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CTAP Example 5 - Floods DRR

#### Stock Budgeting 1 Output Calculator

Introduction
This tool tracks resource stock indicators for output uris. Up to 15 new indicators can be added for each output.

Calculation View Description
v216a

Version: 1.9.0

#### Relations

Use In Childs?
Overwrite Childs?

#### Step 3 of 3. Save

Method 1. Do you wish to save step 2's calculations? These calculations are viewed by opening this particular calculator addin.

#### Step 1

• Step 1. Indicators: Enter up to 10 indicators.
• Step 1. Indicator Name and Description: Name and description for each indicator.
• Step 1. Indicator Date: Make sure that the benchmark, targets, actual, indicators have distinct dates.
• Step 1. Distribution Type: The numeric distribution of QT. Refer to the Stock Calculation 1 reference.
• Step 1. Math Expression:A mathematical expression containing one or more of the Q1 to Q5 variables and/or sibling indicator Q1 to QTM variables. Use strings that identify both the indicator (I1, I2, … In) and the Qx property (Q … QTM), with a period separator between them. Examples include:((I1.Q1 + I1.Q2) * I1.Q3) + I1.Q4)) - (2 * I1.Q5)
• Step 1. Math Operator Type: Mathematical operation to use with QT. MathTypes include: equalto, lessthan, greaterthan, lessthanorequalto, and greaterthanorequalto. Refer to the Stock Calculation 1 reference for the algorithms.
• Step 1. Math Type and Math Sub Type: Mathematical algorithm and subalgorithm to use with Distribution Type, QT, QTD1, and QTD2 to solve for QTM, QTL, and QTU. Refer to the Stock Calculation 1 reference for the algorithms.
• Step 1. QT Amount and Unit: The Unit must be manually entered. The Amount will be the result of the mathematical calculation.
• Step 1. QTD1 Amount and Unit: First distribution, or shape, parameter for QT.
• Step 1. QTD2 Amount and Unit: Second distribution, or scale, for QT.
• Step 1. BaseIO: Base input or output property to update with this indicator's QTM property.
• Step 1. QTM Amount and Unit: Most Likely Estimate for QT. The Unit must be manually entered. The Amount will be the result of the mathematical algorithm.
• Step 1. QTL Amount and Unit: Low Estimate or QT. The Unit must be manually entered. The Amount will be the result of the mathematical algorithm.
• Step 1. QTU Amount and Unit: High Estimate for QT. The Unit must be manually entered. The Amount will be the result of the mathematical algorithm.
• Step 1. Math Result: TEXT string holding results of calculation.

#### Step 2

• Step 2. Use Same Calculator Pack In Descendants?: True to insert or update this same calculator in children.
• Step 2. Overwrite Descendants?: True to insert or update all of the attributes of this same calculator in all children. False only updates children attributes that are controlled by the developer of this calculator (i.e. version, stylehsheet name, relatedcalculatorstype ...)
• Step 2. What If Tag Name: Instructional videos explaining the use of what-if scenario calculations should be viewed before changing or using this parameter.
• Step 2. Related Calculators Type: When the Use Same Calculator Pack in Descendant is true, uses this value to determine which descendant calculator to update. Inserts a new descendant when no descendant has this same name. Updates the descendant that has this same name.
• Step 2. Indicators: Enter up to 5 indicators.
• Step 2. Target Type: Used with Progress analyzers to identify benchmark and actual indicators.
• Step 2. Altern Type: Used with Change by Alternative analyzers to identify alternatives to compare.
• Step 2. Score Math Expression: A mathematical expression containing one or more of the children indicator Q1 to QTM variables. Use strings that identify both the indicator (I1, I2, … In) and the Qx property (Q … QTM), with a period separator between them. Examples include:((I1.QTM + I2.QTM) * I3.Q3) + I4.QTM)) - (2 * I5.QTM)
• Step 2. Score Amount and Unit: The Unit must be manually entered. The Amount will be the result of the Math Expression calculation.
• Step 2. ScoreD1 Amount and Unit: First distribution variable for Score.
• Step 2. ScoreD2 Amount and Unit: Second distribution for Score.
• Step 2. Distribution Type: The numeric distribution of Score. Refer to the Stock Calculation 1 reference.
• Step 2. Score Math Type and Math Sub Type: Mathematical algorithm and subalgorithm to use with Distribution Type, Score, ScoreD1, and ScoreD2 to solve for ScoreM, ScoreL, and ScoreU. Refer to the Stock Calculation 1 reference for the algorithms.
• Step 2. Score Most Likely, Score Low, Score High, Amounts and Units: Results of Distribution Type and Math Type calculations.
• Step 2. Iterations: Number of iterations to use when drawing random number samples for some algorithms.
• Step 2. Confidence Interval: Level of confidence interal to use when reporting all Score and Indicator high and low amounts. Should be an integer such as 95, 90, or 40.
• Step 2. Random Seed: Any positive integer, except 0, will result in the same set of random variables being used each time a calculation is run.
• Step 2. Score BaseIO: Base input or output property to update with the Score Most Likely property.

