GDACS Models
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In the following the models adopted in the GDACS system are presented:
 Earthquakes and Tsunamis
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GDACS approach

The objective of GDACS is to assess the overall impact of earthquakes (and eventually associated tsunamis) on affected countries. GDACS alert levels aim at drawing attention to an event that might turn out to be serious enough to merit international intervention, or, that could overwhelm national authorities’ response capacity. 

JRC has established partnerships with seismological organisations around the world that provide real-time data on earthquakes parameters (magnitude, depth and location). As of September 2017, to improve the potential impact by shaking, GDACS included the earthquake intensity calculations (USGS shakemaps [1]) in the alerting algorithm. These parameters are used to establish an affected area and calculate the population nearby. A country-wide vulnerability indicator moderates the alert level to provide higher/lower alert levels for similar earthquakes in countries that are more/less vulnerable.

GDACS alert levels aim at classifying earthquakes according to the likelihood that the affected societies can no longer cope at national level and will require humanitarian intervention. The final score then considers the level of coping capacity of the affected country or countries, obtained by the INFORM Index [2]. The coping capacity dimension measures the ability of a country to cope with disasters in terms of formal, organized activities and the effort of the country’s government as well as the existing infrastructure, which contribute to the reduction of disaster risk.


[1] https://earthquake.usgs.gov/data/shakemap/

[2] http://www.inform-index.org/

 

Current models

The seismic alerting algorithm

The earthquake damage considered by GDACS is that caused by shaking or by tsunami. To assess the potential impact by shaking, GDACS considers:

  • earthquake intensity calculations (USGS shakemaps)
  • earthquake magnitude
  • hypocenter depth
  • distribution of the population within 100km from the epicenter
  • vulnerability
  • coping capacity of the affected country or countries (INFORM index)

These data are processed by two different models to calculate the Alert Level (“Shakemap” and “EQ Parameters” Alerting Model). The GDACS seismic alerts are primarily based on the “Shakemap” Alerting Model. In cases where the shakemap is not available for any reason - usually because the earthquake is lower than 5.5 in magnitude or there have been some delays (e.g. communication problems between the intensity providers and GDACS), the alert score is calculated using only the parameters that are always available: moment magnitude, hypocentre depth and population at various radii from the epicentre.

GDACS “Shakemap” Alert = ƒ (EQ Intensity, Exposed population, Vulnerability, Coping capacity)

GDACS “EQ parameters” Alert = ƒ (Magnitude, Depth, Exposed population, Vulnerability, Coping capacity) 


The “Shakemap” alerting model

The GDACS “Shakemap” alerts are based on the geographical distribution of the earthquake’s Modified Mercalli scale intensity (MMI) - what is known as “shakemaps”. A rough map of the intensity of earthquakes stronger than about Mw 5.5 is made available a few minutes after the event, principally by the United States Geological Survey (USGS) but also by other institutes around the world that use the Shakemap USGS software, e.g. the National Institution of Geophysics and Volcanology (INGV) of Italy.

The GDACS shakemap-based alert relies on a score, derived by the number of people exposed in each MMI grade, from VII (Very Strong Shaking) upwards, calibrated by the casualties recorded for all seismic events since 2006 (source: DG ECHO daily flash[1], EM-DAT[2]). In some countries with more than 3 or 4 earthquakes in the record, a more detailed Country-specific coefficients This score has been then re-calibrated separately for each country to obtain country-specific correction from the global trend (“country seismic vulnerability”). In addition to the global score, there are  also country-specific scores which have been re-calibrated separately.

More specifically, as soon as GDACs is provided by the shakemap of a strong earthquake (Mw > 5.5) from one of the competent seismological centres, the following sequence is followed:

1. EQ Intensity: if the maximum intensity in a populated place (i.e. with number of people > 0) is not above MMI VI (Strong Shaking) the GDACS alert is GREEN and the Alert Score is set to 0. 

