# Presentation: 721616

## Turning Information into Insight:A Multi-Platform Decision Support Tool for Systems Level Management

**Turning Information into Insight:****A Multi-Platform Decision Support Tool for Systems Level Management**

**Sandia National Laboratories**
**Thomas S. Lowry**
**Vincent C. Tidwell**

- Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company,for the United States Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.

## Resource Management
Decision Making
Multi-stakeholder
Policy
Integration

**Decision Making**
**Multi-stakeholder**
**Policy**
**Integration**

**What is This About?**

## GENTLEMAN, IT APPEARS TO BE UNANIMOUS

THAT WE CANNOT AGREE
-unattributed

**THAT WE CANNOT AGREE**
***-unattributed***

**Motivation**

## Persistent conflict is becoming ‘the norm’
Conflicts occur because of:
Complexity & uncertainty in natural systems
Lack of insight of cause and effect
Conflicting interests & values
Human rationality is bounded
Favors linear/static behaviors 
Creates judgment bias 
Entrenches personal convictions

**Conflicts occur because of:**
**Complexity & uncertainty in natural systems**
**Lack of insight of cause and effect**
**Conflicting interests & values**
**Human rationality is bounded**
**Favors linear/static behaviors **
**Creates judgment bias **
**Entrenches personal convictions**

**What is the Problem?**

## Natural Resources are inherently multi-stakeholder
Perception that negotiation / change implies sacrifice
Lack of insight into the cause and effect relationships
Prevents meaningful dialogue
Prevents agreement / consensus
Lack of connection to the human element

**Natural Resources are inherently multi-stakeholder**
**Perception that negotiation / change implies sacrifice**
**Lack of insight into the cause and effect relationships**
**Prevents meaningful dialogue**
**Prevents agreement / consensus**
**Lack of connection to the human element**

**The ‘Real’ Problem**

- Global Warming

- ????

## Need Tools and Processes
Understand cause and effect
Physical systems
Human systems
Inform the decision making process
Create an environment for consensus and agreement
Open and transparent
Group learning

- Understand cause and effect
- Physical systems
- Human systems
- Inform the decision making process
- Create an environment for consensus and agreement
- Open and transparent
- Group learning

**Motivation – 30,000 ft**

*To Turn** *_*Information*_* **into** *_*Insight*_

## Understand basic behavior
Hydrology
Ecology
Economics
etc
Represent the linkages between these areas

- Collaborative Modeling

**Understand basic behavior**
**Hydrology**
**Ecology**
**Economics**
**etc**
**Represent the linkages between these areas**

**Understand institutional setting**
**Develop ways engage stakeholders**
**Build trust**

- Shared Vision Planning

**Integrated Approach**

## Information To Insight

**Means involving stakeholders in**
**Data collection and/or analysis**
**Developing cause and effect relationships**
**Technical analysis**
**Builds understanding of the system**
**Builds confidence in the analysis**
**Builds trust between stakeholders**

## Modeling
To simulate cause and effect
Stakeholder Involvement
Identify constraints
Mutual understanding
Decision Support
Quantify alternatives

**To simulate cause and effect**
**Stakeholder Involvement**
**Identify constraints**
**Mutual understanding**
**Decision Support**
**Quantify alternatives**

**Information To Insight**

## Information To Insight

**Integrates**
**Planning principles**
**Systems level analysis**
**Collaboration**
**Addresses need for broad involvement**
**Technical analysis is done collaboratively**

## Different Models, Different Answers

**Physical Process Models**
**Simple Analytical**
**Empirical**
**Complex Numerical**
**System Dynamics Models**
**Agent Based Models**

- How do we integrate different types of models into a single framework?
- How can models communicate with each other?
- How do non-modelers interact with them?
- How do we develop stakeholder metrics?
- How do we maintain transparency?
- How do we find solutions in multi-stakeholder / multi-objective problems?
- How do we make all of this useful?

## The CADRe System

- Dynamic Data Manager

- GUI

- TABU

- Impervious Cover

- Stream Buffers

- Pipe Leakage

- Min. Spring Flow

- Pumping Limits

- Drought Triggers

- Compare Results

- Add Method

- Optimization

## Important segment of the Edwards Aquifer in Central Texas - Karstic
Barton Springs is a major aesthetic feature of Austin
Popular recreation area
Home to an endangered species (salamander)
Rapidly growing urban area
Concern about growth in impervious cover over the recharge zone impacting long-term spring flow
History of community conflict
Existing MODFLOW based flow models

**Barton Springs is a major aesthetic feature of Austin**
**Popular recreation area**
**Home to an endangered species (salamander)**
**Rapidly growing urban area**
**Concern about growth in impervious cover over the recharge zone impacting long-term spring flow**
**History of community conflict**
**Existing MODFLOW based flow models**

