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Flood Mapping Tools for Disaster Preparedness and Emergency Response Using Satellite Data and Hydrodynamic Models: A Case Study of Bagmathi Basin, India

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Proceedings of the National Academy of Sciences, India Section A: Physical Sciences Aims and scope Submit manuscript

Abstract

Northern Bihar is one of the major flood prone region in India affecting thousands of human lives and livelihoods during the recurrent floods occurring due to the monsoonal rains. While it is impossible to prevent the occurrence of extreme flood events, disaster planning can help in mitigating its detrimental effects. Monitoring flood extent using satellite observations just after the flood disasters is a core component of rapid emergency response process, which enables the emergency rescue teams to prioritize their efforts in critical areas to save lives and protect health, in addition to providing near real-time flooding information to the decision makers and planners. The main objective of this study is to demonstrate the utility of less data intensive, but equally robust hydrodynamic models to develop flood extent maps in conjunction with freely available remote sensing imageries at different scales. MODIS TERRA satellite data was used to map flood extent from 2001 to 2016 for entire Bihar. Two hydraulic models namely FLDPLN and RRI applied for the Bagmathi basin to evaluate our objectives. Both these models are of varying complexity but generate flood extent patterns with minimum amount of input data. The proposed approach is suited for mapping flood extents to provide an input information in near real time (h) when there is no availability to detailed hydraulic models and satellite datasets. Flood inundation extents from FLDPLN and RRI models were validated with Landsat-7 and MODIS TERRA derived flood extents for model performance. The results show acceptable spatial agreement between model predicted and Landsat-7 observed flood extents, denoting the utility of these tools for flood mapping application in data scarce environments.

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Abbreviations

1D:

One dimensional

2D:

Two dimensional

DEM:

Digital Elevation Model

DTF:

Depth to Flood

EVI:

Enhanced Vegetation Index

FLDPLN:

Floodplain

FMISC:

Flood Management Information System Centre

GIS:

Geographical Information System

HEC-RAS:

Hydrologic Engineering Centre’s—River Analysis System

HFL:

Highest Flood Level

IMD:

Indian Meteorological Department

MSL:

Mean Sea Level

NDVI:

Normalized Difference Vegetation Index

NDWI:

Normalized Difference Water Index

POD:

Probability of Detection

RRI:

Rainfall Runoff Inundation

USGS:

United States Geological Survey

VIC:

Variable Infiltration Capacity

km:

Kilometre

km2 :

Square kilometre

m:

Metre

mm:

Millimetre

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Acknowledgement

The authors would like to thank the funding support from CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Water, Land and Ecosystems (WLE) and Japan’s Ministry of Agriculture, Forestry and Fisheries (MAFF). Authors would also like to thank data provided by NASA’s MODIS and USGS Landsat data to map the inundation extent.

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Authors and Affiliations

  1. International Water Management Institute (IWMI), Colombo, Sri Lanka

    Giriraj Amarnath, Karthikeyan Matheswaran, Niranga Alahacoon & Shuhei Yoshimoto

  2. IWMI, New Delhi, India

    Pooja Pandey

Authors
  1. Giriraj Amarnath
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  2. Karthikeyan Matheswaran
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  3. Pooja Pandey
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  4. Niranga Alahacoon
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  5. Shuhei Yoshimoto
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Correspondence to Giriraj Amarnath.

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Amarnath, G., Matheswaran, K., Pandey, P. et al. Flood Mapping Tools for Disaster Preparedness and Emergency Response Using Satellite Data and Hydrodynamic Models: A Case Study of Bagmathi Basin, India. Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci. 87, 941–950 (2017). https://doi.org/10.1007/s40010-017-0461-7

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  • DOI: https://doi.org/10.1007/s40010-017-0461-7

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