REPORT: VERSION 03
DATE: JULY 2023
PREPARED BY: HEATHER SPRAGUE, AMANDA WEIKMANN, DEREK NORMAN, DAVE
GONG, HARRISON JAEHN, AND TIM NELSON
COASTAL PROTECTION AND
RESTORATION AUTHORITY
150 TERRACE AVENUE
BATON ROUGE, LA 70802
WWW.COASTAL.LA.GOV
2023 COASTAL MASTER PLAN
PROJECT DEVELOPMENT
DATABASE
DOCUMENTATION
ATTACHMENT F6
2023 COASTAL MASTER PLAN. PDD Documentation 2
COASTAL PROTECTION AND
RESTORATION AUTHORITY
This document was developed in support of the 2023 Coastal Master Plan being prepared by the
Coastal Protection and Restoration Authority (CPRA). CPRA was established by the Louisiana
Legislature in response to Hurricanes Katrina and Rita through Act 8 of the First Extraordinary Session
of 2005. Act 8 of the First Extraordinary Session of 2005 expanded the membership, duties, and
responsibilities of CPRA and charged the new authority to develop and implement a comprehensive
coastal protection plan, consisting of a master plan (revised every six years) and annual plans. CPRA’s
mandate is to develop, implement, and enforce a comprehensive coastal protection and restoration
master plan.
CITATION
Sprague, H., Weikmann, A., Gong, D., Norman, D., & Nelson, T. (2023). 2023 Coastal Master Plan:
Attachment F6: Project Database Development Documentation. Version 3. (p. 40). Baton Rouge,
Louisiana: Coastal Protection and Restoration Authority.
2023 COASTAL MASTER PLAN. PDD Documentation 3
ACKNOWLEDGEMENTS
This document was developed as part of a broader Model Improvement Plan in support of the 2023
Coastal Master Plan under the guidance of the Modeling Decision Team:
Coastal Protection and Restoration Authority (CPRA) of Louisiana - Eric White,
Elizabeth Jarrell (formerly CPRA), Stuart Brown, Krista Jankowski, David Lindquist,
Ashley Cobb, Sam Martin, Madeline LeBlanc, Forrest Town (formerly CPRA)
University of New Orleans (UNO) – Denise Reed
The following experts were responsible for the preparation of this document:
Heather Sprague – Arcadis
Amanda Weikmann – Arcadis
Dave Gong - Arcadis
Derek Norman – Arcadis
Harrison Jaehn – Arcadis
Tim Nelson – (formerly) Arcadis
2023 COASTAL MASTER PLAN. PDD Documentation 4
EXECUTIVE SUMMARY
As coastal Louisiana faces increasing threats from flooding and sea level rise, there is a great need to
advance our scientific understanding of the coast and how coastal Louisiana will need to adapt to
future conditions. The Coastal Protection and Restoration Authority (CPRA) is undertaking this
challenge through six-year updates of Louisiana’s Comprehensive Master Plan for a Sustainable
Coast. This document summarizes the process by which CPRA developed candidate projects for
consideration in the 2023 Coastal Master Plan.
The 2023 Coastal Master Plan builds on past progress and establishes a clear vision for the future. It
refines past plans by improving the methods used to ensure projects are evaluated as efficiently,
consistently, and effectively as possible. These improvements include changes to the costing
methodology and project structure, as well as the development of the Project Development
Geodatabase (PDG), the Project Development Database (PDD), and an automated Project Costing Tool
(PCT). This document is intended to serve as the technical documentation as the PDD and PDG are
developed for the Louisiana 2023 Coastal Master Plan. It will be a living document subject to revision
as various portions of the new tools and processes are developed.
2023 COASTAL MASTER PLAN. PDD Documentation 5
TABLE OF CONTENTS
COASTAL PROTECTION AND RESTORATION AUTHORITY ....................................... 2
CITATION ........................................................................................................ 2
ACKNOWLEDGEMENTS ...................................................................................... 3
EXECUTIVE SUMMARY ...................................................................................... 4
TABLE OF CONTENTS ........................................................................................ 5
LIST OF TABLES ............................................................................................... 6
LIST OF FIGURES ............................................................................................. 6
LIST OF ABBREVIATIONS .................................................................................. 7
1.0 INTRODUCTION .......................................................................................... 9
1.1 Project Organization ............................................................................. Error! Bookmark not defined.
1.2 General Database Information ........................................................................................................ 12
2.0 PDD SCHEMA ........................................................................................... 15
3.0 PCT SCHEMA ............................................................................................ 17
4.0 ICM SCHEMA ............................................................................................ 23
5.0 CLARA SCHEMA ........................................................................................ 26
6.0 PT SCHEMA .............................................................................................. 30
7.0 DAP SCHEMA ........................................................................................... 32
8.0 PDG STRUCTURE ...................................................................................... 38
9.0 REFERENCES ............................................................................................ 40
2023 COASTAL MASTER PLAN. PDD Documentation 6
LIST OF TABLES
Table 1. PDD schema definition. ....................................................................... 13
Table 2. Tables in the pdd schema. .................................................................. 16
Table 3. Tables in the pct schema .................................................................... 21
Table 4. Tables in the icm Schema ................................................................... 24
Table 5. Tables in clara Schema ....................................................................... 27
Table 6. Tables in the pt Schema ..................................................................... 31
Table 7. Metric definitions ............................................................................... 32
Table 8. Timeseries data outputs ...................................................................... 34
Table 9. Timeseries data for dap ...................................................................... 35
Table 10. PDG Structure ................................................................................. 38
LIST OF FIGURES
Figure 1. General workflow for data handoffs between modeling teams. ................ 11
Figure 2. Database relation of pdd tables and link to pct schema. ......................... 15
Figure 3. Database relation and structure of metadata and attributes. .................. 17
Figure 4. Database relation and structure of attributes and output cost tables. ...... 18
Figure 5. Database relation and structure of MC, borrow source, and output cost
tables. .......................................................................................................... 18
2023 COASTAL MASTER PLAN. PDD Documentation 7
LIST OF ABBREVIATIONS
ADCIRC ....................................................................... ADVANCED CIRCULATION
AWS ............................................................................. AMAZON WEB SERVICES
BS .................................................................................... BANK STABILIZATION
cf .................................................................................................... CUBIC FEET
cfs ............................................................................... CUBIC FEET PER SECOND
CH ..................................................................................... CHANNEL CREATION
CL ............................................................................................. GAP CLOSURES
CLARA ................................................... COASTAL LOUISIANA RISK ASSESSMENT
CPRA ................................. COASTAL PROTECTION AND RESTORATION AUTHORITY
CWCCIS ................................. CIVIL WORKS CONSTRUCTION COST INDEX SYSTEM
DI ................................................................................................... DIVERSION
EL ............................................................................................ EXISTING LEVEE
ft ..................................................................................................... FOOT/FEET
FWOA ......................................................................... FUTURE WITHOUT ACTION
FWA ................................................................................. FUTURE WITH ACTION
GA ......................................................................................... PROPOSED GATES
GIS ............................................................. GEOGRAPHIC INFORMATION SYSTEM
HR .......................................................................... HYDROLOGIC RESTORATION
ICM .............................................................. INTEGRATED COMPARTMENT MODEL
IP ..................................................................................... INTEGRATED PROJECT
LB ................................................................................................. LANDBRIDGE
LS ..................................................................................................... LUMP SUM
MC ......................................................................................... MARSH CREATION
MPDAP ......................................................... MASTER PLAN DATA ACCESS PORTAL
MPDV ...................................................................... MASTER PLAN DATA VIEWER
NAVD88 ........................................... NORTH AMERICAN VERTICAL DATUM OF 1988
NS ................................................................. NONSTRUCTURAL RISK REDUCTION
O&M ................................................................. OPERATIONS AND MAINTENANCE
OR .................................................................................. OYSTER BARRIER REEF
2023 COASTAL MASTER PLAN. PDD Documentation 8
PCS ............................................................................. PROJECT COST SUMMARY
PCT .............................................................................. PROJECT COSTING TOOL
PDD ............................................................... PROJECT DEVELOPMENT DATABASE
P/E&D ....................................................... PLANNING/ENGINEERING AND DESIGN
PL .......................................................................................... PROPOSED LEVEE
PSC ....................................................... PITTSBURGH SUPERCOMPUTING CENTER
PT ............................................................................................ PLANNING TOOL
PW ................................................................................. PROPOSED FLOODWALL
QAQC ............................................. QUALITY ASSURANCE AND QUALITY CONTROL
RR ..................................................................................... RIDGE RESTORATION
SP ................................................................................ SHORELINE PROTECTION
SR ....................................................................... STRUCTURAL RISK REDUCTION
SQL ................................................................... STRUCTURED QUERY LANGUAGE
SWAN ............................................................... SIMULATING WAVES NEARSHORE
USACE .............................................................. U.S. ARMY CORPS OF ENGINEERS
XX ............................................................................ MISCELLANEOUS QUANTITY
2023 COASTAL MASTER PLAN. PDD Documentation 9
1.0
INTRODUCTION
As Louisiana faces increasing threats from coastal flooding and sea level rise, there is a great need to
advance our scientific understanding of the coast and how coastal Louisiana will need to adapt to
future conditions. The Coastal Protection and Restoration Authority (CPRA) is undertaking this
challenge through six-year updates of Louisiana’s Comprehensive Master Plan for a Sustainable
Coast. The 2023 Coastal Master Plan builds on past progress and establishes a clear vision for the
future. It refines past plans by improving the methods used to ensure projects are evaluated as
efficiently, consistently, and effectively as possible.