#### References

• Refer to the Stock Calculation 1 reference.

Current view of document
CTAP Example 5 - Floods DRR
Output Group
CTAP Output Examples
Output
CTAP Example 5 - Floods DRR
Score Score Unit Score D1 Amount Score D1 Unit Score D2 Amount Score D2 Unit Iterations Confid Int Random Seed Base IO
Score Most Amount Score Most Unit Score Low Amount Score Low Unit Score High Amount Score High Unit Distribution Type Math Type Math Sub Type Observations
9.5829 highest bcr 7.1561 mean 3.0000 sd 10000 90 8 none
7.1712 highest bcr 7.1223 lower 90 % ci 7.2201 upper 90 % ci normal algorithm1 subalgorithm1 1
I6.QTM
sampled descriptive statistics N,Total,Mean,Median,StdDev,Var,Min,Max 10000, 71712.0926, 7.1712, 7.1586, 2.9611, 8.7681, -4.0867, 18.2660, sampled cumulative density function 0.00,0.10,0.20,0.30,0.40,0.50,0.60,0.70,0.80,0.90,1.00 -4.0867,3.3982,4.6907,5.6241,6.4233,7.1588,7.9205,8.7178,9.6407,10.9387,18.2660
Name (N) Label Date Rel Label Math Type Dist Type Base IO Math Operator Math Sub Type
Q1 Amount Q1 Unit Q2 Amount Q2 Unit Q3 Amount Q3 Unit Q4 Amount Q4 Unit Q5 Amount Q5 Unit
QT Amount QT Unit QT D1 Amount QT D2 Amount QT Most Amount QT Most Unit QT Low Amount QT Low Unit QT High Amount QT High Unit
Hazard Distribution 1A 01/01/2005 none algorithm1 none none equalto subalgorithm9
2.7514 100year 1.6509 50year 1.1006 25year 0.5503 10year 0.2752 5year
1.0542 mean flood depth 1.0542 0.1054 1.0547 mean flood depth 1.0530 lower 90 % ci 1.0564 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I1.Q1.distribtype + I1.Q2.100year + I1.Q3. 50year + I1.Q4.25year + I1.Q5.10year + I1.Q6.5year
Exposure Distribution 2A 01/01/2005 none algorithm1 none none equalto subalgorithm9
680,820.2547 location 1 total value 2,122,978.8336 location 2 total value 0.0000 none 0.0000 none 0.0000 none
2,803,799.0884 1, 2 totals 0.0000 0.0000 2,803,799.0884 drr all locations 2,799,472.3044 lower 90 % ci 2,808,125.8724 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I2.Q1.distribtype + I2.Q2.QT + I2.Q3.QTUnit + I2.Q4.QTD1+ I2.Q5.QTD1Unit + I2.Q6.QTD2 + I2.Q7.QTD2Unit + I2.Q8.normalization + I2.Q9.weight + I2.Q10.quantity
Vulnerability Distribution 3A 01/01/2005 none algorithm1 none none equalto subalgorithm9
4.0020 5year 211.6024 10year 438.5988 25year 672.2706 50year 997.0198 100year
0.0000 none 0.0000 0.0000 62.9202 total percent damage 62.8178 lower 90 % ci 63.0226 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I3.Q1.distribtype + I3.Q2.5year + I3.Q3.10year + I3.Q4.25year + I3.Q5.50year + I3.Q6.100year
Loss EP Distribution 4A 01/01/2005 none algorithm1 none none none subalgorithm9
7,827.5399 5year 494,719.0772 10year 1,010,490.4178 25year 1,538,489.3551 50year 2,264,720.5476 100year
