COLLECTION

Drought Observatories datasets

Acronym: DROUGHT

Description

Drought monitoring is based on various indices: the standardized precipitation index (SPI), which shows the deviation from average precipitation and is therefore directly related to drought hazard, while additional indices monitor the status of soil moisture, vegetation, groundwater levels, etc. to assess the potential impacts of droughts.

A method that combines different drought indices (SPI, soil moisture anomalies

and fAPAR anomalies) is proposed in order to identify areas affected by agricultural

drought and also areas with the potential to be affected. The method outcome is the Combined Drought Indicator (CDI) consisting in a classification scheme based in three drought impact levels ("Watch", "Warning" and "Alert"), corresponding to the different stages of the idealized agricultural drought cause-effect relationship. Two additional levels, "Partial recovery" and "Recovery", identify the stages of the vegetation recovery process.

Drought-related indices are processed with dedicated procedures by means of different software products and stored as Oracle spatial tables (grids, see http://edo.jrc.ec.europa.eu/edov2/php/index.php?id=1155) or as raster images. These indices are presented by means of web GISs and charts and delivered via OGC WMS and WCS. See http://edo.jrc.ec.europa.eu/edov2/php/index.php?id=1104 for more details. At the moment only the Combined Drought Indicator (CDI) is registered in this collection.

Contact

Email
Alfred.DE-JAGER (at) ec.europa.eu

Datasets (44)

DATASET | Last updated:
EDO Combined Drought Indicator (CDI) (version 3.0.2)

Combined Drought Indicator based on SPI, soil moisture and fAPAR, to identify areas with potential to suffer agricultural drought, areas where the vegetation is already affected by...

DATASET | Last updated:
EDO Soil Moisture Index (SMI) (version 2.1.3)

Average root zone Soil Moisture Index (SMI) at 5-km spatial resolution. The dataset is derived from 6-hourly LISFLOOD modelled soil moisture in the top two soil layers, as produced...

DATASET | Last updated:
EDO Soil Moisture Index Anomaly (SMA) (version 2.1.3)

Soil Moisture Anomaly (SMA) at 5-km spatial resolution, computed as standardized deviation from a baseline period 1995-2020. The dataset is derived from 6-hourly LISFLOOD modelled ...

DATASET | Last updated:
EDO Combined Drought Indicator (CDI) (version 1.6.1)

Combined Drought Indicator (CDI) based on SPI, soil moisture and fAPAR, to identify areas with potential to suffer agricultural drought, areas where the vegetation is already affec...

DATASET | Last updated:
GDO Ensemble Soil Moisture Anomaly (version 2.3.0)

Soil moisture anomaly maps are computed on a 30-day moving window at a spatial resolution of 0.1 decimal degrees and updated every 10 days. Moving windows have an ordinal reference...

DATASET | Last updated:
EDO Heat and Cold Wave Index (version 1.0.0)

Heat- or coldwaves are classified by duration in days starting from more than one day. The present-day heat/cold wave is classified by accumulating all the past consecutive days wi...

DATASET | Last updated:
EDO Minimum Daily Temperature (version 1.0.0)

Daily interpolated minimum temperature using around 4000 weather stations across Europe and its surrounding areas. The data are interpolated using an inverse distance algorithm sea...

DATASET | Last updated:
EDO Maximum Temperature Anomaly (version 1.0.0)

Anomalies of maximum daily temperature are computed based on the interpolated maximum temperature data per day from 1981 and up to and including 2010. The temperature results are b...

DATASET | Last updated:
EDO Maximum Daily Temperature (version 1.0.0)

Daily interpolated maximum temperature using around 4000 weather stations across Europe and its surrounding areas. The data are interpolated using an inverse distance algorithm sea...

DATASET | Last updated:
EDO Low Flow Index (LFI) (version 2.1.0)

The LFI indicator exploits the simulated 6-hours river water discharge outputs of the JRC’s in-house LISFLOOD hydrological model, in order to capture unbroken consecutive periods o...

Additional information

Published by
European Commission, Joint Research Centre
Created date
2018-12-14
Modified date
2023-03-20
Landing page
http://edo.jrc.ec.europa.eu/