Changes in climate have affected frequency and characteristics of extreme events and natural hazards. To improve understanding of possible changes of agricultural droughts in the future, we explore drought characteristics in long term future projections of Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for different future scenarios based on three Shared Socioeconomic Pathways (SSP). To quantify the intensity of agricultural droughts, the 6-month Standardized Precipitation Evapotranspiration Index (SPEI6) with a 65 year reference period is applied to simulations of 18 ESMs.
Drought related atmospheric variables of the simulations are validated with reanalysis datasets including ERA5 and CRU.
For three future scenarios the projected SPEI6 distributions are analyzed globally and regionally to estimate and characterize the changes in agricultural drought in the future based on multi-model means of change rates, distributions and relative area covered by certain event types. We quantify the change of drought index values for 42 IPCC AR6 WG1 reference regions individually with a focus on those with most harvest area. For higher emission scenarios we find, in agreement with other studies, negative trends in water budget and SPEI in most of them, particularly in the Mediterranean and other arid regions. Increasing reference evapotranspiration emerges as the dominant driver for more extreme drought conditions in these regions. What is considered as the driest 2.3% months during 1950-2014 is projected to be the new normal or moderate condition in arid regions by 2100, following a high emission future scenario (SSP 5-8.5). For this scenario, 20% of the harvest regions surface is considered to be under extreme drought conditions during northern hemisphere autumn. Under a low emission scenario (SSP 1-2.6) with an expected global warming of 1.8°C it would be less than 10%.
How to cite: Lindenlaub, L., Weigel, K., Hassler, B., Jones, C., and Eyring, V.: Characteristics of Agricultural Droughts Under Projected Atmospheric Changes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12753, https://doi.org/10.5194/egusphere-egu25-12753, 2025.
To describe droughts at the global scale, many variables can be employed to express their extent, duration, severity or dynamics. To identify common features of global land drought events (GLDEs) based on soil moisture modelling, we prepared a robust method for their delimitation and classification (cataloguing). Estimates of root-zone soil moisture from the SoilClim model and the mesoscale Hydrologic Model (mHM) were calculated over global land from 1980–2023. Using the 10th and 20th percentile thresholds of soil moisture anomalies, outputs of the two models were merged into a united dataset of drought affected areas in a 10-day step with 0.1° resolution. OPTICS clustering of the gridded data was then used to identify a total of 736 GLDEs. By utilizing four spatiotemporal and three motion-related characteristics for each GLDE, we established threshold percentiles based on their distributions. This information enabled us to categorize droughts into seven severity categories and seven dynamic categories. The severity and dynamic categories overlapped substantially for extremely severe and extremely dynamic droughts but very little for less severe/dynamic categories, despite some very small droughts that have occasionally been very dynamic. The frequency of GLDEs has generally increased in recent decades across different drought categories but the increase is not always statistically significant. Overall, the cataloging of GLDEs presents a unique opportunity to analyze the evolving features of spatiotemporally connected drought events in recent decades and provides a basis for future investigations of the drivers and impacts of dynamically evolving drought events.
How to cite: Řehoř, J., Brázdil, R., Rakovec, O., Hanel, M., Fischer, M., Kumar, R., Balek, J., and Trnka, M.: Cataloguing soil moisture droughts on a global scale since 1980, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20568, https://doi.org/10.5194/egusphere-egu25-20568, 2025.
Chinook salmon (Oncorhynchus tshawytscha) are a keystone species for many ecosystems of western North America, are culturally and spiritually significant for many Indigenous Peoples, and underpin a multi-million dollar industry. However, in recent years extreme summer streamflow droughts have disrupted Chinook migration and rearing patterns. Climate change is driving hydrologic changes throughout the region, but future changes to summer low flows remain highly uncertain. Here we study 375 near-natural catchments throughout the habitat range of Chinook salmon from California to Alaska. The streams span rainfall-dominated, hybrid, snowmelt-dominated, and glacial regimes. Summer discharge has decreased in most catchments, with rainfall-dominated and hybrid catchments seeing the most severe declines.
We develop linear regression models which outperform existing process-based models, and project changes to 2100 under four emissions scenarios. Summer low flows have historically been primarily driven by variability in summer precipitation and moderately influenced by winter snow accumulation and summer temperature. However, we find that future changes will probably be driven by rising temperatures because future summer temperatures could greatly exceed the historical envelope of variability. Some further declines in low flows are probably inevitable in rainfall-dominated and hybrid catchments: under a low-emissions scenario, low flows will continue to decline to mid-century but then stabilize. Under a high-emissions scenario, 1-in-50-year low flows could occur almost every summer in many rainfall and hybrid catchments. In glacial catchments summer discharge has been relatively stable in recent years because increased glacial meltwater flows have compensated for increased evapotranspiration. However, many of these glaciers are projected to disappear within 20 to 30 years, and we project severe declines in summer streamflow when this does occur.