2.  Exposed population: if the maximum intensity is above MMI VI, an expression for weighting the exposed population and a first raw alerting score based on that are calculated:


Scaled Population = 10*Population(MMI IX) + Population(MMI VIII) + 0.1*Population(MMI VII)

and:

Raw Score = (-0.59) + (0.53)×log10(Scaled Population)


3.  Country seismic vulnerability: a country-specific correction is applied to this score, based on a calibration on the number of casualties by previous earthquakes of similar score in this country since 2006. For most cases this correction is the addition or subtraction of a numerical “Country Shakemap Vulnerability” that can range from -1 to +1 (see table):

Shakemap Score = Raw Score + Country Shakemap Vulnerability

In some countries with more than 3 or 4 earthquakes in the record, a more detailed linear correction is applied, of the form y = ax + b.
The “Shakemap” Score is calculated as follows:

Shakemap Score = (-0.59 + C1Shakemap) + (0.53+ C2Shakemap)×log10(Scaled Population)


At this step, the score lower than 1, corresponds roughly, according to the calibration, to a number of casualties less than 10. A score between 1 and 2, corresponds to casualties between 10 and 100. A score higher than 2, corresponds to casualties more than 100.

4. Coping capacity: to calculate the final Alert Score we apply a factor derived from the Lack of Coping Capacity dimension of the INFORM index (INFORM LCC, yearly updated). A normalisation is applied to the original country-specific INFORM LCC (resulting in values vary by 1.5 of South Sudan to 0.5 of Switzerland, see table). If the score obtained from step 3 is >2.0 (corresponds roughly to a number of casualties of 300) and the final score is <1 due to the country-specific coping capacity, the final alert score is set to 1. This allows to avoid over-estimation of the coping capacity of a country. The final GDACS Alert Score is calculated as follows:

GDACS Alert Score = Shakemap Score * INFORM Lack of Coping Capacity

5. Alert level: Finally, the alert score is transformed into an alert level according to the following thresholds:
GDACS Alert Level GDACS Alert Score
[Shakemap]
RED ≥2
ORANGE ≥1 - 2
GREEN 0 - 1

 

In case the event involves 2 or more countries, the highest coefficients within MMI>=7 are considered. 

It is worth mentioning that these alerts do not take into account a possible tsunami. Alerting score for the tsunami is calculated separately; see the session on GDACS Tsunami Alert model.

A graph of the “Shakemap” Alerts after all corrections versus the number of people killed for the calibration sample of earthquakes (events between 2006 and 2016 with more than 2 people killed and with shakemap available) is shown in Figure 1.



Fig. 1 - Earthquakes between 2006 and 2016 with more than 2 people killed and with shakemap available. The GDACS alerts have been re-calculated using the “Shakemap” Model. The events that required an international humanitarian intervention are highlighted. (N.B. Number of deaths for tsunamis are not included).


[1] http://erccportal.jrc.ec.europa.eu/ECHO-Flash

[2] http://www.emdat.be/



The “EQ parameters” alerting model

In this model, the alert score is calculated using only the parameters that are always available: moment magnitude, hypocentre depth and population at various radii from the epicentre. In the “Shakemap” alerting model, a linear regression model has been applied to all deadly earthquakes with more than 1 fatality since 2006, correlating number of fatalities with magnitude, depth and exposed population. Specific corrections are then applied to each country separately, accounting for the different vulnerabilities. 

The steps followed are these:

1. EQ parameters: Moment magnitude (Mw) and depth. The earthquake moment magnitude (Mw) is in unit reported by sources. The alert is based on the last data available at the starting time of the calculation.

2. Exposed population: the exposed population is calculated by the following scaling expression, giving more weight to the exposed population closer to the epicentre:

Scaled Population = 10 * P20 + 2 * (P50 - P20) + 0.5 * (P75 - P50) + 0.1 * (P100 - P75)

where P
X is the population at X km from the epicentre. The coefficients 10, 2, 0.5 and 0.1 are such that for a homogeneous population distribution, Scaled Population = P100.
Then the raw alerting score is calculated as follows:


Raw Score = -7.75 + 0.82 * MW - 0.53 * log10(Depth) + 0.72 * log10(Scaled Population) 

The coefficients have been obtained by a multi-parametric linear regression model on the number of fatalities against the “Raw Score”, as for the “Shakemap” model.

3. Country seismic vulnerability: a country-specific value is then added to the raw score of each new earthquake and a vulnerability-corrected score is obtained, as in Step 3 above. For countries with a large number of events, a further linear regression is applied that can tighten the correlation of score and number of fatalities (C1Classic, C2Classic, Country Classic Vulnerability, see table). The “Classic Parameters” Score is calculated as follows:

“EQ Parameters” Score = (C1Classic * Raw Score) + C2Classic + CountryClassic Vulnerability

At this step, the score lower than 1, corresponds roughly, according to the calibration, to a number of casualties less than 10. A score between 1 and 2, corresponds to casualties between 10 and 100. A score higher than 2, corresponds to casualties more than 100.

