As we enter a future of shifting patterns of water availability, growing water uses and demands, and evolving societal and environmental vulnerabilities, do we fully understand the extent of drought risks and impacts (including their drivers, root causes, trends and dynamics)? And to what extent does this understanding translate into prospective and systemic solutions? This session aims to advance our knowledge of how systemic drought risks emerge and manifest (especially for the most vulnerable), and to inform pathways for drought risk management and adaptation. We invite contributions that connect science, policy, and practice to:
i) deepen our understanding of the systemic nature of drought vulnerability, risks and impacts, including their root causes and social dimensions such as equity and justice;
ii) showcase new methodological approaches for the assessment and monitoring of drought risks (including Impact-based EWS or forecasting) and impacts (including impact data collection);
iii) explore innovative approaches for comprehensive and systemic drought risk management and adaptation, including governance systems that can anticipate, coordinate across scales and sectors, and adapt to systemic drought risks..
We welcome perspectives from socio-hydrology, hydrosocial studies, behavioral science, disaster risk management, social sciences, and adaptation, and we encourage case studies from all regions, especially Global South, less represented geographical contexts and differential vulnerabilities.
Flash droughts emerge from the interaction of precipitation deficits, elevated temperatures, strong winds, and enhanced atmospheric evaporative demand. Their rapid onset poses significant challenges to conventional drought monitoring and decision-making frameworks, with impacts propagating across spatial scales, sectors, and regions not traditionally drought-prone. Existing detection methodologies exhibit substantial variability in event duration and intensification thresholds, often failing to account for regional hydroclimatic characteristics that modulate compound drought drivers. Major gaps persist in consistent detection, hampering effective monitoring, response, and impact assessment. We compare six widely used flash drought indicators based on evaporative demand, soil moisture, precipitation, and multivariate approaches across all contiguous United States catchments over 40 years. We quantify detection consistency, inter-method agreement, and trade-offs between single- and multi-indicator approaches. We further investigate the 2022 flash drought in the coastal state of Connecticut, where impacts dominated water supply in a typically humid region not commonly considered drought vulnerable. Results reveal pronounced inconsistencies among indicators, with limited agreement even between metrics derived from similar variables. Multi-indicator approaches improve robustness but can miss rapidly evolving events due to restrictive thresholds, while single-indicator methods risk over-detection. In Connecticut, only soil moisture-based indicators successfully captured flash drought conditions, demonstrating that standardized nationwide indices using alternative variables would have failed to detect the event, with important consequences for early warning and timely response. Drought declarations were issued only after intensification, constraining local response capacity and limiting mitigation potential, although subsequent voluntary water use reductions likely supported recovery. To address the disconnect between physical detection and real-world consequences, we introduce an impact-based assessment framework leveraging Natural Language Processing to extract and classify flash drought impacts from media reports. By linking detected events with observed societal impacts, this approach validates detection methods and improves sector-relevant monitoring. Our findings underscore the need for region- and sector-specific assessment frameworks integrating physical signals, impact data, and decision-making contexts—essential for managing rapidly evolving drought risks under increasing hydroclimatic variability.
How to cite: Gesualdo, G. and Hadjimichael, A.: Bridging Flash Drought Detection and Impact Assessment for Adaptive Water Management, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8499, https://doi.org/10.5194/egusphere-egu26-8499, 2026.
Recent drought events in Europe have generated cascading impacts across interconnected sectors. Droughts in mountain regions are increasingly complex phenomena, as winter snowpack deficits compound with low rainfall and high temperature anomalies in spring and summer, reducing water availability from upstream to downstream and amplifying impacts across water-dependent systems. Unfolding this complexity into actionable risk diagnostics remains challenging, especially when impacts emerge from interacting hazards, affect multiple interconnected sectors, and evolve through lagged processes and feedbacks. Conceptual frameworks such as Impact Chain (IC) provide a structured representation of hazard–impact relationships, yet their application to compound drought events often remains limited in capturing temporal dynamics, feedback mechanisms, and event-specific processes.
The Upper Adige River Basin in the Italian Alps exemplifies these challenges, given its strong dependence on snow accumulation and melt and the coexistence of competing water uses. During the 2022 drought, the basin experienced widespread impacts across water-dependent sectors. Despite the severity of these impacts, existing assessments have provided limited insights into how compound climatic drivers and sectoral vulnerabilities interact to produce these outcomes.