As discussed in Appendix F: Project Concepts (Sprague, 2023a), previous master plan iterations
required hundreds of Excel spreadsheets, dozens of CSV files, and over forty unique Esri shapefiles to
measure, quantify, calculate, and aggregate project information, which in turn required frequent
manual data transfers between different modeling teams. Because the 2023 Coastal Master Plan is
intended to tackle the analysis of broader, more complicated projects than previous plans, a new
system was devised for defining and assembling the building blocks used to describe a project. This
new system streamlines this process by replacing the cumbersome spreadsheets and shapefiles with
four primary features:
1.
A centrally accessible PostgreSQL database, called the Project Development
Database (PDD), which houses tables of relevant project attributes, metadata, bid
items, costs, and any project-level outputs that may need to be passed between
modeling teams. Custom Structured Query Language (SQL) scripts are used to
access data directly from the PDD as needed and may be stored in the PDD as views
or materialized views.
2.
A python program, called the Project Costing Tool (PCT), which reads inputs from the
PDD, calculates quantities and costs of each feature within a project, and stores
values back into the PDD. Additional data processing scripts are used in conjunction
with the PCT to define project attributes and to streamline quality assurance and
control (QAQC) procedures.
3.
An Esri geodatabase, called the Project Development Geodatabase (PDG), which
contains the geospatial representations of all projects in three feature classes (for
points, polygons, and polylines); in future iterations of the master plan, geospatial
data is intended to be integrated into the PDD with a Spatial Database Engine (SDE).
While the PDG is the source of truth for all geospatial data, a copy of the PDG also
exists, referred to as the Mapping PDG, which joins project-level attributes from the
PDD to the points, lines, and polygons in the PDG. The Mapping PDG is automatically
re-created every time the PDD or PDG is updated.
4.
A reporting system (presently using Jaspersoft software) that reads from the PDD to
2023 COASTAL MASTER PLAN. PDD Documentation 10
produce project-level Project Cost Summary (PCS) reports.
Ultimately, the PDD and PDG act as a central repository for tabular and basic geospatial data used
and generated by the four primary master plan modeling teams: the Advanced CIRCulation (ADCIRC)
and Simulating WAves Nearshore (SWAN) team, the Integrated Compartment Model (ICM) team, the
Coastal Louisiana Risk Assessment (CLARA) model team, and the Planning Tool (PT) team. Basic
project attributes and vector-based geospatial data are developed and then read by the
ADCIRC+SWAN, ICM, and CLARA models. Additional project attributes are produced by these models
and stored back into the PDD. The PCT reads attributes and produces costs, which are in turn read by
the Planning Tool, along with model outputs from the ICM and CLARA, to prioritize projects and store
project-level results back to the PDD (Figure 1). This effort is intended to streamline data generation
and transfer, while greatly reducing the number of files and overall file size required for project
definition within the master plan. The Project Cost Summary (PCS) reports are used to summarize
detailed project attributes and costs for CPRA engineers to review as part of the project definition
process.
To present the project (via vicinity and project maps) and modeling outputs (i.e., estimated cost and
duration, project benefits graphs) in a clear, digestible manner, different fact sheets were created for
at four unique geographic scales. Regional Fact Sheets show compiled data for the five designated
coastal regions of Louisiana (e.g., Chenier Plain, Terrebonne etc.). Parish Fact Sheets are created for
parishes with master plan projects or those impacted by modeling (e.g., Jefferson Parish, Tangipahoa
Parish etc.). Community Fact Sheets documents model outputs and maps for designated community
areas (e.g., Belle Chasse Area, Slidell Area etc.). Finally, Project Fact Sheets provide project specific
data. All facts sheets are found in the Attachments F2 to F5.
Additionally, timeseries data developed by the ICM and CLARA modeling teams are formatted within
the PDD for specific API calls by the Master Plan Data Access Portal (MPDAP), which allows the public
to view and download more detailed model outputs than are available in the fact sheets or in the
Master Plan Data Viewer.
2023 COASTAL MASTER PLAN. PDD Documentation 11
Figure 1. General workflow for data handoffs between modeling teams.
This document is intended to serve as a framework to define the architectural details of the PDD, the
PDG, and the Mapping PDG as it stands in July 2023, at the conclusion of the 2023 Coastal Master
Plan. The attached data model represents a detailed description of all fields in all tables, views, and
materialized views in each schema of the PDD and for each feature class in the PDG and Mapping
PDG. Sections 2.0 through 7.0 detail the structure of the PDD, while Section 8.0 describes the PDG
and Mapping PDG.
1.1
PROJECT ORGANIZATION
As detailed in Appendix F: Project Concepts, there are eight distinct project types evaluated in the
master plan, split into two primary categories: Risk Reduction and Restoration. Risk Reduction
projects can either be Structural (designated as SR) or Nonstructural (NS), while Restoration projects
may fall under one of six categories: Diversions (DI), Hydrologic Restoration (HR), Landbridge (LB),
Marsh Creation (MC), Ridge Restoration (RR), and Integrated Projects (IP). Each project is composed of
one or many Elements, and multiple projects may reference the same Element. There are thirteen
unique Element Types used to define Restoration and Structural Risk Reduction projects: Proposed
Levees (PL), Improvements to Existing Levees (EL), Proposed Floodwalls (PW), Proposed Gates (GA),
Channel Creation (CH), Marsh Creation (MC), Gap Closures (CL), Ridge Restoration (RR), Shoreline
Protection (SP), Bank Stabilization (BS), Oyster Reef (OR), Miscellaneous Quantity (XX), and Lump Sum
(LS). Nonstructural Risk Reduction projects are defined by the CLARA model based on counts of
properties that may be floodproofed, elevated, or acquired, and do not follow the same project-
Element relationships defined elsewhere in the PDD.
2023 COASTAL MASTER PLAN. PDD Documentation 12
Each Element has a subgrouping of Components that comprise some feature of that Element. For
example, Shoreline Protection rubble mound Elements include geotextile base, riprap, navigational
aid, and settlement plate Components. Lists of Components utilized in costing each Element Type are
described in detail in the Project Costing Tool Technical Documentation (Sprague 2023b).
1.2
GENERAL DATABASE INFORMATION
The official PDD is hosted by the Pittsburgh Supercomputing Center (PSC). Credentialed users may
access either database directly via Python or other programming languages or by using a SQL client
such as PGAdmin (a freeware commonly used for managing and supporting PostgreSQL Databases).
The server host of the PDD is vm007.bridges2.psc.edu and the database name is mp23_pdd,
accessible via an SSH tunnel with the host bridges2.psc.edu that require PSC authentication to
connect. Credentials are required to access each database and are available to master plan project
team members upon request.
The foundation of any relational database is the definition of tables, fields, and data types which are
used to house and link relevant data. Relational databases use identification fields called primary
keys to store tabular data. Each table will have a primary key that is unique for an entry in the table
and is typically an auto-incremented integer. Data can then be linked to another table’s data through a
foreign key. A foreign key is the relation to a different table’s primary key. These keys help join tables
together for structure and efficiency. For example:
Data at the project level are stored in the ProjectMetadata table. That data/table has
a primary key ProjectUID.
Another table is ElementDefinition, which has a primary key called ElementUID and a
foreign key PrimaryProjectUID, which relates Element data to the project Metadata
Table.
PostgreSQL databases specifically organize data using objects called schemas
1
, which in turn contain
tables. Different schemas are used to separate tables into logical groups based on relevance to each
modeling team. Permissions are set at the schema level to preserve the integrity of the database by
allowing users to access only the data relevant for their needs. Similarly, each schema can utilize its
1
The term schema may also, at times, reference the architecture of a table itself, including its name,
the names and types of each column, and the assignment of primary and foreign keys. In this docu-
ment, the term schema will only refer to the PostgreSQL definition related to a grouping of tables
within a database.
2023 COASTAL MASTER PLAN. PDD Documentation 13
own set of rules regarding the primary units of measurement, depending on what is required for the
relevant model. Six schemas are defined for the PDD (pct, pdd, icm, clara, pt, and dap
2
), described in
Table 1 and discussed in further detail in Sections 2.0 through 7.0.
Table 1. PDD schema definition.
SCHEMA
DESCRIPTION
pct
TABLES AND VIEWS RELATED TO ELEMENTS,
COMPONENTS, AND COSTS
pdd
TABLES AND VIEWS AT THE PROJECT OR MODEL
GROUP LEVEL, NOT SPECIFICALLY REQUIRED FOR
THE PCT, BUT GENERALLY USED BY ALL MODELING
TEAMS
icm
DIRECT AND MANIPULATED OUTPUTS OF ICM
clara
DIRECT AND MANIPULATED OUTPUTS OF CLARA
pt
DIRECT AND MANIPULATED OUTPUTS OF PT
dap
MANIPULATED TIMESERIES OUTPUTS OF ICM AND
CLARA USED IN THE DATA ACCESS PORTAL
In addition to tables, the PDD schemas store data in views and materialized views. Tables can be
considered to store data that is directly inputted into the PDD, whereas views and materialized views
represent a manipulated version of data stored in tables. These virtual tables store queried
information that combines data from multiple tables, views, or materialized views for users to access
information in a different manner than it is originally stored. A view represents data outputted from a
query that is executed each time it is accessed, whereas a materialized view represents a stored copy
of data outputted by a query. In the PDD, data in materialized views are updated automatically every
day at midnight Central Time but can also be manually updated any time new data is posted.
Generally, within the PDD, views are used for queries related to model inputs and have names
beginning with the prefix “vw_”. For example, the vw_element_assignment view in the pct schema
2
The lowercase pct, pdd, icm, clara, and dap terminology designates the respective schemas within
the (uppercase) PDD database, rather than the Project Costing Tool, the Project Development Data-
base, the Integrated Compartment Model, the Coastal Louisiana Risk Model, or the Master Plan Data
Access Portal.
2023 COASTAL MASTER PLAN. PDD Documentation 14
adds relevant fields from the ProjectMetadata, ElementDefinition, and Candidates tables to the
ElementAssignment table to add useful information like project type, Element type, project name, and
construction duration for each Element assigned to each project. Materialized views are typically used
for aggregating, filtering, and formatting model outputs and have names starting with the prefix “mv_”.