4. Coping capacity: to calculate the final Alert Score we apply a factor derived from the Lack of Coping Capacity dimension of the INFORM index (INFORM LCC, yearly updated) as in the step 4 above. In case the event involves 2 or more countries, the highest value within 100 km is considered. The final GDACS Alert Score is calculated as follows:

GDACS Alert Score = “EQ Parameters” Score * INFORM Lack of Coping Capacity


6. Alert score: as before, the alert score is transformed into an alert level according to the following thresholds:

GDACS Alert Level GDACS Alert Score
[EQ parameters]
RED ≥2
ORANGE ≥1 - 2
GREEN 0 - 1

Regarding the derived country vulnerabilities by the two methods, it is worth mentioning that while they are quite similar, are not the same, as they have been calculated from very different parameters. In case the event involves 2 or more countries, the highest coefficients within MMI>=7 are considered.

In general, the scores derived by the “classical parameters” method tend to be less accurate, with a higher possibility to over-estimate the impact.

At the same time, the tsunami alert score is calculated (see below).

The Tsunami Alerting Algorithm

GDACS tsunami alert calculations are triggered by earthquakes that occur in or near the water. The logic for the tsunami alert is based on (1) the magnitude of the earthquake, (2) the depth of the earthquake, (3) the maximum wave height at any coast reach by the tsunami. The first two parameters are used to look up a tsunami wave height calculation in the JRC Tsunami Database (containing over 132000 scenarios).

For each earthquake of magnitude exceeding 6.5 occuring in a location with positive water depth (from ETOPO30), the tsunami database is queried for the closest matching scenario. Scenarios have been calculated for 13800 locations covering tsunamogenic areas (from NOAA database) for magnitudes ranging from 6.5M to 9.5M with steps of 0.25M.

If a scenario is available, the maximum wave height at a coast is retrieved. The GDACS Alert Score for tsunami relies on the maximum wave height at a coast. As for the Seismic alerting model, the alert score is transformed into an alert level according to the following thresholds:


GDACS Alert Level GDACS Alert Score
[Tsunami]
 Maximum wave height at coast (m)
RED ≥2  ≥3
ORANGE ≥1 - 2  ≥1 - 3
GREEN 0 - 1
 0 - 1

These values are then corrected for earthquake depth in the same way as for earthquakes.

A new calculation is always started with the tight EQ parameters (taking about 20 minutes), but the alert routine does not take it into account. Rather, the IOC alert Matrix is used (see figure below), based only on magnitude. This fall-back routine, although widely used in tsunami warning centres, results in many false alerts.

For each earthquake of magnitude exceeding 6.5 occuring in a location with positive water depth (from ETOPO30), the tsunami database is queried for the closest matching scenario. Scenarios have been calculated for 13800 locations covering tsunamogenic areas (from NOAA database) for magnitudes ranging from 6.5M to 9.5M with steps of 0.25M.

If a scenario is available, the maximum wave height at a coast is retrieved. If the maximum wave height is greater or equal than 3m, the tsunam alert is Red; if it the height is greater or equal than 1m, the alert is Orange; otherwise, the alert is Green. These values are then corrected for earthquake depth in the same way as for earthquakes2.

If no scenario has been precalculated (only very few cases), a new calculation is started (taking about 20 minutes), but the alert routine does not take it into account. Rather, the IOC alert Matrix is used (see figure below), based only on magnitude. This fall-back routine, although widely used in tsunami warning centres, results in many false alerts.

 

Results and limitations

Over the years, the GDACS models have been put to the test, with a high user satisfaction. For earthquakes and tsunamis, the most important aspects are timeliness of alerts (as fast as possible) and avoiding false alerts (don’t wake up people if it’s not needed). The first aspect has been improved steadily by forging agreements with regional seismological institutes around the world to push data to GDACS (rather than GDACS scraping data from their web sites). This is most important for timely triggering of tsunami models. The second aspect is ensured by GDACS’s earthquake vulnerability score (which effectively lowers the alert level for countries able to cope with disasters) and the wave-height-based alerting approach for tsunamis (reducing false tsunami alerts by 90%).

