Lecture 9Constructing a Coastal Data Model for Nearshore Puget

Sound: A GIS Data, Information, and Knowledge Community

Perspectiveand

Ideas for Geog 462 Final Project

Learning Objectives 9.1 What’s the motivation for a

coastal data model? 9.2 What was the information

(knowledge) integration process? 9.3 What are the results? 9.4 What are the valuable

conclusions and directions?

General Motivation… CZM and GIS

Coastal zone management (CZM) requires robust geospatial information to be effective Particularly for nearshore areas… land

development impacts surface water runoff in watersheds that drain into coastal waters

CZM is a multi-stakeholder process that can make use of geographic information systems (GIS) Using GIS can help develop a shared insight

about problems, challenges and solutions about how to manage coastal resources

Community Motivation… Revitalizing Puget Sound

Puget Sound is the 2nd largest estuary in the U.S. In 2007, WA State Governor Gregoire established

the Puget Sound Partnership (PSP) as a state agency. www.psp.wa.gov

PSP coordinates the efforts of citizens, governments, tribes, scientists, businesses and nonprofits to set priorities, implement a regional recovery plan and ensure accountability for results. For more information, go to

Overall revitalization activity expected to last until 2020 (and now beyond), costing billions of dollars.

2014/2015 Action Agenda and 2016 Agenda Update

2014/2015 Action Agenda update

http://www.psp.wa.gov/action_agenda_center.php Prevent pollution from urban stormwater runoff. Polluted runoff

from roads, roofs, parking lots, and other paved areas is the biggest threat to Puget Sound’s water quality. Although we have many tools and technologies for reducing stormwater pollution, we need to make much fuller use of them if we are to stop contamination from flowing into the Sound.

Protect and restore habitat. Restoring damaged shorelines and protecting salmon habitat along the many rivers and streams that flow into Puget Sound is necessary to save salmon and honor tribal treaty rights. We must stop destroying habitat, protect what we have left, and substantially restore the critical habitats that we have lost.

Restore and re-open shellfish beds. Shellfish harvesting is a major Puget Sound industry, and a tribal treaty right. Both are threatened by pollution that has closed more than 7,000 acres of Puget Sound beaches. Shellfish health begins on land, through reduction of pollution from rural and agricultural lands and maintenance and repair of failing septic tanks.

Focusing the Motivation…Linking Research, Teaching, Service Learning

Puget Sound CZM is the motivating substantive theme in Geography 462/562 Coastal GIS.

Geog 462/562 participation is viewed as a core activity within a “learning community”; a learning community as a collection of people interested in learning about coastal GIS topics

Learning about GIS data can enhance understanding of the complexities of the fish and plant life and how human activities influence nearshore habitat.

Learn about the “coastal GIS data community”. Data community – collection of people and

organizations who “share interests” in a data theme and negotiate meaning & value about the data theme when putting it to use in theory and practice

Puget Sound Nearshore basis for data community

…area of marine and estuarine shoreline extending approximately 2,500 miles from the Canadian border, throughout Puget Sound and out the Strait of Juan de Fuca to Neah Bay.

Nearshore – 2500 miles of shore

What is at issue with the PS Nearshore?

The integrity of the nearshore ecosystem is in jeopardy.

Nine of the ten species listed as endangered or threatened within the Puget Sound region inhabit the nearshore.

Pollution in parts of Puget Sound has caused lesions and tumors in flatfish that are eaten by eagles, seals, birds, and porpoises.

Urban and suburban developments along the Puget Sound coast have transformed the shoreline (areas), including (fresh and salt water) estuarine and nearshore habitats.

Changes in the physical processes include limiting food and nutrient sources for marine life, deteriorating beach sediment movement, and altering the flows of surface and groundwater. Let’s look at a depiction of that situation…

Data modeling assists learning about CZM and GIS

Conceptual, logical, physical data modeling is useful for learning about how to represent coastal features associated with water flow from watersheds into estuarine ecosystems – a core issue in previous described problems

Coastal data model can address many of Puget Sound Partnership concerns

Developing a data model… Everyone has a mental model of the

problem Data models help scaffold our mental models

Fully articulated data model consists of three components (Codd 1981): geospatial constructs for structuring data, operations that can be performed on those

structures to derive information from the data, and

rules for maintaining the integrity of data.

