AESC30250 Environmental Data and Modelling

Academic Year 2022/2023

The first part of this module is designed to introduce students to general data management, handling and visualisation as applied to environmental data.
The second part of the module provides an introduction to environmental modelling in the context of agricultural systems, with special focus on carbon and nitrogen cycles. It covers the general background and principles of modelling biogeochemistry (e.g., plant growth and development, soil carbon and nitrogen dynamics and soil greenhouse gas emissions) with a focus on the understanding of the process-based ecosystem model DayCent and its site level application as a practical case study.
The aim of the module is to advance students' data management skills as well as to provide theoretical and practical knowledge of ecosystem process-based modelling of agroecosystems.

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Curricular information is subject to change

Learning Outcomes:

On completion of this module students should be able to:
• Handle, manage, analyse and visualize environmental data using an Excel software
• Conduct a modelling research project considering model assumptions and limitations (research question, hypothesis testing, modelling approach, designing modelling scenarios, interpretation of results)
• Apply the DayCent model at a site scale and integrate the model with available data
• Critically evaluate model performance
• Set up, execute and compare outputs for modelling scenarios

Student Effort Hours: 
Student Effort Type Hours
Lectures

12
Computer Aided Lab

21
Specified Learning Activities

67
Autonomous Student Learning

25
Total

125
Approaches to Teaching and Learning:
The module consists of lectures and exercises, covering both the theoretical background and practical application of data analyses and agroecosystem modelling. The level of students’ understanding and skills gained from the lectures and exercises will be continuously evaluated et the end of each exercise session. The content of the lectures and the speed of delivery will be fine-tuned to the students’ needs. Short video tutorials will assist students to learn modelling skills and solve technical problems more independently and thus will improve students’ overall performance and module time management. Flipped classroom teaching strategy (i.e., instructional assignments) will be employed to better meet the needs of individual students.
 
Requirements, Exclusions and Recommendations
Learning Recommendations:

Students signing up for this module as an Elective should have a strong interest in data analysis and modelling of agroecosystem processes.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Lab Report: The lab report covers the content of the class assignments. Each student must submit at least five out of the eight reports, i.e. five is the minimum number considered for the overall grading. Throughout the Trimester n/a Pass/Fail Grade Scale No

30
Presentation: Presentation of the student final modeling project providing information about the objective, hypotheses, modeling approach and preliminary results. Week 12 n/a Graded No

30
Project: Final modelling project is a written report on the module project at the end of trimester. It includes introduction, material & methods, results, discussion of the results, conclusions and references. Coursework (End of Trimester) n/a Graded No

40

Carry forward of passed components
Yes
 
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Lecturer feedback: On presentation - individually to students, post-assessment via Brightspace within 1 week On project report - individually to students, post-assessment via Brightspace within 2 weeks Students’ feedback on T&L: Midterm feedback (Week 6) – questionnaire on the content and delivery of the module End of semester feedback - online