This study applies and refines the IC framework to perform a forensic analysis of the 2022 drought impacts on the water sector in the Upper Adige River Basin. A scoping phase identified affected sectors and key impact pathways; a qualitative analysis developed a detailed water-sector IC capturing hazard, exposure, vulnerability, impact, and adaptation factors; and a quantitative characterization linked the IC to hydroclimatic variables (SWE, precipitation, temperature, evapotranspiration, and runoff) using threshold-based deficit detection and cross-correlation analysis to assess interactions and time-lagged dependencies.
During winter 2021–2022, snow water equivalent (SWE) remained persistently below average, reaching a seasonal maximum of approximately 105 mm compared to a long-term mean peak of about 150 mm typically observed in mid-March. Snowmelt occurred anomalously early, with SWE dropping below 30 mm by late May, nearly two months earlier than average, substantially reducing meltwater availability during the summer peak-demand period. Concurrently, air temperature exhibited sustained positive anomalies (approximately +1.5 to +3.5 °C from mid-May to mid-September), enhancing evapotranspiration, accelerating snowpack depletion, and contributing to prolonged low-flow conditions. These hydroclimatic anomalies translated into reduced hydropower production, irrigation water shortages affecting agriculture, increased forest fire activity, and heat-related stress on human health.
Overall, these findings advance the IC approach by demonstrating its usefulness as a forensic framework for disentangling how multiple interacting hydroclimatic conditions combined to produce the observed drought impacts. By integrating observational and model-based data into a previously qualitative framework, the approach supports a more structured interpretation of impact propagation across interconnected systems. The IC-based framework also shows potential for informing impact-based early warning systems for compound and multi-hazard hot–dry events, as well as for drought risk assessment and adaptation planning in snow-dependent, multi-sectoral alpine basins facing intensifying climate extremes.
How to cite: Mohammadi, H., Terzi, S., De Angeli, S., Galletti, A., Zebisch, M., Pittore, M., and Boni, G.: Impact Chains to investigate the complex 2022 drought dynamics in the upper Adige River Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8080, https://doi.org/10.5194/egusphere-egu26-8080, 2026.
Climate change is intensifying the frequency and severity of droughts, posing significant risks to regional economies, water resources, and food security. While the direct impacts of droughts on agricultural output and water availability are documented, their medium and long-term economic consequences across multiple sectors remain underexplored. In particular, drought effects may accumulate over time, with multi-year drought conditions potentially compounding economic impacts and creating lasting disruptions to different industries, labour markets, and public services. Given the spatial heterogeneity of drought exposure and economic structures, a fine-grained regional analysis is necessary to understand varying vulnerabilities and adaptation capacities.
Using NUTS 3 regional economic data and firm-level metrics across Europe (1995-2022), combined with high-resolution climate data from EOBS, we employ Local Projection fixed-effects models to examine how drought duration and severity affect various economic outputs like production, productivity, investment, capital stock, and employment. We assess droughts using SPI and SPEI indices at 3, 6, and 12-month accumulation periods and analyze both their contemporaneous and lagged effects on economic outputs at fine spatial level. By combining high spatial resolution drought indices with comprehensive economic data and local projection methods, we capture heterogeneous regional responses that can be masked in national-level analyses. Specifically, we examine cumulative drought impacts over multiple years (1-4 years) to understand how multi-year drought conditions compound their economic consequences, providing insights into the medium-term persistence of drought-induced economic disruptions. This analysis provides crucial information for designing targeted adaptation policies and assessing climate risks at the regional level.
How to cite: Mastropietro, M., Daumas, L., Kotz, M., and Tavoni, M.: Multi-year droughts and their compounding economic impacts in Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15194, https://doi.org/10.5194/egusphere-egu26-15194, 2026.
Drought degrades water quantity and quality, with impacts across multiple sectors. Public water supply is among the most impacted due to its essential role and high societal priority. Despite local evidence that drought can disrupt household water supply, impacts on public water supply remain less systematically studied. Their heterogeneous nature makes them difficult to assess and quantify. Yet, understanding public water supply’s vulnerability is crucial for safeguarding drinking water and supporting climate adaptation strategies. In this study, we analyzed text-based impact records on public water supply from the European Drought Impact Database (EDID) (https://drought.emergency.copernicus.eu/tumbo/edid), currently the most comprehensive collection of text-based drought impact records in Europe. We assessed the occurrence, diversity, and severity of drought impacts by analyzing temporal and spatial patterns in Europe and by investigating the details of the impact descriptions. Additionally, we tested whether the impacts and their severities were associated with natural and socio-economic factors. These potential vulnerability factors included climate, groundwater dependency, population density, and water management structures. Our results reveal substantial diversity in drought impacts on European public water supply, ranging from minor restrictions and demand-management measures to severe supply interruptions and emergency provisions. Impacts extend beyond drinking water to multiple uses, complicating their assessment. Geographically, the Mediterranean region shows a higher proportion of extremely severe impacts than central and northern Europe. The severity scoring system could be applied to the impact records to differentiate between levels of impact severity, but testing against natural and socio-economic factors did not reveal clear patterns. This analysis allowed evaluating the potential and limitations of EDID’s newly introduced severity scoring system in the public water supply sector, providing valuable insights for its future application. While refinement and further testing are needed, the severity scoring approach provides a starting point for quantifying drought impacts. EDID establishes a baseline for harmonized impact assessment and may support the development of adaptive water-management strategies across Europe.
