A Level H1 Geography Map Graph Data Skills Quiz

A-Level Geography H1 Quiz - Map Graph Data Skills - Answer Key

Total Marks: 50

Section A: Map and Spatial Data Interpretation

1. Describe the relief characteristics of the area located in Grid Square 4560. [2]

• Answer: The area is relatively flat/low-lying [1] with elevations generally below 20m (or specific contour reading) [1].
• Marking Note: Accept "gentle slope" if supported by widely spaced contours. Must reference elevation or contour spacing.

2. Calculate the gradient of the slope between Point A and Point B. [2]

• Answer:
  • Rise = 80m - 20m = 60m [1]
  • Run = 200m
  • Gradient = Rise / Run = 60 / 200 = 1 in 3.33 (or 0.3 or 30%) [1]
• Marking Note: 1 mark for correct difference in height, 1 mark for correct calculation/ratio.

3. Identify the most likely land use in Grid Square 4659 and provide one map evidence. [2]

• Answer: Industrial/Commercial [1]. Evidence: Presence of large rectangular building footprints, proximity to main road/railway, or lack of residential symbols [1].
• Marking Note: Evidence must be visible on a standard topographic map (e.g., building shape, transport links).

4. Explain how the drainage pattern influences potential for flash flooding. [3]

• Answer:
  • The pattern is likely dendritic or trellis (depending on map) [1].
  • High density of tributaries/steep upper courses leads to rapid surface runoff [1].
  • This causes water to converge quickly in the lower urban zone, exceeding channel capacity and causing flash floods [1].
• Marking Note: Must link physical drainage characteristic to the hydrological process (rapid runoff/convergence) and the impact (flooding).

5. Evaluate the claim that the settlement pattern is linear. [3]

• Answer:
  • The claim is partially correct/incorrect [1].
  • Evidence for: Settlements align along a main road/river [1].
  • Evidence against: There are clustered/nucleated elements away from the main axis, or the pattern is dispersed [1].
• Marking Note: Evaluation requires looking for counter-evidence or nuance, not just description.

Section B: Graph and Statistical Analysis

6. Describe the seasonal distribution of rainfall in City X. [2]

• Answer: Rainfall is highest in [Month/Season] and lowest in [Month/Season] [1]. There is a distinct wet/dry season (or uniform distribution if applicable) [1].
• Marking Note: Must identify peaks/troughs and characterize the overall pattern.

7. Calculate the annual temperature range. [1]

• Answer: Max Temp - Min Temp = [Correct Value]°C.
• Marking Note: Correct subtraction only.

8. Identify the anomaly in July rainfall and suggest a reason. [2]

• Answer:
  • Anomaly: July rainfall is significantly lower/higher than the surrounding months/trend [1].
  • Reason: E.g., Temporary high-pressure system, typhoon passage, or data error [1].
• Marking Note: Reason must be geographically plausible.

9. Describe the trend in Resource 3. [2]

• Answer: There is a negative correlation [1]. As distance from the city centre increases, population density decreases [1].
• Marking Note: "Negative correlation" or "inverse relationship" is key terminology.

10. Calculate the percentage decrease in population density. [2]

• Answer:
  • Decrease = 15,000 - 3,000 = 12,000 [1]
  • % Decrease = (12,000 / 15,000) * 100 = 80% [1]
• Marking Note: Working must be shown.

11. Explain the variation (scatter) at 5km–8km. [3]

• Answer:
  • This zone may represent a transition area (suburbs) [1].
  • Variation caused by mixed land uses (e.g., parks, industrial estates, high-density apartments) [1].
  • Local factors like transport nodes or topography create pockets of high/low density [1].
• Marking Note: Explanation must go beyond description to suggest causal factors for the variance.

12. Assess the reliability of single-year data for long-term climate. [3]

• Answer:
  • Low reliability [1].
  • Climate is defined by 30-year averages; one year may be an outlier due to extreme events (El Niño/La Niña) [1].
  • Single year does not capture long-term trends or variability [1].
• Marking Note: Must distinguish between weather (short-term) and climate (long-term).

Section C: Fieldwork Data and Methodology

13. Why is double-ring infiltrometer more appropriate? [2]

• Answer:
  • It minimizes lateral water loss (sideways movement) [1].
  • This ensures that water movement is primarily vertical, providing a more accurate measure of vertical infiltration rate [1].
• Marking Note: Key concept is controlling lateral flow.

14. Calculate difference and percentage. [2]

• Answer:
  • Difference = 43 mm/hr [1].
  • Percentage = (2 / 45) * 100 = 4.44% [1].
• Marking Note: Check calculation accuracy.

15. Justify use of bar chart. [2]

• Answer:
  • Data is categorical/discrete (Site A vs Site B) [1].
  • Bar charts allow for easy visual comparison of magnitudes between distinct categories [1].
• Marking Note: Contrast with continuous data (line graph) or proportional data (pie chart).

16. Evaluate usefulness of secondary flood data. [3]

• Answer:
  • Useful: Provides historical context and frequency/magnitude of events that primary data cannot capture [1].
  • Limitation: Secondary data may be incomplete, inaccurate, or not specific to the exact study sites [1].
  • Synthesis: Combining both allows correlation of infiltration capacity with actual flood history [1].
• Marking Note: Evaluation requires weighing strengths and weaknesses.

17. Source of error and minimization. [2]

• Answer:
  • Error: Soil disturbance during ring insertion or uneven ground [1].
  • Minimization: Careful insertion, using a leveling bubble, or repeating measurements and taking an average [1].
• Marking Note: Error and solution must match.

Section D: Synthesis and Evaluation

18. Synthesize Resource 4 and 5 to identify a pattern. [3]

• Answer:
  • Resource 4 shows loss of green space/increase in built-up area [1].
  • Resource 5 shows an increase in LST in the same locations [1].
  • Pattern: Urbanization/replacement of vegetation with concrete/asphalt leads to higher surface temperatures (Urban Heat Island effect) [1].
• Marking Note: Must link the visual change (land use) to the numerical change (temperature).

19. "Quantitative data is always more useful..." To what extent do you agree? [4]

• Answer:
  • Agree: Quantitative data (Resource 5) is objective, precise, and allows for statistical analysis/comparison [1].
  • Disagree: Qualitative data (Resource 4) provides spatial context, visual evidence of land use type, and identifies features numbers cannot (e.g., building height, vegetation type) [1].
  • Judgment: Neither is "always" more useful; they are complementary. Quantitative proves the extent of change, qualitative explains the nature of change [1].
  • Conclusion: Integrated use is best for comprehensive understanding [1].
• Marking Note: Look for balanced argument. "Always" is a strong word that should be challenged.

20. Discuss two limitations of using only these resources for planning. [4]

• Answer:
  • Limitation 1: LST is surface temperature, not air temperature experienced by humans. It may not fully reflect human thermal comfort/health risks [2].
  • Limitation 2: Satellite images are a snapshot in time. They do not show temporal variations (e.g., night vs day, seasonal changes) or subsurface factors (e.g., underground utilities, soil moisture) [2].
  • Alternative: Lack of socio-economic data (who is affected?) or wind flow data.
• Marking Note: 2 marks per well-explained limitation. Must be specific to the resources mentioned.