Many populations of Chinook rear or migrate during the summer months for which we project extraordinary future streamflow droughts. It is unknown whether Chinook populations can shift their life stage timing or find alternate habitats quickly enough to avoid catastrophic impacts. Bold climate action and local mitigation strategies are urgently required to safeguard this ecologically, culturally, and economically vital species against future extreme events.
How to cite: Ruzzante, S., Ulaski, M., and Tom, G.: Rising temperatures will drive summer streamflow droughts and threaten Chinook salmon habitat throughout western North America, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13727, https://doi.org/10.5194/egusphere-egu25-13727, 2025.
The frequency and severity of droughts have intensified in recent decades, significantly impacting water availability and human and ecological systems. This growing trend highlights the need for a comprehensive exploration of drought characteristics and their interconnected dynamics, such as the timing of onset and severity. More often, streamflow drought onset time and deficit volume show nonlinear interdependencies. The seasonality of streamflow response is a widely used indicator to assess flood probabilities, catchment classifications, and even regional frequency analysis. However, understanding streamflow seasonality in influencing low flows across different climate regimes is mainly unexplored. This study investigates streamflow droughts considering daily observations from 1160 global catchments spanning disparate climate regions between 60°N and 60°S. Our analysis indicates that approximately 12% of sites demonstrate pronounced seasonality, significantly affecting drought severity with a dependence strength greater than 0.6. In particular, 50% of sites in the tropics, 11% in subtropics, and 9% in the temperate regime show substantial seasonal impacts on the drought severity, highlighting the diverse influence of seasonality across different climatic zones. Approximately 16% of sites show a significant trend (p<0.10) toward earlier onset, whereas 34% show delayed arrival in streamflow droughts, which indicates possible nonstationarities in low-flow seasonality, potentially impacting other drought properties, severity, and duration. Considering the nonlinear dependence strengths between onset time and deficit volume in a bivariate probabilistic framework, we attempt to investigate the severity of hydrological droughts, conditional to their onset seasonality. Examining representative catchments from each climate zone, we find that winter (Dec - Feb) droughts tend to be more severe than other seasons in temperate and subtropical climate regimes. In contrast, catchments in the tropics experience more severe droughts during the summer (Jun - Aug). While winter droughts are more persistent in the tropics and subtropical regions, summer droughts tend to be longer in temperate regions. The developed model offers a probabilistic forecast of seasonal droughts and helps to assess forecast uncertainty, aiding water management during extreme low-flow seasons and water years. This approach underscores the critical role of incorporating seasonality into drought hazard assessments to enhance water security adaptations in a changing climate.
How to cite: Raut, A. and Ganguli, P.: Developing a Multivariate Probabilistic Framework to Model Onset Seasonality and Event Magnitude of Streamflow Droughts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17168, https://doi.org/10.5194/egusphere-egu25-17168, 2025.
Flash droughts, characterized by their rapid onset, are typically associated with rapid soil moisture depletion caused by insufficient rainfall and heightened evaporative stress. This study broadens the traditional impact-based definition of flash droughts to reveal their significant effects on water resources, specifically through streamflow flash drought events. By analysing perennial catchments across Australia, we identified instances of abrupt reductions in streamflow volumes over short periods. Remarkably, these events can arise from a range of antecedent conditions—wet, normal, or dry— and can potentially have damaging consequences. The severity of impacts varies non-linearly with catchment characteristics, with larger catchments often being more vulnerable. During the onset of these events, streamflow volumes typically decline by a median of 60%, underscoring the intensity of these events. Additionally, such events occur at an average frequency of two per decade across most regions. These findings emphasise the need to enhance the monitoring, forecasting, and management of these events to mitigate the adverse effects on water supply, agriculture, energy production, and other water-reliant sectors.
How to cite: Goswami, P., Gallant, A., and Bende-Michl, U.: Streamflow Flash Droughts in Australia: Occurrence, Characteristics and Impacts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2315, https://doi.org/10.5194/egusphere-egu25-2315, 2025.
