A 250‐Year European Drought Inventory Derived From Ensemble Hydrologic Modeling

Abstract

We present a 250‐year (1766–2015) inventory of European meteorological, hydrological, and agricultural droughts derived from ensemble simulations of the mesoscale Hydrological Model (mHM). The inventory of droughts takes into account an ensemble of 100 simulations from the hydrological model, allowing for assessment of how different meteorological forcing and model parameterizations affect a drought ranking. For the most extreme droughts, the variability in the ranking of drought events is low, while for the years with moderate precipitation deficits, the variability increases. Despite the underlying uncertainties, our drought inventory shows increased recurrence of soil moisture droughts in the Mediterranean and declining spatial extent of hydrological drought in Central Europe over the last three decades.

Increased future occurrences of the exceptional 2018–2019 Central European drought under global warming

“…The assessment of consecutive drought characteristics from 1766–2019 is performed over the central Europe using three types of observed gridded meteorologic datasets: Casty et al 22 for period 1766–1900, CRU TS dataset 23 for period 1901–1949; and E-OBS 45 for period 1950–2019. The composite dataset using monthly precipitation and air temperature is analysed at a spatial resolution of , similarly as in to previous studies 25 , 46 . Furthermore, the E-OBS is used for correcting possible biases in the Casty and CRU data, which is trained on the overlapping period 1950–2015 25 , 46 .…”

“…The composite dataset using monthly precipitation and air temperature is analysed at a spatial resolution of , similarly as in to previous studies 25 , 46 . Furthermore, the E-OBS is used for correcting possible biases in the Casty and CRU data, which is trained on the overlapping period 1950–2015 25 , 46 . To examine the characteristics of the consecutive droughts in the past and future, we procure the state-of-the-art global climate model simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) 38 (detailed description is provided in Supplementary Table S1 ).…”

Moving beyond the catchment scale: Value and opportunities in large‐scale hydrology to understand our changing world

“…This is reflected by the aforementioned difficulty of separating human influence from natural drivers of hydrological drought (Van Loon et al, , ). For such reasons, endeavours such as large‐scale hydrological data rescue (e.g., Le Gros et al, ), reconstructing long‐term and large‐scale high‐resolution climate datasets (Devers, Vidal, Lauvernet, Graff, & Vannier, ) and corresponding near‐natural hydrological datasets (e.g., Hanel et al, ; Moravec, Markonis, Rakovec, Kumar, & Hanel, ) are central in understanding the large temporal and spatial variations of hydrology. Compatibility between, or merging of, national‐scale datasets (e.g., Caillouet, Vidal, Sauquet, Graff, & Soubeyroux, ; Keller et al, ) would be a further advance, as would improved quality assessment of large repositories such as the Global Runoff Data Centre under the auspices of the World Meteorological Organisation.…”

Long‐term variability and trends in meteorological droughts in Western Europe (1851–2018)

“…Furthermore, uncertainty in drought trends in Europe is linked to the use of different periods of analysis (Hannaford et al ., 2013) and deployment of a wide spectrum of possible drought metrics. The latter employ several hydroclimatic variables including, precipitation (Lloyd‐Hughes and Saunders, 2002; Vicente‐Serrano, 2006a), atmospheric evaporative demand (Vicente‐Serrano et al ., 2014b; Spinoni et al ., 2015; Stagge et al ., 2017), streamflow (Hisdal et al ., 2001; Parry et al ., 2012; Hannaford et al ., 2013; Lorenzo‐Lacruz et al ., 2013), groundwater (Lorenzo‐Lacruz et al ., 2017; Marchant and Bloomfield, 2018) and soil moisture simulations (Hanel et al ., 2018; Moravec et al ., 2019).…”