Some of the limitations of the approach are:

  • GDACS automatic alerts cannot always reliably predict the humanitarian impact of a natural disaster event - this is very difficult to predict even by very sophisticated probabilistic seismic risk assessment tools that take into account detailed exposure and vulnerability data, painstakingly gathered over long time-periods.
  • GDACS alerting algorithms are empirical in nature and are intended to give a fast and rough warning to people that realise the limitations of automatic systems and of simple “green - orange - red” schemes.
  • The INFORM Lack of coping capacity Index a simplification of the reality. The main constraints are related to limitations in the methodology and data quality and availability.

Further work

With increasing availability of (real time) data and continuously improving accuracy and detail of models, impact assessment can always improve. GDACS is a collaboration platform open to organisations that have data, models or systems that can significantly contribute towards better impact assessment and new information for emergency responders.

In the past 5-10 years, seismic risk assessment tools have moved into increasing sophistication and detail and are able to take full advantage of the newest developments in hazard, exposure and vulnerability data. All systems are non-commercial and most are open-source and their components can be freely downloaded. The common approach based on the risk equation renders them easily interoperable, but on the other hand this entails significant duplication of effort. Most systems are either ready or are adapting fast to a real-time use, as early impact assessment and warning mechanisms. Additionally, the lack of accurate globally available exposure and vulnerability data is hampering this effort, so a joint effort to collect these data sets would be an enormous benefit to the global risk assessment and – eventually – risk reduction effort.

JRC, as the scientific lead in GDACS, is interested in exploring integration of such products in the existing impact models.

With regards to earthquakes and tsunamis, we are currently moving towards a more comprehensive and transparent process by:

  • The inclusion of the output of at least two seismic risk assessment systems in the GDACS events pages with an automatic calculation after an event, or by a manual update by the system developers in a dedicated space.
  • The integration of probabilistic models and the assessment of the uncertainty, e.g. in relation to the following factors: (i) preliminary uncertainty related to the variation of initial parameters (Mw, depth, location); (ii) number of previous deadly events used to calculate the country seismic vulnerability; (iii) differences in the exposed population due to the use of different global datasets e.g. LandScan and GHSL). This would allow to define and communicate the “alert uncertainty” based on the parameters used to calculate the GDACS alert score.

Additionally, in doing so the Users may take more informative decisions on the basis of the above mentioned parameters.

 


GDACS Alert Level 
GDACS Alert Score
 Tropical cyclones
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Humanitarian impact of tropical cyclones

Tropical cyclones occur in regular seasons in all tropical basins, affecting Island States and coastal areas.

Tropical cyclones cause destruction in three major ways: extreme wind destroying structures, storm surge causing coastal flooding and, the major hazard for weaker storms, extreme rainfall causing flash-floods and landslides. Preparedness and mitigation measures help reduce the impact of cyclones.

GDACS approach

The objective of GDACS is to assess the overall impact of tropical storm events on affected societies in order to evaluate the need for international intervention. The goal is to understand, as it is happening, the hazard in as much detail as possible, model the impact on the affected communities and, taking into account local and national coping capacity, estimate the likelihood that the country can cope with the disaster.

JRC set up an automatic routine that includes the Tropical Cyclone (TC) bulletins produced by the National Oceanic and Atmospheric Administration (NOAA) and the Joint Typhoon Warning Center (JTWC) into a single database, covering all TC basins. This information is used in GDACS for the wind impact, while the heavy rain impact is obtained using the NOAA Ensemble Tropical Rainfall Potential (eTRaP) data. For the storm surge, JRC has developed an analytical tool, introducing the atmospheric forcing in the JRC’s HyFlux2 code and using as input the TC bulletins.

Current models

Impact model based on wind speed and population

Based on track information provided by the National Oceanic and Atmospheric Administration (NOAA) and the Joint Typhoon Warning Center (JTWC), JRC calculates areas around the track affected by high winds. In these areas, GDACS calculates population and critical infrastructure.

In the new methodology the Vulnerability Indicator for Tropical Cyclone described belove has been integrated in the alert model.

JRC developed the Vulnerability Indicator for Tropical Cyclone combining indicators describing the human development (HDI) and the rural populations (Percentage of population in rural areasPopulation living below 10m low elevation in coastal zone). JRC introduced a new Index (Rural Population Index, RPI) for rural population averaging the values of the two chosen indicators for rural population.

The countries were ranked by HDI and RPI using the quartile method and then the scores for the two dimension indices are then aggregated into a composite index using arithmetic mean. The countries were finally assigned to 3 classes, (1) High Vulnerability, (2) Medium Vulnerability, and (3) Low Vulnerability.