The prediction of hydrological droughts in a non-stationary context poses major challenges. Understanding the drivers of drought fluctuations is crucial for developing effective adaptation and management strategies. This study addresses this issue by developing a two-step modelling approach using a multivariate Hidden Markov Model (HMM) and a Multinomial Linear Regression model (MLR), with a bootstrap approach to assess uncertainty. Using HMM, we classify the low water level time series into Dry, Normal, and Wet years and assess the frequency of each class in the historical data. Dry years can be identified as hydrological droughts. To predict low-water level class transitions in a non-stationary context, we propose an MLR framework. With this, we estimate probabilities of low-water level class transitions by inputting external variables into the transition matrix estimates. Precipitation thresholds for annual minima are also derived, with uncertainties and sensitivities assessed via bootstrap resampling. Our framework was successfully applied to the Paraguay River basin (PRB), where long-term changes in hydrological variables are frequent. The HMM transition matrix reveals a long persistence of years in each water level class and an inhomogeneity between the two periods (1901-1960 and 1961-2024). The second period exhibits more extended runs of wet, dry, and non-dry years, suggesting a change in the driving dynamics. A multi-annual hydrological drought lasting for 13 years (1961-1973) was identified, followed by a stretch of 46 years (1974-2019) with no droughts in the study area. Simulations allowed estimates of probabilities of those persistent hydrological conditions at 21% and 4% probability, respectively. Precipitation is the primary predictor of regime shifts, but the class transition probabilities and precipitation thresholds are non-homogeneous and conditional on the current low-water level regime. Different precipitation thresholds were estimated conditioned on the current water levels: 1,040 mm for initiating a hydrological drought during a normal year and 1,180 mm to transition from a hydrological drought to normal conditions. The research advances non-stationary extreme event analysis by proposing an efficient new approach for non-stationary extreme event analysis. The approach is effective in estimating inhomogeneity in hydrological drought occurrence; identifying long persistence of hydrological drought episodes and their associated probabilities; defining precipitation thresholds that trigger drought occurrence conditioned on the current basin state; and revealing the importance of coupled drivers of low water level shifts.
How to cite: Suassuna Santos, M. and Slater, L.: Integrating Hidden Markov and Multinomial Models for Hydrological Drought Prediction under nonstationarity., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3323, https://doi.org/10.5194/egusphere-egu25-3323, 2025.
While precipitation deficits have long been the primary driver of drought, our observational analysis shows that since the year 2000, rising surface temperature and the resulting high evaporative demand have contributed more to drought severity (62%) and coverage (66%) across the western US (WUS). This increase in evaporative demand, largely driven by human-caused climate change, is the main cause of the observed increase in drought severity and coverage. The unprecedented 2020–2022 WUS drought, which led to widespread water shortages and wildfires, exemplifies this shift in drought drivers, with high evaporative demand accounting for 61% of its severity. Climate model simulations corroborate this shift and project that, under the fossil-fueled development scenario (SSP5-8.5), droughts like the 2020–2022 event will transition from being a very rare event (<0.1%) in the pre-2022 period to a 1-in-60-year event by mid-century (2040-2060) and to a 1-in-6-year event by the late 21st century (2080-2100). These projections highlight the urgent need for adaptation measures to mitigate the growing risk of severe drought in the WUS under a changing climate.
How to cite: Zhuang, Y., Fu, R., Lisonbee, J., Sheffield, A., Parker, B., and Deheza, G.: A Transition from Precipitation- to Temperature-Dominated Drought in the Western United States, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3954, https://doi.org/10.5194/egusphere-egu25-3954, 2025.
Climate change and anthropogenic activities have intensified extreme weather events globally. In the summer of 2022, the Yangtze River Basin (YRB) in China experienced an extreme drought, significantly impacting the ecosystems and society. However, the specific effects of this extreme drought on surface and subsurface hydrological dynamics remain unclear. Here we employed satellite-observed terrestrial water storage anomaly (TWSA) and a modified hydrological model with consideration of reservoir operation, human water consumption, and water diversion engineering to quantify how subsurface and surface water in YRB responded to such an extreme drought in 2022. Validation against a series of observations shows that the modified model has good performance in reproducing daily streamflow, reservoir water storage, lake water storage, and snow water equivalent. It achieved more precise GRACE TWSA estimates in the YRB with significant human intervention, and therefore it can accurately quantify both surface and subsurface hydrological responses to the 2022 extreme drought. Compared to the same months (July-December) in 2015-2021, the drought in 2022 resulted in a decrease in precipitation and discharge of 373 km3 (36%) and 324 km3(50%), respectively, while an increase in evapotranspiration of 156 km3 (29%) in the YRB. In general, the surface water storage (SWS) is relatively low from July 2022, followed by subsurface water storage (SSWS) from August 2022, indicating an approximately one-month lag from the former to the latter. During the latter half year of 2022, the SWS and SSWS reduced by 48 km3 and 83 km3, respectively, suggesting the changes in the latter dominated the TWS variations. This study sheds light on the responses of surface and subsurface hydrology to extreme droughts, and the hydrological modeling framework with consideration of human activities proposed here holds applicability beyond the YRB.
