The indicator addresses anomalies and long term trends of vegetation productivity derived from remote sensing observed time series of vegetation indices in areas that are pressured by drought.
Drought pressure is computed as soil moisture deficit within the growing season, using the Soil Moisture Anomaly (SMA) time series of the Copernicus EMS European Drought Observatory of the European Commission Joint Research Centre (EDO, 2019).
Drought impact during the growing season is indicated as a severe negative annual productivity anomaly in drought-pressured areas, i.e. areas with negative annual soil moisture anomalies. Detailed indicator specifications are described under ‘Methodology’.
- Drought hazard (monthly): months with negative SMA values.
- Drought pressure intensity (annual): the negative average SMA values, where the SMA values are aggregated within the vegetation growing season.
- Drought pressure area (annual): sum of the grid cells where the growing season aggregated SMA values are < -1.
Long term average (one value for the time series) drought pressure intensity and area: average of annual drought pressure intensity and area, respectively.
- Drought impact intensity (annual): negative vegetation productivity anomalies in the growing season in areas under drought pressure.
- Drought impact area (annual): sum of the grid cells where the growing season aggregated SMA values are < -1 and the vegetation anomaly is <-0.5.
Soil moisture deficit, i.e. annual drought pressure is derived at the pixel level and is simply defined as:
SMA(gs)<-1 (Equation 1)
Where SMA(gs) refers to the long-term (2000-2021) average annual soil moisture anomalies aggregated within the vegetation growing season.
Negative soil moisture anomalies indicate that the annual average availability of soil moisture for plants drops to such a level that it has the potential to affect vegetation and, hence, cause persistent changes in ecosystem condition.
To indicate drought pressure, strong negative soil moisture anomalies are selected by setting a maximum value at -1 standard deviation (std). This threshold was selected to allow the monitoring of vegetation responses to only considerable soil moisture deficits. Choosing the threshold of -1 std follows the recommendations of the European Drought Observatory (EDO ) of the European Commission’s Joint Research Centre. This approach is also followed in the EEA indicator addressing soil moisture deficit (EEA, 2021).
By applying this threshold, drought impacts can better be distinguished from response in vegetation anomalies due to other environmental pressures such as e.g. wildfires, storms or insects infestations.
The temporal aggregation is performed by averaging the monthly SMA values extracted from the EDO within the vegetation growing season. The vegetation growing season was defined by using the start and the end date of the growing period (SOS or Start of Season and EOS or End Of Season, respectively) extracted from the Medium Resolution Vegetation Phenology and Productivity product of the Copernicus Land Monitoring Service. The SOS and EOS datasets can be explored and downloaded from EEA's data repository under sdi.eea.europa.eu. Direct links to the datasets:
The intensity of drought pressure is the annually aggregated SMA value, which will always be < -1. The drought pressure area is the sum of those grid cells where the growing season aggregated SMA values are < -1.
For the analytical units of this indicator the following datasets were used:
- Administrative boundaries, aligned with the Corine Land Cover: https://sdi.eea.europa.eu/catalogue/srv/eng/catalog.search#/metadata/08c0e074-4a98-4545-bd85-f58fe3f74d82
- Environmental Zones: https://sdi.eea.europa.eu/catalogue/srv/eng/catalog.search#/metadata/6ef007ab-1fcd-4c4f-bc96-14e8afbcb688
- Corine Land Cover accounting layers 2000 and 2018: https://sdi.eea.europa.eu/catalogue/srv/eng/catalog.search#/metadata/fa9bd2f5-8006-42e7-8090-7b9f9b09bf29 and https://sdi.eea.europa.eu/catalogue/srv/eng/catalog.search#/metadata/5a5f43ca-1447-4ed0-b0a6-4bd2e17e4f4d
- Ecosystem types derived from the Corine Land Cover as Look Up Tables (can be distributed upon request).
- Land cover flows: https://sdi.eea.europa.eu/catalogue/srv/eng/catalog.search#/metadata/835d25e0-b9dc-4fb9-a8b6-f9e5336fa357
The pixel based annual drought pressure intensity values are extracted to the analytical units by means of area weighted spatial averaging that resulted in 2700000 records in the database, which is easy to handle in personal computers. Drought impact intensity is then expressed as the minimum value of the area weighted averages within the spatial units. The number of pixels that complied with the criteria in Eq. 1 are then summed within the analytical units and multiplied by 0.25 to express the 500m spatial resolution grid cells in km2 measurement unit.
