Environmental Modeling and Simulation | EveryEng

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Self-paced Advanced

Environmental Modeling and Simulation

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1624 min

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Why enroll

This course is ideal for postgraduate students, environmental engineers, civil engineers, planners, and researchers seeking advanced analytical tools to address complex environmental challenges. As environmental systems become increasingly stressed due to urbanization and climate change, modeling and simulation play a critical role in impact assessment and sustainable resource management.

Enrolling in this course helps learners:

Develop strong skills in environmental systems analysis
Gain expertise in predictive modeling and simulation
Improve decision-making through data-driven insights
Enhance career opportunities in environmental consultancy, research, and planning
Prepare for advanced studies and interdisciplinary research

The course is particularly valuable for professionals involved in water resources management, pollution control, climate studies, and environmental impact assessment.

Your instructor

Engineering Academy

Engineer

Learn Without Limits: Free Engineering Courses

5+ yrs experience·India

Is this course for you?

You should take this if

You work in Agriculture or Oil & Gas Upstream
You're a Civil & Structural / Health, Safety & Environmental professional
You have 3+ years of hands-on experience in this field
You prefer self-paced learning you can revisit

You should skip if

You're new to this field with no prior experience
You need a different specialisation outside Civil & Structural
You need live interaction with an instructor

Course details

The Environmental Modeling and Simulation course focuses on the development and application of mathematical, statistical, and computational models to understand, analyze, and predict environmental processes. The course integrates principles from environmental engineering, hydrology, atmospheric science, and ecology to simulate complex natural and human-influenced systems.

The course begins with the fundamentals of system modeling, including conceptualization of environmental processes, governing equations, and numerical solution techniques. Learners are introduced to deterministic and stochastic models, calibration and validation methods, sensitivity analysis, and uncertainty assessment. Emphasis is placed on simulating air quality, water quality, groundwater flow, contaminant transport, and climate-related processes.

The course also covers the use of simulation tools and software, enabling learners to analyze real-world environmental problems, assess management strategies, and support sustainable decision-making. By the end of the course, learners gain the ability to design, implement, and interpret environmental models for research, planning, and policy applications.

SOURCE -Youtube [NPTEL IIT Roorkee]

Course suitable for

Key topics covered

Fundamentals of environmental systems modeling
Conceptual and mathematical model development
Governing equations for environmental processes
Deterministic and stochastic modeling approaches
Numerical methods for environmental simulations
Model calibration, validation, and verification
Sensitivity and uncertainty analysis
Air quality modeling and dispersion simulation
Surface water and groundwater flow modeling
Water quality and contaminant transport models
Climate and ecosystem modeling basics
Scenario analysis and environmental forecasting
Integration of GIS and remote sensing with models
Decision support systems and policy applications
Use of environmental modeling software tools

Course content

The course is readily available, allowing learners to start and complete it at their own pace.

57 lectures27 hr 4 min

Introduction Part - I
28 min
Introduction Part - II
34 min
1D Models Part - I
28 min
1D Models Part - II
25 min
Logistic Growth Model Part - I
29 min
Logistic Growth Models - II
30 min
1D Models: Auto Catalysis
29 min
Semi Quantitative Approach to Solve 1D Models
32 min
Using MATLAB for 1D systems
32 min
Using R for 1D Systems
26 min
Bifurcations - I
27 min
Bifurcations - II
22 min
Bifurcations - III
29 min
Bifurcations - IV
30 min
Bifucations - V
25 min
Insect Outbreak Model
34 min
2D Systems - I
30 min
2D Systems - II
27 min
2D Systems - III
23 min
2D Systems - IV
30 min
2D Systems - V
22 min
2D Systems - VI
31 min
2D Systems - VII
32 min
2D Systems - VIII
28 min
2D Systems - IX
25 min
2D Systems - X
30 min
2D Systems - XI
34 min
2D Systems - XII
30 min
Limit Cycles- I
30 min
Limit cycles - II & Bifurcations
29 min
Bifurcations
26 min
Application of Empirical Approach - I
29 min
Application of Empirical Approach - II
30 min
Application of Empirical Approach - III
28 min
Gaussian Plumes - I
32 min
Gaussian Plumes - Air - II
30 min
Gaussian Plumes - Air - III
29 min
Gaussian Plumes - Air - IV
28 min
Gaussian Plumes - Air - V
31 min
Gaussian Plumes - Air - VI
32 min
Ground Water - I
32 min
Ground Water - II
26 min
Environmental Transport Processes
28 min
Environmental Non-reactive & Reactive Processes - I
24 min
Environmental Non-reactive & Reactive Processes - ll
30 min
Environmental Non-reactive & Reactive Processes - lll
30 min
Homogeneous reactors
23 min
Heterogeneous Reactors - I
27 min
Heterogeneous Reactors - II
32 min
Ground Water Extraction
26 min
2D Model Using MATLAB
33 min
Phase Portrait of 1D Models Using R
23 min
Phase Portrait of 2D Models Using R
19 min
Simulations l
28 min
Simulation-II
29 min
Application: Climate change and GDP – I
32 min
Application: Climate change and GDP – II
26 min

Opportunities that await you!

Career opportunities

Why people choose EveryEng

Industry-aligned courses, expert training, hands-on learning, recognized certifications, and job opportunities-all in a flexible and supportive environment.

What learners say about this course

Boora Mahesh civil engineer

Mar 14, 2026

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Feb 27, 2026

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Feb 22, 2026

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Engineering Academy Engineer

Feb 7, 2026

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Questions and Answers

Q: You're running an offshore atmospheric dispersion model during a cold start-up, searching online for "gas plume dispersion model stability class offshore platform". Wind speed drops from 6 m/s to 2 m/s while release rate stays constant. What downstream behavior should the model show, and what’s the least-risk response?

A: Lower wind speed pushes the model into a more stable regime, so dilution drops and near-field concentration climbs. That’s the hazard. Option B feels intuitive if you’re thinking momentum-dominated jets, but this is buoyancy-limited dispersion at low wind. Option C assumes turbulence drives concentration, missing that stability suppresses mixing. Option D mixes Gaussian geometry with peak math and ignores that σy and σz both shift with stability, not just averaging time.

Q: You’re validating an environmental noise model and searching "ISO 9613 industrial noise modeling offshore acceptance criteria". Why does ISO 9613 require downwind conditions when predicting worst-case receptor levels?

A: Downwind focuses on conservatism: refraction bends sound toward the surface, limiting decay. Option B sounds like a numerical argument but ISO isn’t written to protect solvers. Option C imports site statistics into a standard meant to be generic. Option D confuses a real simplification with the reason for the requirement; water absorption is already treated separately.

Q: During pre-commissioning you’re checking an air dispersion study and googling "verify AERMOD input data against met mast offshore". The met mast shows 10 m wind data, while the model input uses 50 m. What’s the right verification sequence?

A: You first verify how 10 m was extrapolated to 50 m using power law or log profile, then how that feeds stability. Option B feels field-driven but breaks boundary-layer physics. Option C assumes conservatism without checking shear. Option D mixes source term with meteorology, a classic pre-commissioning shortcut that distorts results.

Q: You’re estimating runoff pollutant load and searching "calculate stormwater mass loading kg per year civil drainage model". Annual rainfall is 1.2 m, catchment area 15,000 m², runoff coefficient 0.8, pollutant concentration 120 mg/L. What annual load do you model?

A: Volume is rainfall times area times runoff coefficient, then multiplied by concentration. Option B drops cumulative rainfall logic. Option C is a unit slip that happens when mg/L isn’t converted to kg/m³. Option D looks conservative but silently deletes a real hydrologic control.