How to cite: Tang, Z., Zhang, Y., and Kong, D.: Using hydrological modeling and satellite observations to elucidate subsurface and surface hydrological responses to the extreme drought, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5487, https://doi.org/10.5194/egusphere-egu25-5487, 2025.
Assessing human influence on groundwater resources globally is a complex challenge, particularly when attempting to disentangle human impacts on groundwater drought dynamics. These impacts may also have a strong influence on groundwater recovery after drought periods, where intensification of groundwater pumping could lead to longer recovery periods. With the GLOBGM v1.0, a 1km global groundwater model (1), we investigate the groundwater drought recovery at different spatial scales and various locations, with and without human influences to see if we can disentangle these signals.
While such large-scale physically-based models are valuable for simulating underlying processes, they are often computationally intensive, especially when simulating at high spatial resolutions up to 1km globally, and rely on more coarser information than locally informed models. To improve future drought recovery insights, a groundwater surrogate model is created that can reproduce groundwater fields as generated by GLOBGM. Integrating machine learning and physically-based models (hybrid approaches) offer a promising solution to not only reduce computational demands but also allow for the integration of observational data. Specifically, we will merge information from observations and the hybrid model to enhance the model's accuracy in representing human influences on drought recovery.
Ultimately, the surrogate model will help us extend the current groundwater drought recovery analysis in the future by enabling the analysis of drought dynamics and human impacts using scenario analyses under different socio-economic forcings.
References:
- Verkaik, J., Sutanudjaja, E. H., Oude Essink, G. H. P., Lin, H. X., and Bierkens, M. F. P.: GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model, Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, 2024.
How to cite: Hauswirth, S. M. and Wanders, N.: Large-scale groundwater drought recovery assessment using a 1km global groundwater model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8264, https://doi.org/10.5194/egusphere-egu25-8264, 2025.
Droughts may have severe impacts on the environment and economy, particularly in regions with high water demand and low annual precipitation. Central Europe is one such region, where droughts reportedly have led to losses in crop yield and biodiversity, disruptions in water transport, shortages of drinking water, among others. To mitigate these impacts, national weather and environmental agencies in the region have developed national drought monitoring tools. The monitoring tools enable early warning, support planning and policymaking, and foster resilience. However, the accuracy of these tools is usually unknown, since validation of such tools has been challenging due to the lack of validation data and the diversity of droughts and their impacts.
Here, we show a quantitative assessment of national drought monitoring products of six countries in Central Europe by comparing them with a novel impact database developed within the Clim4Cast project (1). The database synthesizes impacts of drought on various sectors, including agriculture, hydrology, household water supply, economy and technology, and wildlife, reported in national newspapers published between 2000 and 2023. The drought monitoring tools comprise drought indicators such as standardized precipitation index, standardized precipitation evapotranspiration index, and standardized soil moisture index with different integration periods. We assess the drought indicators in two ways: their ability to detect drought and their ability to capture the severity of the drought. First, the timing of drought impact reporting in the impact database is used to evaluate its ability to detect observed impacts. This evaluation is performed using the area-under-the-receiver-operating characteristics curve (ROC-AUC). The AUC value reveals how well the reported drought events are detected by the drought indicator. AUC value ranges from 0 to 1, where the value of 0.5 shows that the model is random while the value of 1 shows that the model is perfect. Second, for each reported drought event, we correlate the drought severity, as indicated by the drought monitoring tool, with the number of reported impacts in the database.
Our results show that the performance of drought indicators varies regionally in their ability to detect drought signals (AUC values) and their ability to capture the severity of impacts observed (correlation values). The AUC values for some indicators exceed 0.85 for Czechia while in Austria, the AUC values remain below 0.6 for most of the drought indicators. Further, the AUC values first increase with longer aggregation times of the drought index, peaking at around 9 to 12 months and decreases again for longer aggregation times. The correlation values for many drought indicators in most of the countries remain below 0.6, and the values generally decrease with increase in aggregation time. These results aid to understand the strengths and weaknesses of drought monitoring products in each country and assist to develop a common drought monitoring framework for Central Europe.
(1) This work is supported by Interreg Central Europe and the European Union in the framework of the project Clim4Cast (grant number CE0100059).
How to cite: Luintel, N., Bueechi, P. E., and Dorigo, W.: National drought monitoring services in Central Europe: how well do they capture observed drought impacts?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14666, https://doi.org/10.5194/egusphere-egu25-14666, 2025.
