# Geography Unit 2 - Investigative skills, MALHAM

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- Geography Unit 2 Investigations - MALHAM
- AIM
- 2.To investigate the relationship between Bedload size and discharge downstream at Cowside Beck, near Malham in the Yorkshire Dales

- Background
- Theories
- BRADSHAW MODEL:
- The Bradshaw model agrees velocity will increase downstream
- The Bradshaw model believes discharge will increase downstream
- The Bradhsaw model believes bedload size will decrease downstream

- BRADSHAW MODEL:
- what is the location of your study?
- North England, North Yorkshire, Yorkshire dales National Park

- what are the characteristics of your location
- catchment area = 8km2, river flows North-East for 5km, has 3 tributaries, V-shaped upper course and U-shaped glaciated lower course, geology is Limestone and Boulder clay from glacial till (lower course)

- why did you choose that location?
- 1. Short enough to conduct field work on in a short amount of time
- 2.Risk assessment said the areas were okay
- 3.Easily accessible to collect representative data

- Theories
- DATA COLLECTION (qualitative and quantitative) and SAMPLNG
- Describe one method of data collection?
- Depth
- 1.We measured the width of the river with a measuring tape from bank to bank then divided it by 10
- 2.At each 10th of the width we put our metre stick in and measure the depth of the river and at each of the banks
- Evaluate and justify one method of data collection?
- Systematic strategy (representative and efficient), cheap and easy to use
- Sometime metre ruler wasn't straight, fragile, weather affected the choppiness of the water

- Width
- We measured the width of the river with a measuring tape from bank to bank
- Evaluate and justify one method of data collection?
- Relatively accurate, easy to use, water proof, cheap, easily portable
- Easily caught on water (inaccurate), easily slacked, sometimes broken tape so didnt start on O

- Velocity (m/s)
- 1.First we measured the width of the river and then divided it into 4
- 2.So at the lower quartile, median and upper quartile we place our hydroprop a third of the depth into the river
- 3.We then timed how long it took the impeller to spin the length of the thread with a stopwatch
- Evaluate and justify one method of data collection?
- Showed sloping of the river, useful for showing deeper/ erosive parts and shallower/ depositional parts
- Easily breakable, took a long time to set up and to record, human bias from the stopwatch, couldn't see the impeller in the murky water

- Bedload Size
- 1.We measured the width of the river with a measuring tape from bank to bank then divided it by 4
- 2.At each quarter of the width we put our metre stick in and measure the depth of the river and at each of the banks
- 3.Before we removed our metre stick we removed a rock from the bed of the river
- 4.We then used Calipers to measure the longest axis of the bedload and recorded it getting 5 different records at the 3 different sites
- Evaluate and justify one method of data collection?
- shows maximum size of bedload (useful), shows erosion rates, relatively accurate
- sometimes was no rock there, make not be representative of the whole bed, only 1 axis doesnt represent the whole rock

- Secondary data
- OS Maps
- Find the areas we would visit and assess the accessability

- Information booklet
- Background information on the area (rock type, river, history)

- OS Maps

- Depth
- Describe the difference between qualitatve and quantitative data?
- Quantitative
- Numerical data, facts and figures
- E.g. width, depth, velocity
- Objective, conclusive, scientific acceptance

- Qualitative
- Words and opinions
- E.g. annotated photos and sketch maps, description on the location,
- rich in detail, says why

- Quantitative
- Describe your sampling method?
- Systematic (depth)
- 11 samples from each site
- 2 at either bank and 9 inbetween

- evenly based
- Calculated by dividing the width by 10

- 11 samples from each site
- Evaluate/ Justify your sampling method?
- Advantages: representative and efficient, took away human bias, not all clustered
- Disadvantages: not fully representative of the whole river, more biased than random sampling, little flexibility
- DATA COLLECTION (qualitative and quantitative) and SAMPLNG
- Describe one method of data collection?
- Depth
- 1.We measured the width of the river with a measuring tape from bank to bank then divided it by 10
- 2.At each 10th of the width we put our metre stick in and measure the depth of the river and at each of the banks
- Evaluate and justify one method of data collection?
- Systematic strategy (representative and efficient), cheap and easy to use
- Sometime metre ruler wasn't straight, fragile, weather affected the choppiness of the water

