MSc Environmental Monitoring, Modelling and Reconstruction

Fees for entry in 2027 have not yet been set. For reference, the fees for the academic year beginning September 2026 were as follows:

• MSc (full-time)
  UK students (per annum): £15,200
  International, including EU, students (per annum): £33,600

The fees quoted above are fully inclusive of tuition, administration and computational costs.

Fees for entry are subject to yearly review. The University reserves the right to increase your tuition fee by up to 7% each year for courses lasting more than one year, including to reflect rising costs associated with delivering our educational and wider student experience. Postgraduate fees information .

Always contact the admissions team if you are unsure which fee applies to your qualification award and method of attendance.

International student CAS deposit

Self-funded international applicants are required to pay a deposit of £2500 towards their tuition fees before a confirmation of acceptance for studies (CAS) is issued. Some applicants will be required to pay a higher deposit. More information on tuition fee deposits .

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

We know that student finance can be complicated. The links below provide further information to help guide you.

• Learn more about - student finance options for UK students .
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• Graduates of The University of Manchester and Manchester Metropolitan University can receive a 10% discount on their master's degree tuition fees as part of our Manchester Alumni Loyalty Discount scheme.

The unit is run as a series of lectures and practicals where the focus is on preparing the student to be able to select the appropriate technique for measuring environmental data, to be able to analysis data, use Geographical Information Systems (GIS), and apply industry-standard software for hydrological modelling, river modelling, water resource modelling, and glacier runoff modelling in a range of climatic zones around the globe.

Each week, a new measurement and modelling approach will be introduced in a lecture, and students will then gain hands-on experience in data analysis, using GIS, applying numerical and machine learning (ML) models and interpreting model output. No prior experience is required: students are taught how to use GIS, industry-standard numerical modelling software, and Python for statistical analysis and ML.

The unit starts by using different numerical models (1D and 2D) and machine learning to explore flood hydrology and the mechanism of flooding, including techniques to collect and analyse hydrometric data. The unit prepares students to use GIS and apply geospatial analysis techniques to climate and rainfall data.

Students apply hydrological models to examine catchment flow dynamics and use one-dimensional (1D) and two-dimensional (2D) numerical river models to explore channel and floodplain hydraulics for rivers in the UK. The unit introduces ML models written in Python, such as Long Short-Term Memory (LSTM) networks, used to predict river flows under varying hydrological conditions.

The unit’s focus shifts to low flows, drought, water scarcity and food insecurity. The unit prepares students to apply water balance models as a tool to solve water security problems and help policymakers resolve water conflicts at the basin, regional and global scales. The unit introduces ML models written in Python to predict lake levels

Students use real-world data from the Rift Valley Lakes Basin (RVLB) in Ethiopia and learn how water stress is a constraint to agricultural production and economic development, resulting in food insecurity and poverty.

Students model water demands from irrigation agriculture and be able to model the sensitivity of water demand to different crop types, cropping patterns, and irrigation practices and model the change in water demands because of a future warmed climate.

The unit then examines global future megatrends, population growth, urbanisation, and climate change and their impacts on society. The unit introduces students to climate change models and some of the predicted impacts around the world, with a focus on East Africa.

Students analyse lake level data to identify seasonal and long-term trends, test for non-stationarity, and apply a Python-based SARIMA (Seasonal Autoregressive Integrated Moving Average) model, a statistical method for time series forecasting, to predict lake levels with a particular focus on East Africa.

The final part of the unit examines the glacial hydrological processes in mountain catchments. Students apply a glacier runoff model and perform a model calibration and sensitivity analysis on model parameters. The students make use of hydrometeorological data collected in the Upper Indus Basin, in the Karakoram Himalaya, Northern Pakistan.

To develop a student’s understanding of data analysis, environmental measurement, and the application of environmental modelling approaches in research and/or consultancy.

Specific aims are to:

• Equip students with the knowledge and skills to select and apply appropriate environmental measurement and modelling techniques across a range of hydrological systems.
• Develop students’ ability to analyse, interpret, and visualise environmental data using Geographical Information Systems (GIS), numerical models (hydrological and hydraulic), and machine learning (ML) methods.
• Provide practical experience with industry-standard modelling tools for hydrological, river, water resource, and glacier runoff modelling.
• Enable students to apply modelling approaches to address real-world environmental challenges such as flooding, drought, water scarcity, and climate change impacts.
• Enable students to critically understand the role of environmental modelling in policy-making, resource management, and climate resilience at local, regional, and global scales.
   

By taking this unit, students can expect to develop broader academic skills, including in hydrology and water resources.

Students will also develop employability skills, including data analysis, GIS, and environmental modelling, working independently and meeting deadlines.

The unit will also engage students in the development of their key skills in problem-solving, interpreting data and model output, and scientific writing through weekly practical exercises and the production of a practical book.