The interplay of hydro-climate extremes poses critical challenges to water resource management, particularly in agriculture-dominated regions where climate variability significantly affects crop production, irrigation demands, and overall agricultural sustainability. The Eastern India river basins, including the Brahmani and Baitarani, are significantly dependent on monsoonal rainfall for irrigation, drinking water, and hydroelectric power generation, making them vital for analyzing concurrent hydro-climate drought extremes. This study investigates the concurring dynamics of hydro-climate droughts driven by changes in precipitation patterns, temperature extremes, and declining river flows. The Standardized Precipitation Index (SPI), Standardized Temperature Index (STI), and Standardized Runoff Index (SRI) are employed to analyze precipitation, temperature, and runoff extremes, focusing on dry-wet dynamics within the consecutive seasons. This analysis is conducted using historical data (1979–2018) and future climate projections (2021–2060) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Additionally, we have analyzed trends in precipitation and temperature variability alongside their influence on runoff. Our findings reveal that the frequency and intensity of concurrent hydro-climate drought events are projected to increase within the seasons, with significant impacts on the monsoon season, including reduced rainfall, extended dry spells, and depleted runoff. These changes exacerbate water scarcity and heighten agricultural vulnerabilities in the region. The interconnected nature of these extremes highlights the need for integrated water resource management strategies that prioritize climate resilience. This research emphasizes the importance of adaptive measures to mitigate the socio-economic impacts of hydro-climate droughts in Eastern India, ensuring the sustainability of ecosystems and livelihoods in the face of an uncertain future climate.
How to cite: Swain, S. S., Mishra, A., and Chatterjee, C.: Concurrent Hydro-climate Drought Extremes in Eastern India Under Climate Change Scenarios, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-760, https://doi.org/10.5194/egusphere-egu25-760, 2025.
Over the last decade, our understanding of meteorological drought has evolved from an understanding of the mechanisms causing droughts to develop, to include an understanding of how they intensify and terminate. In this review, we show that the understanding of Australian drought has evolved from one that associates drought primarily with large-scale processes typically related to low precipitation, towards an understanding of the importance of processes that promote heavy to extreme precipitation. It is now understood that Australian meteorological droughts develop and intensify largely through a sustained absence of synoptic systems responsible for strong moisture transport and ascent, together with an absence of wet phases of large-scale modes of climate variability. The return of these heavy precipitation-promoting processes is key to drought termination, and can play a role in post-drought flooding. This presentation will summarise this new mechanistic understanding of Australian meteorological drought, drawing on observational, climate model and machine learning-based research. Furthermore, this presentation will outline a research agenda to address identified knowledge gaps to better the understanding, simulation and prediction of drought in Australia and around the world.
How to cite: Holgate, C. and the Coauthors of the Australian meteorological drought review: Meteorological drought development, intensification and termination mechanisms: an Australian review, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17135, https://doi.org/10.5194/egusphere-egu25-17135, 2025.
Compared to other natural disasters, drought is a disaster that continues and accumulates over time, with its impacts depending on the spatial extent of droughts over prolonged periods. Droughts propagate in time and space. Especially, the spatial drought propagation refers to expansion of drought from specific regions to other regions due to increased magnitude or transition of drought center. This study aims to conduct quantitative assessment of spatial drought propagation that has been relatively understudied in South Korea. We identified the seasonal source regions and analyzed the impacts of spatial drought propagation of meteorological droughts in South Korea, using propagation potential (PP) and potential influence of source region (PISR). The PP indicates the difference in intensity between drought propagation from a specific grid to other grids and from other grids to the specific grid. A grid with positive PP values is defined as a source region, while a grid with negative PP values is defined as a sink region. A source region refers to the region of early drought onset that propagates to other regions within the basin, and a higher PP value represents a higher intensity of drought propagation. The PISR is the proportion of drought events propagated from drought onset of source regions within the basin. In this study, the highest absolute values of PP exist in spring, which has the highest risk of drought due to the climate in South Korea, and this result indicates a frequent occurrence of spatial propagation. On the other hand, the lowest absolute values of PP exist in autumn. We estimate that drought onset in sink region is more likely influenced by propagation from source regions, rather than individual drought occurrence. In conclusion, the PP is considered for detecting the source regions of meteorological drought and assessing the seasonality of spatial propagation. In addition, the PISR quantitatively assesses the impact of source regions, determining that sink regions are high hazard influenced by source regions, rather than individual drought occurrence. The results of this study can contribute to detecting the areas where the drought can propagate ahead of time to minimize the impact of droughts.
Acknowledgement: This research was supported by a grant (2022-MOIS63-001) of Cooperative Research Method and Safety Management Technology in National Disaster funded by Ministry of Interior and Safety (MOIS, Korea).
