Secondary 3 Geography Practice Paper 1

TuitionGoWhere Practice Paper - Geography Secondary 3: Answer Key & Marking Scheme

Subject: Geography | Level: Secondary 3 | Paper: Practice Paper 1 - Map, Graph & Data Skills | Total Marks: 50

Section A: Map Skills (20 marks)

1. Study the map extract of Area X. (a) Six-figure grid reference of spot height 142: 032054
Marking: 1 mark for correct 6-fig GR. Must have 3 digits Easting (032) and 3 digits Northing (054). Accept 032054 or 032 054.

(b) Direction of quarry from Benchmark 12.5m (062048): North West (NW) or West North West (WNW)
Marking: 1 mark. Quarry is at approx 055055. Benchmark at 062048. Quarry is West (lower easting) and North (higher northing). Accept 8-point or 16-point compass rose directions between WNW and NW.

(c) Straight-line distance between Bridge (055062) and Wind Pump (082038):
Working:

• Map distance: Measure distance on map. $\Delta E = 082 - 055 = 27$ mm (2.7 km). $\Delta N = 062 - 038 = 24$ mm (2.4 km). Wait, grid squares are 1km = 4cm (40mm) on 1:25,000 map.
• Correction: On 1:25,000, 1km = 4cm = 40mm.
• Bridge (055062) -> Wind Pump (082038).
• Easting diff: $082 - 055 = 27$ units (0.27 km? No, grid refs are in 100m units usually for 6-fig. 6-fig: 055 = 5.5km? No. Standard 6-fig: 055062 means E 05.5km, N 06.2km. Let's assume 100m grid for 6-fig).
• Standard Topo Map: 4cm = 1km. Grid lines 1km apart (4cm).
• Bridge at 055062 (E 5.5km, N 6.2km). Wind Pump at 082038 (E 8.2km, N 3.8km).
• $\Delta E = 2.7$ km. $\Delta N = 2.4$ km.
• Distance $= \sqrt{2.7^2 + 2.4^2} = \sqrt{7.29 + 5.76} = \sqrt{13.05} \approx 3.61$ km.
• Alternative: Measure on paper. If map printed correctly, measure cm $\times$ 0.25.
• Answer: 3.6 km (accept 3.5 – 3.7 km).
  Marking: 1 mark for correct measurement method/working, 1 mark for correct answer with units (km).

(d) Average gradient between Spot Height 142 (032054) and River Bank (035051): Working:

• Vertical Interval (VI): Spot height = 142m. River bank at 035051. Contours near river? River flows at bottom of valley. Contour at 035051 likely 20m or 40m? Spot height 142 at 032054. Next contour south is 120m, then 100m, 80m, 60m, 40m, 20m. River at 035051 is near 20m contour? Let's assume river level $\approx$ 20m (sea level at coast).
• VI = $142 - 20 = 122$ m.
• Horizontal Equivalent (HE): Distance on map between 032054 and 035051.
• $\Delta E = 3$ (300m). $\Delta N = 3$ (300m). Wait, Northing decreases from 054 to 051 = 300m. Easting increases 032 to 035 = 300m.
• Map distance $= \sqrt{300^2 + 300^2} = \sqrt{180,000} \approx 424$ m.
• Gradient $= \frac{VI}{HE} = \frac{122}{424} = \frac{1}{3.47}$.
• Answer: 1 : 3.5 (accept 1 : 3.4 – 1 : 3.6).
  Marking: 1 mark for correct VI (122m), 1 mark for correct HE measurement/calculation (~424m), 1 mark for correct ratio format 1:x.

2. (a) Drainage pattern: Dendritic
Marking: 1 mark.

(b) Two reasons with map evidence:

1. Uniform rock structure / Homogeneous geology: The tributaries join the main river at acute angles (less than 90°), resembling tree branches, indicating the underlying rock has uniform resistance to erosion. [1]
2. Gentle, undulating relief: Contour lines show gentle slopes (wide spacing) in the upper catchment (e.g., around 0207), allowing water to flow in random directions and form a branching network rather than being forced by structural controls (faults/joints) or steep slopes. [1]
3. Alternative: Absence of major faults/joints controlling river course (no straight line segments/right angle bends). [1] Marking: 1 mark per valid reason + map evidence. Max 3 marks.

