Data Interpretation and Reporting Claire Mason. Merging of sieve and laser data 1. Sieve data...

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Data Interpretation and Reporting Claire Mason

Transcript of Data Interpretation and Reporting Claire Mason. Merging of sieve and laser data 1. Sieve data...

Page 1: Data Interpretation and Reporting Claire Mason. Merging of sieve and laser data 1. Sieve data directly entered into an Excel spreadsheet = weights in.

Data Interpretation and Reporting 

Claire Mason

Page 2: Data Interpretation and Reporting Claire Mason. Merging of sieve and laser data 1. Sieve data directly entered into an Excel spreadsheet = weights in.

Merging of sieve and laser data

1. Sieve data directly entered into an Excel spreadsheet = weights in g.

2. Laser data from the Malvern exported into an Excel spreadsheet in same file = percentage volume.

3. Any sample falling through sieve pan added to total amount of fine sediment (which has been laser sized).

4. The laser data is converted into weight using the total amount of fine sediment (step 3).

5. The sieve weights and laser ‘weights’ are then added together for each fraction

6. The percentage weight in each fraction is then calculated.

Page 3: Data Interpretation and Reporting Claire Mason. Merging of sieve and laser data 1. Sieve data directly entered into an Excel spreadsheet = weights in.

Advantages

• complete PS distribution achieved.

Page 4: Data Interpretation and Reporting Claire Mason. Merging of sieve and laser data 1. Sieve data directly entered into an Excel spreadsheet = weights in.

Disadvantages• merging two inherently different methods

• assumes sediment in sieve pan has same distribution as the fine sediment that has been laser-sized.