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

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. http://www.harriscountyfws.org/ UH-DAIS

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

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

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.

Flood Risk Mapping Wharton County, Texas http://abc13.com/news/wharton-mayor-calls-for-voluntary-evacuation/744958/ Wharton County Fire Chief Wharton County April 2016 Flooding

Automated Flood Risk Mapping Hand-based Flood Risk Maps

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

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

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

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

Backup Slides UH-DAIS

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

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

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