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Flood Risk Estimator
Enhancing capacities of flood prone communities

1. Project Title:

Enhanced capacity of flood prone communities through early warning system

2. Project Objectives:

The project aims to reduce disaster risk of the most vulnerable communities in flood prone area of district Layyah. The specific objective is to strengthen the capacity of vulnerable flood prone communities in district Layyah to understand, mitigate and respond to risk, and benefit through the use of flood Early Warning System.

3. Introduction:

Flood Modeling is the simulation of real flood events for prediction of flood water along creeks, floodplains and urban areas and estimation of the areas that can be inundate. It also helps in prediction of flood likelihood. Flood modelling is seen as an integral part of flood management. Models are used for planning and design as well as for forecasting floods so that mitigating measures can be taken in time. Decision support systems based on models are increasingly being used by engineers and scientists in flood management.
This project is a consortium of Doaba Foundation and City Pulse (Pvt.) Ltd. to develop Floodplain modeling of Indus River along district Layyah. It uses a unique approach of community based GIS and a more technical modeling processes to estimate elements at risk at a particular water discharge level. Pages ahead give details of processes involved in this task.

4. Brief Methodology :

This section describes the process involved in flood plain modeling using GIS. Details of each step are given below:

  • Acquisition of remotely sensed data
  • Field data collection
  • Development of vectors layers for elements at risk and critical facilities
  • Data preparation and modeling in HECRAS
  • Front end application development
  • Development of video animations on flooding at different water discharges

4.1 Acquisition of remotely sensed data:

Since the field based elevation mapping of the large area (2500+sq. km) is time consuming and expensive process, we opted the acquisition and purchase of satellite images/ aerial photographs and digital elevation model. 0.6m aerial photograph is being used for developing vector layers while 15m DEM is being used for understanding topography of the study area. Annexure 1 shows the comparison of available options for satellite images and DEMs with their unit cost as of Dec 2011.

4.2 Field data collection:

Data from field is mainly required for building a database of settlements and critical facilities falling in floodplain. For this purpose online search has been carried out to explore secondary data sets available with Education, Health and Meteorology departments. This resulted in district level list of schools and health facilities for reference .
In addition, 0.6m satellite images have been printed on A0 sized Glossy sheets to a scale of 1:10000. Total study area comprises of 40 sheets (Figure A shows the Index Map for the printed satellite images while Figure B shows the screen shot of a typical Satellite Image Map). These images will be used in field survey to collect information from communities about critical facilities. Table below gives the details of required field based data, their collection method and collection process.

Sr. No. Data Set Collection Method Process
1 Villages Primary Obtain from field using community based mapping process on printed satellite images. Demarcate village location on satellite image along with village code and enter details of village in Village Information sheet
2 Schools Primary and secondary Collect list of schools from NEMIS database for reference. Verify schools location and list using community based mapping process on printed satellite images. Demarcate school location on satellite image along with school code and enter details of school in School Information sheet.
3 Health Facilities Primary and secondary Collect list of health facilities from DHO for reference. Verify health facility location and list using community based mapping process on printed satellite images. Demarcate facility location on satellite image along with health facility code and enter details of health facility in Health Facility Information sheet
4 Public Buildings Primary Obtain from field using community based mapping process on printed satellite images. Demarcate public building location on satellite image along with building code and enter details of public building in Public Buildings Information sheet
5 Livestock Hospitals Primary Same as above
6 Bridges Primary Field survey using GPS. Save geographic coordinates of bridge in GPS device and enter the related attribute information on the Bridges Information Sheet
7 Culverts Primary As above
8 Embankments Primary As above

4.3 Development of vector layers for elements at risk and critical facilities:

This task includes the development of vector layers for preparing base map and locate element at risk. It comprises of two phased efforts:

  • Digitizing road network and built up area from Aerial photos: This task operates in silo after the image acquisition and continues till completion without dependency on other project tasks. Resultantly, two shapefile are obtained; Road network (polylines) and Built up area (polygons)
  • Developing shapefiles for field based locational data: This task is dependent on the completion of field work. In this phase following shapefiles are developed:
Sr. No. Shapefile Name Type Process
1 Villages Point Layer Once the image maps have been populated with field work, point layers are created for each theme and points are marked in ArcGIS as they appear in field maps. Codes assigned on map are also added as attribute to respective shapefile. Later on, detailed attributes collected on paper sheets are transferred to excel sheets and linked to each theme to populate the shapefile attributes.
2 Schools Point Layer
3 Health Facilities Point Layer
4 Public Buildings Point Layer
5 Livestock Hospitals Point Layer
6 Bridges Point Layer Location data for these layers is collected from field using GPS. While attributes information is recorded on paper formats. GPS files are converted to shapefile and associated attribute data is liked from excel sheets.
7 Culverts Point Layer
8 Embankments & Sipers Point Layer

To speed up the process, it is advised to develop/ update shape files on daily basis once the data reaches back from field. It helps in verification, identification of data gaps and revisiting field if required.

After the completion of field data on paper maps, next stage is to transfer the geo information in digital layer. It has been tested that the following approach is very efficient for field teams with limited GIS working knowledge:

    1. Compile field data in MS Excel.
    2. There should be one sheet for one theme i.e one sheet contain data of all villages, one for schools, one sheet for bridges+ culverts and one sheet for Embankments+ Sipers
    3. There should be unique code for each entity in each sheet
    4. Since there will be point layers for villages, schools, health facilities, public buildings, livestock hospitals, bridges and culverts; it is best to develop these layers in Google earth using ADD PLACEMARK tool . For each placemark give the unique code you have already assigned in Excel sheet.
    5. Save Placemarks of all villages in one KML/KMZ file and convert it to Shapefile.
    6. Repeat the process for each theme and resultantly we get shapefiles for villages, schools, health facilities, bridges+ culverts, etc. All shapefile will have a Code field in its attribute table.
    7. Link Shapefile tables with respective Excel sheets to get final comprehensive shapefiles.
    8. Mostly, shapefiles obtained from Google earth KML conversion or GPS field coordinates are based on either WGS84 or unknown projection system. These need to be re-projected to UTM  Zone 42N with WGS84 for consistency.
  • Compilation of geo-data in File Geo-database: All shapefiles and rasters are arranged in a File Geo-database to ensure consistency and ease of data handling.

city pulse

4.4 Data preparation and modeling in HECRAS

For this project, ArcGIS and HECRAS are being used to manage the flood plain modeling component. ArcGIS is a leading GIS package with full functionality of data capture, store, manage, analysis and represent information developed by ESRI.

On the other hand, Hydraulic Engineering Centerís River Analysis System (HEC-RAS) allows to perform one dimensional steady and unsteady river flow hydraulic computations for a full network of natural and constructed channels. The system is comprised of a graphical user interface (GUI), separate hydraulic analysis components, data storage and management capabilities, & graphics and reporting facilities. The effects of various obstructions such as bridges, culverts, and structures in the flood plain may be considered in the computations. The steady flow system is designed for application in flood plain management and flood insurance studies to evaluate floodway encroachments . Figure below present the process of data preparation and modeling in HECRAS.

Below Figure represents model development process and flow for Flood plain modeling using HECRAS.


4.5 Front end application development and WebGIS development

A front end GIS application is being developed to give a charming face to all complicated modeling work. The idea is to develop an easy to use graphical user interface for users with less/no command on GIS modeling.