1. Meetings 05/22/2017 Research Interests in Flooding
Helping First Responders with DS/GIS/CS to Deal with Flooding
Flood Risk Mapping (in collaboration with UT Center for Research in Water Resources)
Expert System for Flood Risk Mapping

2. 1. Predicting, Mapping, and Understanding Flooding
Research Tasks:
Predict Water Levels
Flood Risk Mapping
Early Warning System
Understand Flooding
People: Christariny Hutapea,
Yue Cao, Chong Wang, and
Yongli Zhang.
UH-DAIS

3. 2. Background: NSF Planning Proposal (Eick&Peres)
Design of a Generic Water Level Prediction and Flood Early Warning System
Overview:
Flood is the most hazardous natural disasters in the world …Consequently, many US cities developed sensor based early warning systems that collect water level and other data in real-time…One major research goal of the proposal is the development of a flood early warning system that provides the capability to predict future water levels. To accomplish this goal novel data-driven water level prediction techniques that interpolate the past into the future will be investigated, compared and fused with classical hydrological models. However, for a flood early warning system to be useful, it is critical to ensure that the needs of the stakeholders interacting with such a system are considered in the system design. Investigating the behavioral aspects and human-computer interaction aspects of stakeholders using flood warning systems is the second major research goal of this proposal. To accomplish these two goals, we plan to assemble a strong research team that consists of surface hydrologists and members of organizations, such as NOAA, that develop water level prediction models and representatives of flood control districts and emergency management departments of several US cities.
Status: Currently under review!
UH-DAIS

4. Helping First Responders with DS/GIS/CS to Deal with Flooding
How do First Responders use Flood Risk Maps? How is feedback from First Responders used to Enhance Flood Risk Maps?
What other information is important to communicate to first responders when dealing with flood events? What is the current approach communicating this information?
What role does GIS contribute play in helping first responders do deal with flood events?
Human Computer Interaction (HCI): How to present flooding related information to first responders? What formats are the best to display information? What are the best communication strategies for first responders?
Can crowd sourcing help to alleviate the effects of flooding? If yes, what should it be used for?
What is needed in the future? What should future research focus on the enhance the ‘state of the art’ of dealing with flooding?
What about planning procedure to deal with flooding events?
UH-DAIS

5. 3. Automated Flood Risk Mapping
Austin Fire
First Responder Vehicle
Flood Risk Map
Creating these maps is a lot work and requires GIS and hydrology knowledge.

6. Flood Risk Mapping Wharton County, Texas
Wharton County
Fire Chief
Wharton County
April 2016 Flooding

7. Automated Flood Risk Mapping
Hand-based
Flood Risk Maps

8. Polygon Analysis for Better Flood Risk Mapping
Flooded Areas
From Past Floods
FEMA Flood
Risk Zones
Find Correspondence
Find Agreement,
Combine, Validate
Hand Value
Multi-Contour
Maps
DEM (Digital
Elevation Maps)
HEC-RAS Generated
Polygons
Austin Fire
First Response
Vehicle Flood
Risk Map
UH-DAIS

9. Analyzing Different Polygonal Data that Describe Levels of Flood Risks
Benefits and Objectives:
Flood Risk Map Validation
Flood Risk Map Standardization
Creating Flood Risk Maps Automatically
Mapping Agreement/Disagreement with Respect to Different Flood Risk Models.
Understanding the weakness/strength of particular methods
Creating “combined” flood risk models
Dynamic Flood Risk Maps that adapt their appearance based on contextual information
UH-DAIS

10. UH-DAIS Research to Address these Problems
Computational Methods to create flood risk maps from point-wise or grid-based flood risk assessment (e.g. hand value maps or elevation maps). We investigated in the past and are currently investigating:
graph-based approaches
Continuous function based approaches
Similarity Assessment Methods to find Agreement Between Different Polygonal Flood Risk Maps
Correspondence Contouring Methods (e.g. find a sequence of elevation thresholds so that the obtained contour polygons best match with FEMA flood risk zones)
Computing Agreement Maps between Different Methods
Creating “better” flood risk maps by combining information from different sources.
UH-DAIS

11. 4. Expert Systems for Flood Risk Mapping
Local
Information
(Watersheds, Elevation Maps,…)
Expert
System
creates
User
(not an expert
in GIS and
hydrology)
Flood Risk
Mapping
Knowledge
Base

12. Backup Slides
UH-DAIS

13. 2. A Generic DAG-Based Chaining Approach for WLP
R(t),R(t-1),…(Rainfall)
W(t), W(t-1),…(Water-level)
V(t),V(t-1) (Stream Velocity)
S(t), S(t-1)… (Soil Moisture)
D(t), D(t-1),…(Discharge)
Raw Data
DAG of
Measuring Points
Prediction Scenario
Mapping Tool
currently under
development at UH
Model Execution
Framework
Data Sets
(one for each Measuring Point)
Single Target
Prediction
System
uses f2 f1 f3 f4
DAG
Models
(one for each Measuring Point)
off the shelf

14. Height Above Nearest Drainage (HAND)
developed by: UT Austin Center for Research in Water Resources
Flood
HAND
Normal

15. Texas Hand Map (7,600,000 Address Points)
237 counties mapped
16 CSEC counties geocoded
1 non-CSEC county geocoded