Welcome to Physical Geography Fieldwork

Fieldwork is geography come to life! Instead of just reading about rivers or coastlines in a textbook, physical fieldwork involves going outside, measuring natural processes, and gathering your own geographical evidence. Don't worry if fieldwork seems daunting at first; it follows a clear, step-by-step route that you can easily master.

For your OCR GCSE (9–1) Geography B (J384) course, physical fieldwork is assessed in Component 01: Our Natural World (Section B). It makes up part of the 15% fieldwork component across your GCSE. You will be asked questions about your own physical fieldwork experience as well as questions about unfamiliar fieldwork studies carried out by others.

The OCR Fieldwork Requirements

Let's look at the basic rules set by OCR for your fieldwork:

  • Two Mandatory Days: You must carry out a minimum of two days of fieldwork outside the classroom: one in a physical environment and one in a human environment.
  • Contrasting Locations: The fieldwork must take place outside of your school grounds in contrasting locations.
  • Physical Themes: Your physical study will link directly to topics such as Rivers (e.g., how channel shape or bedload changes downstream), Coasts (e.g., how coastal management affects beach profiles or sediment size), or Hazards/Climate.

Top Tip: Always make sure you can name the exact location of your physical fieldwork (e.g., River Carding Mill, Shropshire or Chesil Beach, Dorset) and describe its main physical characteristics. Examiners regularly note that students lose marks by simply writing "a river in England"!

The 6 Stages of the Geographical Enquiry Process

All geographical enquiries follow a logical, six-stage cycle. Think of this as your geographical investigation roadmap:

Stage 1: Asking Questions (Formulating Hypotheses)

Every enquiry begins with a question or a hypothesis (a testable prediction).
Example Enquiry Question: "How does bedload size change from the upper to the lower course of the river?"
Example Hypothesis: "Bedload size and angularity will decrease downstream due to attrition and erosion."

Stage 2: Collecting Evidence (Fieldwork Methods)

This is where you go out into the field to collect data. To get high marks, you need to understand the different data types and sampling techniques you used.

Data Classifications
  • Primary Data: First-hand data you collect yourself in the field (e.g., measuring river velocity with an impeller flowmeter, measuring pebble length with calipers).
  • Secondary Data: Information collected by someone else that you use to support your study (e.g., historical flood data from the Environment Agency, geology maps, or historical weather records).
  • Quantitative Data: Numerical measurements that can be easily recorded and graphed (e.g., river depth in cm, pebble width in mm).
  • Qualitative Data: Descriptive, non-numerical information (e.g., annotated field sketches, photographs of river features).
Sampling Strategies

You cannot measure every single pebble or every single drop of water, so you must select a sample:

  • Random Sampling: Every sample point or pebble has an equal chance of being chosen (e.g., using a random number table to pick coordinates on a grid). Advantage: Avoids human bias. Disadvantage: Can accidentally miss key areas.
  • Systematic Sampling: Data is collected at regular intervals along a line or grid (e.g., measuring river depth every \(0.5\text{ m}\) across a transect, or testing a pebble every \(2\text{ m}\)). Advantage: Easy to organise and provides an even spread.
  • Stratified Sampling: Dividing the site into distinct sub-groups or zones and sampling proportionally from each (e.g., taking samples from both the riffles and the pools of a river). Advantage: Ensures all parts of the river or coast are represented.

Stage 3: Processing and Presenting Evidence

Once you return to the classroom, raw numbers need to be turned into clear visual formats. You must be confident in selecting and interpreting these presentation techniques:

  • Bar Charts: Best for comparing discrete categories (e.g., average pebble size at 5 different river sites).
  • Line Graphs: Ideal for showing continuous change over a distance (e.g., river cross-profiles).
  • Scatter Graphs: Used to look for relationships/correlations between two variables (e.g., distance downstream vs. pebble roundness). You should be able to draw and interpret a line of best fit.
  • Pie Charts & Proportional Symbols: Useful for displaying proportions or showing quantities located directly on a map.
  • Cartographic Skills: Locating study sites on OS maps using 4-figure and 6-figure grid references at \(1:25,000\) and \(1:50,000\) scales, as well as shading choropleth maps.

Stage 4: Analysing and Explaining Evidence

Analysis involves looking at your graphs and maps, spotting patterns, and explaining them using your geographical understanding.

  • Describe the Pattern: Say what the graph shows (e.g., "As distance from source increases, pebble length decreases").
  • Use Data: Always back up your points with specific figures from your graphs (e.g., "At Site 1, average pebble length was \(12.4\text{ cm}\), falling to \(3.1\text{ cm}\) at Site 5").
  • Explain the 'Why': Use geographical theory to explain the cause (e.g., "This occurs because pebbles collide with each other during transport, wearing down their edges through attrition").
  • Identify Anomalies: Point out any values that break the overall pattern and suggest why they might have occurred (e.g., a sudden increase in pebble size due to a nearby tributary adding fresh, un-eroded sediment).

Stage 5: Drawing Conclusions

In this stage, you summarise your findings and link them directly back to your original hypothesis or enquiry question. State clearly whether your evidence supports or refutes your initial prediction.

Stage 6: Evaluating the Enquiry

Evaluation is all about being critical of your own methods. To achieve top marks, do not just list what went wrong; explain how limitations affected your results and what improvements you would make.

Essential Mathematical & Statistical Skills

You need to be able to calculate and interpret key statistical measures in your exam:

  • Mean: The mathematical average. Sum of all values divided by the total number of values:

    \(\text{Mean} = \frac{\sum x}{n}\)

  • Median: The middle value when the data set is arranged in ascending order.
  • Mode: The most frequently occurring value in the data set.
  • Range: The difference between the highest and lowest values:

    \(\text{Range} = \text{Maximum Value} - \text{Minimum Value}\)

  • Percentage Change: Used to show how much a measurement has increased or decreased:

    \(\text{Percentage Change} = \left( \frac{\text{New Value} - \text{Original Value}}{\text{Original Value}} \right) \times 100\)

Key Distinctions & Common Pitfalls

Accuracy vs. Reliability

These two terms are often confused by students:

  • Accuracy: How close a measurement is to the true, real value. (Example: Using digital calipers instead of a standard ruler gives higher accuracy when measuring pebble axes).
  • Reliability: Whether your results are consistent and can be reproduced if the test is repeated. (Example: Measuring river velocity 3 times at each site and calculating an average improves reliability).

Command Words in Fieldwork Questions

OCR uses specific command words in the Section B fieldwork exam:

  • Describe: State the facts or patterns clearly without giving reasons.
  • Explain: Give reasons why something happens using geographical concepts.
  • Justify: Give valid reasons to support why a specific method, sampling technique, or presentation choice was selected.
  • Assess / Evaluate: Weigh up strengths and weaknesses, consider the significance of limitations, and reach a reasoned final judgement.

Quick Review: Summary of Key Takeaways

  • Fieldwork Requirement: Minimum of 2 contrasting days (1 physical, 1 human) outside school grounds.
  • Enquiry Framework: 6 stages: Asking Questions \(\to\) Collecting Evidence \(\to\) Processing & Presenting \(\to\) Analysing & Explaining \(\to\) Drawing Conclusions \(\to\) Evaluating.
  • Data Types: Primary (collected yourself) vs. Secondary (collected by others); Quantitative (numbers) vs. Qualitative (descriptive/visual).
  • Sampling Types: Random (equal chance), Systematic (regular intervals), Stratified (split by sub-groups).
  • Evaluation Strategy: Clearly separate accuracy from reliability, identify anomalies, and explain how method limitations influenced your overall conclusion.