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Droughts are natural hazards that lead to severe impacts in the agricultural sector. Mountain regions are thought to have abundant water, but have experienced unprecedented drought conditions as climate change is affecting their environments more rapidly than other places. The effect radiates by reducing water availability well beyond the mountains' geographical locations. This study aims to improve the understanding of agriculture's vulnerability to drought in Europe's pre-Alpine region, considering two case studies that have been severely impacted in the past. We applied a mixed-method approach combining the knowledge of regional experts with quantitative data analyses in order to define the region-specific vulnerability based on experts' identified factors. We implemented two aggregation methods by combining the vulnerability factors that could be supported with subregional data. Whereas the equal weighting method combines all factors with the same weight, the expert weighting method combines the factors with varying weight based on the expert's opinion. These two methods resulted in vulnerability maps with the expert weighting showing a higher vulnerability, and partly relocating the medium and lower vulnerabilities to other subregions within the case study regions. In general, the experts confirmed the resulting subregions with higher vulnerability. They also acknowledged the value of mapping vulnerability by adopting different aggregation methods confirming that this can serve as a sensitivity analysis. The identified factors contributing most to the regions' vulnerability point to the potential of adaptation strategies decreasing the agriculture's vulnerability to drought that could enable better preparedness. Apart from region-specific differences, in both study regions the presence of irrigation infrastructure and soil texture are among the most important conditions that could be managed to some extent in order to decrease the regions' vulnerability. Throughout the analyses, the study benefited from the exchange with the experts by getting an in-depth understanding of the regional context with feedback relations between the factors contributing to vulnerability. Qualitative narratives provided during the semi-structured interviews supported a better characterization of local vulnerability conditions and helped to better identify quantitative indicators as proxies to describe the selected vulnerability factors. Thus, we recommend applying this mixed-method approach to close the gap between science and practitioners.

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.

Drought affects the European Alpine mountain region, despite a humid climate. Droughts' damaging character in the past and increasing probability in future projections call for an understanding of drought impacts in the mountain regions. The European Drought Impact report Inventory (EDII) collects text reports on negative drought impacts. This study presents a considerably updated EDII focusing on the Alpine region. This first version release of an Alpine Drought Impact report Inventory (EDIIALPS) classifies impact reports into categories covering various affected sectors and enables comparisons of the drought impact characteristics. We analysed the distribution of reported impacts on the spatial, temporal and seasonal scale and by drought type for soil moisture drought and hydrological drought. For the spatial analysis, we compared the impact data located in the Alpine region to the whole of Europe. Furthermore, we compared impact data between different climatic and altitudinal domains (the northern region vs. the southern region and the pre-Alpine region vs. the high-altitude region) and between the Alpine countries. Compared to the whole of Europe, in the Alpine region agriculture and livestock farming impacts are even more frequently reported, especially in the southern region. Public water supply is the second most relevant sector but overall less prominent compared to Europe, especially in spring when snowmelt mitigates water shortages. Impacts occur mostly in summer and early autumn, with a delay between those impacts initiated by soil moisture and those initiated by hydrological drought. The high-altitude region shows this delay the strongest. From 1975 to 2020, the number of archived reports increases, with substantially more impacts noted during the drought events of 1976, 2003, 2015 and 2018. Moreover, reported impacts diversify from agricultural dominance to multi-faceted impact types covering forestry, water quality, industry and so forth. Though EDIIALPS is biased by reporting behaviour, the region-specific results of negative drought impacts across the water-rich European mountain region demonstrate the need to move from emergency response to prevention and preparedness actions. These may be guided by EDIIALPS' insights to regional patterns, seasons and drought types.

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.

Drought management frameworks are dependent on methods for monitoring and prediction, but quantifying the hazard alone is arguably not sufficient; the negative consequences that may arise from a lack of precipitation must also be predicted if droughts are to be better managed. However, the link between drought intensity, expressed by some hydrometeorological indicator, and the occurrence of drought impacts has only recently begun to be addressed. One challenge is the paucity of information on ecological and socioeconomic consequences of drought. This study tests the potential for developing empirical drought impact functions based on drought indicators (Standardized Precipitation and Standardized Precipitation Evaporation Index) as predictors and text-based reports on drought impacts as a surrogate variable for drought damage. While there have been studies exploiting textual evidence of drought impacts, a systematic assessment of the effect of impact quantification method and different functional relationships for modeling drought impacts is missing. Using Southeast England as a case study we tested the potential of three different data-driven models for predicting drought impacts quantified from text-based reports: logistic regression, zero-altered negative binomial regression (hurdle model), and an ensemble regression tree approach (random forest). The logistic regression model can only be applied to a binary impact/no impact time series, whereas the other two models can additionally predict the full counts of impact occurrence at each time point. While modeling binary data results in the lowest prediction uncertainty, modeling the full counts has the advantage of also providing a measure of impact severity, and the counts were found to be reasonably predictable. However, there were noticeable differences in skill between modeling methodologies. For binary data the logistic regression and the random forest model performed similarly well based on leave-one-out cross validation. For count data the random forest outperformed the hurdle model. The between-model differences occurred for total drought impacts and for two subsets of impact categories (water supply and freshwater ecosystem impacts). In addition, different ways of defining the impact counts were investigated and were found to have little influence on the prediction skill. For all models we found a positive effect of including impact information of the preceding month as a predictor in addition to the hydrometeorological indicators. We conclude that, although having some limitations, text-based reports on drought impacts can provide useful information for drought risk management, and our study showcases different methodological approaches to developing drought impact functions based on text-based data.

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.

Current drought monitoring and early warning systems use different indicators for monitoring drought conditions and apply different indicator thresholds and rules for assigning drought intensity classes or issue warnings or alerts. Nevertheless, there is little knowledge on the meaning of different hydro-meteorologic indicators for impact occurrence on the ground. To date, there have been very few attempts to systematically characterize the indicator–impact relationship owing to sparse and patchy data on drought impacts. The newly established European Drought Impact report Inventory (EDII) offers the possibility to investigate this linkage. The aim of this study was to explore the link between hydro-meteorologic indicators and drought impacts for the case study area Germany and thus to test the potential of qualitative impact data for evaluating the performance of drought indicators. As drought indicators two climatological drought indices – the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) – as well as streamflow and groundwater level percentiles were selected. Linkage was assessed though data visualization, extraction of indicator values concurrent with impact onset, and correlation analysis between monthly time series of indicator and impact data at the federal state level, and between spatial patterns for selected drought events. The analysis clearly revealed a significant moderate to strong correlation for some states and drought events allowing for an intercomparison of the performance of different drought indicators. Important findings were strongest correlation for intermediate accumulation periods of SPI and SPEI, a slightly better performance of SPEI versus SPI, and a similar performance of streamflow percentiles to SPI in many cases. Apart from these commonalities, the analysis also exposed differences among federal states and drought events, suggesting that the linkage is time variant and region specific to some degree. Concerning "thresholds" for drought impact onset, i.e. indicator values concurrent with past impact onsets, we found that no single "best" threshold value can be identified but impacts occur within a range of indicator values. Nevertheless, the median of the threshold distributions showed differences between northern/northeastern versus southern/southwestern federal states, and among drought events. While the findings strongly depend on data and may change with a growing number of EDII entries in the future, this study clearly demonstrates the feasibility of evaluating hydro-meteorologic variables with text-based impact reports and highlights the value of impact reporting as a tool for monitoring drought conditions.