How to cite: Szillat, K., Hlavsová, M., Rossi, L., Blauhut, V., and Stahl, K.: Drought Impacts on Public Water Supply in Europe: a challenge of diversity and severity assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1180, https://doi.org/10.5194/egusphere-egu26-1180, 2026.
Droughts are becoming more frequent, severe, and spatially extensive, placing unprecedented pressure on socioecological systems. Robust drought risk assessment is therefore essential to inform targeted adaptation actions and public investment decisions. However, conventional indicator-based approaches, often built on global secondary datasets, typically underrepresent context-specific vulnerabilities, equity dimensions, and intersectoral linkages, and rarely translate quantitative risk estimates into implementable and fiscally viable adaptation pathways.
This contribution presents an enhanced, participatory drought risk assessment methodology based on an extended Economics of Climate Adaptation (ECA) Framework, applied in Zambia and Pakistan. The framework couples probabilistic drought hazard modelling, high-resolution exposure mapping, asset-specific vulnerability functions, and cost-benefit analysis (CBA) of adaptation pathways within a structured, stakeholder-led process. ECA’s analytical backbone is the open-source CLIMADA modeling platform, which enables transparent, reproducible, and scale-agnostic integration of hazard, exposure, and vulnerability components. The modular architecture allows consistent application across sectors and spatial scales while remaining adaptable to locally defined data, assumptions, and stakeholder priorities. In addition to economic losses, non-economic impacts—such as food insecurity, service disruption, and social protection needs—are explicitly represented, enabling a more systemic representation of drought risk.
A core feature of the framework is the integration of stakeholder perspectives throughout the assessment process. National and subnational authorities, technical agencies, and local experts contribute to shaping the study scope, prioritizing key assets, validating assumptions and cost estimates, identifying feasible adaptation options, and assessing their effectiveness. Adaptation investment pathways are co-developed as spatially and temporally sequenced portfolios of measures, and CBAs are conducted to support prioritization under fiscal constraints. This participatory design addresses common limitations of externally driven climate risk modelling, including insufficient consideration of local knowledge, institutional constraints, and power asymmetries in knowledge production. The resulting pathways are not only technically sound but also socially approved and relevant for decision-makers.
Implementation in Zambia and Pakistan follows a series of co-development stages involving workshops, webinars, questionnaires, and direct consultation with stakeholders. In Pakistan, the resulting adaptation pathways are translated into Planning Commission Pro Formas, creating a direct mechanism for integrating scientific evidence into national public investment planning. In Zambia, outputs are operationalized through a Drought Risk and Adaptation Platform—an interactive, user-friendly dashboard developed in consultation with end users to support sustained uptake and institutional learning.
The two case studies demonstrate how participatory, risk-based, and economically grounded drought assessments can inform multisectoral adaptation strategies and strengthen national and sub-national decision-making capacities. By coupling advanced risk modelling with equitable, co-production processes and quantitative evaluation, this work provides a replicable framework for bridging science, policy, and practice to manage systemic drought risks in drought-prone regions.
How to cite: Widjaja, C. N., Peter, M., Behre, C. E., Waldschmidt, F., and Gyawali, D.: How can we include local perspectives into probabilistic risk and adaptation modelling? Case studies of participatory drought risk assessment from Pakistan and Zambia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1671, https://doi.org/10.5194/egusphere-egu26-1671, 2026.