For example, the mv_land_veg_project_lnd_fwoa materialized view in the icm schema filters data
saved in the land_veg table to display just FWOA land area for a select subset of vegetation types,
aggregated for each candidate project.
Views and materialized views in the PDD are used to aggregate and format data in a way that is more
useful to other modeling teams (e.g., formatting data from ICM output tables use in the Planning Tool,
etc.) or for creating master plan related documents (e.g., the 2023 Coastal Master Plan itself and
other fact sheets). Detailed information, like field names, index fields and data sources, for the views
and materialized views can be found in Supplemental Material F6.1:
PDD Data Model Excel Workbook
.
2023 COASTAL MASTER PLAN. PDD Documentation 15
2.0
PDD SCHEMA
The pdd schema stores information required for the development and modeling of projects but not
specifically required for the PCT. Data is in this schema is generally reported at a project or model
group level. The pdd tables are read by all modeling teams and linked using the ProjectID as opposed
to the UID fields utilized in the pct schema (see Section 3.0). Figure 2 shows the database relations
between tables in the pdd schema and their connection to the source of the ProjectID field in the
ProjectMetadata table in the pct schema.
Figure 2. Database relation of pdd tables and link to pct schema.
Project development information, including candidate project durations, model group assignment, and
lists of project prerequisite and mutually exclusive projects, are stored in the pdd tables, as
summarized in Table 2. Descriptions of each field in the pdd schema tables are available in
Supplemental Material F6.1:
PDD Data Model Excel Workbook
.
Some views and materialized views in the PDD represent data that is relevant to both projects and
Elements. For example, in the Planning Tool, MC Elements are treated as pieces of larger IP, LB, or MC
projects, but may also be modeled as individual projects themselves. In this case, and therefore have
both cost and benefit information, just as other projects do. To efficiently combine these data, an
additional ID field called the CombinedID is used to store both ProjectIDs and ElementIDs as
appropriate in a mixed dataset.
2023 COASTAL MASTER PLAN. PDD Documentation 16
Table 2. Tables in the pdd schema.
TABLE NAME
DESCRIPTION
PRIMARY KEY
NUMBER OF
COLUMNS
NUMBER OF
ROWS
AlternativeDefinition
DEFINES RELATIONSHIP BETWEEN PROJECTS AND MODEL GROUPS OF ALTERNATIVE RUNS (G515-G521)
MODELGROUP, PROJECTID
6
277
Candidates
LIST OF ALL CANDIDATE PROJECTS TO BE EVALUATED IN THE MASTER PLAN MODELS, ALONG WITH ANY ATTRIBUTES AT THE
PROJECT LEVEL THAT ARE REQUIRED FOR MULTIPLE MODELS, BUT NOT FOR THE PCT
PROJECTID
4
166
CommunityAgriculture
LINKS A SUBSET OF COMMUNITIES THAT PRODUCE AGRICULTURE TO THE ECOREGIONS UPON WHICH THEY ARE DEPENDENT;
USED TO DEFINE THE AGRICULTURE METRIC
COMMUNITYNAME
2
17
CommunityDefinition
DEFINES COMMUNITY-LEVEL METADATA SUCH AS THE ECOREGION, PARISH, AND AREA IN WHICH THEY RESIDE
COMMUNITYID
10
374
CommunityFishing
LINKS A SUBSET OF COMMUNITIES THAT HAVE PROMINENT FISHING INDUSTRIES TO THE RESOURCE USE AREAS (I.E.,
COLLECTION OF ECOREGIONS) UPON WHICH THEY ARE DEPENDENT; USED TO DEFINE THE FISHING METRIC
COMMUNITYNAME, RESOURCEUSEAREA
2
40
CommunityFishingResource
LINKS A SUBSET OF COMMUNITIES THAT HAVE PROMINENT FISHING INDUSTRIES TO THE HABITAT CODES OF SPECIES THAT
ARE FISHED IN THEIR RESOURCE USE AREA; USED TO DEFINE THE FISHING METRIC
COMMUNITYNAME, HABITATCODE
2
203
CommunityOilGas
LINKS A SUBSET OF COMMUNITIES THAT HAVE PROMINENT OIL AND GAS INDUSTRIES TO THE REGIONS UPON WHICH THEY ARE
DEPENDENT; USED TO DEFINE THE OIL AND GAS METRIC
COMMUNITYNAME, REGION
2
55
ExtractionPointAssignment
ASSIGNS EACH EXTRACTION POINT TO ONE OR MANY PROJECTS AND DEFINES THE DISTANCE BETWEEN THAT POINT AND THE
PROJECT.
EXTRACTIONPOINT, PROJECTID
3
943
ExtractionPointDefinition
DEFINES A LIST OF EXTRACTION POINTS USED TO QAQC MODEL RESULTS AND THEIR CORRESPONDING ECOREGION
EXTRACTIONPOINT
2
678
MetricDefinition
DEFINES METRICS USED THROUGHOUT THE ICM AND CLARA MODELS, INCLUDING A DESCRIPTION, RELEVANT SECTORS, AND
UNITS
METRICID
9
24
ModelDefinition
DEFINES THE RELATIONSHIP BETWEEN PROJECTS AND MODEL GROUPS FOR PROJECT-LEVEL RUNS (MODEL GROUPS BETWEEN
600 AND 699)
MODELGROUP, PROJECTID
5
238
MutuallyExclusive
DEFINES WHICH PROJECTS SHOULD NOT BE IMPLEMENTED WITH EACH OTHER, BECAUSE THEY HAVE OVERLAPPING
FOOTPRINTS OR REDUNDANT INTENDED BENEFITS
MUTUALLYEXCLUSIVE, PROJECTID
2
21
NaturalProcessesUse
CATEGORICALLY DEFINES THE WAY IN WHICH A PROJECT MAKES USE OF NATURAL PROCESSES
DOMINANTCHARACTERISTICS,
PROJECTTYPECODE
4
11
ParishDefinition
DEFINES PARISH-LEVEL METADATA, SUCH AS THE REGION IN WHICH IT RESIDES AND THE DESCRIPTIONS FOR USE IN THE
PARISH FACT SHEETS
PARISHFIPS
7
24
RegionDefinition
ASSIGNS EACH ECOREGION TO A REGION AND INCLUDES OTHER ECOREGION METADATA, SUCH AS NAME AND DESCRIPTION
ECOREGION, REGION
6
25
ResourceUseAreaDefinition
DEFINES THE ECOREGIONS THAT COMPRISE EACH RESOURCE USE AREA USED IN DEFINING THE FISHING METRIC
ECOREGION, RESOURCEUSEAREA
2
33
2023 COASTAL MASTER PLAN. PDD Documentation 17
3.0
PCT SCHEMA
The pct schema is used to store tables related to Elements, Components, and costs, as well as queries
for different views of the data. The PCT reads data from the pct, pdd, and icm schemas and writes
results back into the pct schema. All units for fields in the pct are in imperial units, due to the PCT’s
dependency on US-based engineering design features, such as the Element design templates
themselves and available bid item data.
FIGURE 3, FIGURE 4, AND
Figure 5. Database relation and structure of MC, borrow source, and output cost
tables.
show the general structure of the pct schema, with relations between primary and foreign keys in red.
As shown in Figure 3, Elements are initialized in the ElementDefinition table and linked to projects in
the ElementAssignment table. Elements may be assigned to one or many different projects, such as
when two DI projects have the same general features, but unique operating regimes. Each element is
also assigned a PrimaryProjectUID, indicating the source project where that element originated. As
Element attributes are changed over time, the PDD archives the change and incrementally increases
the version number for that Element. All attributes from the appropriate Attribute table are then linked
to the relevant version of the Element in the Version table via the VersionUID, and costs are calculated
only for the most up-to-date versions of Elements.
Figure 3. Database relation and structure of metadata and attributes.
The PCT reads from each attribute table to produce quantities and costs for each component within
2023 COASTAL MASTER PLAN. PDD Documentation 18
each Element. Figure 4 describes how Components are linked to the Item table, which holds the unit
costs for each available bid item. Many different types of Components may link to the same bid item;
for example, mechanical dredging is used to build ridges for RR elements and to dredge channels for
CH elements. The Item table is in turn linked to the CostCategory and CostIndex tables, which are
used to escalate inputted bid item costs to 2020 USD using the U.S. Army Corps of Engineers (USACE)
Civil Works Construction Cost Index System (2020). The Item table is also linked to the
ConfidenceRanking table, which is used to provide a range of cost estimates based on assigned
uncertainties in each bid item unit cost.
Figure 4. Database relation and structure of attributes and output cost tables.
Design marsh elevations vary over time due to sea level rise and subsidence. As such, the ICM
determines the required area and volume to build marsh for each model group and environmental
scenario, as the same project may be implemented in different years, depending on how it is modeled.
The PCT, therefore, calculates MC Element costs for each combination thereof. Additionally, the PCT
also determines MC Element costs for multiple borrow source options so that the Planning Tool can
optimize project selection based on limited sediment availability. Figure 5 describes how these costs
are linked to both inputted dredge mobilzation attributes that vary by Element and Borrow Source and
by the ICM-produced area and volume attributes that vary by model group and scenario.
Figure 5. Database relation and structure of MC, borrow source, and output cost
tables.
2023 COASTAL MASTER PLAN. PDD Documentation 19
Tables in the pct schema fall into four general categories, shown below. Table 3 provides a summary
of all database tables in the pct schema and descriptions of all table fields are available in
Supplemental Material F6.1:
PDD Data Model Excel Workbook
.
1.
Metadata and Version Tracking. project, Element, and Version metadata, including
descriptive attributes (e.g., names and descriptions) as well as data related to how
Elements and projects are linked to each other.