Students will gain experience with software through the weekly practicals by using industry-standard GIS and modelling software for hydrological and hydraulic modelling (1D and 2D).
 

Overall, the digital skills the students will learn include data and statistical analysis in Excel, Geographical Information Systems (QGIS), industry-standard 1D and 2D river modelling software (Flood Modeller) and hydrological models and learn about the use of water resource models (WEAP).

More specifically, students will have the opportunity to enhance their digital literacy through:

Digital Learning and Development:

• Navigating/accessing/ learning materials via the Virtual Learning Environment (VLE)
• Engaging in online tasks/activities/quizzes through technology-enhanced learning tools, for example, VLE and Mentimeter
• Undertaking online assessments
• Responding to online feedback
• Managing a portfolio of skills and development.

Digital Communication, Collaboration and Participation:

• Using a range of digital communications media appropriately, i.e., email/online forums)
• Communicating in a synchronous and asynchronous context
• Participating in online environments, i.e. Teams, VLE, Collaborate
• Sharing digital resources and content.

Information, Data and Media Literacy:

• Using appropriate search engines/indexes/databases to find information.
• Manage and retrieve information for study, i.e. referencing software.
• Presenting information, i.e. practical book
• Referencing digital sources of information appropriately
• Producing visualisations of data and reports (Excel, QGIS, Word, Google Col-Lab)
• Analysing data through data analysis software, GIS, modelling, and statistical analysis.

Digital Proficiency and Productivity:

• Using basic functions of productivity software, including text editing, spreadsheet, and GIS image editing
• Engaging with university platforms, including the VLE, email, library search tools, and assignment submission tools (e.g. Canvas Platform)
• Using specialist software, for example, QGIS, Flood Modeller, Excel, and Google Co-Lab)
• Managing projects, schedules and work plans using digital tools, for example calendar and Teams.

Digital Creation and Problem Solving:

• Producing digital resources such as figures for inclusion in the practical book
• Designing a digital solution to academic problems in applied hydrology and water resources using environmental modelling
• Selecting and interpreting digital data from GIS and hydrological and hydraulic (1D and 2D) models to answer questions and solve hydrological and water resource problems.
   

-hour lecture plus 2-hour practical on the computer cluster each week.
Content

1.    Measurement and Modelling in Environmental Science

Lecture: Flood Hydrology, Modelling and Modelling

• Principles and practice of UK flood hydrology.
• Hydrometric measurement and stage-discharge rating curves.
• Importance of modelling floods.
• Building 1D, 2D and 3D model with real-world case studies.
• Calibrating models.
• Interpolation techniques.

Practical: Climate Analysis and Hydrological Modelling using data for the Rift Valley Lakes Basin, Ethiopia.

2.    Rainfall-Runoff Modelling and Design Hydrology.

Lecture: Rainfall-Runoff Modelling and Design Flow Estimation

• Design hydrology.
• Rainfall-runoff processes.
• Types of rainfall-runoff models.
• Using the Revitalised FEH Rainfall-Runoff (ReFH) models.
• Calibrating and validating model parameters.
• Model uncertainty and limitations.
• Statistical methods to estimate return period design flows.

Practical: Hydrology and Hydrological Analysis - estimating design flood peaks at river gauges using data for UK catchments.

3.    Advanced Modelling in Environmental Science

Lecture: Hydraulic River Modelling

• Flood modelling process and why it’s relevant.
• Differences in 2D & 3D hydraulic models and application to real-world problems.
• Practical knowledge of industry-leading modelling software and capabilities.
• Using state-of-the-art Flood Modeller Pro software. 
• Using Machine Learning (ML), such as Long Short-Term Memory (LSTM) networks, to predict river flows.

Practical: Hydraulic River Modelling – Using Flood Modeller Pro (FMP) software to model river flows and levels for UK rivers.

4.    Water Resource Modelling

Lecture: Water Scarcity

• Water-Food-Energy Nexus and why it’s relevant for water resource modelling.
• Global water insecurity, water conflicts, and the economics of water scarcity.
• Drought and drought monitoring systems.
• Water balance modelling and application to real-world problems.
• ML models to predict lake levels.

Practical: Climate and water demand analysis for the Rift Valley, Ethiopia (Part 1).

5.    Water and Food Security

Lecture: Water Scarcity and Irrigation Agriculture

• Constraints to economic and agricultural development.
• Irrigation demands.
• Factors affecting evapotranspiration.
• Measurement and calculation of evapotranspiration.
• Crop factors, cropping patterns and calendars.
• Irrigation application methods, efficiencies, and water losses.
• Reservoir simulation and water balance modelling.

Practical: Climate and water demand analysis for the Rift Valley, Ethiopia (Part 2).