Drought is a slow-onset, systemic risk that impacts water, food, and socio-ecological systems, particularly in semi-arid regions under climate change. However, conventional assessments focus on hazard intensity and frequency, thereby overlooking persistence and recovery dynamics—key characteristics governing cumulative impacts and long-term resilience. To address this limitation, this study applies an integrated, process-oriented approach to Morocco, a Mediterranean climate hotspot highly vulnerable to water scarcity. Specifically, we employ the Standardized Precipitation Evapotranspiration Index (SPEI) to analyze historical conditions (1976–2025) and future climate projections (2030–2060, SSP3-7.0) across three complementary dimensions: the Drought Hazard Index (DHI), the Drought Persistence Index (DPI), and the Recovery–Development Ratio (RDR). Our results reveal a pronounced shift in drought characteristics. Historically, 55.85% of Morocco experienced high drought hazard, with most droughts (72.51%) exhibiting low persistence. In contrast, future projections indicate a substantial expansion of high-hazard areas (68–72%), alongside a marked increase in moderate-to-high persistence events. Most critically, slow-recovery events rise from 35.69% historically to over 50% under the future scenario, indicating more severe, persistent, and prolonged droughts that will test adaptive capacities. These evolving drought dynamics will have profound societal and sectoral consequences. Agriculture will face greater food insecurity, urban water systems will confront equity challenges, and ecosystems will risk irreversible decline. Impacts disproportionately affect vulnerable populations. Consequently, the proposed approach is essential for developing impact-based early-warning systems and stakeholder-informed, co-developed adaptation strategies capable of addressing these compounding, socially differentiated risks.
How to cite: Acharki, S. and Hadri, A.: From hazard to recovery: Integrating drought persistence and resilience in Morocco under climate change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22927, https://doi.org/10.5194/egusphere-egu26-22927, 2026.
Droughts are among the most widespread and damaging natural hazards, yet information on individual events remains fragmented and difficult to compare across countries, despite being essential for drought risk assessment and for mitigation, adaptation strategies. For this reason, this work focuses on building a detailed, event-based drought database for the African continent by combining and expanding existing disaster data sources. Beyond serving as a comprehensive archive of past events, the database is intended to support the empirical derivation of drought impact functions and vulnerability curves.
The database relies on impact data from past drought events extracted from two main types of sources: global disaster loss databases and disaster reports. For the first category, three widely used platforms are adopted as a starting point: EM-DAT, IDMC, and DesInventar with records limited to the 2012–2024 period. The three databases differ substantially in the types of impacts recorded, which reflect different dimensions of impact indicator, as well as in data structure, spatial resolution, and temporal detail. For the first aspect, EM-DAT primarily reports affected populations, IDMC focuses on displaced populations, and DesInventar includes both affected people and damaged cropland expressed in hectares.
A comparative analysis of the three databases enabled the construction of an integrated dataset. Within the study period, EM-DAT reports 87 events across 31 countries, IDMC 31 events in 12 countries, and DesInventar 26 events in 10 countries. When considering only country and year of event onset or registration, 20 intersecting events were identified, with only two events common to all three databases. Although integration enriches the original datasets, substantial uncertainty remains in both the identification of individual drought events and the consistent quantification of impacts, mainly due to the limited overlap among sources.
To address these limitations, the study explores disaster reports through the use of artificial intelligence. A prompt-based approach using large language models is developed to extract structured information from unstructured text, including event timing, location, impacts, and affected sectors.
The AI-based extraction is implemented within a Python workflow to automate data processing and reduce manual curation. The approach has been tested in Somalia using 17 reports from United Nations agencies, government sources, and humanitarian organizations. Independent information on drought events in the Somaliland region was used for validation. Results show that the AI-assisted extraction successfully identifies drought events already present in the integrated database while providing more detailed impact descriptions, including clearer differentiation of affected populations consistent with IPCC classifications and explicit identification of impact drivers. The methodology is intended to be extended to the entire African continent.
How to cite: Ghiggini, F., Ottonelli, D., Trasforini, E., Cremonese, E., D'Andrea, M., Ghizzoni, T., and Rudari, R.: Building a Comprehensive Drought Impact Dataset by Integrating Disaster Databases and Reports with the use of Large Language Models., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18357, https://doi.org/10.5194/egusphere-egu26-18357, 2026.
Drought is a slow-onset hazard with impacts that develop over time and space, making it particularly suitable for an impact-based monitoring approach compared to more sudden hazards. This study explores how large language model (LLM)–classified newspaper articles and Twitter messages can be used for drought impact monitoring in the Netherlands, and what needs to be considered when applying such approaches.
Results show that both data sources are valuable for extracting drought impact information and broadly align with temporal drought patterns. Different impact categories exhibit distinct temporal peaks, suggesting that reported impacts may function as early signals of drought development. At the same time, clear differences emerge between data sources. Spatial impact patterns derived from newspapers show greater variation in reported impact counts, while Twitter-based patterns are more strongly shaped by population density and platform-specific usage. The most frequently reported impact categories per region reflect underlying land-use characteristics.
