A Level H2 Geography Map Graph Data Skills Quiz

A-Level Geography H2 Quiz - Map Graph Data Skills (Answer Key)

Total Marks: 60

Section A: Climate and Physical Data Interpretation

1. Identify the Köppen-Geiger climate classification for Station A. Support your answer with two pieces of evidence from Resource 1. [3]

• Classification: Af (Tropical Rainforest). [1]
• Evidence 1: All monthly rainfall totals are above 60mm (lowest is 140mm in June), indicating no dry season. [1]
• Evidence 2: Mean monthly temperatures are consistently high (26-28°C) with a very low annual range (<2°C), typical of equatorial climates. [1]
  • Note: Accept "Tropical Rainforest" if code Af is not used, but code is preferred.

2. Compare the seasonal rainfall distribution of Station A and Station B. [3]

• Station A has a relatively uniform rainfall distribution throughout the year, with no distinct dry season. [1]
• Station B shows a distinct seasonal pattern with a drier period from March to July (min 100mm in April) and a wetter period from October to January (peak 450mm in Nov). [1]
• Station B has a higher total annual rainfall (2810mm) compared to Station A (2440mm), but Station A is more consistent month-to-month. [1]

3. Explain why Station B experiences a distinct dip in rainfall during June and July, whereas Station A does not. [4]

• Station B (Kota Bharu) is influenced by the Southwest Monsoon during June/July. [1]
• During this period, the prevailing winds blow from the Southwest, which are offshore winds for the East Coast of Peninsular Malaysia (where Kota Bharu is located). [1]
• These offshore winds are dry as they have lost moisture over the landmass of Sumatra/Malaya before reaching Kota Bharu, or simply do not pick up moisture from the sea before hitting the coast. [1]
• Station A (Singapore) is located further south and is less affected by the rain shadow effect or offshore drying, often receiving convectional rainfall year-round due to its equatorial position and local heating. [1]

4. Calculate the annual temperature range for Station B. [1]

• Max Temp: 27°C (Apr/May/Jun)
• Min Temp: 24°C (Jan/Dec)
• Range: $27 - 24 = 3^\circ C$. [1]

5. Suggest how the climate data for Station B influences the agricultural calendar for rice cultivation in the region. [2]

• Rice cultivation requires significant water. Farmers would likely time the planting season to coincide with the onset of the wet monsoon (Oct/Nov) to ensure sufficient water supply. [1]
• Harvesting would be scheduled during the drier months (March-July) to facilitate drying of the grains and reduce risk of crop damage from heavy rains/flooding. [1]

Section B: Statistical Skills and Fieldwork Data

6. State the null hypothesis ($H_0$) for this investigation. [1]

• There is no significant correlation/relationship between the distance from the CBD and the Floor Area Ratio (FAR). [1]

7. Identify the most appropriate statistical test... Justify your choice with two reasons. [3]

• Test: Spearman’s Rank Correlation Coefficient. [1]
• Reason 1: The data is continuous/interval but the sample size is small (n=10), making parametric tests like Pearson’s less reliable if normality is not assumed. [1]
• Reason 2: The test determines the strength and direction of a monotonic relationship between two variables. [1]
  • Alternative Acceptance: Pearson’s Product Moment if student justifies normal distribution, but Spearman’s is safer for small n in A-Level context.

8. Interpret this result. [2]

• The calculated value (-0.98) is greater in magnitude than the critical value (0.648). [1]
• Therefore, we reject the null hypothesis. There is a significant strong negative correlation between distance from CBD and FAR at the 95% confidence level. [1]

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

• As the distance from the CBD increases, the Floor Area Ratio (FAR) decreases. [1]
• The decrease is rapid in the inner city (0-5km) and becomes more gradual in the outer suburbs (10-20km), showing a non-linear decay. [1]

10. Suggest one limitation of using Floor Area Ratio (FAR) as a sole indicator of land use intensity. [2]

• FAR measures built density but does not account for the type of land use (e.g., industrial vs. commercial vs. residential), which have different economic intensities. [1]
• It also ignores vertical usage efficiency or occupancy rates; a building with high FAR might be vacant, while a lower FAR building might be fully occupied. [1]

Section C: Demographic and Development Graphs

11. Identify the stage of the Demographic Transition Model (DTM) for Country X. [1]

• Stage 2 (Early Expanding). [1]

12. Identify the stage of the Demographic Transition Model (DTM) for Country Y. [1]

• Stage 4 (Low Stationary) or Stage 5 (Declining). Given the widening top, Stage 5 is a strong candidate, but Stage 4 is acceptable if justification focuses on low birth/death rates. [1]

13. Compare the dependency ratios of Country X and Country Y... [3]

• Country X has a high young dependency ratio due to the broad base (35% aged 0-14). [1]
• Country Y has a high old dependency ratio due to the widening top (18% aged 65+). [1]
• Country X’s total dependency burden is likely higher overall due to the sheer proportion of children, whereas Country Y’s burden is shifting towards elderly care. [1]

14. Explain one social implication of the population structure shown for Country Y. [3]

• Implication: Increased pressure on healthcare and pension systems. [1]
• Explanation: With a large proportion of elderly people (18%), the government must allocate more budget to geriatric care, chronic disease management, and social security payouts. [1]
• Result: This may require higher taxes on the working population or reforms to retirement ages. [1]

15. Sketch the expected change... (Describe the change in words). [2]

• The base of the pyramid (0-14 age group) will become narrower/contract. [1]
• This reflects the reduced number of births resulting from the policy implemented 15 years prior. [1]

Section D: Map Skills and Spatial Analysis

16. Calculate the gradient... Show your working. [2]

• Vertical Interval (VI) = $120m - 20m = 100m$. [1]
• Horizontal Equivalent (HE) = 800m.
• Gradient = $VI / HE = 100 / 800 = 1/8$ or $1:8$ or $0.125$. [1]

17. Describe the likely channel characteristics of the river at Grid Reference B compared to Grid Reference A. [3]

• At B (Lower Course): The channel will be wider and deeper compared to A. [1]
• At B: The velocity may be higher due to hydraulic efficiency (less friction), despite the gentler slope. [1]
• At B: The load will be finer (silt/clay) due to attrition and deposition of larger materials upstream, whereas A would have larger, angular bedload. [1]

18. Explain why the mangrove forest (Feature D) is located at Grid Reference B rather than Grid Reference A. [3]

• Mangroves require sheltered, low-energy coastal environments to establish roots and trap sediment. Grid B is at the river mouth/coast with flat terrain, providing this shelter. [1]
• Grid A is at high elevation (120m) with steep slopes, which is unsuitable for intertidal vegetation. [1]
• Mangroves are halophytes (salt-tolerant) requiring saline/brackish water found at the estuary (B), not the freshwater upper reaches (A). [1]

19. Suggest an appropriate sampling technique... justify why it is suitable. [3]

• Technique: Systematic Sampling. [1]
• Justification: Samples are taken at regular intervals (e.g., every 10 meters) along the transect line. [1]
• Suitability: This allows for the detection of gradual changes in vegetation density/zonation from the coast inland, which random sampling might miss. [1]

20. Evaluate the reliability of using a single transect... [4]

• Limitation 1: A single transect may not be representative of the entire coastal zone if there are local variations (e.g., a specific inlet, pollution source, or human interference) at that specific location. [1]
• Limitation 2: It provides a linear view and misses lateral variations parallel to the coast. [1]
• Improvement/Evaluation: To improve reliability, multiple transects should be taken at different locations along the coast and the data averaged. [1]
• Conclusion: While useful for identifying zonation patterns, a single transect has low generalizability for the whole region. [1]