How to cite: Son, H.-J., Han, J., and Kim, T.-W.: Detecting Source Regions of Spatial Drought Propagation and Quantitative Assessment of Their Potential Influence in South Korea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5531, https://doi.org/10.5194/egusphere-egu25-5531, 2025.
Climate projections indicate that Fenno-Scandinavia will experience increased precipitation in the future. However, the region might paradoxically face both intensified floods and more severe seasonal droughts. Little research has explored this apparent contradiction and its implications for drought frequency. Most of the current drought projections are based on global climate models with very low resolution. In this study, we use convection-permitting regional climate models (CPRCMs) based on HARMONIE-Climate at a resolution of about 3 km to investigate meteorological drought projections in Fenno-Scandinavia. For the first time this model was run for 20-year time slices (1986-2005, 2041-2060 and 2081-2100), allowing for climate analysis with explicitly resolving convection rather than relying on parameterisation, giving overall more accurate precipitation output.
Using the Standardized Precipitation Index (SPI), we found an increase in the frequency of the most extreme and unprecedented meteorological droughts. Southern Scandinavia experiences a significant increase in the most extreme droughts, especially during the growing season. To identify these increases in drought extremes, we developed a new drought threshold method using the fact that the index is standardised to compare future drought frequency to historical data. This method does not use a single drought definition, but rather compares the drought frequency for multiple intensities. Importantly, our results show significant increase in droughts projected using the 3 km convection resolving models compared to the 12 km models with convection parameterisation. This indicates that current regional climate models possibly underestimate drought risk. The projections indicate larger crop yield reduction due to short but severe dry spells during the growing season and potential impacts on natural ecosystems. The combination of overall wetter conditions with more intense seasonal droughts presents new challenges for water resource management. We recommend the usage of the drought threshold method to analyse drought projections in order to also take the intensity of the drought into account. Future work will apply the new drought threshold method to regional climate model ensemble data for greater robustness.
How to cite: Häberli, R., Kaas, E., Christensen, O. B., and Thejll, P.: High-Resolution Climate Models Reveal Increasing Meteorological Drought Intensity in Fenno-Scandinavia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10024, https://doi.org/10.5194/egusphere-egu25-10024, 2025.
Drought is a pervasive and destructive natural hazard with far-reaching impacts on various sectors that could threaten human lives. For effective mitigation and management, especially under global warming conditions, reliable means of assessing droughts are vitally important for precise monitoring and assessment. This study examines the impact of climate change on drought conditions in Jordan, a region prone to water scarcity and climate-related vulnerabilities. First, we conduct a comprehensive evaluation of drought simulation capabilities using a COordinated Regional Downscaling Experiment (CORDEX) multi-domain set consisting of 21 model simulations from three domains: Africa (AFR), Middle East and North Africa (MENA), and South Asia (WAS). Using the Standardized Precipitation Evapotranspiration Index (SPEI), which accounts for both precipitation and temperature, we assess the models' performance against historical data (1976-2005) from the Climate Research Unit at the University of East Anglia. This validation identifies a subset of model simulations that reliably generate SPEI values for Jordan. Building on these validated models, we then investigate future drought conditions for the end of the twenty-first century (2070-2099) under the RCP8.5 scenario. Projected changes reveal a significant rise in temperature and a drying tendency, with anticipated reductions in precipitation. Future drought characteristics indicate a substantial increase in severity, with decreasing frequency but increasing duration, and an expanding spatial extent of drought conditions. The outcomes of this study provide valuable insights for drought monitoring and highlight the urgent need for proactive mitigation and adaptation strategies to enhance resilience against the projected intensification of drought conditions in Jordan. These findings serve as an early warning for policymakers and stakeholders to establish efficient plans for addressing the increasing challenges posed by drought in the region and offer insights into evaluating CORDEX models for drought-related studies in other regions.
How to cite: Alkhasoneh, H. and Rowe, C.: Climate Change and Drought in Jordan: A Comprehensive Analysis Using CORDEX Regional Climate Model Simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-902, https://doi.org/10.5194/egusphere-egu25-902, 2025.
This study investigates the forecasting of drought characteristics—specifically duration, frequency, and intensity—in Syria, utilizing an ensemble of 13 models from the latest CMIP6 dataset across two Shared Socioeconomic Pathways (SSPs). The research compares CMIP6 model outputs with observed climate data from CRU TS v4.06 and ERA 5 for the reference period (1970–2000). Results show that the CMIP6 ensemble effectively replicates key climate parameters such as precipitation and temperature, while also capturing drought characteristics in Syria. However, most models tend to underestimate winter and spring precipitation, though they accurately represent the general decline in seasonal and annual rainfall. Syria's central, eastern, and northeastern regions, characterized by high temperatures and low precipitation, are particularly vulnerable. Future projections indicate significant temperature increases in northern, eastern, and northeastern Syria, with a general decline in precipitation, particularly in the southwest.