6.    Modelling in Mountain Environments

Lecture: Glacier Hydrology and Modelling

• Water resource prediction in high mountain basins
• Glacier hydrology and drainage systems
• Hydrometeorological measurement in mountain basins 
• Energy balance and degree day modelling
• Different types of glacier runoff models
• Limitations and constraints in modelling mountain basins
• Use of the glacier runoff model.

Practical: Glacier Runoff Modelling using data from Passu Glacier, Karakoram Himalayas, Northern Pakistan.
 

Each theme is taught using synchronous lectures (1 hour) supported by asynchronous lecture videos and lecture podcasts, and synchronous computer practical exercises (2 hours) using video guides asynchronously with weekly face-to-face and online drop-in help sessions.

The synchronous lectures cover different modelling approaches and themes; the relevant theory; the modelling approach, and usage cases for the model, with real-world examples.

The weekly synchronous computer practicals are taught through guided learning. Each computer practical is accompanied by an exercise document and guided videos, where students download and use data and models to simulate environmental processes, and plot / interpret the results based on a theme introduced in the lecture video.

Software used is freely available online for formative learning, most of which can be used away from the University. The distance learning students can remotely access the University computer clusters to access software.

Weekly activity is supplemented with asynchronous online video to aid with technical tasks, with regular help through a weekly synchronous office hour (face-to-face and online) and asynchronous help sessions, and via discussion boards and emails.

The course includes weekly online Tests so that the tutor can keep track of individual progress.

Experts from the industry share their knowledge of environmental modelling via videos using state-of-the-art software available to download at no cost.

Summative assessment through online Canvas  tests for each computer practical session, with immediate feedback, is given each week.

Summative assessment is through a practical book based on computer-based practical exercises related to each theme taught.

The Practical Book as a summative assessment is split into two parts. Part 1 is the Online Tests (20% of the total mark) and Part 2 is the written Practical Book of short answers (80%) to selected questions in the 5 computer practicals (max 2600 word limit ).

• Explain the importance of the water-food-energy nexus, global water insecurity, causes of water conflicts, and the economics of water scarcity, and how water resources modelling can assist policymakers for food security and poverty reduction purposes.

• Explain hydrometeorological data collection and environmental monitoring methods.
• Categorise different modelling approaches including hydrological and hydraulic (1D 2D and 3D) modelling, water resource modelling, glacier modelling, and climate models and apply using case studies.

• Apply flood hydrology and be able to estimate design flows used to resolve flooding problems.
• Apply industry-standard software for environmental modelling purposes and recognise their application to real-world problems.
• Use a glacier runoff model and interpret model output, to evaluate model performance and evaluate model parameters through sensitivity analysis.

Assessment task 1
Practical Book:
Part 1. 
Online Exercise Tests.
8 Test (7 to 19 questions).
Equivalent 400 words max.
Electronic feedback after submission date.
20% weighting.

Assessment task 2
Practical Book:
Part 2.
Practical Book – Short Answers from selected questions in the 5 Practicals.
2600 words.
Written online feedback via Canvas within 4 weeks.
80% weighting.

Assessment task 1
Electronic feedback after submission date.

Assessment task 2
Written online feedback via Canvas within 4 weeks.

R & D Project FD1913 ‘Revitalisation of the FSR/FEH rainfall-runoff method’
Flood Estimation Handbook Supplementary Report.
Flood Estimation Handbook (FEH) Volumes 1 – 5.
Shaw, E. (1991). Hydrology in Practice.

Ferguson, R. I., 1999. Snowmelt runoff models. Progress in Physical Geography, 23 (2), 205-227.

Fountain, A. G., and Tangborn, W., 1985. Overview of contemporary techniques. In Young, G. J. (ed.),
Techniques for the prediction of runoff from glacierized areas. International Association of Hydrological Sciences Publication number 149, 27-41.

Lowe, A.T. and Collins, D.N. 2001. Modelling runoff from large glacier basins in the Karakoram Himalaya using remote sensing of the transient snowline. International Association of Hydrological Sciences Publication number 267, 99-104.

Richard, C., and Gratton, D. J., 2001. The importance of the air temperature variable for the snowmelt runoff modelling using the SRM. Hydrological Processes, 15 (18), 3357-3370.

Turpin, O. C., Ferguson, R. I., and Clarke, C. D., 1997. Remote sensing of snowline rises as an aid to testing and calibrating a glacier runoff model. Phys. Chem. Earth, 22, 3-4, 279-283.

Various authors, 2003. Mountain Hydrology and Water Resources, Journal of Hydrology, Vol. 282, issues 1-4, 1-181.
 

Practicals: 24 hours
Office hours: 12 hours

Assessment hours (including preparation time) = 90 hours
Lecture prep (asynchronous learning): 12 hours

Time spent on unit 150 hours.