0.0000 none 0.0000 0.0000 144,874.0250 total avg ann damages 144,421.6280 lower 90 % ci 145,324.2592 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I4.Q1.distribtype + I4.Q2.5year + I4.Q3.10year + I4.Q4.25year + I4.Q5.50year + I4.Q6.100year
Project Costs 5A 01/01/2005 none algorithm1 none none equalto subalgorithm9
0.0000 none 0.0000 none 0.0000 none 0.0000 none 0.0000 none
0.0000 mean avg annual costs 0.0000 0.0000 37,135.6783 mean avg annual costs 37,075.2292 lower 90 % ci 37,196.1274 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I5.Q1.installcost + I5.Q2.installdistrib + I5.Q3.omcost+ I5.Q4.omdistrib+I5.Q5.isprojectcost
Benefit Cost Analysis 6A 01/01/2005 none algorithm1 none none equalto subalgorithm9
2,822,866.0243 base damage 194.4730 base cost 353,033.1945 AC1A_B damage 257,928.7206 AC1A_B cost 0.0000 none
2,212,098.5822 net benefits 0.0000 0.0000 9.5829 2_QTM_0.05_75, bcr 9.5699 lower 90 % ci 9.5975 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I6.Q1.distribtype + I6.Q2.100year + I6.Q3.50year + I6.Q4.25year + I6.Q5.10year + I6.Q6.5year
Cost Effectiveness Analysis 7A 01/01/2005 none algorithm1 none none equalto subalgorithm9
144,874.0250 base damage 180.3240 base cost 18,118.2314 AC1A_B damage 226,856.6584 AC1A_B cost 0.0000 none
1.7883 net benefits 0.0000 0.0000 1.7883 2_QTM_0.12_50, cer 1.7907 lower 90 % ci 1.7856 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I7.Q1.distribtype + I7.Q2.100year + I7.Q3.50year + I7.Q4.25year + I7.Q5.10year + I7.Q6.5year
Output Series: CTAP Example 5 - Floods DRR
Score Score Unit Score D1 Amount Score D1 Unit Score D2 Amount Score D2 Unit Iterations Confid Int Random Seed Base IO
Score Most Amount Score Most Unit Score Low Amount Score Low Unit Score High Amount Score High Unit Distribution Type Math Type Math Sub Type Observations
9.5829 highest bcr 7.1561 mean 3.0000 sd 10000 90 8 none
7.1712 highest bcr 7.1223 lower 90 % ci 7.2201 upper 90 % ci normal algorithm1 subalgorithm1 1
I6.QTM
sampled descriptive statistics N,Total,Mean,Median,StdDev,Var,Min,Max 10000, 71712.0926, 7.1712, 7.1586, 2.9611, 8.7681, -4.0867, 18.2660, sampled cumulative density function 0.00,0.10,0.20,0.30,0.40,0.50,0.60,0.70,0.80,0.90,1.00 -4.0867,3.3982,4.6907,5.6241,6.4233,7.1588,7.9205,8.7178,9.6407,10.9387,18.2660
Name (N) Label Date Rel Label Math Type Dist Type Base IO Math Operator Math Sub Type
Q1 Amount Q1 Unit Q2 Amount Q2 Unit Q3 Amount Q3 Unit Q4 Amount Q4 Unit Q5 Amount Q5 Unit
QT Amount QT Unit QT D1 Amount QT D2 Amount QT Most Amount QT Most Unit QT Low Amount QT Low Unit QT High Amount QT High Unit
Hazard Distribution 1A 01/01/2005 none algorithm1 none none equalto subalgorithm9
2.7514 100year 1.6509 50year 1.1006 25year 0.5503 10year 0.2752 5year
1.0542 mean flood depth 1.0542 0.1054 1.0547 mean flood depth 1.0530 lower 90 % ci 1.0564 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I1.Q1.distribtype + I1.Q2.100year + I1.Q3. 50year + I1.Q4.25year + I1.Q5.10year + I1.Q6.5year