- Width
- We measured the width of the river with a measuring tape from bank to bank
- Evaluate and justify one method of data collection?
- Relatively accurate, easy to use, water proof, cheap, easily portable
- Easily caught on water (inaccurate), easily slacked, sometimes broken tape so didnt start on O

- Velocity (m/s)
- 1.First we measured the width of the river and then divided it into 4
- 2.So at the lower quartile, median and upper quartile we place our hydroprop a third of the depth into the river
- 3.We then timed how long it took the impeller to spin the length of the thread with a stopwatch
- Evaluate and justify one method of data collection?
- Showed sloping of the river, useful for showing deeper/ erosive parts and shallower/ depositional parts
- Easily breakable, took a long time to set up and to record, human bias from the stopwatch, couldn't see the impeller in the murky water

- Bedload Size
- 1.We measured the width of the river with a measuring tape from bank to bank then divided it by 4
- 2.At each quarter of the width we put our metre stick in and measure the depth of the river and at each of the banks
- 3.Before we removed our metre stick we removed a rock from the bed of the river
- 4.We then used Calipers to measure the longest axis of the bedload and recorded it getting 5 different records at the 3 different sites
- Evaluate and justify one method of data collection?
- shows maximum size of bedload (useful), shows erosion rates, relatively accurate
- sometimes was no rock there, make not be representative of the whole bed, only 1 axis doesnt represent the whole rock

- Secondary data
- OS Maps
- Find the areas we would visit and assess the accessability

- Information booklet
- Background information on the area (rock type, river, history)

- OS Maps

- Depth
- Describe the difference between qualitatve and quantitative data?
- Quantitative
- Numerical data, facts and figures
- E.g. width, depth, velocity
- Objective, conclusive, scientific acceptance

- Qualitative
- Words and opinions
- E.g. annotated photos and sketch maps, description on the location,
- rich in detail, says why

- Quantitative
- Describe your sampling method?
- Systematic (depth)
- 11 samples from each site
- 2 at either bank and 9 inbetween

- evenly based
- Calculated by dividing the width by 10

- 11 samples from each site
- Evaluate/ Justify your sampling method?
- Advantages: representative and efficient, took away human bias, not all clustered
- Disadvantages: not fully representative of the whole river, more biased than random sampling, little flexibility

- Systematic (depth)

- Describe one method of data collection?

- Systematic (depth)

- Describe one method of data collection?
- DATA PRESENTATION
- Describe your data presentation technique?
- Scatter Graph of Bedload size and Discharge
- Bedload size = dependent variable = on Y axis
- Had to go to 14cm

- Discharge = independent variable = on X axis
- had to go to 1.5 cumecs

- I plotted the 15 sets of data with a cross and then plotted a line of best fit with my ruler making sure it went through as many crosses as possible and if it couldn't i made sure there were even numbers of crosses below and above

- Bedload size = dependent variable = on Y axis

- Scatter Graph of Bedload size and Discharge
- Evaluate/ justify your data presentation technique?
- Advantages: shows the relationship between 2 variables, can plot all samples and so retains sample size, uses exact data values, shows clusters and anomalies
- Disadvantages: may no show a correlation at all, continuous data is needed, may be unclear if there are lots of data, flat lines of best fit give inconclusive results

- RESULTS
- Bedload average: 9.4 to 8.5 to 6.9cm
- Discharge (CUMECS): 0.07 to 0.39 to 0.71
- Velocity averages (m/s): 0.16 to 0.35 to 0.35

- Describe your data presentation technique?
- DATA ANALYSIS
- Describe your data analysis techniques?
- 1. State a null hypothesis
- 2. Establish variables (discharge and bedload size)
- 3. Rank the values 1 to 15
- 4. minus the first set of variables from the second (ranks)
- 5. square all the answers
- 6. Add all the squared numbers together
- 7. Put the figure into the equation