Developing a Coastal Data Model through information integration Goal: Develop an overall “conceptual data

schema” - a collection of feature classes and potential relationships that form the core of a PS nearshore database design

Information integration involves identifying, comparing, contrasting, synthesizing feature classes

Three steps in the method used… each used a different source of “community

knowledge” knowledge to perform integration analysis

Integration Analysis - Three Steps

Step 1 - integrate watershed data (ArcHydro Data Model) and marine data (ArcMarine Data Model)

Step 2 - identify coastal feature classes described within a textbook reader about coastal zone management and add them to the feature class list for the coastal data model.

Step 3 - use recommendations from Puget Sound Nearshore Partnership report to further contextualize the coastal data model with regard to operations

Knowledge from a different “community of practice” associated with each step together composes a diversified coastal data model

Step 1 - Using ArcHydro and ArcMarine Data Models

ArcHydro Data Model describes geospatial and temporal data about surface water resource features in watersheds (Whiteaker, Schneider, Maidment 2001)

Addresses principal water resource features on a landscape Describes how water moves from feature to feature through

multiple connective networks and channels over time ArcMarine Data Model provides integration of

important features of the ocean-marine realm, both natural and human-made (Wright 2006)

Considers how marine and coastal data can be most effectively integrated within 4D space-time based on the multidimensional and dynamic nature of ocean data and processes

Step 1 Results – Data Models(See table 1 in reading)

Geospatial Data Types ArcHydro Data Model ArcMarine Data Model

Fixed point Drainage area centroids Marker, buoy, transponder

Instantaneous point Discharge measurement, dissolved oxygen value

Raw bathymetry

Line Stream Sediment transport line

Polygon Catchment Habitat, marine boundaries

Time duration points Flow gauge Current meter

Time duration vectors Temperature at one point to temperature at another point

Algae bloom trawl

Time duration areas Water surface elevation Oil spill

Feature classes Drainage, network, channel, hydrology

Watershed, waterbody, monitoring points, streams

Step 2 - Feature Classes from a Coastal Zone Management

Book Collection of feature classes and several

attributes compiled from a text reader about coastal zone management

Another form of expert knowledge (Coastal Zone Management - Beatley, Brower, and Schwab 2002 published by Island Press)

Authors of a textbook are themselves experts in a topic, and that topic is peer reviewed by other experts familiar with the topic

Step 2 Results - CZM feature classes

(see table 2 in reading)• Barrier Islands• Estuaries• Coastal Marshes• Coral Reefs• Rocky Shores• Bluffs• Tides (dynamic, temporal)• Currents• Wind (Currents/Patterns)• Erosion and Accretion• Pollution and Toxic Contaminants• Wetlands (Protected/Unprotected)• Habitats – endangered species

• Land use and zoning of areas• Building code• Soil Composition/make-up• Catch Basins/ catchments• Watershed areas• Streams/Rivers/Water Flow• Ports – Freight and Passenger• Ferry Systems/Water Taxi• Continental Shelf/Slope• Water Depth/Slope• Land Cover – (e.g. Beach/Dunes)• Present Buildings/Structures• Infrastructure (on land, underneath)

Step 3Puget Sound Nearshore

Partnership On October 13th, 2006, the Puget Sound

Partnership executive committee released recommendations for focusing efforts in the Puget Sound area

Recommendations are useful for… a) identifying fundamental theme for improving the health

of Puget Sound, b) identifying features that can corroborate the list

identified from reviewing Beatley, Brower, and Schwab (2002) as well as those in the integration of the ArcHydro and ArcMarine Data Models, and

c) identifying primary and secondary processes that encourage various GIS data analyses in which we derive information as a basis for decision support to restore the Sound

Step 3 Results – Processes(see table 3 in reading;

possible geog 462/562 final project topics)