Exposure Distribution 2A 01/01/2005 none algorithm1 none none equalto subalgorithm9
680,820.2547 location 1 total value 2,122,978.8336 location 2 total value 0.0000 none 0.0000 none 0.0000 none
2,803,799.0884 1, 2 totals 0.0000 0.0000 2,803,799.0884 drr all locations 2,799,472.3044 lower 90 % ci 2,808,125.8724 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I2.Q1.distribtype + I2.Q2.QT + I2.Q3.QTUnit + I2.Q4.QTD1+ I2.Q5.QTD1Unit + I2.Q6.QTD2 + I2.Q7.QTD2Unit + I2.Q8.normalization + I2.Q9.weight + I2.Q10.quantity
Vulnerability Distribution 3A 01/01/2005 none algorithm1 none none equalto subalgorithm9
4.0020 5year 211.6024 10year 438.5988 25year 672.2706 50year 997.0198 100year
0.0000 none 0.0000 0.0000 62.9202 total percent damage 62.8178 lower 90 % ci 63.0226 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I3.Q1.distribtype + I3.Q2.5year + I3.Q3.10year + I3.Q4.25year + I3.Q5.50year + I3.Q6.100year
Loss EP Distribution 4A 01/01/2005 none algorithm1 none none none subalgorithm9
7,827.5399 5year 494,719.0772 10year 1,010,490.4178 25year 1,538,489.3551 50year 2,264,720.5476 100year
0.0000 none 0.0000 0.0000 144,874.0250 total avg ann damages 144,421.6280 lower 90 % ci 145,324.2592 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I4.Q1.distribtype + I4.Q2.5year + I4.Q3.10year + I4.Q4.25year + I4.Q5.50year + I4.Q6.100year
Project Costs 5A 01/01/2005 none algorithm1 none none equalto subalgorithm9
0.0000 none 0.0000 none 0.0000 none 0.0000 none 0.0000 none
0.0000 mean avg annual costs 0.0000 0.0000 37,135.6783 mean avg annual costs 37,075.2292 lower 90 % ci 37,196.1274 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I5.Q1.installcost + I5.Q2.installdistrib + I5.Q3.omcost+ I5.Q4.omdistrib+I5.Q5.isprojectcost
Benefit Cost Analysis 6A 01/01/2005 none algorithm1 none none equalto subalgorithm9
2,822,866.0243 base damage 194.4730 base cost 353,033.1945 AC1A_B damage 257,928.7206 AC1A_B cost 0.0000 none
2,212,098.5822 net benefits 0.0000 0.0000 9.5829 2_QTM_0.05_75, bcr 9.5699 lower 90 % ci 9.5975 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I6.Q1.distribtype + I6.Q2.100year + I6.Q3.50year + I6.Q4.25year + I6.Q5.10year + I6.Q6.5year
Cost Effectiveness Analysis 7A 01/01/2005 none algorithm1 none none equalto subalgorithm9
144,874.0250 base damage 180.3240 base cost 18,118.2314 AC1A_B damage 226,856.6584 AC1A_B cost 0.0000 none
1.7883 net benefits 0.0000 0.0000 1.7883 2_QTM_0.12_50, cer 1.7907 lower 90 % ci 1.7856 upper 90 % ci
This Indicator is used in a CTAP tutorial demonstrating disaster risk reduction for floods in Semarang, Indonesia.
I7.Q1.distribtype + I7.Q2.100year + I7.Q3.50year + I7.Q4.25year + I7.Q5.10year + I7.Q6.5year
Dataset: CTAP Example 5 - Floods DRR IRI This output is used to support a CTAP tutorial for floods in Semarang, Indonesia.