2.
General Lookup Tables. Background data needed to estimate costs, such as bid item
unit costs and cost escalation indices.
3.
Element Attributes. Attribute data used to define projects and determine costs for
each of the 13 Element types.
4.
PCT Outputs. Outputted costs at the Element and Component levels.
The project metadata table is used to define and describe all projects that have ever been considered
in any master plan since 2012. This table serves as the foundation for project organization within the
PDD. These metadata attributes are common for all Restoration and Risk Reduction projects. As
described in Figure 3 and Table 3, the ElementDefinition, ElementAssignment, and Version tables are
used to define Element-level metadata and link Elements to specific projects and versions. Inputs are
versioned; however, outputs are not versioned since the database will always reflect a live view of the
latest information. Versioning inputs allows for the regeneration of past attributes versions, should
they be required.
Several tables are required to facilitate intermediate calculations in the PCT as well as to provide
additional information to other modeling teams and to any report generation software. The Costs table
summarizes the application of unit costs and cost percentages, while Gate and Type tables link to
Attribute and Component tables to describe general information not provided elsewhere in the PDD,
but needed by modeling teams, such as information about the generic gate sizes. The CostCategory
and CostIndex tables contain price index information from the US Army Corps of Engineers Civil Works
Construction Cost Index System, also known as CWCCIS (USACE, 2020). These are used to adjust Unit
Costs for inflation based on Year and Cost Category UID, and Appendix F1 contains a more detailed
description of the cost escalation process.
Certain costs are generally applied as a percentage of other costs (e.g., contingency is typically 20% of
construction costs). These costs and their associated percentage values are contained in the
CostPercentage table. Certain projects may require cost percentages that differ from the default
values, and these exceptions are assigned to specific projects in the CostPercentageOverride table.
Appendix F1 has more detail regarding how cost percentages are applied.
Principal attributes for each Element type that comprise projects proposed in the 2023 Coastal Master
Plan are stored in attribute specific tables. These attribute tables contain all information required for
2023 COASTAL MASTER PLAN. PDD Documentation 20
the functions of the PCT. Appendix F1 provides additional project- and Element-level assumptions.
Some attributes are provided in multiple tables (e.g., crest elevation for proposed and existing levee
features) for the PCT to appropriately calculate required quantities of materials.
AS DESCRIBED IN
Figure 5. Database relation and structure of MC, borrow source, and output cost
tables.
, the PCT pulls data from the Attributes_MC and BorrowOptions tables in the pct schema, along with
the mc table in the icm schema, to produce costs that vary by model group, Scenario, and Borrow
Source. Data listed in the BorrowOptions table are determined at the Cell level before being
aggregated within an Element.
PCT output tables are used to store the cost estimation results from the PCT, calculated for each
Component comprising each Element in the ElementComponents table, for each Element in the
ElementCosts table, and for each MC Element-borrow source combination in the BorrowOptionsCosts
table. Costs are produced for three unique Cost Scenarios to determine a likely range of values, and
ranges may vary by Environmental Scenario and model group. All costs are reported in 2020 USD, and
are reported either in direct dollar values or, in the BorrowOptionsCosts table, in dollars per cubic foot
of sediment required to build an MC Element. Additional information regarding cost calculation
assumptions can be found in Appendix F1.
The ElementComponents table intentionally does not have a primary key, as the same Element may
have costs associated with multiple uniquely calculated quantities of the same Component. For
example, EL Elements typically have two entries associated with the sediment material component –
one positive value representing quantity of material needed to upgrade the levee, and one negative
value representing the amount of material that is already there in the existing feature.
2023 COASTAL MASTER PLAN. PDD Documentation 21
Table 3. Tables in the pct schema
CATEGORY
NAME
DESCRIPTION
PRIMARY KEY
NUMBER OF COLUMNS
NUMBER OF ROWS
METADATA AND
VERSION
TRACKING
TABLES
ElementAssignment
LINK BETWEEN PCT.ELEMENTDEFINITION AND PCT.PROJECTMETADATA, USED TO MATCH ONE
ELEMENT TO ONE OR MANY PROJECTS
ELEMENTASSIGNMENTUID
4
1,607
ElementDefinition
LIST OF ALL ELEMENTS AND RELEVANT METADATA; ONLY PROJECTS CONSIDERED FOR THE 2023
MASTER PLAN ARE BROKEN DOWN INTO ELEMENTS
ELEMENTUID
9
1,346
IssuesContact
STORING MESSAGES RECEIVED FROM THE PCT USER INTERFACE
CONTACT_ID
6
0
ProjectMetadata
LIST OF ALL PROJECTS PROPOSED SINCE THE 2012 MASTER PLAN AND RELEVANT METADATA
PROJECTUID
12
437
Version
LINK BETWEEN ELEMENTS AND VERSIONS
VERSIONUID
7
1,346
GENERAL LOOKUP
TABLES
BorrowSourceSedimentType
DESCRIPTION OF SEDIMENT TYPE IN EACH BORROW SOURCE
BORROWSOURCE
8
41
Component
LIBRARY OF ALL COMPONENTS USED IN ANY ELEMENT, AND THEIR LINK TO THE SPECIFIC BID
ITEMS WITH CORRESPONDING UNIT COSTS
COMPONENTUID
5
143
ConfidenceRanking
LOOKUP TABLE THAT RELATES CONFIDENCE RANKINGS FOR UNIT COSTS TO DESCRIPTIONS AND
PERCENTAGE VALUES.
RANKING
4
5
Conversions
LIBRARY OF CONVERSION FACTORS BETWEEN UNITS (I.E., SQUARE FEET TO ACRES), USED TO
LINK THE UNITS OF MEASUREMENT OF THE COMPONENTS TO THE BID ITEMS
CONVERSIONUID
4
22
CostCategory
SUMMARY OF EACH OF THE TWENTY CATEGORIES IN THE USACE CIVIL WORKS CONSTRUCTION
COST INDEX SYSTEM
COSTCATEGORYUID
2
20
CostIndex
LIBRARY OF COST INDEXES PER CATEGORY PER YEAR, PULLED FROM THE USACE CIVIL WORKS
CONSTRUCTION COST INDEX SYSTEM
COSTINDEXUID
4
322
CostPercentage
DEFAULT PERCENTAGES FOR EACH OF THE SIX PRIMARY COST PARAMETERS APPLIED TO SUMS
OF COMPONENT COSTS (CONSTRUCTION MANAGEMENT, SURVEYS, MOBILIZATION, OPERATIONS
AND MAINTENANCE (O&M), P/E&D, AND CONTINGENCY)
COSTPERCENTAGEUID
5
6
2023 COASTAL MASTER PLAN. PDD Documentation 22
CATEGORY
NAME
DESCRIPTION
PRIMARY KEY
NUMBER OF COLUMNS
NUMBER OF ROWS
CostPercentageOverride
PERCENTAGE OVERRIDES BY PROJECTID FOR ANY OF THE RELEVANT SIX PRIMARY COST
PARAMETERS
COSTPERCENTAGECODE,
PROJECTUID
3
48
Gates
LOOKUP TABLE RELATING GATE CODES TO GATE-SPECIFIC ATTRIBUTES USED IN THE ICM, SUCH
AS INVERT ELEVATION AND WIDTH
GATEUID
3
29
Item
LIBRARY OF UNIT COSTS AND LINK TO THE PCT.COSTCATEGORY
ITEMUID
8
129
Types
LOOKUP TABLE THAT RELATES TYPE CODES TO TYPE DESCRIPTIONS (E.G., HR: HYDROLOGIC
RESTORATION).
TYPEUID
5
19
ELEMENT
ATTRIBUTES
TABLES
Attributes_**
ATTRIBUTES FOR EACH OF THE 13 ELEMENT TYPES (BS, CH, CL, EL, GA, LS, MC, OR, PL, PW, RR,
SP, AND XX), ASSOCIATED WITH EACH VERSION OF EACH ELEMENT
VERSIONUID
VARIABLE, SEE
SUPPLEMENTAL MATERIAL
F6.1
VARIABLE, SEE
SUPPLEMENTAL MATERIAL
F6.1
BorrowOptions
DREDGE MOBILIZATION ATTRIBUTES FOR EACH ELEMENT-BORROW SOURCE COMBINATION
BORROWOPTIONUID
7
542
PCT OUTPUT
TABLES
BorrowOptionCosts
COSTS ASSOCIATED WITH EACH THE LATEST VERSION OF EACH ELEMENT ASSOCIATED WITH
EACH BORROW SOURCE IT IS LINKED TO IN THE PCT.BORROWOPTIONS TABLE
BORROWOPTIONUID,
COSTSCENARIO,
MODELGROUP, SCENARIO,
VERSIONUID
13
5,670
ElementComponents
QUANTITIES AND COSTS ASSOCIATED WITH THE COMPONENTS OF THE LATEST VERSION OF EACH
ELEMENT
7
17,877
ElementCosts
COSTS ASSOCIATED WITH THE LATEST VERSION OF EACH ELEMENT
COSTSCENARIO,
MODELGROUP, SCENARIO,
VERSIONUID
11
5,718
2023 COASTAL MASTER PLAN. PDD Documentation 23
4.0
ICM SCHEMA
Data in the icm schema falls into three general categories, shown below and discussed in greater
detail throughout this section.
1.
General Lookup Tables. Project-level definition of operation regimes and ecoregions
2.
