Enhanced Flood Disaster Response Capability: developing high resolution remote sensing
technology into an advanced knowledge management system to monitor, assess and plan
emergency responses to during flood disasters
Abstract
Every year Kazakhstan experiences hundreds of natural disasters ranging from earthquakes to
mudslides and flooding affecting thousands of people including a death toll of 100s. Many of
these are preventable if risk assessments are used to better predict flood events and influence the
planning and activities in river basins. They would also be preventable if better information was
available prior to natural disasters for planning of emergency preparedness and during disasters
for leading disaster recovery events.
Remote sensing technology is increasingly used for water resource monitoring and assessments
during flood disasters and river flooding as it provides unique methods and solutions to meet the
information requirements of water engineers responsible for water resources management. This
project aims to advance the application of Remote Sensing in the context of flood disaster
management by integrating high resolution remote sensing technology into a map-based
Knowledge Management System (KMS) that provides valuable information to decision makers,
disaster recovery teams and the public. The system uses satellite and meteorological data to
enable risk and impact assessments. During disasters, it is capable to use geo-spatial imagery
from unmanned aviation vehicles (UAV) to provide real time information for emergency and
response planning.
This geo-spatial platform is used as an early warning system for experts to predict and plan for
emergencies including the assessment of emergency impacts, the planning of evacuations and the
movement of tactical response units. The platform also enables the sending of alert messages to
mobile phone users within risk areas and the coordination and monitoring of tactical response
units via GPS.
Introduction
The special features of Kazakhstan’s nature make it potentially susceptible to such natural
disasters as: earthquake, debris flows, avalanches, landslides and mudslides, drought, sharp drops
in air temperature, blizzards and snowstorms, rising water levels, river flooding and flooding of
other water bodies.
Direct losses from natural disasters exceed well over US $20 million per year. That data does not
take into account the possible effects of large-scale catastrophes, which have occurred many
times in the history of Kazakhstan, particularly catastrophic earthquakes (UNDP, 2000).
With regard to flood disasters, it is important to note that in the last years the number of floods as
a result of human activity has risen sharply. For example, floods on the Syrdaria river occur due
to the increased level of water release from the Shardara reservoir in winter (due to violation of
water release schedule). Threat is also posed by sewage water reservoirs of a number of
Kazakhstan's large cities (Almaty, Aktyubinsk, Taraz and others).
Remote sensing technology can directly contribute to water resource monitoring and assessments
during flood disasters and river flooding. Moreover, it provides unique methods and solutions to
meet the information requirements of water engineers responsible for water resources
management.
This project aims to advance the application of Remote Sensing in the context of flood disaster
management by integrating high resolution remote sensing technology into a map-based
Knowledge Management System (KMS). Remote Sensing Technology used to complement the
development of a Knowledge Management System by advancing the remote sensing capability
and image processing to near-real time. This capability can be used to monitor and assess a river
basin to develop flood extent and predictions.
The objective of this research and engineering project is to:
 Develop a knowledge management system for water resources development and
management
 Integrate remote sensing technology into a knowledge and communication platform
 In, details, to study the practice of water resource management and information sources
as they relate to the river basins in East Kazakhstan
 Obtain Remote sensing data and develop software algorithms to synthesize hydrological
data
 To conduct research on flood potential of rivers for the development of geospatial flood
risk maps
This project uses high resolution remote sensing data to develop advanced algorithms for
assessing and monitoring water resources for river basin water resource management (Figure 1).
The data is provided by Kazakhstan state company ‘KGS’ from its own remote sensing Satellites
KazEOsat-1 and KazEOsat-2 or KGS partner’s satellites. The project will use Remote Sensing
data procured from a high resolution (1 m panchromatic and 4 m multispectral) remote sensing
and it is anticipated that accurate bathymetric measurements can be achieved up to 20 meters and
deeper.