3. (a) Contour interval: 20 metres
Marking: 1 mark. (Stated in map margin/legend).

(b) Relief of area Eastings 02–05, Northings 04–07:

• General character: Hilly / Undulating highland. [1]
• Specific features: A distinct hill with spot height 142m at 032054 forms the highest point. [1]
• Slope: Steep slopes on the western and northern sides (contours closely spaced), gentler slopes towards the south-east leading down to the river valley (contours widely spaced). [1]
• Valley: A V-shaped valley / river valley cuts through the south-eastern corner (River flowing SE), with convex slopes. [1 - any 3 points for 3 marks] Marking: 1 mark per valid descriptive point with map evidence (grid refs/contour spacing). Max 3 marks.

(c) Widely spaced/absent contours near coast (06–09, 02–04):

• Gradient: Very gentle / Flat / Low gradient (almost 0°). [1]
• Landform: Coastal plain / Alluvial plain / Floodplain / Mangrove swamp area. [1] Marking: 1 mark for gradient, 1 mark for landform.

4. Kampong Ayer (045065) (a) Site factors (with map evidence):

1. Water supply: Located adjacent to the river (fresh water for drinking, irrigation, transport). [1]
2. Dry point / Flood avoidance: Situated on slightly higher ground (contours 20m-40m) just above the mangrove swamp / floodplain (low-lying, wet ground) to the south/east. [1]
3. Defence / Shelter: Backed by higher ground / hills (spot height 142 to NW) offering protection from prevailing winds/coastal storms. [1]
4. Bridging point / Route focus: Located near a bridge (055062) and convergence of tracks/roads, facilitating trade and communication. [1] Marking: 1 mark per factor + evidence. Max 3 marks.

(b) Possible function: Fishing village / Port / Trading settlement / Agricultural collection centre.
Justification: Proximity to river/sea (mangroves/fishing), road/bridge access for trade, surrounded by cultivated land.
Marking: 1 mark for valid function linked to evidence.

Section B: Graph & Data Interpretation (18 marks)

5. Climate Graph for Station P (5°N, 100°E) (a) Annual Temperature Range: $28.5^\circ\text{C} - 26.5^\circ\text{C} = \mathbf{2.0^\circ\text{C}}$
Marking: 1 mark. Correct subtraction, units.

(b) Total Annual Rainfall: $150+100+180+220+200+150+150+180+200+250+300+280 = \mathbf{2360 \text{ mm}}$
Marking: 1 mark. Correct total, units.

(c) Complete Climate Graph (Figure 1):

• Rainfall Bars: Vertical bars for all 12 months reaching correct values on Left Axis (0-350mm). Jan(150), Feb(100), Mar(180), Apr(220), May(200), Jun(150), Jul(150), Aug(180), Sep(200), Oct(250), Nov(300), Dec(280).
• Temperature Line: Points plotted at mid-month for Jul(27.5), Aug(27.5), Sep(27.0), Oct(27.0), Nov(26.5), Dec(26.5) on Right Axis (25-30°C), joined smoothly to existing Jun point. Marking: 1 mark for accurate rainfall bars (all 12, correct height, touching). 1 mark for accurate temperature plots (Jul-Dec). 1 mark for correct line joining + labels/neatness.

(d) Climate Type: Tropical Rainforest Climate (Af) / Equatorial Climate
Marking: 1 mark.

(e) Two characteristics explained:

1. High, uniform temperatures year-round: Mean monthly temps range only 26.5–28.5°C (Range 2°C). Caused by location near equator (5°N), receiving high, consistent insolation throughout the year with no distinct winter. [2]
2. High, year-round rainfall (no dry month): All months > 100mm (min 100mm Feb). Total > 2000mm. Caused by constant high temperatures $\rightarrow$ high evaporation $\rightarrow$ convectional rainfall / ITCZ influence year-round. [2] Marking: 1 mark for identifying characteristic (stat), 1 mark for explanation/link to latitude/process. $\times 2$. Max 4 marks.