Importantly, impact reporting is not neutral. The type of news outlet and social media actor influences which drought impacts are emphasised, and drought attention in both newspapers and social media is subject to memory effects and competition with other societal events. Building on these insights, the study additionally explores how drought is framed in social media discourse, distinguishing between diagnostic, prognostic, and motivational framing, and examining how these framing types evolve over time and across drought phases.
Overall, the results highlight that developing a drought impact monitoring system requires explicit choices regarding data sources, classification methods, impact definitions, and interpretative lenses, as these choices directly shape how drought impacts, vulnerabilities, and societal responses are represented.
How to cite: Lam, M., Dewulf, A., Sutanto, S., Hellegers, P., and van Oel, P.: Drought impacts and drought framing in news and social media: an LLM-based approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18362, https://doi.org/10.5194/egusphere-egu26-18362, 2026.
The 2022 European drought was a record-breaking event in both severity and spatial extent, exposing critical shortcomings in current drought risk management across the continent. Drawing on two companion studies developed within the Drought in the Anthropocene (DitA) network, this contribution presents integrated insights from a Europe-wide survey of 481 water managers and hydroclimatic data, to reflect on the state of drought preparedness and institutional responses.
The first study offers a physical-to-policy overview of the drought, highlighting how intensifying climate hazards and rising water demands are amplifying drought risks. Impacts were widespread, with Mediterranean regions particularly hard-hit, and covering central and Eastern Europe throughout the summer. Many countries still show limited presence of preparedness and largely rely short-term and responsive measures, highlighting rregional disparities in response capacity. Nevertheless, the study also points towards significantly growing awareness and preparedness. The second study focuses on institutional preparedness. It shows that organisations with forecasting systems or drought management plans in place responded significantly earlier and rated their actions as more effective. Furthermore, over one-third of respondents reported updating or introducing management plans following the previous droughts, indicating a general learning trajectory in the aftermath of major events. Both studies end by advocating for a European Drought Directive to enshrine systemic, long-term, and coordinated drought risk management approaches in European governance.
These findings were only made possible thanks to the broad, interdisciplinary, and collaborative nature of the DitA network. Its widespread reach allowed us to connect with practitioners across 30 countries, making it one of the most comprehensive surveys of the management of the 2022 European drought. The interdisciplinary composition of the network also enabled the research to speak directly to high-level policy questions, bridging science and governance. Together, these two studies demonstrate how systemic drought risk emerges from the interplay between biophysical changes and institutional preparedness, and how tackling these challenges requires interdisciplinary approaches. The 2022 drought must not only serve as a warning signal but also as a turning point towards coordinated, systemic, and equitable drought risk governance in Europe.
How to cite: Biella, R., Shyrokaya, A., and Ionita, M. and the Drought in the Anthropocene (DitA) working group - Panta Rhei/HELPING: Lessons from the 2022 European Drought through an Interdisciplinary Lens: working with the Drought in the Anthropocene (DitA) Network, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22719, https://doi.org/10.5194/egusphere-egu26-22719, 2026.
Drought is widespread and complex natural hazard, with far-reaching consequences for ecosystems, economies, and societies. Recent analyses reveal pervasive drying trends across all continents, consistent with a long-term increase in atmospheric evaporative demand and a substantial expansion of drought-affected areas over the past decades. Climate projections further indicate that drought frequency, intensity, and spatial extent are very likely to continue increasing in the future. In parallel with these emerging trends, national drought monitoring systems began to develop in the mid-1990s, evolving from country-specific initiatives toward regional and continental platforms. However, systematic monitoring of drought impacts has lagged hazard monitoring and has largely remained limited to individual countries or specific sectors, with only very recent attempts at global coverage. To address these limitations, the TerraDrought initiative was launched in November 2025 with the aim of integrating real-time drought monitoring and forecasting with independent, continuous acquisition of drought impact information on the global scale. By providing timely, publicly accessible data and visualizations, TerraDrought enables more objective evaluation of ongoing drought events, supports attribution analyses, and improves communication of drought risks and impacts to decision-makers, journalists, and the general public. The system is designed to complement existing national and regional platforms and to serve as an interim solution in regions where operational drought monitoring and impact reporting are not yet established.
How to cite: Hlavsová, M., Svoboda, M., Hayes, M., Smith, K., Poulsen, C., Zhang, B., Balek, J., Dvořák, J., and Trnka, M.: TerraDrought: Global drought monitoring, forecasting and impact reporting, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2746, https://doi.org/10.5194/egusphere-egu26-2746, 2026.
