent attendance at a specific online class. In that case, students should discuss the problem with the coordinator, and attend another session, if available.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. confidently explain the different processes in the hydrological cycle
LO2. independently collect spatial and temporal water data and analyse and interpret this data and understand relevant related QA processes
LO3. link water quantity and water quality to landscape, climate and management
LO4. calibrate and validate a hydrological model
LO5. articulate advantages and disadvantages of using simulation models for catchment management
LO6. identify the interplay between data availability, data quality and models
LO7. critically analyse problems around sustainable water resource management policy and practice in Australia using course material, scientific literature, policy and popular media.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Overall feedback has been positive, however there is some grumbling about the coding in the unit. We have this year tried to revise some of the practicals to make them more applicable to current problems and applications.

Additional information

Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

General laboratory safety rules

No eating or drinking is allowed in any laboratory under any circumstances
A laboratory coat and closed-toe shoes are mandatory
Follow safety instructions in your manual and posted in laboratories
In case of fire, follow instructions posted outside the laboratory door
First aid kits, eye wash and fire extinguishers are located in or immediately outside each laboratory

As a precautionary measure, it is recommended that you have a current tetanus immunisation. This can be obtained from University Health Service: unihealth.usyd.edu.au/

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

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