Model Outputs. Data output from the ICM that is ultimately used to define benefits or
other metrics in the PT or that is used as inputs to the PCT
The ICM calculates many types of metrics that are stored in the PDD, including habitat suitability, land
area, and area of various types of vegetated cover. Benefits evaluated in the Planning Tool typically
represent the difference in these metrics between the FWA and the FWOA ICM runs. When benefits
are captured within the footprint of a project itself, they are considered “direct” benefits, and when
they are captured within the region surrounding the project but not in the footprint itself, they are
considered “indirect” benefits. The sum of direct and indirect benefits is referred to as the “total”
benefits. Additionally, because the Planning Tool allows individual MC Elements that are part of MC
Projects to compete for inclusion in the master plan just as other Projects do, benefits must be
captured at both the project level and the MC Element level. This necessitates the need for a field that
sometimes represents the ProjectID and sometimes represents the ElementID, depending on which
benefit data is being represented, called the “CombinedID”. The CombinedID represents the
ElementID for 94 MC Elements and 11 IP, 15 LB, 13 DI, 10 HR, and 22 RR Projects, for a total of 165
unique CombinedIDs. These terms are found frequently in the names and fields of the materialized
views present in the icm schema.
Table 4 provides a summary of all database tables in the icm schema. Units for all data in the icm
schema are metric and may be converted to imperial units for use in other models. Descriptions of all
fields in icm schema tables is available in Supplemental Material F6.1:
PDD Data Model Excel
Workbook.
2023 COASTAL MASTER PLAN. PDD Documentation 24
Table 4. Tables in the icm Schema
CATEGORY
TABLE NAME
DESCRIPTION
PRIMARY KEY
NUMBER OF
COLUMNS
NUMBER OF
ROWS
GENERAL
LOOKUP
TABLES
ecoregion_definition
USED TO ASSIGN PROJECTS TO ECOREGIONS THAT ARE AFFECTED BY THE PROJECT, USED
TO GROUP ICM OUTPUTS
ECOREGION, PROJECTID
3
371
element_ecoregion_definition
USED TO ASSIGN MC ELEMENTS TO THE ECOREGION IN WHICH THE FOOTPRINT LIES, USED
TO GROUP ICM OUTPUTS
ELEMENTID
3
132
mc_elevation
DEFINES THE TARGET DESIGN ELEVATION FOR EACH MC ELEMENT FOR EACH SCENARIO; SEE
APPENDIX F1 FOR MARSH ELEVATION DESCRIPTION
ELEMENTID, SCENARIO
3
636
operation_regime
DEFINITION OF OPERATIONAL STRATEGIES AND TRIGGERS FOR DIVERSION STRUCTURES
PROJECTID
5
26
MODEL
OUTPUT
TABLES
ag_salinity
SALINITY INDEX FOR EACH CROP IN EACH COMMUNITY FOR EVERY MODEL GROUP,
ENVIRONMENTAL SCENARIO, AND YEAR COMBINATION
COMMUNITYNAME, CROP, DATE,
MODELGROUP, SCENARIO, YEAR_ICM
9
408,096
all_combined_benefits_by_ecoregion
SUPPLEMENTAL PROCESSED MODEL OUTPUT TABLE FOR MODEL GROUP 600; CONTAINS
PROCESSED BENEFITS BY ECOREGION, COMBINEDID, YEAR, AND ENVIRONMENTAL
SCENARIO
COMBINEDID, ECOREGION, MODELGROUP,
PROJECTID, SCENARIO, YEAR_FWOA
17
1,700
archaeological
LAND AREA OF THE GRID CELL ASSOCIATED WITH EACH ARCHAEOLOGICAL SITE FOR EVERY
MODEL GROUP, ENVIRONMENTAL SCENARIO, AND YEAR COMBINATION
DATE, ECOREGION, MODELGROUP,
SCENARIO, SITE, YEAR_ICM
10
TBD
geomorph_output_exp_annual
ANNUAL TIMESERIES DATA COMPILED FROM ICM OUTPUT FILES FOR A VARIETY OF METRICS,
INCLUDING SALINITY, MEAN WATER LEVEL, TIDAL RANGE, ELEVATION, DEPTH, MINERAL
DEPOSITION, MINERAL ACCRETION, ORGANIC ACCUMULATION, ORGANIC ACCRETION, DEEP
SUBSIDENCE, SHALLOW SUBSIDENCE, LANDTYPEID AND FFIBS.
MODELGROUP, SCENARIO, CALENDARYEAR,
EXTRACTIONPOINT
21
TBD
habitat_diversity
CALCULATED SHANNON INDEX FOR EACH REGION FOR EVERY MODEL GROUP,
ENVIRONMENTAL SCENARIO, AND YEAR COMBINATION
DATE, MODELGROUP, REGION, SCENARIO,
YEAR_ICM
8
TBD
hsi
HABITAT SUITABILITY INDEX FOR EACH ECOREGION FOR EVERY MODEL GROUP,
ENVIRONMENTAL SCENARIO, AND YEAR COMBINATION
DATE, ECOREGION, HABITATCODE,
MODELGROUP, SCENARIO, YEAR_ICM
9
2,934,048
hydro_output_annual
ANNUAL TIMESERIES DATA COMPILED FROM ICM OUTPUT FILES FOR A VARIETY OF METRICS,
INCLUDING SALINITY, MEAN WATER LEVEL, TOTAL SUSPENDED SOLIDS, TEMPERATURE,
LAND AREA, AND SUMMER TIDAL RANGE.
CALENDARYEAR, DATE, HYDROCOMPID,
MODELGROUP, SCENARIO
13
371,696
hydro_output_daily
DAILY TIMESERIES DATA COMPILED FROM ICM OUTPUT FILES FOR A VARIETY OF METRICS,
INCLUDING SALINITY, MEAN WATER LEVEL, TOTAL SUSPENDED SOLIDS, TEMPERATURE, AND
TIDAL RANGE.
CALENDARDAY, DATE, HYDROCOMPID,
MODELGROUP, SCENARIO
12
135,761,964
land_veg
AREA OF LAND AND VEGETATION COVER FOR EACH LAND/VEGETATION TYPE IN EACH
ECOREGION FOR EVERY MODEL GROUP, ENVIRONMENTAL SCENARIO, AND YEAR
COMBINATION
DATE, ECOREGION, MODELGROUP,
SCENARIO, VEGETATIONCODE, YEAR_ICM
9
5,087,907
2023 COASTAL MASTER PLAN. PDD Documentation 25
CATEGORY
TABLE NAME
DESCRIPTION
PRIMARY KEY
NUMBER OF
COLUMNS
NUMBER OF
ROWS
mc
MC AREAS AND VOLUMES FOR EVERY MODEL GROUP, ENVIRONMENTAL SCENARIO, AND
YEAR COMBINATION; SOURCE OF DATA USED IN THE PCT
DATE, ELEMENTID, MODELGROUP,
SCENARIO, YEAR_FWOA
8
78,140
mc_shallow_open_water
REPRESENTS THE AREA OF SHALLOW OPEN WATER WITHIN EACH MC ELEMENT FOOTPRINT
OF CANDIDATE PROJECTS FOR PARALLEL AND SERIAL IMPLEMENTATION YEARS; SEE
APPENDIX F1 FOR MORE INFORMATION
ELEMENTID, MODELGROUP, PROJECTID,
SCENARIO
8
478
2023 COASTAL MASTER PLAN. PDD Documentation 26
5.0
CLARA SCHEMA
Data in the clara schema falls into three general categories, shown below and discussed in greater
detail throughout this section. Table 5 provides a summary of all database tables in the clara schema
and descriptions of all table fields are available in Supplemental Material F6.1:
PDD Data Model Excel
Workbook
.
1.
General Lookup Tables. Definition of Nonstructural Risk Reduction Projects, including
costs, structure counts, and other relevant metadata
2.
Model Outputs. Data output from CLARA that is ultimately used to define benefits or
other metrics in the PT
3.
Archived Data: A mix of general look-up tables and model outputs that reference an
outdated list of communities
There are officially 374 distinct communities represented in the CLARA and ICM models, 314 of which
are estimated to experience flood risk across 5 distinct asset types. These 374 communities represent
the breakdown of 221 uniquely named communities in 30 areas across parish, ecoregion, and levee
boundaries – for instance, the named “Amelia” community comprises 5 unique Community IDs (11:
Amelia-TE-in, 12: Amelia-TE-out, 348: Amelia-Assumption-TE-in, 349: Amelia-Assumption-TE-out, and
350: Amelia-St Mary-TE-in) and rolls up to the Morgan City Area.
While some data tables summarize results for each of the five asset types for each of the 314
communities, other tables remove rows where there are no assets of a certain type present within a
community, leading to some inconsistencies in row counts across tables. Previous community lists had
different counts of impacted communities, and row counts in archived data reflect these differences.
More details on CLARA modeling and attributes can be found in Appendix E: Overview of
Improvements to Risk Modeling (ADCIRC+SWAN, CLARA) for 2023 (Martin, 2023; Wilson, 2023a).
