Global inundation forecasting combining GloFAS and flood hazard maps: A case study of the 2017 Brahmaputra

Hydrological Services for Business 8th May 2018

John Bevington, Beatriz Revilla-Romero, Charles Allatson, Sally Dempsey, Elizabeth Wood Flood Foresight

Near real-time and forecast flood inundation maps for riverine flooding

Enables flood early warning and improved targeting of mitigation and response activities

Imagery Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CNES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User Community Exposure / Asset data

Post-event Rainfall maps and loss forecast assessment

Modelling and mapping

Near real-time Forecast flood inundation inundation maps maps

Forecast impact / loss Early Flood estimation warning ££ Mapping the full lifecycle of floods

Demonstration How it works

Flood Mapping

Generalised 2D hydraulic modelling with national coverage

JBA Flood Maps

Library of mapping

model outputs

computed

- Static, pre Static,

Database of AEP to outline flood depth

lookups Dynamic, operational Dynamic,

1. Real-time (gauged) or forecast 2. Lookup between in-river 3. Select flood outline with closest match 4. Intersect with flood receptors to derive (modelled) in-channel levels or flows conditions and impact mapping to forecast conditions impacts information JBA Flood Hazard Maps

• 30m resolution undefended river flood and surface water hazard maps

• Indicative flood extent and depths for 6 return periods: ▪ 20-year ▪ 100-year ▪ 500-year

▪ 50-year ▪ 200-year ▪ 1,500-year

DigitalGlobe, GeoEye How it works

Flood Mapping

Generalised 2D hydraulic modelling with national coverage

JBA Flood Maps

Library of mapping

model outputs

computed

- Static, pre Static,

Database of AEP to outline flood depth

lookups Dynamic, operational Dynamic,

1. Real-time (gauged) or forecast 2. Lookup between in-river 3. Select flood outline with closest match 4. Intersect with flood receptors to derive (modelled) in-channel levels or flows conditions and impact mapping to forecast conditions impacts information Brahmaputra pilot August 2017

8 Brahmaputra Pilot Project

• basin: – 30 m resolution flood hazard maps – Daily updates – 0 -10 day forecast – Ensemble forecast (fluvial) – allowing uncertainty and likelihood assessment

Flood Foresight inundation footprint (16 August 2017) Results – flood peak animation

Click image to animate Ensemble-based flood likelihood

Use of probabilistic footprints to assess the confidence of the forecasts at longer lead-times Higher probability (dark colours) shows greater agreement of the ensemble and therefore higher probability of flooding. It is essential to understand uncertainty when used in public alert systems.

Preliminary data Probabilistic forecasting Area flooded per District - Comparison

• Most potentially affected districts in the area: Sonitpur, , and Lakhimpur. Potential population impacted by flooding- Comparison

Input data: Sentinel 1 vs Flood Foresight

Potential population impacted by flooding on the 12th August - Area a2

2,000,000

1,800,000

1,600,000 Flood Foresight [90% Threshold] 1,400,000 Sentinel 1 (t)

1,200,000

1,000,000

Population 800,000

600,000

400,000

200,000

0 t t-1 t-2 t-3 t-4 t-5 t-6 t-7 t-8 t-9 Flood Foresight - Lead time

*t=0 no ensemble spread Summary

GloFAS + Flood Foresight:

• GloFAS allows us to scale Flood Foresight globally

– Supporting decision-making in several sectors

• Provides consistent methodologies and data for (trans)national flood and impact analysis • Provides a framework for flood forecasting to make use of the best available data

– Flood maps, gauge data, forecast data, EO data

• Flexible integration • Opportunities – data providers and commercial evaluations Thanks

Contact: [email protected] [email protected]