Figure 1. Development and application of algorithms
A conceptual knowledge management framework has been developed to enquire and collect
relevant information for flood related disaster management and recovery. The framework was
developed by understanding and mapping water resource management and decision making
processes. The framework includes nine (9) distinct but interrelated components. These are
shown in Table 1.
TABLE 1. Components of Water resources knowledge management framework
Water resources knowledge management framework
Water Resource Strategy and Policy
Stakeholder Management
Ownership, Responsibility, Authority and Resources
Inventory of the water resource and its infrastructure
Condition and Performance of a water resource and its infrastructure
Valuations and Financial Review
Monitoring, Control and Knowledge Management
Internal Process Development and Review
Risk Assessment, Management, and Emergency Response
The Knowledge Management System consists of four parts: wireless sensor network, local
server, monitoring service platform and application server which are connected and operated
coordinately. They form an integral part of real time data collecting, management of information,
comprehensive analysis and supporting planning, and real time control. The previously
developed algorithms will be embedded into the software script to integrate (near) real-time
monitoring and control into a software platform used to manage water resources and their
controlling infrastructure.
It can be divided into two parts: central management system and communication system. The
central management system includes a monitoring service platform and application server. The
monitoring service platform provides real time data collection of various parameters related to
water resources management, such as temperature, moisture content (air humidity), water flow
rate, water volume, water quality and rain fall. The system analyses the validity of the data before
saving it to a central database. It can output the information in a variety of charts or simulation
graphs to show trending including short term forecasting or prediction. That involves
mathematical modelling using artificial intelligence and context-awareness, based on data that
have been collected.
Apart from that, the system has built-in decision making, for example activate certain control, or
send alert messages, when there is a sudden change in key parameters. The communication
system includes both wired and wireless communication. Various sensors are communicating
wirelessly with a control terminal (local server that serves as a coordinating focal point) that is
located within the coverage area using various standards.
Stereoscopic images of an area are used to develop a data elevation model (DEM) of a river bed.
The challenge with collecting stereoscopic imagery of the shallow ocean floor is in how light
interacts with the water interface. At high angles of incidence, light is completely reflected off
the water surface thus preventing any sub-aquatic profiles from being observed. In this
application, sensors are required to collect enough high-resolution stereoscopic imagery within
the narrow angle to penetrate the surface of a water body.
Furthermore, once these very high resolution images analyzed, this data will be put into KMS.
Therefore, based on imagery data web-based software it would be possible to predict flood
extent and send ‘warning messages’ to residents living nearby a water body.
It is crucial to integrate local knowledge, GIS and maps into the process of disaster risk
management. There are three main reasons for this integration: (i) a hazard map plays a key role
in disaster risk identification, and it is an effective tool in making local knowledge visible; (ii)
local knowledge is essential for disaster risk management; and (iii) GIS maps have advantages
over conventional maps. First, hazard maps are fundamental to the development of a communitybased methodology for collecting and displaying the disaster vulnerabilities and risks that
comprise the core content of local knowledge (Hatfield,2006). Hazard mapping is one of the first
steps of producing a community vulnerability inventory. The flood disaster mapping can
contribute to proper planning and resource allocation for disaster preparedness.
With the mapping and geo-spatial analysis of information as a basis, it is anticipated that the
integration of real-time monitoring provides a comprehensive knowledge management systems
to support water resource management and environmental engineering decision making
processes in regulatory and public agency organizations. It is anticipated that the development of
a real-time online monitoring and assessment capability based on genetic algorithms and
statistical pattern recognition has potential to find significant, customized application to advance
the management of water resources and environmental systems by enabling real time and remote
monitoring of physical and hydraulic attributes of water resources.
Once we have a prototype of the web-based software application established, we will register a
Limited Liability Company that will offer a web-based software and data subscriptions to our
customers. Currently, we are targeting one particular client segment: any government agency
involved in water resources management.
Further information on Commercialization part, Team and Fee Calculation can be found in a
separate file.