2023 COASTAL MASTER PLAN. PDD Documentation 27
Table 5. Tables in clara Schema
CATEGORY
TABLE NAME
DESCRIPTION
PRIMARY KEY
NUMBER OF
COLUMNS
NUMBER OF
ROWS
GENERAL
LOOKUP
TABLES
asset_count
BASELINE COUNT OF ASSETS FOR EACH COMMUNITY IN COASTAL
LOUISIANA, USED FOR EXPOSURE AND RISK ANALYSIS
ASSETTYPE, COMMUNITYID
3
877
asset_count_critical_infrastructure
BASELINE COUNT OF CRITICAL INFRASTRUCTURE ASSETS FOR EACH
COMMUNITY IN COASTAL LOUISIANA, USED FOR EXPOSURE ANALYSIS
CLARAGROUPID, COMMUNITYID,
SOURCEDATASET
4
2,760
asset_count_historic_properties
BASELINE COUNT OF HISTORIC PROPERTIES FOR EACH COMMUNITY IN
COASTAL LOUISIANA, USED FOR EXPOSURE ANALYSIS
COMMUNITYID
2
70
community_info
DISPLAYS DEMOGRAPHIC INFORMATION (E.G. PERCENT OF PEOPLE
WHO IDENTIFY AS ASIAN, BLACK ETC., PERCENT OF LOW TO MODERATE
INCOME) AND THE TOTAL POPULATION FOR EACH NAMED COMMUNITY
COMMUNITYNAME
17
219
nsattributes
DISPLAYS COSTS AND COUNTS OF ASSETS REQUIRING FLOODPROOFING,
ACQUISITION, AND ELEVATION FOR NS PROJECTS, COMMUNITIES,
ASSET TYPES, AND PARTICIPATION RATES
ASSETTYPE, COMMUNITYID, NSPROJECTID,
PARTICIPATIONRATE
10
9,420
nsprojects
DESCRIBES THE CONDITIONS UNDER WHICH EACH NONSTRUCTURAL
PROJECT IS DEFINED
NSACQTHRESHOLD, NSFRAGILITYSCENARIO,
NSMODELGROUP, NSPROJECTID,
NSRETURNPERIOD, NSSCENARIO,
NSYEAR_FWOA
7
12
population_projections
POPULATION PROJECTIONS IN FIVE-YEAR INCREMENTS FOR EACH
PARISH IN COASTAL LOUISIANA FOR MULTIPLE MIGRATION AND SSP
SCENARIOS
CALENDARYEAR, SCENARIO, PARISHFIPS,
MIGRATION, DATE, SSP
8
21,440
population_projections_census_bloc
kgroup
DECADAL POPULATION PROJECTIONS FOR EACH CENSUS BLOCK GROUP
IN COASTAL LOUISIANA FOR MULTIPLE MIGRATION AND SSP SCENARIOS
DATE, CALENDARYEAR, SSP, SCENARIO,
PARISHFIPS, GEOID, MIGRATION, PERCENTILE
10
1,122,300
source_dataset_definition
DEFINES AND GROUPS SOURCE DATASETS FOR CRITICAL ASSETS INTO
CATEGORIES USED TO DISPLAY DATA IN PROJECT FACT SHEETS
SOURCEDATASET
4
63
MODEL
OUTPUT
TABLES
damage
ESTIMATED DAMAGE BY RETURN PERIOD FOR FWOA AND FWP MODEL
RUNS FOR SR PROJECTS
ASSETTYPE, COMMUNITYID, DATE,
FRAGILITYSCENARIO, MODELGROUP,
PROJECTID, PUMPINGID, RETURNPERIOD,
SCENARIO, YEAR_FWOA
15
1,921,680
2023 COASTAL MASTER PLAN. PDD Documentation 28
CATEGORY
TABLE NAME
DESCRIPTION
PRIMARY KEY
NUMBER OF
COLUMNS
NUMBER OF
ROWS
exposure
COUNTS OF EXPOSED ASSETS FOR FWOA AND FWP MODEL RUNS FOR
SR PROJECTS
ASSETTYPE, COMMUNITYID, DATE,
FRAGILITYSCENARIO, MODELGROUP,
PROJECTID, PUMPINGID, RETURNPERIOD,
SCENARIO, YEAR_FWOA
15
892,060
exposure_critical_infrastructure
COUNTS OF EXPOSED CRITICAL INFRASTRUCTURE FOR FWOA AND FWP
MODEL RUNS FOR SR PROJECTS
CLARAGROUPID, COMMUNITYID, DATE,
FRAGILITYSCENARIO, MODELGROUP,
PROJECTID, PUMPINGID, RETURNPERIOD,
SCENARIO, SOURCEDATASET, YEAR_FWOA
15
2,812,480
exposure_historic_properties
COUNTS OF EXPOSED HISTORICAL PROPERTIES FOR FWOA AND FWP
MODEL RUNS FOR SR PROJECTS
COMMUNITYID, DATE, FRAGILITYSCENARIO,
MODELGROUP, PROJECTID, PUMPINGID,
RETURNPERIOD, SCENARIO, YEAR_FWOA
13
71,400
flood_depths
10TH, 50TH, AND 90TH PERCENTILE FLOOD DEPTHS FOR EACH CLARA
GRID CELL
DATE, FRAGILITYSCENARIO, MODELGROUP,
POINTID, PUMPINGID, RETURNPERIOD,
SCENARIO, YEAR_FWOA
13
27,758,280
flood_elevations_icm
TIMESERIES OF DECADAL WATER SURFACE ELEVATIONS AT EACH CLARA
GRID CELL BY ANNUAL EXCEEDANCE PROBABILITY
AEP, DATE, HYDROCOMPID, MODELGROUP,
SCENARIO, YEAR_FWOA
13
629,460
flood_elevations_icm_storm
TIMESERIES OF DECADAL WATER SURFACE ELEVATIONS AT EACH CLARA
GRID CELL BY SYNTHETIC STORM MODELED IN ADCIRC
DATE, HYDROCOMPID, MODELGROUP,
SCENARIO, STORMID, YEAR_FWOA
9
11,185,020
grid_definition
LATITUDE AND LONGITUDE OF EACH CLARA GRID CELL
POINTID
3
126,174
median_ground_elevation
TIMESERIES OF DECADAL MEDIAN GROUND ELEVATIONS AT EACH
CLARA GRID CELL
DATE, MODELGROUP, POINTID, SCENARIO,
YEAR_FWOA
8
2,775,828
nsrisk
RISK IN TERMS OF EXPECTED ANNUAL DAMAGE FOR FWOA AND FWP
MODEL RUNS FOR NS PROJECTS
ASSETTYPE, COMMUNITYID,
FRAGILITYSCENARIO, MODELGROUP,
NSPROJECTID, PARTICIPATIONRATE,
PUMPINGID, SCENARIO, YEAR_FWOA
20
695,120
risk
RISK IN TERMS OF EXPECTED ANNUAL DAMAGE FOR FWOA AND FWP
MODEL RUNS FOR SR PROJECTS
ASSETTYPE, COMMUNITYID, DATE,
FRAGILITYSCENARIO, MODELGROUP,
PROJECTID, PUMPINGID, SCENARIO,
YEAR_FWOA
19
310,860
water_percentage
ANNUAL TIMESERIES REPRESENTING THE PERCENTAGE OF A CLARA
GRID CELL THAT IS COVERED IN WATER
DATE, MODELGROUP, POINTID, SCENARIO,
YEAR_FWOA
8
126,174
2023 COASTAL MASTER PLAN. PDD Documentation 29
CATEGORY
TABLE NAME
DESCRIPTION
PRIMARY KEY
NUMBER OF
COLUMNS
NUMBER OF
ROWS
ARCHIVED
DATA
community_ids
DEFINES THE ORIGINAL LIST OF COMMUNITIES AND THEIR METADATA,
SUCH AS NAME AND PARISH LOCATION; REPLACED WITH
PDD.COMMUNITYDEFINITION
MPCOMMUNITYID
9
473
damage_original
SAME AS DAMAGE, BUT LINKED TO MPCOMMUNITYID RATHER THAN
COMMUNITYID
ASSETTYPE, DATE, FRAGILITYSCENARIO,
MODELGROUP, MPCOMMUNITYID, PROJECTID,
PUMPINGID, RETURNPERIOD, SCENARIO,
YEAR_FWOA
15
977,760
exposure_original
SAME AS EXPOSURE, BUT LINKED TO MPCOMMUNITYID RATHER THAN
COMMUNITYID
ASSETTYPE, DATE, FRAGILITYSCENARIO,
MODELGROUP, MPCOMMUNITYID, PROJECTID,
PUMPINGID, RETURNPERIOD, SCENARIO,
YEAR_FWOA
15
1,942,200
nsattributes_original
SAME AS NSATTRIBUTES, BUT LINKED TO MPCOMMUNITYID RATHER
THAN COMMUNITYID
ASSETTYPE, MPCOMMUNITYID, NSPROJECTID,
PARTICIPATIONRATE
10
52,380
nsrisk_original
SAME AS NSRISK, BUT LINKED TO MPCOMMUNITYID RATHER THAN
COMMUNITYID
ASSETTYPE, FRAGILITYSCENARIO,
MODELGROUP, MPCOMMUNITYID,
NSPROJECTID, PARTICIPATIONRATE,
PUMPINGID, SCENARIO, YEAR_FWOA
20
314,280
project_community_link
LINKS EACH PROJECT TO ONE OR MANY ARCHIVED COMMUNITIES.
MPCOMMUNITYID, PROJECTID
3
432
risk_original
SAME AS RISK, BUT LINKED TO MPCOMMUNITYID RATHER THAN
COMMUNITYID
ASSETTYPE, DATE, FRAGILITYSCENARIO,
MODELGROUP, MPCOMMUNITYID, PROJECTID,
PUMPINGID, SCENARIO, YEAR_FWOA
19
1,353,150
temporary_community_link
LINKS THE UPDATED COMMUNITYIDS WITH THE ARCHIVED
MPCOMMUNITYIDS, USED IN EARLY ITERATIONS OF PROJECT FACT
SHEETS
3
397
2023 COASTAL MASTER PLAN. PDD Documentation 30
6.0
PT SCHEMA
Data in the pt schema falls into two general categories, shown below and discussed in greater detail
throughout this section. Table 6 provides a summary of all database tables in the pt schema and
descriptions of all table fields are available in Supplemental Material F6.1:
PDD Data Model Excel
Workbook
.
1.
Direct PT Outputs. Data output from PT used to defined project costs and benefits.
2.
Post-Processed PT Outputs. Data output from PT that is post-processed specifically
for use in the master plan fact sheets.
The Planning Tool uses direct outputs from the PCT, ICM, and CLARA models to perform a cost-benefit
analysis across a variety of metrics to prioritize candidate projects for selection in the master plan.