Annual drought impact is quantified as:
SMA(gs)<0 and LINTa<-0.5 (Equation 2)
Where LINTa (Large Integral anomaly) refers to the 2000-2021 annual anomalies in growing season productivity derived from remote-sensing data and approximated using vegetation indices (see more explanation below).
The LINT anomalies were calculated as standard deviations from the long-term mean:
LINTa(year xi-n)=(LINT(xi)-LINT(LTA))/LINT(std)) (Equation 3)
Where xi-n indexes the time series (from i=2000 till n=2021), LINT(LTA) is the long term, or 2000-2021 average of the LINT values and LINT(std) is the long term standard deviation of the LINT values for the same period.
The threshold of a -0.5 standard deviation was selected to indicate small deviations from the long-term mean and to allow for moderate productivity levels under drought impact to be accounted for. In a Europe-wide study, this is a pragmatic solution that provides a wide overview of drought impact situations in Europe. However, local studies might consider setting a lower or higher threshold to reflect local conditions.
As vegetation productivity decline may be also caused by anthropogenic impacts, pixels with land use change were excluded from the statistical population based on the Copernicus Corine Land Cover 2000-2018 accounting layers datasets.
Vegetation productivity: LINT, or Large
In summary, vegetation productivity is derived from remote-sensing observed time series data of vegetation indices. The vegetation index used for the LINT index is the Plant Phenology Index (PPI) (Jin and Eklundh, 2014). The PPI is based on the MODIS Nadir BRDF-adjusted reflectance product (MODIS MCD43 NBAR). The product provides reflectance data for the MODIS ‘land’ bands (1-7), adjusted using a bidirectional reflectance distribution function. This function models values as if they were collected from a Nadir view to remove so-called cross-track illumination effects. The PPI is a new vegetation index optimised for the efficient monitoring of vegetation phenology. It is derived from radiative transfer solution using reflectance in the visible-red (RED) and near-infrared (NIR) spectral domains. The PPI is defined as having a linear relationship with the canopy green Leaf Area Index (LAI) and its temporal pattern is very similar to the temporal pattern of gross primary productivity (GPP) estimated by flux towers at ground reference stations. The PPI is less affected by the presence of snow than other commonly used vegetation indices such as the Normalized Difference Vegetation Index (NDVI) or the Enhanced Vegetation Index (EVI).
The product is distributed with a 500m pixel size (MODIS Sinusoidal Grid) with an 8-day compositing period. The large integral, or LINT, used in this indicator is the mathematical integral calculation of the smoothed and gap-filled PPI time series data between the start and end of the growing season points, being the SOS and EOS datasets described above.
All input data sets are derived with wall-to-wall coverage of the land surface of the EEA-38 region.
No gap filling was needed.
The indicator is a headline indicator for monitoring progress towards the 8th Environment Action Programme. It contributes mainly to monitoring aspects of the 8th EAP priority objective Article 2.2.b that shall be met by 2030: ‘continuous progress in enhancing and mainstreaming adaptive capacity, including on the basis of ecosystem approaches, strengthening resilience and adaptation and reducing the vulnerability of the environment, society and all sectors of the economy to climate change, while improving prevention of, and preparedness for, weather- and climate-related disasters’ (EU,2022). More specifically, and in accordance with the European Commission Communication on the 8th EAP monitoring the indicator assesses whether the EU will ‘decrease the area impacted by drought and loss of vegetation productivity’ by 2030, (EC, 2022).
Justification for indicator selection
Droughts are extreme climate events that are induced by temporary water deficits and may be related to a lack of precipitation, soil moisture, streamflow or any combination of the three taking place at the same time. Droughts differ from other extreme natural events in several ways. First, unlike earthquakes, floods or tsunamis, which occur along generally well-defined fault lines, river valleys or coastlines, droughts can occur anywhere (with the exception of permanent snow cover or desert regions, where conditions such as drought do not occur). Second, on one hand droughts are extreme events which can occur several times within a year causing strong and contemporary impact on the ecosystems. On the other hand droughts can also develop gradually, resulting from a prolonged period (from months to years) of water supply conditions that are below average at a specific location.