Global crop productivity heavily relies on snow availability, which has declined in many snow-dependent regions due to warmer winters and intensified snow droughts. However, our understanding of crop yield sensitivity to snow droughts remains limited. Here, we show that winter wheat croplands have experienced an increase in snow drought frequency (5.3%−6.7% more events per decade) from 1960 to 2020. To assess the sensitivity of winter wheat yield to snow droughts, we utilized explainable machine learning, gridded yield datasets, and the standardized snow water equivalent index (SWEI) from 1982 to 2016. Our findings reveal a significant increase in yield sensitivity to SWEI over 25% of Northern Hemisphere winter wheat croplands. Elevated fertilizer application rates, increased freezing stress, and slightly decreased precipitation are identified as primary drivers amplifying this sensitivity. These findings highlight the increasing vulnerability of crop systems to snow droughts, which is critical for guiding agricultural adaptation in a warming future with reduced snowpack.
How to cite: Huijiao, C., Shuo, W., Peng, Z., and Amir, A.: Winter Wheat Yield Sensitivity to Snow Drought Is Increasing Across the Northern Hemisphere , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3689, https://doi.org/10.5194/egusphere-egu26-3689, 2026.
Droughts are becoming more frequent and severe in the Netherlands, particularly affecting sandy soil regions that depend strongly on local precipitation and groundwater. Current operational monitoring, however, faces two related but distinct limitations. First, drought is typically assessed using individual indicators, without explicitly analysing drought propagation in the hydrological cycle, limiting insight into when precipitation deficits begin to affect the subsurface water state. Second, the main operational indicator for the growing season, i.e. precipitation deficit, assumes a uniform reference grass evapotranspiration (RET), thereby neglecting substantial differences in water demand among vegetation types. Together, these limitations constrain both the interpretation of drought dynamics and the representation of spatially differentiated drought conditions. This study addresses these challenges for the Aa of Weerijs catchment in the Netherlands by analysing drought propagation and refining the operational precipitation deficit indicator.
Drought propagation was analysed for the period 1993–2024 using indices representing different drought types: meteorological (Standardized Precipitation Index, SPI, and Standardized Precipitation Evapotranspiration Index, SPEI), agricultural (Palmer Drought Severity Index, PDSI), and hydrological (Standard groundwater Index, SGI). The results reveal clear differences in timing and persistence across drought types. Agricultural droughts (PDSI) respond rapidly to meteorological anomalies and generally recover quickly, whereas groundwater droughts show delayed onset and prolonged recovery due to relatively slow water replenishment in the subsurface.
In parallel, the study refines the commonly used precipitation deficit (PD), which is currently based on RET for well-watered grass and therefore ignores vegetation heterogeneity. A vegetation-specific precipitation deficit (PDveg) was developed by replacing the uniform RET with vegetation-specific potential evapotranspiration (PETveg). PETveg was generated at 80 m spatial resolution by modifying PyWaPOR framework to generate zero moisture stress conditions. The resulting PDveg reveals strong spatial variability in drought development that is masked by the conventional indicator, with markedly different deficit dynamics across forests, crops, natural areas, and tree nurseries. To support operational use, percentile-based thresholds (P70–P95) were derived from 14-day PDveg gains for each vegetation type. These thresholds distinguish four levels of drought severity, from mild to extreme.
Finally, irrigation-intensive areas were identified using unsupervised clustering of remote-sensing indicators. High AET/PET ratios, together with small differences between precipitation deficits derived from AET and PET, indicated such areas. This approach provides a data-driven way to map high water-use zones without relying on extensive in-situ data.
Together, these results show that drought propagation analysis enhances understanding of temporal drought dynamics, while vegetation-sensitive indicators improve the representation of spatial variability in drought conditions, providing complementary insights for spatially targeted water management.
How to cite: Ali, M. H., Ning, Y., Chow, R., and Nunes, J. P.: Advancing Operational Drought Monitoring Through Propagation Analysis and Vegetation-Specific Precipitation Deficits, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4292, https://doi.org/10.5194/egusphere-egu26-4292, 2026.
