ALPINE DROUGHT
OBSERVATORY

Indices
Reported Impacts
Impacts and risk
Impact probabilities
Vulnerabilities
Hydro
About the Data
About the Project
Terms and Conditions

About the Data

The ADO project is generating a wide array of datasets for monitoring of drought which are all made available under an open data license. All datasets are shared through our Environmentdal Data Platform, which offers a variety of interfaces for accessing the data, including hosted jupyter environments, openEO API through the web editor or directly using the python and R client libraries and OGC standards like the WFS and Web Coverage Service (WCS). To create a user account on the EDP please contact SupportCSS@eurac.edu​​.

An overview of the code that makes up the ADO Platform can be found here on GitLab.

The data shown on this webpage is CC-BY-4.0 licensed and can be found on this Github Repository

Drought Indices

Citation

If you use any ADO drought indices from the ADO Webportal or its Github data repository, the Environmental Data Platform (raw data access) please cite the data like shown here:

Standardised Precipitation Index (SPI)

Standardised Precipitation-Evapotranspiration Index (SPEI)

Standardised Snow Pack Index (SSPI)

Soil Moisture Anomalies (SMA)

Vegetation Health Index (VHI) / Vegetation Condition Index (VCI)

Metadata and Raw Data Access on the Environmental Data Platform

All ADO collections available on the EDP can be found using this link.

Hydrogical Data

Citation

  • TBD

Access to Hydrological Database

The database contains observational daily discharge and water level data deriving from the first measurement (which differs for each region) to the present, with more than 1400 stations. These datasets were collected from multiple data providers within the ADO study region, covering the countries Austria, France, Germany, Italy, Slovenia, and Switzerland. The spanned period is 1869-2021. For some regions in Italy there are records to 2022. The missing data were added to have a continuous time series.

Access the Hydrological Database directly via the Environmental Data Platform

Drought Impacts

Citation

  • Reported Impacts, TBD
  • Impact Probabilities, TBD
  • Vulnerabilities, TBD

Reported impacts

The reported drought impacts stem from the Alpine Drought Impact report Inventory (EDIIALPS V1.0) developed during the project period. To create EDIIALPS, information was gathered and transcribed from national databases and reports. Compiled knowledge on the impacts of historic and recent drought events from a variety of available information sources is presented as this has never been done across the European Alpine region. The Alpine Space covers the Alps and their foothills, as well as different climatic zones and therefore allows the consideration of water and natural resource flow and exchange typical of mountain regions. With the region's extent, we therefore include drought impacts not only at high altitudes, but also in downstream areas of the water-rich source regions (e.g. the river basins Po, Rhine, Danube etc.). Besides the most prominent impact category 'agriculture and livestock farming', many impact reports also relate to 'public water supply', 'forestry', 'aquatic ecosystems'.

For further information on the database please read: Stephan, R., Erfurt, M., Terzi, S., Žun, M., Kristan, B., Haslinger, K., and Stahl, K.: An inventory of Alpine drought impact reports to explore past droughts in a mountain region, Natural Hazards and Earth System Sciences Discussions, 21, 2485–2501, available at https://doi.org/10.5194/nhess-21-2485-2021, 2021. To access EDIIALPS as a plain dataset follow this link https://doi.org/10.6094/UNIFR/218623

Impact probabilities

Explore the probability of soil-moisture drought impacts (DSM) and hydrological drought impacts (DH) across the Alpine Space!

DSM impacts cover mostly impacts on agriculture and forestry, and their occurrence probability is calculated with the Soil moisture anomalies (SMA-1). DH impacts cover mostly impacts on water supply, water quality, and freshwater ecosystems, and their occurrence probability is calculated with the Standardized Precipitation Evapotranspiration Index (SPEI-3). Select different index-scenarios to visualize the impact probability.

The darker the red, the more likely impacts occur. Regions without any impacts are coloured in white.

These risk maps have been developed with impact data from the EDIIALPS V1.0. Impacts in each NUTS region were assigned to two groups: soil-moisture drought impacts (DSM) and hydrological drought impacts (DH). The DSM impacts stem mostly from the impact categories Forestry, and Agriculture and livestock farming (see Deliverable DT3.1.1). The so-called hydrological drought impacts stem mostly from the impact categories Public water supply, Freshwater ecosystems and Water quality. For each NUTS3 region, we fit a generalized linear model with a logit link to regress the likelihood of a drought impact against SPEI-3 and SMA-1. With the fitted model we then predicted impact occurrences for different SPEI-3 and SMA-1 values in order to estimate the occurrence probability for each NUTS 3 region. NUTS 3 regions without sufficient DSM or DH impact data to estimate a model are shown as regions with missing ata. The method (model and scenario mapping) follows the method by Blauhut et al. (2015).

For further details on the application for ADO, please read: Deliverable DT3.2.1. Blauhut V., Gudmundsson L., Stahl K. (2015) Towards pan-European drought risk maps: quantifying the link between drought indices and reported drought impacts, Environmental Research Letters 10, 014008 https://doi.org/10.1088/1748-9326/10/1/014008

Vulnerability

The mapped vulnerability factors were identified by analyzing agriculture's vulnerability to drought in the two case study regions of the project: Thurgau (CH) and Podravska (SI). During semi-structured interviews project partners and external experts were asked to identify the most important factors contributing to the overall vulnerability an in addition, whether the factor has an increasing or decreasing effect on the final vulnerability in order to be able to quantitatively describe the vulnerability component. They identified 10 common factors for both study regions, whereas they identified 6 factors solely for Thurgau and 13 factors solely for Podravska. The applicability of these factors for other parts of the Alpine region can be questioned especially when considering the differences between the case study regions highlighting the region-specific character of vulnerability. However, the factors presented here and on the platform can be seen as a first estimate how vulnerable the agriculture across the Alpine Space is.

For further details read: Deliverable DT3.3.1 and Stephan, R., Terzi, S., Erfurt, M., Cocuccioni, S., Stahl, K., and Zebisch, M.: Assessing agriculture's vulnerability to drought in European pre-Alpine regions, Nat. Hazards Earth Syst. Sci., 23, 45–64, https://doi.org/10.5194/nhess-23-45-2023, 2023.