This dataset contains the results of a farmers’ survey in the Ping Catchment in Thailand. The aim of this survey was to identify the specific socioeconomic impacts that historical droughts in the Ping catchment have had for agricultural communities, and identify factors affecting adaptation decisions, as well as analyse the communications with and amongst farmers at the local scale in the Ping catchment during drought. Villages in the Ping catchment with a history of drought were selected to represent typical agricultural production typologies. In total, 176 questionnaires were completed with a close to even distribution of respondents coming from the provinces of Chiang Mai (n=41), Lamphun (n=45), Kamphaeng Phet (n=45) and Tak (n=45). Full details about this dataset can be found at https://doi.org/10.5285/155e1867-bc9d-44f0-9f85-0f682964f720

This dataset contains high-resolution (5 km) Standardized Precipitation Evaporation Index (SPEI-HR) drought data for Central Asia. There are forty-eight different SPEI time scales and the available period is from 1981 - 2018, the data was produced using Climate Hazards group InfraRed Precipitation with Station’s (CHIRPS) precipitation dataset and Global Land Evaporation Amsterdam Model’s (GLEAM) potential evaporation dataset. The SPEI-HR dataset, over time and space, correlates fairly well with SPEI values estimated from coarse-resolution Climate Research Unit (CRU) dataset. Furthermore, the SPEI-HR dataset, for 6-month timescale, displayed a good correlation of 0.66 with GLEAM root zone soil moisture and a positive correlation of 0.26 with normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modelling System (GIMMS).

This dataset consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM). The SPEI dataset covers the whole of the African continent for a 36-year-long period (1981–2016) at a horizontal resolution of 5 km (0.05 deg) and a monthly time resolution. The dataset is provided in NetCDF format with in a Geographic Lat/Lon projection. Due to the lower reliability of SPEI over areas with low hydro-climatic variability, the areas with barren or sparsely vegetated areas in Africa were masked out based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface type product (MCD12Q1).

Data comprise measurements of plant biomass and community composition, soil microbial community composition, greenhouse gas emissions and soil carbon and nitrogen pools from a drought experiment superimposed on a the long-term Colt Park grassland restoration experiment in northern England. Rainfall was manipulated using rain-out shelters on experimental grassland plots where fertiliser application and seed addition have been managed to enhance plant species diversity. The scientific purpose was to test the hypothesis that management aimed at biodiversity restoration increases the resistance and recovery of carbon cycling to short-term summer drought. Full details about this dataset can be found at https://doi.org/10.5285/8a41b2a2-01d7-409e-adf5-fba3f3770f29

5km gridded Standardised Precipitation Index (SPI) data for Great Britain, which is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al [1]. There are seven accumulation periods: 1, 3, 6, 9, 12, 18, 24 months and for each period SPI is calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1862 to 2015. This version supersedes previous versions (version 2 and 3) of the same dataset due to minor errors in the data files. NOTE: the difference between this dataset with the previously published dataset "Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]" (Tanguy et al., 2015; https://doi.org/10.5285/94c9eaa3-a178-4de4-8905-dbfab03b69a0) , apart from the temporal and spatial extent, is the underlying rainfall data from which SPI was calculated. In the previously published dataset, CEH-GEAR (Tanguy et al., 2014; https://doi.org/10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e) was used, whereas in this new version, Met Office 5km rainfall grids were used (see supporting information for more details). The methodology to calculate SPI is the same in the two datasets. [1] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California. Full details about this dataset can be found at https://doi.org/10.5285/233090b2-1d14-4eb9-9f9c-3923ea2350ff

This dataset is a model output, from the Grid-to-Grid hydrological model driven by observed climate data (CEH-GEAR rainfall and Oudin temperature-based potential evaporation). It provides daily mean river flow (m3/s) for 260 catchments, for the period 1891 to 2015. The catchments correspond to locations of NRFA gauging stations (http://nrfa.ceh.ac.uk/). The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity (http://www.mariusdroughtproject.org/). Full details about this dataset can be found at https://doi.org/10.5285/0ceb4f85-0bbf-49f0-ab70-cfc137ab7d4d

Standardised Precipitation Index (SPI) data for Integrated Hydrological Units (IHU) groups (Kral et al. [1]). SPI is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [2]. SPI is calculated for different accumulation periods: 1, 3, 6, 12, 18, 24 months. Each of these is in turn calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1961 to 2012. [1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Groups. NERC-Environmental Information Data Centre doi:10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902 [2] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California. Full details about this dataset can be found at https://doi.org/10.5285/dfd59438-2170-4472-b810-bab33a83d09f

This dataset is a model output, from the Grid-to-Grid hydrological model driven by observed climate data (CEH-GEAR rainfall and Oudin temperature-based potential evaporation). It provides monthly mean flow (m3/s) and soil moisture (mm water/m soil) on a 1 km grid for the period 1891 to 2015. To aid interpretation, two additional spatial datasets are provided: - Digitally-derived catchment areas on a 1km x 1km grid - Estimated locations of flow gauging stations on a 1km x 1km grid and as a csv file. The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity (http://www.mariusdroughtproject.org/). Full details about this dataset can be found at https://doi.org/10.5285/f52f012d-9f2e-42cc-b628-9cdea4fa3ba0

This dataset is a model output, from the Grid-to-Grid hydrological model driven by weather@home2 climate model data. It provides a 100-member ensemble of daily mean river flow (m3/s) for 260 catchments, for the following time periods: historical baseline (HISTBS: 1900-2006), near-future (NF: 2020-2049) and far-future (FF: 2070-2099). It also includes a baseline period (BS: 1975-2005). The catchments correspond to locations of NRFA gauging stations (http://nrfa.ceh.ac.uk/). The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity. Full details about this dataset can be found at https://doi.org/10.5285/f6cac471-7d92-4e6d-be8a-9f7887143058

This dataset is a model output, from the Grid-to-Grid hydrological model driven by observed climate data (CEH-GEAR rainfall and MORECS potential evaporation). It provides daily mean river flow (m3/s) for 260 catchments, for the period 1960 to 2015. The catchments correspond to locations of NRFA gauging stations (http://nrfa.ceh.ac.uk/). The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity (http://www.mariusdroughtproject.org/). Full details about this dataset can be found at https://doi.org/10.5285/5f3c1a02-d5c4-4faa-9353-e8b68ce2ace2