Drought projections based on SPI_12 and SPEI_12 indices indicate more severe, prolonged, and intense drought conditions, particularly in Syria’s arid and semi-arid regions. Under the high-emission scenario (SSP5–8.5), these areas are at heightened risk of severe droughts, with consistent overestimation of drought intensity and duration due to excessive temperature projections. This highlights the importance of accurate climate data for policymaking to prevent misallocation of resources and inadequate responses to droughts. Projections also suggest that areas previously less vulnerable to droughts, such as Syria's western coastal regions, may experience prolonged dry spells by the end of the 21st century. The findings underscore the need for mitigation strategies, improved water resource management, and adaptive planning to address the growing drought risks in Syria. Enhanced research and more reliable projections for semi-arid regions are critical for future climate adaptation efforts.
How to cite: Mathbout, S., Martin Vide, J., Lopez Bustins, J. A., Boustras, G., Papazoglou, P., and Raai, F.: Projections of Drought Characteristics in Syria under CMIP6 Climate Change Scenario, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9142, https://doi.org/10.5194/egusphere-egu25-9142, 2025.
Flash drought is a complex phenomenon distinguished by an unsual rapid development driven by severe precipitation deficits and/or anomalous increases in atmospheric evaporative demand (AED). While most research has focused on drier parts of the world, flash droughts can occur in temperate regions like the United Kingdom (UK). Historically most attention in the UK has focused on long, multiannual drought events driven by successive dry winters (e.g. 2004 – 2006). However, recent years have seen rapid onset flash droughts as part of exceptionally arid summers (e.g. 2018) that have had severe and widespread impacts on people and ecosystems alike. Here, we analysed the occurrence of this type of rapid-onset drought events in the UK for the period 1969-2021. Our results show that flash droughts affected both the wetter regions of north-west and the drier regions of south-east over the last five decades. Flash droughts frequency exhibit a high interannual variability, as well as a large spatial differences. Central and northern regions were the most frequently affected by flash droughts in comparison to southeastern region. Overall, positive trends were reported in eastern and northern regions, while negative and non-significant trends predominate over the western region. In UK, flash drought development responds primarily to precipitation variability, although AED is important as a secondary driver of flash drought triggering in the drier regions of southeastern England. Likewise, we found that flash droughts typically develop under remarkable positive anomalies in sea level pressure and 500 hPa geopotential height associated to the presence of high-pressure systems. This study presents a first detailed characterisation of flash drought in UK, providing useful information for drought assessment and management, and a baseline against which future changes in flash drought occurrence can be projected.
How to cite: Noguera, I., Hannaford, J., and Tanguy, M.: Flash droughts over the United Kingdom, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9538, https://doi.org/10.5194/egusphere-egu25-9538, 2025.
With climate change, new forms of droughts have emerged and/or gained major interest, such as flash droughts and dry spells. Contrarily to the classical concept of droughts, which are often defined as slow-evolving and long-lasting extremes with no definite start and end, these rapidly emerging droughts have rapid onset and clear duration.
In this study, we analyze trends of frequency and duration of rapidly emerging droughts using four dry spell (DS) and four flash drought (FD) definitions, as well as the co-occurrence of DS and FD. We also evaluate the impact of DS and FD occurrence on crop yields. To achieve that, we use 52 DWD weather stations with daily measurements across Germany with no missing data between 1980 and 2023. The DS and FD definitions require precipitation, temperature, soil moisture and actual and potential evapotranspiration series. ETP is computed using the Penman-Monteith equation. ETA and SM are obtained from the WOFOST crop simulation model using maize as the default crop.
Results show strong positive trends across Germany on both duration and frequency for both DS and FD, with particularly intense trends on compound dry-hot events (all latitudes), in short to mid-length dry spells (7 to 20 days – all latitudes), and in southern Germany (most FD and DS event definitions). We also observe a high co-occurrence rate (synchronicity) between dry spells and flash droughts in northern Germany, which could assist in developing early warning systems. Finally, results indicate strong correlations between rapidly emerging drought occurrence and significant crop losses, particularly when FD and DS are concentrated in the early summer months.
How to cite: Alencar, P. and Paton, E.: Dry spells and flash droughts – a comparative analysis of definitions, co-occurrence, trends, and impacts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9454, https://doi.org/10.5194/egusphere-egu25-9454, 2025.