Climate change is expected to increase the risk of drought in parts of the Nordic region. Although the region is considered water-rich, events such as the 2018 European-scale drought have shown that the combination of warm temperatures, low rainfall, and growing household water consumption during the summer season can put pressure on municipal water systems and cause seasonal water shortages. In Sweden, where water management is largely decentralized, there is currently no long-term or national-level overview of the impacts of drought on municipal water supplies. To create this spatiotemporal overview, we used public communication on water savings and water use restrictions, which are the most common municipal responses to drought and are typically published in Swedish news outlets. We extracted the dates, locations, and cited causes of the water use reduction measures from approximately 10,000 articles published between 2006 and 2025, applying both simple (keyword-based detection) and advanced text-mining methods (Large Language Models (LLMs)). While simple approaches were sufficient to extract locations and dates, LLMs performed better in classifying the causes of the demand-management measures (e.g., meteorological, hydrological, anthropogenic drought). The results show that around 50% of Swedish municipalities implemented demand-reduction measures in the summer of 2018 due to prolonged dry and warm weather. In 2023, a dry start of the summer and precautionary measures caused 20% of the municipalities to adopt such measures. Overall, dry weather, high temperatures, low groundwater levels, as well as high water consumption, water systems reaching maximum capacity, and precautionary principles were among the most common reasons for municipalities to issue water use restrictions. These results not only demonstrate the potential of text-mining approaches to uncover drought impacts to water supply, but also highlight the human dimension of drought. They can thereby inform drought risk management and solutions to ensure more robust and sustainable water supplies in the future.
How to cite: Fernandez, J., Zahra, S., and Mård, J.: Mapping drought impacts to municipal water supply in Sweden using news media and text-mining, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7332, https://doi.org/10.5194/egusphere-egu26-7332, 2026.
Agricultural drought, defined here as insufficient soil water availability to sustain crop growth during the vegetation period, is an emerging climate risk in Lower Austria. Although the region has historically benefitted from relatively reliable summer precipitation, recent decades have seen an increasing frequency of dry spells and heat periods, with direct consequences for crop yields and farm income. This study presents results from a regional agricultural drought risk assessment that evaluates crop-specific changes in drought risk under current and future climate conditions and explores the potential moderating effects of nature-based solutions in the form of hedgerows.
The assessment builds on the CLIMAAX drought risk workflow, which integrates climate variables, soil moisture dynamics, and evapotranspiration into a process-oriented crop production model. For application in Lower Austria, the workflow was adapted to incorporate regionally specific information, including irrigation infrastructure, soil characteristics, and dominant production systems. This allows drought risk to be assessed not only as a function of climate forcing, but also in the context of local agronomic and socio-economic conditions.
At the core of the model is a daily simulation of crop water demand and supply throughout the growing season. Gridded climate data (temperature, precipitation, radiation, humidity, and wind) are combined with soil parameters such as available water capacity and rooting depth to determine periods of water stress during critical phenological stages. These deficits are then used to estimate potential yield losses, enabling spatially explicit estimates of drought impacts. Simulations are performed for a historical baseline as well as mid- and end-century climate scenarios under RCP4.5 and RCP8.5. The workflow was adapted to estimate annual yield losses, accounting for extreme drought years which would otherwise be masked by period averages.
To evaluate the role of nature-based solutions in mitigating agricultural drought, the current extent of multifunctional hedgerows and a set of hedge scenarios were incorporated into the model. Microclimatic effects of hedgerows on evapotranspiration were represented using empirical change factors derived from field experiments in Lower Austria (Orfánus and Eitzinger, 2010). These factors describe a linear reduction in evapotranspiration in the lee of an 8 m high hedge, ranging from 0.5 at the hedge to 1.0 at a distance of 80 m, and were applied based on prevailing wind direction. High-resolution (10 m) simulations were made for selected drought years to capture local hedge effects on soil moisture and crop water stress.
Results indicate declining productivity for maize, sugar beet, soybean, and sunflower across all climate scenarios, while wheat and barley show increasing yield potential compared to the baseline scenario. Hedge scenario simulations demonstrate a measurable reduction in drought stress during dry years, underscoring the potential of multifunctional hedgerows as a supportive landscape-scale adaptation measure that can simultaneously mitigate drought risk and soil erosion. While hedgerows may introduce trade-offs related to shading and competition under average moisture conditions, the modelling framework provides a robust basis for identifying climatic and spatial contexts in which their net effect on crop productivity is positive, thereby supporting targeted and climate-resilient implementation strategies.
How to cite: Schalk, V., Spiekermann, R., Wittholm, J., and Kienberger, S.: Modelling climate change impacts on crop productivity and the role of hedgerows in mitigating drought risk in Lower Austria, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7963, https://doi.org/10.5194/egusphere-egu26-7963, 2026.
