In the case of droughts, GDACS alerts combine automated procedures with source information from authoritative institutions, media and scientific organisations.

The data supporting the GDACS class and score attribution are extracted from the Global Drought Observatory (GDO). This, together with additional resources, are re-interpreted in order to fit GDACS purposes. Drought alerts are issued according to this colour scale:

GDACS Class Description
GREEN A confirmed drought, but no evidence of impacts or mild/intermediate impacts associated to a high coping capacity. No specific action would be envisaged by international aid providers.
ORANGE A drought with relevant impacts to the economy or assets, but not to people, at least not life threatening. National government provides aid in some form and official declarations of a drought/disaster are released. The drought reaches international media outlets. International humanitarian aid providers may be alerted, or international cooperation triggered.
RED Like orange, plus very severe or life-threatening impacts to people: migrations and internal displacements, famine or starvation, violence explicitly related to water resources conflicts. International humanitarian aid is needed or has been requested/dispatched.
Table 1

The main indicator for the spatial delineation of a drought event from GDO is the Risk of Drought Impact in Agriculture (RDrI-Agri). It deals with agricultural drought and combines physical indicators of drought hazard with exposure and vulnerability of a region/country, according to the well-known framework: Risk = Hazard x Exposure x Vulnerability. Therefore, the RDrI indicator synthesizes the severity of a drought with the socio-economic conditions of the affected regions, inferring the magnitude of potential impacts from such event. All components of the indicator are dynamic and change in time, but hazard in particular, which is updated every ten days.

Since the focus of GDACS is on the humanitarian side of natural disasters, the synthetic index for drought should reflect the humanitarian severity (potential impact) of a given event. This requirement is satisfied partly by the RDrI-Agri, but the calibration of the indicator is still too loose for GDACS standards and succinctness needs. So it must be evaluated further in order to narrow down the flagged events only to the most relevant ones and to attribute the GDACS score.

The procedure starts from the global RDrI-Agri indicator, which is extracted automatically at each ten days update and stripped of its lowest risk class, out of three possible (Low, Medium, High).
An algorithm then checks whether the remaining patches on the map (i.e. candidate events) match two simple criteria:

  1. • The event is at least one month old (i.e. it is flagged as drought for at least three updates in a row, to avoid very short dry spells)
  2. • The event extends over an area of at least 3 cells of 1 decimal degrees of second class according to RDrI indicator or, alternatively, over a single cell with the worst RDrI class. As mentioned, the first class of risk is not considered, no matter for how long it lasted or its extension over an area.

Both requirements must be met to pass the candidate drought event to the next evaluation stage. If so, the algorithm produces a layer of spatial polygons outlining the extent of the drought. If the process identifies a new location previously not flagged as under drought, it tries to associate it to an adjacent existing spatial polygon, before generating a new event. A few attributes are added to the output, including a unique identifier for the event and the country or sub-national region where the drought mostly occurs. Events that spatially split at some point in time are treated as a single continuous event. The algorithm typically produces a good number of individual “drought events”, which necessarily need to be validated and possibly merged before release.

In fact, experts from the drought team evaluate the spatial polygons issued by the unsupervised process. They prioritize higher scores according to RDrI, for which the evaluation is particularly careful. First they circumscribe the area, taking into account geographical and climatic domains. Then, they merge events relatively close in space and linked to the same climatological drivers. Knowing the potential specificity of droughts in certain regions, they look at the various indicators produced by GDO, to characterize the drought. At this stage, at least the green status is attributed to events deemed to be relevant.

For events seemingly severe according to physical indicators, the operators seek for independent validation from national or regional climatological monitoring systems. They also proceed to query the European Media Monitor (EMM, ) in search for evidence of impacts reported from the ground, in relation to the event. This helps to attribute a numeric score and a subclass to the event (see table), particularly to promote an “orange event” to the worst red category, for which drought indicators cannot provide sufficient information. A single source is not considered enough evidence, unless coming from official sources like governments or associated partners/agencies. A few independent sources of information are required before accepting alleged impacts as valuable for the score attribution.

The icon on the main GDACS+ map is placed at the geographical centroid of the event, taking into account the position of all related polygons.

In addition to RDrI-Agri, other sectorial drought risk indicators will be considered in the future, to address more broadly GDACS scope.

For purely reference terms and by no means for completeness, below in Table 2 is reported a breakdown of the broad categories listed in Table 1 with examples, associating the impact severity of a drought event to the GDACS score value.

GDACS Value Subclass description (with possible indicative conditions, not all present, nor exhaustive) Recent examples
0.25 A locally confined dry spell of low or intermediate severity, without evidence of impacts. -
0.5 A widespread meteorological drought revealed by indicators, but no evidence of impacts, or minor impacts with high coping capacity. Italy 2017: Some isolated water supply issues, local damages to crops.
0.75 A widespread drought with minor impacts, or in presence of high coping capacity. It reaches national relevance and may reach international media too. United Kingdom 2010/12: A long lasting event resulting in low reservoir levels, hosepipe ban, loss of yield, ecosystems damage.
1.0 Intermediate transitional value: this value is attributed only to those events fading away towards the lower class. -
1.25 Relevant sectorial impacts in presence of high coping capacity, or mild to intermediate impacts otherwise. Northern-Central Europe 2018: Widespread economic damages in different sectors and countries, some local water supply issues and costs for mitigation.
California 2015: Severe economic damages and thousands of jobs lost in agriculture; relevant mitigation costs.
1.5 Impact to the wider economy; livestock famine and mass sale; protests; empty or not viable reservoirs. South Africa 2017/18: Relevant economic damage, very high cost for mitigation and serious discomfort for people.
Argentina/Uruguay 2018: Major economic damage for agriculture and some local water supply issues, plus a mild global impact on grain commodities.
1.75 Serious issues for water supply and remarkable population discomfort; reduced availability of grains and food price hikes; political instability. China 2010: despite strong state support, huge damages to agriculture, millions people exposed from mild to very severe water shortages, global impact on grain prices.
Sri Lanka 2017: Insufficient coping capacity, many vulnerable people exposed, rising food prices.
2.0 Local migrations/displacement; local food insecurity and food assistance required; riots. Pakistan 2018: local food insecurity, reported deaths due to malnutrition, vulnerable rural communities displaced.
2.5 Widespread food insecurity; migrations and refugees; food and water assistance needed. Afghanistan 2018: No coping capacity and migrations due to lack of water, with local famine.
3.0 Likely or actual widespread loss of lives, with famine and/or actual lack of water. East Africa 2011: Famine with thousands of deaths related to malnutrition.
Table 2