Data stored in the pt schema of the PDD is a small subset of the Planning Tool outputs, specifically
used to report project-level benefits and costs. The Planning Tool may determine that multiple borrow
sources are required to construct MC Elements based on sediment availability, which may impact the
cost of a project. Additionally, the Planning Tool interpolates land area benefits for restoration projects
over two distinct time horizons: across the construction duration of a project and across the time
difference between a project whose Elements are constructed in parallel compared to being
constructed in a serial manner. More information about the Planning Tool and its processes can be
found in Appendix G: Decision-Making (Wilson et al., 2023).
2023 COASTAL MASTER PLAN. PDD Documentation 31
Table 6. Tables in the pt Schema
CATEGORY
TABLE NAME
DESCRIPTION
PRIMARY KEY
NUMBER OF
COLUMNS
NUMBER OF
ROWS
DIRECT PT
OUTPUT
TABLES
project_borrow_volume
ESTIMATED VOLUME OF SEDIMENT THAT EACH MC ELEMENT IS PULLING FROM EACH
RELEVANT BORROW SOURCE
DATE, PROJECTBORROWVOLUMEUID
9
18,110
restoration_adjusted_benefit
INTERPOLATED LAND AREA BENEFITS FOR ALL RESTORATION PROJECTS. BENEFITS
ARE INTERPOLATED DURING THE CONSTRUCTION DURATION AND ADJUSTED BY A
SHALLOW-OPEN WATER FACTOR TO ACCOUNT FOR PARALLEL RATHER THAN SERIAL
CONSTRUCTION OF ELEMENTS WITHIN A PROJECT
DATE, RESTORATIONADJUSTEDBENEFITUID
11
47,434
restoration_project_benefit
INTERPOLATED LAND AREA BENEFITS FOR EACH RESTORATION PROJECT IN EACH
PLANNING TOOL ALTERNATIVE.
DATE, RESTORATIONPROJECTBENEFITUID
12
1,556,508
restoration_project_cost
ESTIMATED COSTS FOR EACH RESTORATION PROJECT IN EACH PLANNING TOOL
ALTERNATIVE. COSTS ACCOUNT FOR ELEMENTS ASSIGNED TO MULTIPLE BORROW
SOURCES.
DATE, RESTORATIONPROJECTCOSTUID
8
21,646
risk_project_benefit
ESTIMATED BENEFITS IN TERMS OF EAD AND EASD FOR EACH SR PROJECT IN EACH
PLANNING TOOL ALTERNATIVE
RISKPROJECTBENEFITUID
13
2,073,776
risk_project_cost
ESTIMATED COSTS FOR EACH SR PROJECT IN EACH PLANNING TOOL ALTERNATIVE.
RISKPROJECTCOSTUID
9
54,584
POST-
PROCESSED
PT OUTPUT
TABLES
project_benefits_summary
SUMMARY OF PROJECT BENEFITS SPECIFICALLY FORMATTED FOR USE IN PROJECT
FACT SHEETS. DATA CREATED BY SCRIPT USED TO GENERATE LAND AREA GRAPHICS
FOR THE PROJECT FACT SHEETS.
DATE, MODELGROUP, PROJECTID, SCENARIO
11
296
2023 COASTAL MASTER PLAN. PDD Documentation 32
7.0
DAP SCHEMA
In addition to the Master Plan Data Viewer, CPRA developed a Master Plan Data Access Portal
(MPDAP) for users to view and download more detailed model outputs. These outputs include
timeseries data for a variety of variables from the ICM, CLARA, and ADCIRC models (Table 7) at various
spatial scales (Table 8) and time scales (decadal, annual, or daily). Views were developed and stored
in the dap schema for the MPDAP API to read. Views are summarized in Table 9 below.
Table 7. Metric definitions
VARIABLE
DEFINITION
UNIT
DAMAGE
DAMAGE BY AEP
DOLLARS
DEPTH
WATER DEPTH
M
EAD
EXPECTED ANNUAL DAMAGE
DOLLARS
EAD_NS
EXPECTED ANNUAL DAMAGE WITH NONSTRUCTURAL
PROJECTS IMPLEMENTED
DOLLARS
EADSTR
EXPECTED ANNUAL STRUCTURAL DAMAGE
DOLLARS
EADSTR_NS
EXPECTED ANNUAL STRUCTURAL DAMAGE WITH
NONSTRUCTURAL PROJECTS IMPLEMENTED
DOLLARS
EASD
EXPECTED ANNUAL NUMBER OF STRUCTURES DAMAGED
COUNT
EASD_NS
EXPECTED ANNUAL NUMBER OF STRUCTURES DAMAGED WITH
NONSTRUCTURAL PROJECTS IMPLEMENTED
COUNT
ELEVATION
WATER SURFACE ELEVATION BASED ON AEP
M
ELEVATION_STORM
WATER SURFACE ELEVATION BASED ON SPECIFIC STORM
EVENTS
M
EXPOSURE
STRUCTURES EXPECTED TO EXPERIENCE FLOODING
COUNT
EXPOSURE_CI
CRITICAL INFRASTRUCTURE EXPECTED TO EXPERIENCE
FLOODING
COUNT
2023 COASTAL MASTER PLAN. PDD Documentation 33
VARIABLE
DEFINITION
UNIT
EXPOSURE_HP
HISTORICAL PROPERTIES EXPECTED TO EXPERIENCE
FLOODING
COUNT
FFIPS
FORESTED, FRESH, INTERMEDIATE, BRACKISH OR SALINE
SCORE
UNITLESS
GROUND_ELEVATION
MEDIAN GROUND ELEVATION
M
HSI
HABITAT SUITABILITY INDEX
UNITLESS
LND
LAND AREA (INCLUDING FLOTANT MARSH AND BAREGROUND)
M
2
LND_ID
LANDTYPE ID
UNITLESS
MNRL_ACCR
MINERAL ACCRETION
CM
MNRL_DEP
MINERAL DEPOSITION
G/CM^2-YR
ORG_ACCR
ORGANIC ACCRETION
CM
ORG_ACCU
ORGANIC ACCUMULATION
G/CM^2-YR
POPULATION
US CENSUS PPOPULATION ESTIMATE
COUNT
SAL
SALINITY
PPT
SAL2WKMAX
SALINITY (2 WEEK MAX)
PPT
STG
MEAN WATER LEVEL
M
SUBSI_DEEP
DEEP SUBSIDENCE
MM/YR
SUBSI_SHALLOW
SHALLOW SUBSIDENCE
MM/YR
TMP
TEMPERATURE
⁰
C
TRG
TIDAL RANGE
M
TSS
TOTAL SUSPENDED SOLIDS
MG / L
VEG
AREA BY VEGETATION TYPE
M
2
2023 COASTAL MASTER PLAN. PDD Documentation 34
VARIABLE
DEFINITION
UNIT
WAVE
WAVE HEIGHT BASED ON AEP
M
WAVE_STORM
WAVE HEIGHT BASED ON SPECIFIC STORM EVENTS
M
Table 8. Timeseries data outputs
GEOGRAPHY
DEFINITION
COUNT
EXP
EXTRACTION POINT
2,941
CGRID
CLARA GRID
126,174
COMM
CLARA COMMUNITY
314
COMP
HYDRO COMPARTMENT
1,787
ECOR
ECOREGION
28
PARISH
PARISH
67
BG
CENSUS BLOCK GROUP
3,741
2023 COASTAL MASTER PLAN. PDD Documentation 35
Table 9. Timeseries data for dap
SCHEMA
GEOGRAPHY
TIME UNIT
VARIABLE
FULL NAME
SOURCE TABLE
CLARA
BG
DECADAL
POPULATION
DAP.VW_CLARA_BG_DECADAL_POPULATION
POPULATION_PROJECTIONS_CENSUS_BLOCKGROUP
CLARA
CGRID
DECADAL
DEPTH
DAP.VW_CLARA_CGRID_DECADAL_DEPTH
FLOOD_DEPTHS
CLARA
CGRID
DECADAL
GROUND_ELEVATION
DAP.VW_CLARA_CGRID_DECADAL_GROUND_ELEVATION
MEDIAN_GROUND_ELEVATION
CLARA
COMM
DECADAL
DAMAGE
DAP.VW_CLARA_COMM_DECADAL_DAMAGE
DAMAGE
CLARA
COMM
DECADAL
EAD
DAP.VW_CLARA_COMM_DECADAL_EAD
RISK
CLARA
COMM
DECADAL
EAD_NS
DAP.VW_CLARA_COMM_DECADAL_EAD_NS
NSRISK
CLARA
COMM
DECADAL
EADSTR
DAP.VW_CLARA_COMM_DECADAL_EADSTR
RISK
CLARA
COMM
DECADAL
EADSTR_NS
DAP.VW_CLARA_COMM_DECADAL_EADSTR_NS
NSRISK
CLARA
COMM
DECADAL
EASD
DAP.VW_CLARA_COMM_DECADAL_EASD
RISK
CLARA
COMM
DECADAL
EASD_NS
DAP.VW_CLARA_COMM_DECADAL_EASD_NS
NSRISK
CLARA
COMM
DECADAL
EXPOSURE
DAP.VW_CLARA_COMM_DECADAL_EXPOSURE
EXPOSURE
CLARA
COMM
DECADAL
EXPOSURE_CI
DAP.VW_CLARA_COMM_DECADAL_EXPOSURE_CI
EXPOSURE_CRITICAL_INFRASTRUCTURE
CLARA
COMM
DECADAL
EXPOSURE_HP
DAP.VW_CLARA_COMM_DECADAL_EXPOSURE_HP
EXPOSURE_HISTORIC_PROPERITES
CLARA
COMP
DECADAL
ELEVATION
DAP.VW_CLARA_COMP_DECADAL_ELEVATION
FLOOD_ELEVATIONS_ICM
CLARA
COMP
DECADAL
ELEVATION_STORM
DAP.VW_CLARA_COMP_DECADAL_ELEVATION_STORM
FLOOD_ELEVATIONS_ICM_STORM
CLARA
COMP
DECADAL
WAVE
DAP.VW_CLARA_COMP_DECADAL_WAVE
FLOOD_ELEVATIONS_ICM
CLARA
COMP
DECADAL
WAVE_STORM
DAP.VW_CLARA_COMP_DECADAL_WAVE_STORM
FLOOD_ELEVATIONS_ICM_STORM
CLARA
PARISH
DECADAL
POPULATION
DAP.VW_CLARA_PARISH_DECADAL_POPULATION
POPULATION_PROJECTIONS
ICM
COMP
ANNUAL
LND
DAP.VW_ICM_COMP_ANNUAL_LND
HYDRO_OUTPUT_ANNUAL
2023 COASTAL MASTER PLAN. PDD Documentation 36
SCHEMA
GEOGRAPHY
TIME UNIT
VARIABLE
FULL NAME
SOURCE TABLE
ICM
COMP