6. Employment Structure (Figure 2) (a) Comparison (with stats):

• Primary Sector: Country A (45%) is much higher than Country B (5%). Diff = 40%. [1]
• Secondary Sector: Country B (25%) is slightly higher than Country A (20%). [1]
• Tertiary Sector: Country B (60%) is double / much higher than Country A (30%). [1]
• Quaternary Sector: Country B (10%) is higher than Country A (5%). [1 - any 3 distinct comparisons with stats for 3 marks] Marking: 1 mark per valid comparative statement using % data. Max 3 marks.

(b) Level of Development:

• Country A: Low / Less Developed (LDC / Developing). Reason: Dominant Primary sector (45%) indicates reliance on agriculture/raw material extraction; low Tertiary (30%) and Quaternary (5%) indicate limited services/knowledge economy. [2]
• Country B: High / More Developed (MDC / Developed). Reason: Dominant Tertiary (60%) and significant Quaternary (10%) sectors indicate advanced service/knowledge economy; very low Primary (5%) shows mechanised agriculture/minimal resource extraction. [2] Marking: 1 mark for correct classification, 1 mark for data-linked reasoning per country. Max 4 marks.

(c) Two changes in Country A's structure due to urbanisation (next 20 yrs):

1. Decrease in Primary %: Mechanisation of agriculture, rural-urban migration reduces farm labour. [1]
2. Increase in Secondary % (initially) then Tertiary %: Industrialisation (manufacturing growth) followed by shift to services (retail, finance, admin) as economy matures. [1] Marking: 1 mark per valid structural change described. Max 2 marks.

7. Infiltration Investigation (a) Line Graph (Figure 1) - Infiltration Rate (mm/min) for Grassy Field: Calculations (Rate = $\Delta$Cumulative / 5 min):

• 0-5 min: $15/5 = \mathbf{3.0}$ mm/min (Plot at 2.5 min)
• 5-10 min: $13/5 = \mathbf{2.6}$ mm/min (Plot at 7.5 min)
• 10-15 min: $10/5 = \mathbf{2.0}$ mm/min (Plot at 12.5 min)
• 15-20 min: $7/5 = \mathbf{1.4}$ mm/min (Plot at 17.5 min)
• 20-25 min: $5/5 = \mathbf{1.0}$ mm/min (Plot at 22.5 min)
• 25-30 min: $3/5 = \mathbf{0.6}$ mm/min (Plot at 27.5 min) Marking: 1 mark for correct rate calculations (implied by plots). 1 mark for accurate plotting at mid-intervals. 1 mark for smooth curve/line joining points + labels.

(b) Trend: Steady / Rapid decrease in infiltration rate from 3.0 mm/min to 0.6 mm/min over 30 minutes.
Marking: 1 mark.

(c) Why Concrete Car Park = 0 mm/min:

1. Impermeable surface: Concrete is a solid, non-porous material with no pore spaces for water to enter. [1]
2. No soil/vegetation cover: Absence of soil matrix, macropores (roots/worm holes), or vegetation to facilitate infiltration; water becomes surface runoff immediately. [1] Marking: 1 mark per reason. Max 2 marks.

(d) Improve Reliability: Repeat the experiment (replicates) at multiple locations within each land-use type and calculate an average. / Use a larger infiltrometer ring. / Control initial soil moisture content (antecedent conditions).
Marking: 1 mark for valid suggestion.

Section C: Geographical Investigation & Data Response (12 marks)

8. Urban Environmental Quality Investigation (a) Two Primary Data Collection Methods:

1. Environmental Quality Survey (EQS) / Bi-polar Index: Scoring criteria (e.g., building condition, noise, air quality, greenery, litter) on a scale (e.g., -5 to +5 or 1-10) at each site. [1]
2. Field Sketches / Annotated Photographs: Visual recording of environmental features at each site for qualitative comparison. [1] Other valid: Traffic/Pedestrian Counts, Noise Meter readings, Air Quality Monitor readings, Questionnaire/Interviews with residents.
   Marking: 1 mark each. Max 2 marks.

