How do we identify flash droughts? A case study in Central European Croplands

Abstract

Many definitions and delineation methods exist for identifying flash droughts (FDs), which are events of rapid and unusual large depletion of root-zone soil moisture, in comparison to average moisture conditions, due to climatic compound conditions over a short period of several weeks. Six FD identification methods were compared to analyse their functioning using data from several experimental cropland sites across Central Europe. Co- and misidentification of the FD time series were assessed using confusion and synchronicity metrics on a local scale. Even though a large degree of synchronicity of individual FD events was observed, some divergence in drought periods was detected, which was related to four intrinsic differences in the underlying FD definitions: (1) type of critical variable; (2) velocity of drought intensification; (3) pre-set threshold values for final depletion and/or (4) minimum length of the duration of FDs. To balance the strengths and weaknesses of those methods that are not based on soil moisture, we suggest using an ensemble approach for event identification, which is validated in this study for the temperate central European region. In doing so, the current unclearly defined sub-types of FDs can be detected, regardless of the different combinations of compound drivers and differences in intensification dynamics. All methods were implemented in an R package and are available as a Shiny app for the public.

Flash drought: A state of the science review

“…Noguera et al (2021) demonstrated that using different variables, even while employing the same identification methodology, can reveal very different results regarding the spatial and seasonal hotspots of flash drought within Spain. Alencar and Paton (2022) used time series analysis to show how various methods and indicators result in substantial variability in flash drought timing and intensity.…”

Exploring drought hazard, vulnerability, and related impacts to agriculture in Brandenburg

“…We further calculated empirical yield gaps per county for 12 crops for the last 10 years (2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020)(2021)(2022), by subtracting actual reported yields (total production in tonnes) by the regional statistical authority (Amt für Statistik Berlin-Brandenburg, 2022;Alencar, 2022) from an estimate of expected yields under non-drought conditions. We refer to expected yields as the product of cropped area (per crop type in a given year) and the respective 5-year average yield (tonnes per hectare) per LBG from the time 2010-2014.…”

Flash droughts and their impacts -using newspaper articles to assess the perceived consequences of rapidly emerging droughts

“…Rapid onset is a decisive factor in the definition FDs. Multiple conflicting definitions have been proposed since its introduction in the academic literature (Alencar and Paton 2022). An initial debate focused on whether FDs were short-lived droughts (Mo and Lettenmaier 2016), or intense evolving droughts (Ford and Labosier 2017).…”

“…However, seminal questions remain concerning what should be considered an FD. Although clear thresholds have been proposed (Christian, Basara, Otkin, et al 2019;Li et al 2020;Osman et al 2021;Yuan et al 2023), their transferability across case studies is limited (Alencar and Paton 2022). The lack of wellestablished criteria has led to a growing diversity of definitions and monitoring tools for FDs.…”

“…The lack of wellestablished criteria has led to a growing diversity of definitions and monitoring tools for FDs. However, these definitions and tools still lack validation and transferability (Lisonbee, Woloszyn, and Skumanich 2021;Alencar and Paton 2022). Hence, FD research would benefit from studies applying multiscale and multi-variable frameworks (Liang and Yuan 2021).…”