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Drought directly and indirectly affects the entire socio-economic and environmental sectors in southwestern Germany. Such impacts are a result of the drought hazard and an underlying vulnerability of the systems. With respect to climate change and the dynamics of vulnerability over time, it becomes crucial to investigate the preceding components, in order to understand possible future magnitudes of the hazard and drivers of drought impacts. Therefore, drought indices were generated from the early nineteenth century in order to identify exceptional meteorological summer droughts. Documentary evidence and historical yield statistics were used to contextualise historical drought events by drought impacts and responses. Considering both, selected summer drought events were analysed and mutually compared based on the impact on society and ecology, as well as societal responses to these. The derived standardised indices highlight differences between severe droughts in duration and temporal peculiarity and put into perspective the current understanding of the intensity of recent drought hazards. The discourse analysis reveals that the propagation of drought and the kinds of impacts have remained rather similar through time, only shifting to modern livelihood assets. However, vulnerability, which strongly depends on the societal contexts, has changed over time and lowered severity of impacts, especially with regard to food and water supply, as well as human health.

Drought in Europe is a hazard with a wide range of transboundary, environmental and socio-economic impacts on various sectors including agriculture, energy production, public water supply and water quality. Despite the apparent importance of this natural hazard, observed pan-European drought impacts have not yet been quantitatively related to the most important climatological drivers to map drought risk on a continental scale. This contribution approaches the issue by quantitatively assessing the likelihood of drought impact occurrence as a function of the standardized precipitation evapotranspiration index for four European macro regions using logistic regression. The resulting models allow mapping the sector-specific likelihood of drought impact occurrence for specific index levels. For the most severe drought conditions the maps suggest the highest risk of impact occurrence for 'Water Quality' in Maritime Europe, followed by 'Agriculture & Livestock Farming' in Western Mediterranean Europe and 'Energy & Industry' in Maritime Europe. Merely impacts on 'Public Water Supply' result in overall lower risk estimates. The work suggests that modeling and mapping for North- and Southeastern Europe requires further enhancement to the impact database in these regions. Such maps may become an essential component of drought risk management to foster resilience for this hazard at large scale.

Droughts often have a severe impact on the environment, society, and the economy. The variables and scales that are relevant to understand the impact of drought motivated this study, which compared hazard and propagation characteristics, as well as impacts, of major droughts between 1990 and 2019 in southwestern Germany. We bring together high-resolution datasets of air temperature, precipitation, soil moisture simulations, and streamflow and groundwater level observations, as well as text-based information on drought impacts. Various drought characteristics were derived from the hydrometeorological and drought impact time series and compared across variables and spatial scales. Results revealed different drought types sharing similar hazard and impact characteristics. The most severe drought type identified is an intense multi-seasonal drought type peaking in summer, i.e., the events in 2003, 2015, and 2018. This drought type appeared in all domains of the hydrological cycle and coincided with high air temperatures, causing a high number of and variability in drought impacts. The regional average drought signals of this drought type exhibit typical drought propagation characteristics such as a time lag between meteorological and hydrological drought, whereas propagation characteristics of local drought signals are variable in space. This spatial variability in drought hazard increased when droughts propagated through the hydrological cycle, causing distinct differences among variables, as well as regional average and local drought information. Accordingly, single variable or regional average drought information is not sufficient to fully explain the variety of drought impacts that occurred, supporting the conclusion that in regions as diverse as the case study presented here, large-scale drought monitoring needs to be complemented by local drought information to assess the multifaceted impact of drought.

Present-day drought early warning systems provide the end-users information on the ongoing and forecasted drought hazard (e.g. river flow deficit). However, information on the forecasted drought impacts, which is a prerequisite for drought management, is still missing. Here we present the first study assessing the feasibility of forecasting drought impacts, using machine-learning to relate forecasted hydro-meteorological drought indices to reported drought impacts. Results show that models, which were built with more than 50 months of reported drought impacts, are able to forecast drought impacts a few months ahead. This study highlights the importance of drought impact databases for developing drought impact functions. Our findings recommend that institutions that provide operational drought early warnings should not only forecast drought hazard, but also impacts after developing an impact database. There still lacks a forecast system that inform end-users regarding the drought impacts, which will be however important for drought management. Here the authors assess the feasibility of forecasting drought impacts using machine-learning and confirm that models, which were built with sufficient amount of reported drought impacts in a certain sector, are able to forecast drought impacts a few months ahead.

Since 1990, natural hazards have led to over 1.6 million fatalities globally, and economic losses are estimated at an average of around USD 260–310 billion per year. The scientific and policy communities recognise the need to reduce these risks. As a result, the last decade has seen a rapid development of global models for assessing risk from natural hazards at the global scale. In this paper, we review the scientific literature on natural hazard risk assessments at the global scale, and we specifically examine whether and how they have examined future projections of hazard, exposure, and/or vulnerability. In doing so, we examine similarities and differences between the approaches taken across the different hazards, and we identify potential ways in which different hazard communities can learn from each other. For example, there are a number of global risk studies focusing on hydrological, climatological, and meteorological hazards that have included future projections and disaster risk reduction measures (in the case of floods), whereas fewer exist in the peer-reviewed literature for global studies related to geological hazards. On the other hand, studies of earthquake and tsunami risk are now using stochastic modelling approaches to allow for a fully probabilistic assessment of risk, which could benefit the modelling of risk from other hazards. Finally, we discuss opportunities for learning from methods and approaches being developed and applied to assess natural hazard risks at more continental or regional scales. Through this paper, we hope to encourage further dialogue on knowledge sharing between disciplines and communities working on different hazards and risk and at different spatial scales.