(b) Sampling Strategy:

• Strategy: Systematic Sampling along a transect line radiating from CBD. [1]
• Description: Select sites at regular intervals (e.g., every 1 km or every 500m) along a straight line (transect) from CBD centre outwards. [1]
• Justification: Ensures even spatial coverage across the urban gradient (CBD $\rightarrow$ Fringe); removes researcher bias in site selection; allows easy replication; captures transition zones effectively. [1] Marking: 1 mark ID, 1 mark description, 1 mark justification. Max 3 marks.

(c) (i) Relationship: Positive correlation / As distance from CBD increases, Environmental Quality Score increases.
Marking: 1 mark.

(ii) Explanation using data:

• Building Height decreases (Site 1: 45 storeys $\rightarrow$ Site 5: 2 storeys). Lower density reduces heat island effect, overcrowding, visual pollution, allowing more open space/greenery. [1]
• Traffic Count decreases (Site 1: 320 $\rightarrow$ Site 5: 15). Less traffic $\rightarrow$ lower noise pollution, air pollution (NOx, PM2.5), congestion, and accident risk. [1]
• Combined effect: Lower density (building height) and lower pressure (traffic) create a cleaner, quieter, greener, more spacious environment $\rightarrow$ Higher EQ Score. [1] Marking: 1 mark for linking Building Height, 1 mark for linking Traffic Count, 1 mark for synthesis/explanation of mechanism. Max 3 marks.

(d) Limitation of Single Transect:

• Lack of representativeness / Spatial bias: A single line may pass through anomalous zones (e.g., a park, industrial estate, wealthy/poor sector) not typical of the whole city at that distance. It ignores sectoral variations (e.g., Hoyt's model - sectors of similar land use radiating out). Results cannot be generalised to the whole urban area.
  Marking: 1 mark for valid limitation (spatial bias/anomaly/sectoral variation).

9. Scatter Graph: GDP per capita vs Crude Birth Rate (Figure 3) (a) General Relationship: Strong negative (inverse) non-linear correlation. As GDP per capita increases, Crude Birth Rate decreases. The rate of decrease is rapid at low GDP levels but flattens out (asymptotic) at high GDP levels.
Marking: 1 mark for "negative correlation/inverse", 1 mark for "non-linear/curvilinear/flattens at high GDP".

(b) Reasons for Country Z Anomaly (Low CBR for ~$5,000 GDP):

1. Government Policy: Strong anti-natalist policies (e.g., China's former One-Child Policy, Singapore's "Stop at Two") effectively suppressing birth rates despite lower income. [1]
2. High Female Education / Empowerment: High literacy/female labour force participation / access to contraception leading to delayed marriage/smaller families despite moderate income. [1]
3. High Cost of Living / Urbanisation: High housing/education costs in a specific urban context (e.g., post-Soviet states, some Latin American countries) discouraging large families. [1]
4. Demographic Momentum / Age Structure: Ageing population / out-migration of youth skewing CBR low. [1] Marking: 1 mark per valid, distinct reason. Max 3 marks.

(c) Spearman's Rank ($R_s = -0.88$): (i) Negative sign: Indicates a negative / inverse monotonic relationship (as one variable increases, the other tends to decrease). [1] (ii) Magnitude 0.88: Indicates a very strong / strong strength of correlation (close to -1.0). [1] (iii) Conclusion:

• Calculated $|R_s| = 0.88$.
• Critical value (p=0.05, n=20) = 0.438.
• Since $0.88 > 0.438$, the result is statistically significant at the 95% confidence level (p < 0.05).
• Conclusion: Reject the Null Hypothesis. There is a statistically significant negative correlation between GDP per capita and Crude Birth Rate for these 20 countries. The probability of this occurring by chance is less than 5%. [2] Marking: 1 mark for comparing calculated vs critical value correctly. 1 mark for correct conclusion phrasing (reject null / significant correlation).

TOTAL MARKS: 50 End of Marking Scheme