ANNUAL
SAL
DAP.VW_ICM_COMP_ANNUAL_SAL
HYDRO_OUTPUT_ANNUAL
ICM
COMP
ANNUAL
SAL_2WKMAX
DAP.VW_ICM_COMP_ANNUAL_SAL_2WKMAX
HYDRO_OUTPUT_ANNUAL
ICM
COMP
ANNUAL
STG
DAP.VW_ICM_COMP_ANNUAL_STG
HYDRO_OUTPUT_ANNUAL
ICM
COMP
ANNUAL
TMP
DAP.VW_ICM_COMP_ANNUAL_TMP
HYDRO_OUTPUT_ANNUAL
ICM
COMP
ANNUAL
TSS
DAP.VW_ICM_COMP_ANNUAL_TSS
HYDRO_OUTPUT_ANNUAL
ICM
COMP
DAILY
SAL
DAP.VW_ICM_COMP_DAILY_SAL
HYDRO_OUTPUT_DAILY
ICM
COMP
DAILY
STG
DAP.VW_ICM_COMP_DAILY_STG
HYDRO_OUTPUT_DAILY
ICM
COMP
DAILY
TMP
DAP.VW_ICM_COMP_DAILY_TMP
HYDRO_OUTPUT_DAILY
ICM
COMP
DAILY
TRG
DAP.VW_ICM_COMP_DAILY_TRG
HYDRO_OUTPUT_DAILY
ICM
COMP
DAILY
TSS
DAP.VW_ICM_COMP_DAILY_TSS
HYDRO_OUTPUT_DAILY
ICM
ECOR
ANNUAL
HSI
DAP.VW_ICM_ECOR_ANNUAL_HSI
HSI
ICM
ECOR
ANNUAL
LND
DAP.VW_ICM_ECOR_ANNUAL_LND
LAND_VEG
ICM
ECOR
ANNUAL
VEG
DAP.VW_ICM_ECOR_ANNUAL_VEG
LAND_VEG
ICM
EXP
ANNUAL
DEPTH
DAP.VW_ICM_EXP_ANNUAL_DEPTH
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
FFIBS
DAP.VW_ICM_EXP_ANNUAL_FFIBS
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
GROUND_ELEVATION
DAP.VW_ICM_EXP_ANNUAL_GROUND_ELEVATION
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
LND_ID
DAP.VW_ICM_EXP_ANNUAL_LND_ID
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
MNRL_ACCR
DAP.VW_ICM_EXP_ANNUAL_MNRL_ACCR
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
MNRL_DEP
DAP.VW_ICM_EXP_ANNUAL_MNRL_DEP
GEOMORPH_OUTPUT_EXP_ANNUAL
2023 COASTAL MASTER PLAN. PDD Documentation 37
SCHEMA
GEOGRAPHY
TIME UNIT
VARIABLE
FULL NAME
SOURCE TABLE
ICM
EXP
ANNUAL
ORG_ACCR
DAP.VW_ICM_EXP_ANNUAL_ORG_ACCR
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
ORG_ACCU
DAP.VW_ICM_EXP_ANNUAL_ORG_ACCU
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
SAL
DAP.VW_ICM_EXP_ANNUAL_SAL
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
SAL_2WKMAX
DAP.VW_ICM_EXP_ANNUAL_SAL_2WKMAX
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
STG
DAP.VW_ICM_EXP_ANNUAL_STG
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
SUBSI_DEEP
DAP.VW_ICM_EXP_ANNUAL_SUBSI_DEEP
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
SUBSI_SHALLOW
DAP.VW_ICM_EXP_ANNUAL_SUBSI_SHALLOW
GEOMORPH_OUTPUT_EXP_ANNUAL
ICM
EXP
ANNUAL
TRG
DAP.VW_ICM_EXP_ANNUAL_TRG
GEOMORPH_OUTPUT_EXP_ANNUAL
2023 COASTAL MASTER PLAN. PDD Documentation 38
8.0
PDG STRUCTURE
The PDG and Mapping PDG contain geospatial data required to support project definition, PCT cost
estimation, and communication of project details to the public. Feature classes within the PDG are
listed in Table 10, and feature classes that are also present in the Mapping PDG are denoted with an
asterisk (*). Each Element with a corresponding geospatial footprint contains one record in either the
Points, Lines, or Polygons feature class in the PDG; however, if an Element is linked to multiple
Projects in the ElementAssignment table in the pct schema, multiple records for that Element exist in
the corresponding feature class in the Mapping PDG. Additionally, feature classes in the PDG contain
attributes at the Element level, while those in the Mapping PDG contain additional attributes at the
project level. Element-level attributes are common across the Points, Lines, Polygons, and
Polygons_cells feature classes. Additional fields for Polygons_cells, Lines and ElementPath feature
classes are detailed in Supplemental Material F6.1:
PDD Data Model Excel Workbook
. Element feature
classes in the Mapping PDG contain additional fields as shown in Supplemental Material F6.1. Default
GIS fields (ObjectID, Shape, Shape_Length, and Shape_Area) are present in all feature classes but are
not included in Supplemental Material F6.1.
Attributes are linked to the PDD using the LegacyElementNumber (i.e., ElementID) as primary keys.
The PDD remains the source of truth for attributes that are populated from the PDD, as they are only
included as fields in PDG feature classes as references to facilitate mapping and GIS tool calculations.
These attributes are populated with data from the PDD after updates are made to the PDD or PCT, as
described in Attachment F7: Project Costing Tool Documentation (Sprague, 2023b). Conversely, some
fields are only defined in the PDG and are used solely to facilitate GIS tool calculations.
Table 10. PDG Structure
FEATURE CLASS
DESCRIPTION
POINTS*
MULTIPOINT FEATURES OF PROPOSED ELEMENTS, SUCH AS GATES OR
PUMPS
LINES*
LINE FEATURES OF PROPOSED ELEMENTS, SUCH AS STONE ARMOR OF
SHORELINE PROTECTION OR LEVEE ALIGNMENTS OF STRUCTURAL RISK
REDUCTION
POLYGONS*
POLYGON FEATURES OF PROPOSED MC ELEMENTS
POLYGONS_CELLS
POLYGON FEATURES OF PROPOSED MC 2,000-ACRE CELLS
2023 COASTAL MASTER PLAN. PDD Documentation 39
FEATURE CLASS
DESCRIPTION
ELEMENTPATH*
LINE FEATURES REPRESENTING THE PATHS DRAWN FROM BORROW
SOURCES TO MC ELEMENTS, AS PRODUCED BY THE DREDGE MOBILIZATION
TOOL, DESCRIBED IN THE PROJECT COSTING TOOL TECHNICAL
DOCUMENTATION
ELEMENTASSIGNMENT
TABLE MIRRORING THE ELEMENTASSIGNMENT TABLE IN THE PDD, USED
TO LINK ELEMENT-LEVEL GEOSPATIAL DATA IN THE POINTS, LINES,
POLYGONS, POLYGONS_CELLS, AND ELEMENTPATH FEATURE CLASSES TO
PROJECTS AS NECESSARY
* FEATURE CLASSES THAT ARE ALSO PRESENT IN THE MAPPING PDG
2023 COASTAL MASTER PLAN. PDD Documentation 40
9.0
REFERENCES
Martin, S. (2023). 2023 Coastal Master Plan: Appendix E: Overview of Improvements to Risk Modeling.
Baton Rouge, Louisiana: Coastal Protection and Restoration Authority.
Sprague, H, Nelson, T. Weikmann, A, Norman, D, Gong, D. (2023a). 2023 Coastal Master Plan:
Attachment F1: Project Concepts. Baton Rouge, Louisiana: Coastal Protection and Restoration
Authority.
Sprague, H., Nelson, T., Weikmann, A., Gong, D., & Norman, D. (2023b). 2023 Coastal Master Plan:
Attachment F7: Project Costing Tool Documentation. Version 2. Baton Rouge, Louisiana:
Coastal Protection and Restoration Authority.
U.S. Army Corps of Engineers (2020). Civil Works Construction Cost Index System (CWCCIS). Manual
No 110-2-1304. September.
Wilson, M. T., Panis, C., Groves, D. G., Reed, D., & DeWeese, J. (2023). 2023 Coastal Master Plan:
Appendix G: Decision-Making. Version 3. (p. 16). Baton Rouge, Louisiana: Coastal Protection
and Restoration Authority.
Wilson, M. T., Fischbach, J. R., Johnson, D. R., Wang, J., Kane, P., Geldner, N., & Littman, A. (2023a).
2023 Coastal Master Plan: Attachment E3: Nonstructural Protection Evaluation Results.
Version 3. (pp. 36). Baton Rouge, Louisiana: Coastal Protection and Restoration Authority.
Wilson, M. T., Panis, C., Groves, D. G., Reed, D., & DeWeese, J. (2023b). 2023 Coastal Master Plan:
Attachment G1: Planning Tool Methods and Results. Version 2. (p. 89). Baton Rouge,
Louisiana: Coastal Protection and Restoration Authority.