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US Army Corps of Engineers BUILDING STRONG ® STEP 2: INVENTORY AND FORECAST Planning Principles & Procedures – FY 11.

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Presentation on theme: "US Army Corps of Engineers BUILDING STRONG ® STEP 2: INVENTORY AND FORECAST Planning Principles & Procedures – FY 11."— Presentation transcript:

1 US Army Corps of Engineers BUILDING STRONG ® STEP 2: INVENTORY AND FORECAST Planning Principles & Procedures – FY 11

2 BUILDING STRONG ® Objectives  Define inventory and forecast  Describe data collection process and requirements  Discuss forecasting techniques  Identify most important output of Step 2

3 BUILDING STRONG ® Why Inventory?  Describe historic and existing conditions  Refine and expand problems and opportunities  Define future without project condition

4 BUILDING STRONG ® How to Inventory  Information Gathering Strategy  Develop and describe in Project Management Plan (PMP)  Re-evaluate

5 BUILDING STRONG ® Information Gathering Strategy  Geographic Area  Relevancy  Quantity  Accuracy  Timing  Period of time

6 BUILDING STRONG ® Examples of Data Used in Planning Foundation characteristics Infrastructure Geologic formations Minerals Land classificationsDrainage patterns Aquifer characteristicsYields Rain gauge dataPrecipitation records Evaporation rates Gauging stations locations Stream flow recordsSediment loads Groundwater qualitySurface water quality Flora and faunaHistoric structures Endangered speciesSignificant resources Habitat typesPopulation Land usesStructure values Structure elevationsIncome distribution EmploymentCommodity demand StakeholdersCommodity movements Vessel fleet characteristics

7 BUILDING STRONG ® Example Data Flood Management Study Data NeededPurposeSuggested Sources Water surface elevations by flood frequency Define floodplain. Estimate damages/benefits. Formulate plans. Hydrologic/hydraulic analyses Property at risk of floodingEstimate damages/benefits. Formulate plans. Hydrologic/hydraulic analyses. Flooded area maps. Structure/Content valuesEstimate damages/benefits. Formulate plans Field surveys. Commercial data (Marshall & Swift, others)

8 BUILDING STRONG ® Example Data Flood Risk Management Study (Cont.) Data NeededPurposeSuggested Sources Depth-damage curvesEstimate damages/benefits. Generic curves. Site specific surveys. Ecological resources impacted by plans Develop mitigation measures. Published data. Resource agencies. Field surveys. Unit costsCost estimatesMCACES. Commercial sources.

9 BUILDING STRONG ® Data Collection  Potential sources: ► Primary From original research ► Secondary Collected by others Internet

10 BUILDING STRONG ® Planners Website http://usace.army.mil/CECW/PlanningCOP/Pages/psa.aspx Planner's Study Aids: Coastal Storm Damage Reduction Ecosystem Restoration Flood Risk Management Hydropower Navigation Recreation Water Supply/Water Quality Watershed Formulation and Evaluation

11 BUILDING STRONG ® For Additional Information on Available Data  Flood Risk Management ► Stuart A. Davis, IWR ► Eric Thaut, SPD  Deep-Draft/Inland Navigation ► Ian Mathis, IWR ► Navigation Data Center, IWR ► Wesley Walker, LRD ► Bernard Moseby, SAM  Ecosystem Restoration ► Jodi Staebell, MVR

12 BUILDING STRONG ® Criteria to Identify Data Needed  Required ► Laws ► Policies ► Regulations  Nice to Know

13 BUILDING STRONG ® Helpful or Harmful?  Recent reports  Checklists  “Typical” study  Available information  Templates

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20 Inventory and Forecast  Four Conditions: ► Existing condition. ► Historic condition. ► Future without condition. ► Future with condition.  Target

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26 Inventory and Forecast  Four Conditions: ► Existing condition. ► Historic condition. ► Future without condition. ► Future with condition.  Target.  Three types of comparisons: ► With-and-without analysis. ► Before-and-after analysis. ► Gap analysis.

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30 Inventory and Forecast  Four Conditions: ► Existing condition. ► Historic condition. ► Future without condition. ► Future with condition.  Target  Three types of comparisons: ► With-and-without analysis (Col. 5 - Col.4). ► Before-and-after analysis (Col. 5- Col. 3). ► Gap analysis (Col. 5- Col. 1).

31 BUILDING STRONG ® FORECASTING

32 BUILDING STRONG ® References  ER 1105-2-100, Appendix E, Paragraph E-3a(2)  ER 1105-2-100, Appendix E, Sections II and X ► Specific guidance for each Civil Works mission Without Project Condition Handbook Handbook on Deep Draft Forecasting

33 BUILDING STRONG ® What is a Forecast and Why Do it?  What: Informed guess about the future, a future condition or scenario  Why: Anticipate future conditions that are uncertain.  To define the base condition, the future without project condition and the future with projects condition

34 BUILDING STRONG ® Forecasts are based on:  Data  Expertise and Experience  Assumptions

35 BUILDING STRONG ® What do we forecast?  Variables  Scenarios (Conditions)

36 BUILDING STRONG ® Variables to forecast: those that affect decisions

37 BUILDING STRONG ® Conditions to Forecast  Base Condition - condition at the time of implementation (base year)  Without Condition - condition if no action takes place (period of analysis)  With Condition - condition if a particular course of action is taken (period of analysis)

38 BUILDING STRONG ® Forecast Without Project Condition  Primary outcome of Step 2.  Forecast of the future, without any action to solve the problem at hand. Does not mean “no change”.  Most likely condition or use RBA  Used for plan evaluation (with vs. without)

39 BUILDING STRONG ® Assumptions  Data, expertise and experience help make an informed forecast and thus reduce uncertainty.  Assumptions address the remaining uncertainty.  When uncertainty is significant, assumptions are also significant.

40 BUILDING STRONG ® Annual Hotel Revenues

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43 BUILDING STRONG ® Forecasting Methods  Quantitative ► Percentage growth ► Regression ► Simulation ► Mathematical programming  Qualitative ► Subjective judgment ► Expert opinion

44 BUILDING STRONG ® Criteria to Select Forecasting Method  Purpose  Reliability of Data  Level of Disaggregation  Uncertainties and Scenarios  Short vs. Long Term

45 BASE YRTIME+20 YEARS 0- 10- 20-

46 BASE YRTIME+20 YEARS 0- 10- 20- Existing at base yr

47 BASE YRTIME+20 YEARS 0- 10- 20- Existing at base yr Target

48 BASE YRTIME+20 YEARS 0- 10- 20- Existing at base yr Target Future Without (ER) Future Without (FDR/NAV)

49 BASE YRTIME+20 YEARS 0- 10- 20- Existing at base yr Target Future Without (ER) Future with Plan A

50 BASE YRTIME+20 YEARS 0- 10- 20- Existing Target Future Without (ER) Future with Plan A

51 BASE YRTIME+20 YEARS 0- 10- 20- Existing Target Future Without (ER) Future with Plan A Before& After

52 BASE YRTIME+20 YEARS 0- 10- 20- Existing Target Future Without (ER) Future with Plan A With & Without

53 BASE YRTIME+20 YEARS 0- 10- 20- Existing Target Future Without (ER) Future with Plan A With & Without Gap

54 BUILDING STRONG ® Summary  In Step 2, data collected is used to verify or re-define problems and opportunities identified in Step 1  Future without project condition is primary outcome of Step 2  Collect only information you need and use it  “Without” or “No Action” does not mean no change  Assumptions matter.

55 BUILDING STRONG ® Forecaster’s Motto OFTEN WRONG BUT NEVER IN DOUBT


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