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, meant as the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work tests the capability of commonly applied drought indices and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and combines information on past drought impacts, drought indices, and vulnerability factors into estimates of drought risk at the pan-European scale. This hybrid approach bridges the gap between traditional vulnerability assessment and probabilistic impact prediction in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro-region-specific sensitivities of drought indices, with the Standardized Precipitation Evapotranspiration Index (SPEI) for a 12-month accumulation period as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictors, with information about land use and water resources being the best vulnerability-based predictors. The application of the hybrid approach revealed strong regional and sector-specific differences in drought risk across Europe. The majority of the best predictor combinations rely on a combination of SPEI for shorter and longer accumulation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, appropriateness of drought indices selection for specific applications, and drought risk assessment.

Drought is a natural hazard that can cause a wide range of impacts affecting the environment, society, and the economy. Providing an impact assessment and reducing vulnerability to these impacts for regions beyond the local scale, spanning political and sectoral boundaries, requires systematic and detailed data regarding impacts. This study presents an assessment of the diversity of drought impacts across Europe based on the European Drought Impact report Inventory (EDII), a unique research database that has collected close to 5000 impact reports from 33 European countries. The reported drought impacts were classified into major impact categories, each of which had a number of subtypes. The distribution of these categories and types was then analyzed over time, by country, across Europe and for particular drought events. The results show that impacts on agriculture and public water supply dominate the collection of drought impact reports for most countries and for all major drought events since the 1970s, while the number and relative fractions of reported impacts in other sectors can vary regionally and from event to event. The analysis also shows that reported impacts have increased over time as more media and website information has become available and environmental awareness has increased. Even though the distribution of impact categories is relatively consistent across Europe, the details of the reports show some differences. They confirm severe impacts in southern regions (particularly on agriculture and public water supply) and sector-specific impacts in central and northern regions (e.g., on forestry or energy production). The protocol developed thus enabled a new and more comprehensive view on drought impacts across Europe. Related studies have already developed statistical techniques to evaluate the link between drought indices and the categorized impacts using EDII data. The EDII is a living database and is a promising source for further research on drought impacts, vulnerabilities, and risks across Europe. A key result is the extensive variety of impacts found across Europe and its documentation. This insight can therefore inform drought policy planning at national to international levels.

Forecasting of drought impacts is still lacking in drought early-warning systems (DEWSs), which presently do not go beyond hazard forecasting. Therefore, we developed drought impact functions using machine learning approaches (logistic regression and random forest) to predict drought impacts with lead times up to 7 months ahead. The observed and forecasted hydrometeorological drought hazards – such as the standardized precipitation index (SPI), standardized precipitation evaporation index (SPEI), and standardized runoff index (SRI) – were obtained from the The EU-funded Enhancing Emergency Management and Response to Extreme Weather and Climate Events (ANYWHERE) DEWS. Reported drought impact data, taken from the European Drought Impact Report Inventory (EDII), were used to develop and validate drought impact functions. The skill of the drought impact functions in forecasting drought impacts was evaluated using the Brier skill score and relative operating characteristic metrics for five cases representing different spatial aggregation and lumping of impacted sectors. Results show that hydrological drought hazard represented by SRI has higher skill than meteorological drought represented by SPI and SPEI. For German regions, impact functions developed using random forests indicate a higher discriminative ability to forecast drought impacts than logistic regression. Moreover, skill is higher for cases with higher spatial resolution and less lumped impacted sectors (cases 4 and 5), with considerable skill up to 3–4 months ahead. The forecasting skill of drought impacts using machine learning greatly depends on the availability of impact data. This study demonstrates that the drought impact functions could not be developed for certain regions and impacted sectors, owing to the lack of reported impacts.

Droughts are multidimensional hazards that can lead to substantial environmental and societal impacts. To understand causes and impacts, multiple perspectives need to be considered. Many studies have identified past drought events and investigated drought propagation from meteorological droughts via soil moisture to hydrological droughts, and some studies have included the impacts of these different types of drought. However, it is not certain whether the increased frequency and severity of drought events in the past decade is unprecedented in recent history. Therefore, we analyze different droughts and their impacts in a regional context using a multidisciplinary approach. We compile a comprehensive and long-term dataset to investigate possible temporal patterns in drought occurrence and place recent drought events into a historical context. We assembled a dataset of drought indices and recorded impacts over the last 218 years in southwestern Germany. Meteorological and river-flow indices were used to assess the natural drought dynamics. In addition, tree-ring data and recorded impacts were utilized to investigate drought events from an ecological and social perspective. Since 1801, 20 extreme droughts have been identified as common extreme events when applying the different indices. All events were associated with societal impacts. Our multi-dataset approach provides insights into similarities but also the unique aspects of different drought indices.

During the last 20 years, Argentina experienced several extreme and widespread droughts in many different regions, including the core cropland areas. The most devastating recent events were recorded in the years 2006, 2009 and 2011. Reported impacts of the main events induced losses of more than 4 billion U.S. dollars and more than 1 million persons were reported to be directly or indirectly affected. In this paper, we analyse the drought risk in Argentina, taking into account recent information on drought hazard, exposure and vulnerability. Accordingly, we identified the most severe droughts in Argentina during the 2000–2015 period using a combination of drought hazard indicators and exposure layers. Three main events were identified: (1) during spring 2006 droughts peaked in the northeast of Argentina, (2) in 2009 precipitation deficits indicated a drought epicenter in the central Argentinian plains, and (3) in 2011 the northern Patagonia region experienced a combination of natural disasters due to severe drought conditions and a devastating volcanic eruption. Furthermore, we analysed the dynamics of drought exposure for the population and the main economic sectors affected by municipality, i.e., agriculture and livestock production. Assets exposed to droughts have been identified with several records of drought impacts and declarations of farming emergencies. We show that by combining exposure and vulnerability with drought intensity it is feasible to detect the likelihood of regional impacts in different sectors.