Droughts can occur in most parts of the world, even in wet and humid regions, and can have profound impacts on agriculture, industry, tourism and ecosystems and the services they provide. For example, in arid and semi-arid ecosystems (including the Mediterranean regions), limited water availability is a recurrent phenomenon and governs plant growth and phenology. On the other hand, in temperate, boreal and tropical ecosystems, sporadic prolonged dry periods can lead to water-limited conditions and have far-reaching impacts on ecosystems’ carbon balance and structure. The immediate impacts of droughts within the growing season (i.e. a few weeks in duration) are, for example, declines in crop production, poor pasture growth and declines in fodder supplies from crop residues. Prolonged water shortages (e.g. of several months or years in duration) may, among other things, lead to a reduction in hydro-electric production and potentially to increase wildfire occurrences.
The monitoring and assessment of drought impacts are complex because different types of impacts vary in their severity and often vary depending on the different phases of the given drought event. Therefore, most empirical studies of drought impacts have focused on agricultural crop production, which is direct, immediately observable, well understood and easy to quantify. Reports on drought impacts in the category ‘terrestrial ecosystems’ were found for a only few years and are limited in number in the European Drought Impact Report Inventory (EDII) database (Stahl et al., 2016). This is consistent with the earlier conclusions of Lackstrom et al. 2013, who claim that there is a lack of data on and understanding of the impacts of droughts on sectors other than agriculture and water resources.
Hence, due to a lack of records of direct impacts of drought on ecosystems, a proxy for ecosystems condition is needed. Differences in the physiological response of vegetation to water deficits cause differences in the sensitivity and resilience of terrestrial ecosystems to drought, and ultimately influence the types of impacts that droughts have, i.e. impacts that slow growth or reduce greenness, that lead to loss of biomass or that result in plant mortality. Consequently, significant changes in vegetation productivity provide an indication/early warning of imminent, irreversible impacts on ecosystems’ equilibrium states. Furthermore, by requiring the reduction in vegetation productivity to coincide with a negative soil moisture anomaly, the likelihood of other phenomena than drought being the cause of the reduced vegetation productivity is reduced.
Results from the dashboard:
Long term average (2000-2020) drought impact in forests was largest in Cyprus, Luxembourg, Malta and Portugal (dashboard), with up to 8% of forests affected annually. In 2021 in the EU, only forests in Finland and Sweden were affected more than the 2000-2020 average. Among the non-EU countries, forests in Albania, Kosovo, Montenegro, Norway and Türkiye showed higher than average impact. The 2000-2020 average drought impact in croplands was highest in Cyprus, Luxemburg and Malta (9% of the croplands impacted annually). In Cyprus, Finland and Greece the 2021 drought impact in croplands was higher than the average of the previous years whereas in the non-EU countries crops in Albania, Kosovo, Montenegro, Norway and Türkiye were affected more than the previous years. The 2000-2020 average impact on grasslands was highest in Cyprus, Estonia, Lithuania and Luxembourg (annually up to 10% of grasslands impacted). In the EU the 2021 impact on grasslands was only in Finland and Sweden higher than the 2000-2020 annual average impact, whereas in non-EU countries the 2021 impact on grasslands exceeded the annual average in Albania, Bosnia, Kosovo, Montenegro, Norway and Türkiye. Although drought impacts on wetlands affected less than 0.25% of each country’s wetland area, these impacts are significant, as wetlands are very important for biodiversity and climate change mitigation and adaptation.
In the beginning of the century drought impact mostly occurred in South, South-East and Continental Europe. In the last decade countries in the Atlantic region (e.g. the Benelux states), in the Baltic region and in Scandinavia also experienced strong drought impact on increasingly large areas. Exceptional drought impacts in the EU-27 region occurred in 2005 in Portugal, in 2006 in Estonia, in 2014 in Cyprus, in 2016 in Malta, in 2019 in Lithuania and in 2020 in Luxembourg, where drought impacted around or above 50% of the country´s area.
In May 2020, the EU adopted a biodiversity strategy for 2030 (COM(2020) 380 final), related to protecting and restoring nature. The strategy states that the ‘biodiversity crisis and the climate crisis are intrinsically linked. For the EU, the cost of not reaching the 2020 biodiversity strategy headline target of halting the loss of biodiversity and ecosystem services has been estimated at EUR50 billion per year. In addition to these economic costs, loss of biodiversity means that ecosystems and the societies that rely upon them are more fragile and less resilient in the face of challenges such as climate change, pollution and habitat destruction. Droughts have an impact on several land and soil functions, as well as ecosystem services, in both urban and rural areas. By putting pressure on natural ecosystems, droughts hampered the achievement of the EU biodiversity strategy’s 2020 objectives.