Protect existing habitat and prevent further losses Restore amount and quality of habitat; reduce fragmentation Reduce toxics entering the Sound Reduce pollution from human and animal wastes into the Sound Promote and support new and existing treatment facilities Improve water quality and habitat; managing stormwater runoff Identify, prioritize, and implement retrofits where stormwater

runoff is causing environmental harm; mitigation strategies Provide water for people, fish and wildlife, and the environment Protect ecosystem biodiversity and recover imperiled species Implement existing recovery plans and create recovery

programs for species at risk of extinction lacking current recovery plans

Overall Results Feature classes identified in steps 1, 2, and 3

are collected together in Table 4 in reading. The feature classes are grouped into feature

datasets We identify the most likely geospatial data

type to act as a database representation Not all features would be used in all

applications, so it is important to identify which feature classes and processes are to be manipulated by what data operations

Coastal Data Model Features and Geospatial Data Construct

Types(abbreviated Table 4)

Features/Process Geospatial Data Construct TypesRaster Point Line Polygon Network

Physical/Natural Shoreline

Human Infrastructure/Impact

Dynamic Natural Phenomena

Water and Water Bodies

Underwater Topography

But, data and operations are needed to generate information

Coastal Data Model Operations lead to Applications -

1 Interaction of particular spaces, for example: dairy

farms and urban sites, or tsunami impacts upon various types of soil composition related to land cover and erosion hazards

Operations: Buffering, flow accumulation, overlays

These are basic interaction operations which can help to show what kinds of areas may be affecting one another. Isolating areas that may have adverse externalities or affects on one another. Some critical areas (receptors) are vulnerable to pollution (stressors or hazards)

Coastal Data Model Operations lead to Applications -

2 Pollution runoff/stormwater runoff, for example: finding

where it occurs by identifying critical areas of concern

Operations: Hydrology operations for flow, identification of spaces

The hydrology tools (fill, flow direction, flow accumulation, basin tool, and watershed tool) allow for showing how and where water and other pollutants would flow from one area to another. This is useful again in establishing where and how runoff occurs, and finding areas where new infrastructure for this type of runoff needs to be placed and where mitigation retrofits need to be applied to already present infrastructure. This is a serious goal for the Puget Sound Partnership as detailed in their draft recommendations.

Coastal Data Model Operations lead to Applications -

3 Tidal Currents and pollution interaction with tides,

for example: dump points of sewage and how it moves with these tides in the water

Operations: Flow direction/accumulation (hydrology), movement on top of water

This application examines how water mixes (or how pollution interacts in currents and tides when entering bodies of water) can be done with certain water flow/accumulation operations, as well as digitizing and creating new shapefiles for directionally of tides/currents. Understanding how water interacts with itself is important to understand how different substances of pollution would move within it and affect specific zones.

Coastal Data Model Operations lead to

Applications - 4 Migratory animal movement from ecosystem to

ecosystem, for example: Birds, Whales, Salmon, or Turtles

Operations: Network Analyst tools

The construction and mapping of networks can establish areas through which migratory migratory animals pass. It can characterize the distances in which they travel and the times in which they arrive in those areas and the total time in takes them to move from area to area. This application would examine the overall ecosystem interaction.

Coastal Data Model Operations lead to Applications -

5 Transportation interaction with the coast, for

example: Ferry systems/road systems for automobiles

Operations: Network Analyst tools, Flow direction and Accumulation (Hydrology)

As with migratory animals, these networks will allow us to point to areas of concern that these transportation system may pass through affecting the coast. These are strongly linked to discovering the pollution that comes from these transportation systems, as we can use traffic counts and vehicle miles traveled on particular road segments (or travel segments with say the Ferry system) to show how much pollution is coming from road segments and also where mitigation retrofits need to be added.

Conclusions about Data Models

Data models enable and limit GIS applications for data communities of practice (that is groups of people using GIS data in various ways)

Integrating perspectives from different communities of knowledge practice (per the three integration steps) results in a diversified data model

Participatory GIS-based data model development forms the foundation of community-based analytic-deliberative decision processes that draw together diverse stakeholder, technical specialist (scientist), and decision maker perspectives

Prospects for Research, Education and Outreach Service in the

Community Educational activity is part of exploratory

work on multi-stakeholder participatory modeling that addresses coastal environmental improvement programming as a social (community) learning process.

What is the opportunity for social learning about complex problems when that learning is set within an engaging situation like “revitalizing Puget Sound”? … such engagement is a basis of enhancing

participatory governance with the use of GIS in democratic settings