- What were the conclusions of your data analysis?
- The calculated rs is -0.499. as this is greater than the critical value of 0.521 at the p=0.05 significance level i must reject my null hypothesis. a correlation of this strength could occur by chance more than 5% of the time and therefore it can be said there is no significant correlation between increasing discharge and decreasing bedload size

- Evaluate/ justify your method of data analysis?
- Advantages: 95% accurate, allows us to see a correlation, determines the strength and direction of the relationship
- Disadvantages: Complex, easy to make mistakes on, doesnt explain why, correlation doesnt mean causation

- Describe your data analysis techniques?
- CONCLUSIONS
- 1. In conclusion our hypothesis “velocity
will increase with distance downstream” appears to be correct. Average velocity
increased from 0.16m/s at site one to 0.35m/s at site 2 and 0.35m/s at site 3.
- This was because friction decreased due
to erosion (like abrasion) so the channel was more efficient and water could
move faster (increased velocity). This was also due to the gravitational energy
converting into kinetic energy so the river was travelling at a higher speed.
- However the only problem was that site 2's
data was higher than expected according to the Bradshaw Model which was was
because the channel had been artificially straightened and so sinuosity
decreased and efficiency increased.
- Also the were also tributaries just
before site 2 which would have increased the discharge of the river at that point
- So this proves the Bradshaw model as well as our hypothesis

- Also the were also tributaries just
before site 2 which would have increased the discharge of the river at that point

- However the only problem was that site 2's
data was higher than expected according to the Bradshaw Model which was was
because the channel had been artificially straightened and so sinuosity
decreased and efficiency increased.

- This was because friction decreased due
to erosion (like abrasion) so the channel was more efficient and water could
move faster (increased velocity). This was also due to the gravitational energy
converting into kinetic energy so the river was travelling at a higher speed.
- 2. In conclusion our hypothesis "as discharge increases, bedload size decreases" appears to have no correlation
- We calculated that rs is 0.499. as this is greater than the critical value of 0.521 at p=0.05 significance level, i must reject my null hypothesis
- A correlation of this strength could occur by chance more than 5 % of the time and therefore it can be said that there is no significant correlation between increasing discharge and decreasing bedload size.
- This may because of the type of rocks (limestone and millstone grit) and other factors that affected it instead like velocity
- In my next investigation i could investigate velocity and bedload size instead

- This may because of the type of rocks (limestone and millstone grit) and other factors that affected it instead like velocity

- A correlation of this strength could occur by chance more than 5 % of the time and therefore it can be said that there is no significant correlation between increasing discharge and decreasing bedload size.

- We calculated that rs is 0.499. as this is greater than the critical value of 0.521 at p=0.05 significance level, i must reject my null hypothesis

- 1. In conclusion our hypothesis “velocity
will increase with distance downstream” appears to be correct. Average velocity
increased from 0.16m/s at site one to 0.35m/s at site 2 and 0.35m/s at site 3.
- EVALUATION
- Strengths
- Collected lots of data
- investigated relationships and tested hypothesises

- Weaknesses
- Primary data we only visited 5 site, unrepresentative of a 5km long river
- visit more sites?

- Weather restricted our access to sites 2 and 3
- could have waited for the snow to clear?

- It was all done on one day so its unrepresentative for the rest of the year
- come back on other days or different times of the year?

- Only one river so may not be generalisable to all rivers
- Do more rivers?

- Primary data we only visited 5 site, unrepresentative of a 5km long river

- Strengths
- RISK ASSESSMENT
- Slips, trips and falls in river, walking in the snow
- correct shoes
- working as a team
- behaved sensibly

- Hypothermia
- 6 layers of clothing
- Brang a hot drink
- Ate high density energy food

- Weils disease
- No drinking the water
- Covered up any cuts
- Used gloves in the river

- Slips, trips and falls in river, walking in the snow

- AIM
- Evaluate/ justify your data presentation technique?
- Advantages: shows the relationship between 2 variables, can plot all samples and so retains sample size, uses exact data values, shows clusters and anomalies
- Disadvantages: may no show a correlation at all, continuous data is needed, may be unclear if there are lots of data, flat lines of best fit give inconclusive results

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