Climate change accelerates the loss of biodiversity through droughts, flooding and wildfires, while the loss and unsustainable use of nature in turn also contribute to climate change’. The new EU Strategy on Adaptation to Climate Change (COM(2021) 82 final) shows the importance of healthy soils in minimising impacts of floods and droughts. The new Soil Strategy for 2030 (COM(2021) 699 final) points out the crucial and urgent need to address the human caused impacts on soils due to climate change and it calls for the same level of protection for soils that is given to air and water. Therefore, the Committee strongly recommends to integrate in the new EU Soil Strategy actions against erosion and desertification linked to extreme floods, droughts and fires. Climate change impacts is also reflected in the proposal for a nature restoration law, adopted in June 2022 by the European Commission, that aims to put all natural and seminatural ecosystems on the path to recovery by 2030. Droughts negatively affect agricultural ecosystems, the resilience of forest ecosystems and in urban ecosystems droughts indirectly affect the ability of green urban spaces to protect people against heatwaves. In particular, the impacts of extended droughts on ecosystems need to be assessed because they can lead to significant loss of vegetation productivity and irreversible damage to the condition of ecosystems and land degradation, in extreme cases desertification.
Drought pressures on natural ecosystems also play an important role in the EU’s ability to implement its strategy on green infrastructure (GI). In contrast to the most common ‘grey’ (human-made, constructed) infrastructure approaches that serve one single objective, GI promotes multifunctionality, which means that the same area of land is able to perform several functions and offer multiple benefits if its ecosystems are in a healthy state. More specifically, GI aims to enhance nature's ability to deliver multiple valuable ecosystem goods and services, potentially providing a wide range of environmental, social, climate change adaptation and mitigation, and biodiversity benefits. Droughts diminish the normal condition of ecosystems and their capacity to provide services that could be integrated into GI.
The EU legislation for LULUCF as part of the 2030 climate target sets clear targets for the LULUCF sector for each Member States. The capacity of forests and other land uses to store and remove carbon from the atmosphere will depend on management as well as a number of natural circumstances, such as variations in growing conditions (soil quality, temperature, precipitation and droughts) and frequency of natural disturbances (storms and fires). The regulation provides some flexibility for Member States to compensate excess emissions due a changing climate including natural disturbances that are beyond their control and cause significant emissions. To apply these flexibilities there is a need for spatial explicit information on the long-term impact of climate change resulting in excess emissions or diminishing sinks that are beyond their control or the effects of an exceptionally high proportion of organic soils in the managed land area, including information such as aridity, mean temperatures, mean precipitations, frost days, the duration of methodological or soil moisture droughts. The accounting for natural disturbances is following a statistical approach where Member States need to provide information on the type of natural disturbance and how they have been accounted for since 2001 to 2020 and some more information. Accounting for natural disturbances has been foreseen for forests only for the 2021-2025 reporting period, whereas the new LULUCF regulation foresees application to land land uses. The drought impact indicator can be used to confirm submitted MSs data when natural disturbances are reported especially from 2026 on when natural disturbances can be accounted for on all impacted lands.
The role of the common agricultural policy (CAP) is to provide a policy framework that supports and encourages producers to address economic, environmental (i.e. relating to resource efficiency, soil and water quality, and threats to habitats and biodiversity) and territorial challenges, while remaining coherent with other EU policies. This translates into three long-term CAP objectives: (1) viable food production, (2) sustainable management of natural resources and climate action, and (3) balanced territorial development. Given the pressure that droughts put on natural resources, agriculture’s environmental performance has to improve through more sustainable production methods. Farmers also have to adapt to challenges stemming from changes to the climate by pursuing climate change mitigation and adaption actions.
No specific targets.
Related policy documents
- Climate-ADAPT: Adaptation in EU policy sectors. Overview of EU sector policies in which mainstreaming of adaptation to climate change is ongoing or explored.
- Climate-ADAPT: Country profiles. Overview of activities of EEA member countries in preparing, developing and implementing adaptation strategies.
- Decision No 1386/2013/EU of the European Parliament and of the Council of 20 November 2013 on a General Union Environment Action Programme to 2020 ‘Living well, within the limits of our planet’. Published: 2013-11-20 Corporate author(s): Council of the European Union, European Parliament Subject: biodiversity , economic growth, environmental impact , environmental protection, EU programme, investment , management of resources , pollution control.
