OBJECTIVES

The main objective of this project is the development of a simplified but efficient early warning model for flood events, at worldwide extent. This system was created to give an alert in case of heavy rainfalls around the world which can be used by humanitarian assistance organizations (like the World Food Programme) to evaluate the event and understand the potentially floodable areas in places where their assistance is needed.

EXPECTED OUTPUTS The main outputs consist of thematic maps that show the areas in which heavy rainfalls are occurring. River basins are shown in different colors that indicate the level of criticality, according to the severity of rainfalls. The maps are delivered through a dynamic website powered by a geonetwork node.

METHODOLOGY This completely automated system runs at river basin scale and uses 3B42 and 3B42RT satellite rainfall data products from Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA).

TRMM data coverage (http://disc.sci.gsfc.nasa.gov/data/datapool/TRMM_DP/01_Data_Products/).

The first step is the analysis of historical rainfall data downloaded from TRMM ftp server and stored in a data warehouse, developed in ORACLE (ITHACA’s rainfall database). The 3B42 dataset has been chosen for this kind of analysis, as it provides ten years of data (from 1998) with a temporal resolution of three hours and gridded with a resolution of

EARLY WARNING SYSTEM FOR FLOOD EVENTS

Topic Early Warning, Emergency response

Keywords Floods, Rainfall, River basins, Data Warehouse, Hydrological Analysis

Geographic extent Global extent with particular focus on World Food Programme’s areas of action

0.25°x 0.25° per cell. Rainfall information related to each single cell of 3B42 has been resampled at the resolution of a single hydrographical basin, before being loaded onto ITHACA’s database.

Stream line and drainage basin layers used for the entire analysis. The six levels of river basin data are from HYDRO1k geographic database. Rainfalls conditions are monitored at basin scale. Rainfall data from 1998 to 2007 have been used to calculate the depth-duration-frequency (DDF) curves, that allow the characterization of rainfalls for each drainage unit. In addition, a specific application calculates critical events over this set of data, comparing cumulated rainfalls with DDF curves. The final output of this procedure is the creation of a complete historical database of heavy rainfalls with global coverage and single basin resolution.

Flow chart of the Historical Analysis of DDF curves at basin scale.

The actual “Early Warning System” is based on DDF as well, but it uses real time information to monitor current rainfall conditions. Near real-time satellite rainfall data (3B42RT) were chosen for this application, which compares the real-time rainfall intensities with the curves developed by the hydrological model. The early warning tool downloads data from the 3B42RT ftp server and creates cumulates for selected durations, typical for each hydrographical basin. When these cumulates exceed the DDF curve, the system gives an alert in term of critical rainfalls for a single basin. Since lag times between heavy rainfalls and peak discharge are to be expected, the calculation of morphometric characteristics of some drainage basin, are to be taken into account. One of the fundamental parameters in hydrology is the time of concentration, which is an idealized concept defined as the time taken for a drop of water falling on the most remote point of a drainage basin to reach the outlet; this parameter allows the calculation of the lag time, that is the lag from the centroid of mass of the rainfall excess to the peak of the hydrograph (assumed to be 0.6 of the time of concentration). In other words, thanks to the lag time the system detects in advance the critical period in which rainfalls could create floods, it monitors cumulate rainfalls in this period and it detects those that exceed the DDF curve.

Examples of alert situations determined by the “Early Warning System for Flood Events”.

To run the system in real time, a grid architecture has been designed. A grid master (grid master node) is connected to the TRMM server and to the Oracle DBMS (with historical data) and the analysis procedures are delegated to others nodes. In particular the grid master node manages all the preliminary procedures of extraction and transformation from the primitive data; whereas the hydrological analysis and the related detection of critical rainfalls are delegated to grid nodes. The designed network is connected to a web server to store critical events and to publish information.

ITHACA Grid Flood architecture

Analysis of satellite imagery acquired during similar past events:

Using information on historical floods from other databases or performing ad hoc analyses, hazard maps can be associated to alerts, where floodable areas are identified. A specific algorithm has been implemented by ITHACA using MOD09 and MOD35 (from Modis Terra) to classify automatically the flooded areas during a selected period.

Simplify schema of the automatic procedure of extraction of flooded areas.

Web application:

Once they are triggered, alerts are automatically mapped and the overall situation can be visualized on the web application. The web interface, which was developed by extending OpenLayers functionalities, has the aim to offer an easy access to the data and also to map and alert the basins that are potentially under emergency. The user can choose a tool to zoom to the basin level with the activation of informative layers extracted from ITHACA GSDI (Global Spatial Data Infrastructure).Another important tool allows to print maps in PDF format in a complete WYSIWYG (What You See Is What You Get) way, creating automatically a legend, a scale bar and an appropriate canvas with ITHACA’s logo and a customized title. The server side application provides the replica of the alert data from Oracle to PostgreSQL in a totally automated manner. The application layers are served using the WMS OGC standard.

WORKFLOW

Workflow of the Early Warning System for flood events.

FUTURE DEVELOPMENTS

� Collaboration with other research institutes (Dartmouth Flood Observatory, JRC) in order to share historical vector data related to floods.

� Comparison of gauged discharges as measured at ground stations with the remotely sensed rainfall values, to evaluate how discharge responds to rainfall conditions. It would allow the understanding of lag time precision between rainfall excess and peak discharge, as our system calculates it in a completely automatic way using only drainage basin morphometric parameters. In addition, the monitoring of rainfall conditions would make it possible to predict discharge behavior.

OUTPUT SAMPLES