Chapter 5
An Overview of the Integrated Flood
Analysis System (IFAS) Studies
in Insufficiently Gauged Catchments:
Approaches, Challenges, and Prospects
M. F. Chow
Abstract Flooding problem is becoming a great challenge for developing countries
because of climate change deforestation and urbanization processes. Lack of hydrological data and catchment information has hindered the local government to set up
the flood early warning system where can predict the lead time of flood and thus
reduce the vulnerability to flood disaster. Therefore, the Integrated Flood Analysis
System (IFAS) is developed to predict the flood event in insufficiently gauged catchments. IFAS can automatically collect the geographical data, soil type, land uses, and
satellite rainfall data to set up the river basin model for flood simulations. This paper
provides an overview of approaches, challenges, and prospects of using IFAS model
for flood prediction at several river basins with different catchment characteristics in
Asian countries. The results of previous studies suggest that IFAS can better simulate the flood in large river basins compared to small river basins. Flood forecasting
with calibrated satellite rainfall data in IFAS model performed higher reproducibility
than satellite rainfall without calibration particularly for the beginning and peak of
hydrograph.
Keywords Flood forecasting · Flood early warning system · Insufficiently gauged
catchment · Satellite rainfall
5.1 Introduction
According to the IPCC report, frequent flood and drought events are occurring worldwide due to the intensification of hydrological cycle driven by climate change which
results in the spatiotemporal fluctuation of rainfall (IPCC 2014). The damages due
to the past 24 major flood events in Pakistan have caused an aggregated financial loss
M. F. Chow (B)
Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000
Kajang, Selangor, Malaysia
e-mail: mingfaichow12345@gmail.com
© Springer Nature Switzerland AG 2021
R. Djalante et al. (eds.), Integrated Research on Disaster Risks, Disaster Risk Reduction,
https://doi.org/10.1007/978-3-030-55563-4_5
71
An Overview of the Integrated Flood
Analysis System (IFAS) Studies
in Insufficiently Gauged Catchments:
Approaches, Challenges, and Prospects
M. F. Chow
Abstract Flooding problem is becoming a great challenge for developing countries
because of climate change deforestation and urbanization processes. Lack of hydrological data and catchment information has hindered the local government to set up
the flood early warning system where can predict the lead time of flood and thus
reduce the vulnerability to flood disaster. Therefore, the Integrated Flood Analysis
System (IFAS) is developed to predict the flood event in insufficiently gauged catchments. IFAS can automatically collect the geographical data, soil type, land uses, and
satellite rainfall data to set up the river basin model for flood simulations. This paper
provides an overview of approaches, challenges, and prospects of using IFAS model
for flood prediction at several river basins with different catchment characteristics in
Asian countries. The results of previous studies suggest that IFAS can better simulate the flood in large river basins compared to small river basins. Flood forecasting
with calibrated satellite rainfall data in IFAS model performed higher reproducibility
than satellite rainfall without calibration particularly for the beginning and peak of
hydrograph.
Keywords Flood forecasting · Flood early warning system · Insufficiently gauged
catchment · Satellite rainfall
5.1 Introduction
According to the IPCC report, frequent flood and drought events are occurring worldwide due to the intensification of hydrological cycle driven by climate change which
results in the spatiotemporal fluctuation of rainfall (IPCC 2014). The damages due
to the past 24 major flood events in Pakistan have caused an aggregated financial loss
M. F. Chow (B)
Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000
Kajang, Selangor, Malaysia
e-mail: mingfaichow12345@gmail.com
© Springer Nature Switzerland AG 2021
R. Djalante et al. (eds.), Integrated Research on Disaster Risks, Disaster Risk Reduction,
https://doi.org/10.1007/978-3-030-55563-4_5
71