- EU 2020 Biodiversity Strategy. In the Communication: Our life insurance, our natural capital: an EU biodiversity strategy to 2020 (COM(2011) 244) the European Commission has adopted a new strategy to halt the loss of biodiversity and ecosystem services in the EU by 2020. There are six main targets, and 20 actions to help Europe reach its goal. The six targets cover: full implementation of EU nature legislation to protect biodiversity; better protection for ecosystems, and more use of green infrastructure; more sustainable agriculture and forestry; better management of fish stocks; tighter controls on invasive alien species; a bigger EU contribution to averting global biodiversity loss.
- EU Adaptation Strategy Package. In April 2013, the European Commission adopted an EU strategy on adaptation to climate change, which has been welcomed by the EU Member States. The strategy aims to make Europe more climate-resilient. By taking a coherent approach and providing for improved coordination, it enhances the preparedness and capacity of all governance levels to respond to the impacts of climate change.
- EU Biodiversity Strategy for 2030. The European Commission has adopted the new EU Biodiversity Strategy for 2030 and an associated Action Plan (annex) - a comprehensive, ambitious, long-term plan for protecting nature and reversing the degradation of ecosystems. It aims to put Europe's biodiversity on a path to recovery by 2030 with benefits for people, the climate and the planet. It aims to build our societies’ resilience to future threats such as climate change impacts, forest fires, food insecurity or disease outbreaks, including by protecting wildlife and fighting illegal wildlife trade. A core part of the European Green Deal, the Biodiversity Strategy will also support a green recovery following the COVID-19 pandemic.
- Evaluation of the EU Adaptation Strategy Package. In November 2018, the EC published an evaluation of the EU Adaptation Strategy. The evaluation package comprises a Report on the implementation of the EU Strategy on adaptation to climate change (COM(2018)738), the Evaluation of the EU Strategy on adaptation to climate change (SWD(2018)461), and the Adaptation preparedness scoreboard Country fiches (SWD(2018)460). The evaluation found that the EU Adaptation Strategy has been a reference point to prepare Europe for the climate impacts to come, at all levels. It emphasized that EU policy must seek to create synergies between climate change adaptation, disaster risk reduction efforts and sustainable development to avoid future damage and provide for long-term economic and social welfare in Europe and in partner countries. The evaluation also suggests areas where more work needs to be done to prepare vulnerable regions and sectors.
- Green Infrastructure (GI) — Enhancing Europe’s Natural Capital. Green infrastructure is a strategically planned network of natural and semi-natural areas with other environmental features designed and managed to deliver a wide range of ecosystem services such as water purification, air quality, space for recreation and climate mitigation and adaptation. This network of green (land) and blue (water) spaces can improve environmental conditions and therefore citizens' health and quality of life. It also supports a green economy, creates job opportunities and enhances biodiversity. The Natura 2000 network constitutes the backbone of the EU green infrastructure.
- Our life insurance, our natural capital: an EU biodiversity strategy to 2020. European Commission (2011).
- Science for Environment Policy. In Depth Report – Ecosystems Services and Biodiversity. European Commission 2015.
The approach cannot account for land use/land cover changes that have occurred within a pixel for the period of analysis. For example, clear cuts within forest ecosystems or the use of irrigation systems as part of the management in agricultural areas might increase or decrease the vegetation productivity independently of drought occurrences. This can introduce noise in the datasets that might bias the pixel-based relationships between drought pressure and vegetation productivity.
Another source of uncertainty is related to the simplification of the drought impact model for its implementation in the operational setting. On one hand, the same thresholds for deviations in soil moisture and vegetation production imply similar impacts/impact severity in different sectors (agriculture, forestry, etc), which gives an acceptable approximation on the continental scale but might need to be adjusted to local conditions. In this study, only meteorological drought distribution and intensity are considered. Still, in some cases, the start, end, severity and spatial extent of a drought, as well as the propagation of its impacts through the whole land systems, might change as a result of additional climate and/or surrounding biophysical conditions, such as temperature, snowpack, albedo and soil’s water-holding capacity.
Data sets uncertainty
The dataset represents the average trend of productivity of all terrestrial ecosystems within an area covered by a pixel of 500x500m. Therefore, the dataset can only be used at the ecosystem level indicating drought impacts on main terrestrial ecosystems. As opposed to field measurements, remote sensing products measure vegetation light absorption from a satellite at several hundred km height which might introduce bias due to atmospheric disturbances.
No uncertainty has been identified.