Drought events pose significant threats to water resources, agriculture, and socio-economic systems across Europe. Effective early warning systems require the integration of hazard forecasts with vulnerability and exposure information to support risk-based decision-making. Here, we present an interactive web-based dashboard developed using R Shiny that provides a probabilistic drought risk assessment at the NUTS-3 (Nomenclature of Territorial Units for Statistics) regional level across Europe. The dashboard integrates seasonal drought forecasts based on two complementary indicators: the Standardized Precipitation Index (SPI) and the Standardized Streamflow Index (SSI) for meteorological and hydrological droughts respectively. Operational forecasts are derived from a 51-member ensemble based on the E-HYPE (European Hydrological Predictions for the Environment) hydrological model output, enabling a probabilistic assessment up to seven months ahead. By selecting multiple accumulation periods (SPI and SSI for 1, 3, 6, 9, 12, and 24 months) users can explore drought condition at different lead times and initialization months. A key innovation of our approach is the implementation of a dynamic risk matrix that combines drought severity and probability with exposure indicators. The risk matrix visualizes the intersection of forecast drought probability (categorized as 30%, 50%, and 70% exceedance thresholds) and population density, allowing users to identify regions where drought hazard coincides with high vulnerability. Additionally, the dashboard incorporates land use exposure data derived from CORINE (Coordination of Information on the Environment) Land Cover, providing information on urban, agricultural, and forest areas potentially affected by drought conditions. The interactive map interface allows users to select any NUTS-3 region to instantly visualize region-specific risk assessments, exposure profiles, and forecast statistics. This tool demonstrates the potential of combining ensemble-based seasonal forecasts with geospatial exposure data for operational drought risk management and supports decision-makers in water resource management, agriculture, and civil protection sectors.
How to cite: Mohammadi, B., Yang, W., Rosberg, J., and Pechlivanidis, I.: An Interactive Shiny Dashboard for Probabilistic Drought Risk Assessment in Europe Using Seasonal Forecast Ensembles of SPI and SSI, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9117, https://doi.org/10.5194/egusphere-egu26-9117, 2026.
The traditional understanding of drought events assumes a progression starting with meteorological drought – anomalies in key drought-driving factors – followed by impacts on agricultural crops and forest stands, and subsequently a decline in streamflow and reservoir levels. If these impacts reach sufficient intensity and duration, socio-economic drought may be declared. However, the 2025 drought in Central Europe challenged this paradigm by lacking the expected agricultural and forestry impacts, misleading even experienced climatologists. In this study, we analyze the sequence of events during the 2025 drought in Central Europe, which combined recurring meteorological drought episodes with significant hydrological drought, yet coincided with lush vegetation – a condition referred to as “green drought.” Using previously unavailable datasets, we demonstrate that despite seemingly favorable vegetation conditions, the productivity of both agricultural crops and forests declined. Furthermore, we examine drought events from 2001 to 2025 across Central Europe to identify potential occurrences of similar “green drought” phenomena.
We acknowledge support from AdAgriF - Advanced methods of greenhouse gases emission reduction and sequestration in agriculture and forest landscape for climate change mitigation (CZ.02.01.01/00/22_008/0004635).
How to cite: Bartošová, L., Hlavsová, M., Rakovec, O., Semerádová, D., Balek, J., Kettaren, R., Barcza, Z., Žalud, Z., and Trnka, M.: Beyond Traditional Drought Paradigms: Identifying and Understanding ‘Green Drought’ in Central Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20331, https://doi.org/10.5194/egusphere-egu26-20331, 2026.
Drought is one of the most important environmental hazards in the Horn of Africa region, causing annual human and livestock losses and multi-million dollar economic losses. Monitoring and timely detection of drought plays a key role in natural resource management and mitigating its impacts. One of the common methods for monitoring agricultural drought is the use of the Vegetation Condition Index (VCI) based on remote sensing. While useful, the VCI has also several substantial limitations and cannot be a robust and generalizable method for different regions due to differences in climate, land cover, and spatio-temporal dynamics.
In this study, a new and robust framework for drought detection based on MODIS time-history satellite images is developed. This method uses the NDVI and statistical analysis based on percentiles to define dynamic thresholds that depend on the climatic conditions of each region. Thus, the proposed method is not dependent on fixed values and is able to adaptively consider spatial and temporal changes in vegetation cover.
The proposed framework has been tested in several counties in Kenya and its results have been validated with field reports and ground data. The results show that the proposed method has a higher ability to identify drought robustly than methods based on fixed thresholds and can be used as an effective tool for drought monitoring in regions with diverse climates and land cover.
How to cite: Rowhani, P., Memarian Sorkhabi, O., Hopling, C., Muthoka, J., Todd, M., Kniveton, D., Oliver, S., and Mutanda, N.: Redefining agricultural drought monitoring and forecasting in Kenya. , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21206, https://doi.org/10.5194/egusphere-egu26-21206, 2026.
