AESC30250 Environmental Data and Modelling

Academic Year 2024/2025

The first part of this module is designed to introduce students to general data management, handling and visualization, and basic statistics 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 and SPSS 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 analysis 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

Not yet recorded.


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 final project report - individually to students, post-assessment via Brightspace within 2 weeks Students’ feedback on T&L: End of semester feedback - online