Depending on the wind speed, the population in the area, and the vulnerability of the affected countries alert levels are set as follows:

Wind speed

Population

Vulnerability

Alert Level

38 – 73 mph (TS)

< 10M

Low – Medium - High

Green

38 – 73 mph (TS)

> 10M

High

Orange

74 – 110 mph (Cat 1-2)

> 100K or > 10%

Medium – High

Orange

74 – 110 mph (Cat 1-2)

> 1M

High

Red

> 111 mph (Cat 3)

> 100K or > 10%

Medium – High

Red

> 111 mph (Cat 3)

> 1M

Low

Orange

> 131 mph (Cat 4)

> 1M

Low

Red

Storm surge

In addition, GDACS calculates population potentially affected by storm surge, but this is not taken into account in the alert model yet. Storm surge is calculated using HyFlux2, a numerical hydrodynamic code implementing shallow water equations.

The atmospheric forcing included in the storm surge model are the pressure drop and the wind-water friction. The effects of the short waves induced by the wind (wave setup) and the precipitations are not yet implemented in the model. The model has been validated mainly in areas of shallow water (Caribbean, Bay of Bengal). Results in other basins may be inaccurate.

Alert thresholds are set at: Orange >1m, Red >3m.

Extreme rainfall

To account for flooding and other effects of extreme rainfall, GDACS reports on the extreme rainfall calculated  by NOAA NESDIS. The ensemble tropical rainfall potential product (eTRaP) is a high resolution estimate of rainfall based on multiple passive microwave remote sensing images. GDACS considers both the accumulated rainfall (for standing floods) and the rain rates (for landslides and flash floods). The current models (and associated rainfall alert levels) are experimental.

The goal is to provide appropriate alert levels when rainfall causes large landslides and flash floods with humanitarian consequences. The current thresholds are conservative:

  • Total cyclone accummulation (mm):   Green <200mm, Orange >200mm, Red >500mm.
  • Maximum rain rate (mm/h):  Green <17mm/h, Orange >17mm/h, Red >33mm/h. 

Results and limitations

Overall, GDACS has a good record of assessing the impact of tropical cyclones. All red alerts triggered humanitarian intervention or a major national relief effort. GDACS typically provides impact reports 72h before landfall using the official tropical cyclone advisory bulletins. Some cyclones were underestimated because the rainfall and storm surge were not taken into account until 2012.

The main weaknesses identified in a 2008 study [reference] were addressed. A cyclone vulnerability score was implemented to reduce alert scores on resilient countries; a rainfall and storm surge model were developed; and impact of small Island States was calculated differently.

Uncertainty in meteorological forecasts is propagated in GDACS results, causing alert levels to change upwards or downwards. For each advisory, the alert messages use an alert level related to what is to come, ignoring the previous impact. However, the main impact report on the web site shows the alert status of the whole storm, and is modified with each advisory.

Further work

With increasing availability of (real time) data and continuously improving accuracy and detail of models, impact assessment can always improve. GDACS is a collaboration platform open to organisations that have data, models or systems that can significantly contribute towards better impact assessment and new information for emergency responders. JRC, as the scientific lead in GDACS, is interested in exploring integration of such products in the existing impact models.

With regards to tropical cyclones, we’re currently working on:

  • Storm surge impact assessment: a continuous evaluation of the hydrodynamic models in different settings, as well as improved impact assessment, integrated with other hazard components (rain, wind).
  • Extreme rainfall impact assessment: NOAA’s eTRaP models use satellite-based rainfall estimates to forecast extreme rainfall in the next 24h. This data is used in a risk model in development at JRC.
  • Social and mass media analysis for rapid situation awareness.
 GDACS Models
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GDACS models

This page is currently in development to report on the status of GDACS models. Please check back later for more complete information.

GDACS approach

The selection and alert level of natural hazards in GDACS is based on automatic impact assessment models. GDACS software continuously scrapes or receives scientific data on natural hazards. Information about the location, strength and other characteristics is then used to calculate an affected area. Different models are used for different disaster types. Subsequently, the potential impact of the event is assessed by calculating the population within the affected area and their vulnerability. All calculations and assessments are done automatically by software, without human intervention.

GDACS uses models for earthquakes, tsunamis and tropical cyclones. For floods, GDACS alerts are manually curated by the Dartmouth Flood Observatory. For volcanoes, GDACS currently reports on VAAC alerts, which are not appropriate for humanitarian intervention. Research and development is continous to improve the global monitoring.