**Barton Springs Case Study**

## Barton Springs

## Barton Springs

**Barton Springs**

- Contributing Zone

- Recharge Zone

- Confined Zone

## Barton Springs

**Barton Springs**

## Stakeholder Involvement

- _Benefits_

- _Consequences_

- Historical

- Present

- Future

**Stakeholder Involvement**

- Historical Trend

- Projected Outcomes

- Narrative Elicitation

**Notes:**
HOW is narrative elicitation incorporated?
Through informal discussion/survey techniques each stakeholder is asked to define key influences, as they perceive them, on the conflict situation.
In particular researchers are listening for:
Historical trend analysis – how does the stakeholder perceive the nature of change to date
Projected future outcomes – what is the best/worst of all possible outcomes in the future
Controlling factors – what are the key decisions or controls that can influence which future outcome occurs
Tasks –  what are the things that you, or a community, can do to change situation and achieve the best outcome
Measures – if the community takes the appropriate actions, how will you be able to measure/see when you’ve reached an improved state 
Surprisingly, the narrative process tends to open dialogue. People are interested in sharing the why, how, and what they see about a particular situation. For a scientist, this changes what we model and how we present our results. For a policy maker, or facilitator for conflict resolution, this process evokes the key concerns and motivations behind the conflictive situation and enables better dialogue and discussion to possibly promote change.
What we are doing with narrative is not actually far removed from the procedure used in Ensemble Streamflow Prediction
The major distinction is that our historic data set and probability functions are defined by individual perceptions

## Barton Springs

**Controlling factors**
**what are the key decisions or controls that can influence which future outcome occurs**
**Tasks**
**what are the things that a community can do to change the situation and achieve the ‘best’ outcome**
**Measures**
**if the community takes the appropriate actions, how will you be able to measure/see when you’ve reached an improved state **

## Modeling Tasks

**Groundwater flow**
**Spring flow**
**Drawdown**
**Saturated thickness**
**Drought Triggers**
**Changes in recharge**
**Urban sprawl**

**Quick execution**
**Real-time feedback**

## System Dynamics

- Barton Springs Water Conservation District
- Groundwater Availability Model (GAM)

## System Dynamics - Calibration

## Multiple Objectives

**Preserve flow in Barton Springs**
**Protect endangered species**
**Maximize pumping**
**Maximize reliability**
**Maximize economic benefit**
**Minimize environmental impact**
**Minimize impact on daily life**

## Decision Support

**TABU Search**
**Allow users to specify objectives, such as:**
**Minimize sprawl**
**Maximize spring flow**
**Minimize droughts**
**TABU Search uses deterministic algorithm to find ‘optimal’ policy settings to achieve objectives**
**Create new, un-intuitive solutions**

## The CADRe System

**Integrated ‘software wrapper’**
**Links spatially explicit, high-fidelity models to systems based analysis**
**Reduces redundancy and duplicate effort**
**Provides interface for rapid dispute resolution w/in a stakeholder process**
**Allows for multi-attribute / multi-objective optimization**
**Allows for ranking of scenarios based on user preferences**

## The CADRe System

- Dynamic Data Manager

- GUI

- TABU

- Impervious Cover

- Stream Buffers

- Pipe Leakage

- Min. Spring Flow

- Pumping Limits

- Drought Triggers

- Compare Results

- Add Method

- Optimization

- SD Model

- PP Model

- Adapter

- Adapter

## DEMONSTRATION

## Benefits

**SD model executes much faster than the PP model**
**Scenario testing**
**Stakeholder education**
**Allows for connecting spatially explicit physical processes to other systems**
**Provides a single user interface that works with both types of models**
**Provides optimization and ranking of different scenarios based on user preferences**
**Modular approach allows for application to different types of problems**

## SWAQ

**National Science and Technology Council**
**Committee on Environment and Natural Resources**
_**S**_**ub-committee on **_**W**_**ater **_**A**_**vailability and **_**Q**_**uantity**
**Interagency Development of a SWAQ-endorsed Federal Initiative**
**Initiative to develop Collaborative Tools & Processes for US Water Solutions**
**Develop and advance the integration of computer-based modeling tools within multi-stakeholder public decision processes**
**Objective, Establish Federal Funding to:**
***Review current uses***** and programs on the use of “collaborative decision support tools” in water problems **
***Develop a framework for evaluation***** of the effectiveness of combinations of computer tools and collaborative interventions for a range of water problems and settings**
***Initiate targeted “pilot” or “demonstration” projects***** to develop basic principles and best practices**
***Develop an interagency focal point***** to ****serve as an information clearinghouse to provide unified direction, integration & consistency**

## Acknowledgements

**Sandia National Laboratories**
**Thomas S. Lowry**
**Vincent C. Tidwell**
**Suzanne Pierce**
**Mona Aragon**
**University of Texas**
**John M. Sharp**
**Marcel Dulay**
**David Eaton**
**Michael Ciarleglio**
**Aliza Gold**
**Roy Jenevein**
**A host of others.....**
**William Cain**

- A Cast of Thousands

## THANK YOU

- cadre.sandia.gov

- www.iwr.usace.army.mil/cadre/