Droughts and floods are becoming increasingly frequent and severe as a result of climate change, driven by rising temperatures and shifting precipitation patterns. Despite the growing recognition of the linkages between droughts and floods, no study has systematically analysed their combined impacts, particularly the economic consequences of compound drought-flood events (CDFEs). To address this gap, we developed a novel framework for identifying CDFEs and standalone flood events in Europe by utilizing various observational data, including precipitation, streamflow, and soil moisture. These events were then matched with flood impact records from the Historical Analysis of Natural Hazards in Europe (HANZE) database using both catchment-based and event-based approaches. By comparing the economic impacts of CDFEs with those of standalone flood events, we quantified the extent to which CDFEs result in higher impacts.
Our findings reveal that CDFEs impose higher economic impacts compared to standalone flood events. Significant differences are also observed in the upper tail of economic losses for CDFEs compared to standalone flood events, which implies that CDFEs are more likely to result in catastrophic losses, posing a greater challenge to risk management strategies. Our study highlights the critical need to consider the interactions between droughts and floods in disaster risk management.
How to cite: Deng, S., Guntu, R., Khosh Bin Ghomash, S., Zhao, D., and Kreibich, H.: Do compound drought-flood events cause greater damages than standalone flood events?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9824, https://doi.org/10.5194/egusphere-egu25-9824, 2025.
After a decade long period of dry conditions in central Chile, the so called “Megadrought”, the winter of 2023 was an extraordinary wet season with two extreme precipitation events that led to two mayor floods. In June and August of 2023 (austral winter) two intense Atmospheric Rivers (AR) impacted the central region of Chile, resulting in high streamflow and flooding. The two hydrometeorological events produced significant infrastructure, social and economic damages in the region. The June 22-25 event occurred during a strong (Category 4) and persistent (~72 hrs) zonal AR. Intense precipitation was registered in several weather stations along the Central Andes Cordillera foothills, with total precipitation above 800 mm/event in several stations. Anomalous windy and warm temperature conditions were recorded, positioning the freezing level at higher-than-average elevations, and thus, creating a potential rain-on-snow (ROS) flood hazards in some catchments. We use the Achibueno en la Recova River (ARR) catchment as a case study as it had the highest recorded instantaneous peak flow in more than 30 years of records. Satellite images and data from a high elevation snow station show a persistent snowpack above the 2000 masl with about 200 mm of snow water equivalent, which began to melt at the beginning of the event, suggesting that a rain-on-snow event may have enhanced the flood. We implemented a physically based hydrological model using the Cold Regions Hydrological Model at the ARR catchment to reproduce the event, estimate the contribution of the ROS to the flood event and understand the controlling physical mechanisms. The hydrological model was compared against snow water equivalent and streamflow records, reasonably representing both the timing and the magnitude of these variables. Model results suggest that the ROS significantly contributed to the event, representing about 18% of the streamflow volume (1.1x108 m3), primarily during the first 2 days. The ratio between the Terrestrial Water Input (i.e., snowmelt plus rainfall) to rainfall show values between 1.7 and 1.9 at elevations between 2000 and 3000 masl, with higher values at south-facing slopes. The energy balance shows that most of the energy to melt the snowpack comes from the advected energy from the rain (43%), followed by net radiation (37%), latent (10%) and sensible (10%) heat fluxes. This study is, to the authors knowledge, the first documented study of a ROS event in the Chilean Andes with a significant societal and economic impact, which may help to better understand the potential of future ROS floods in The Andes.
How to cite: Krogh, S., Garreaud, R., Scaff, L., Bozkurt, D., and Valenzuela, R.: The major June 2023 flood event in Central Chile: A rain-on-snow case study at the Achibueno en la Recova River catchment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10672, https://doi.org/10.5194/egusphere-egu25-10672, 2025.
Extreme hydrometeorological events such as floods and droughts can lead to severe socio-economic and environmental impacts, which can be amplified through temporally compound events, when successive hazards occur before the system can recover from the first event. This situation may arise not only from repeated occurrences of the same hazard, but also from shifts between contrasting hydrometeorological hazards. In this study, we propose a framework for consistently identifying and characterizing high-flow spells (HFS) and low-flow spells (LFS), and the transitions from one type of spell to another that might be of particular interest to stakeholders. We use baseflow as a proxy to determine catchment recovery between spells, and a mixed threshold approach to identify the spells in long discharge time series. We apply the methodology to 643 catchments of the CAMELS-FR dataset in France, with at least 30 complete hydrological years of data over the 1970-2021 period. The spells were characterized in terms of duration and severity. We further analyzed the spatiotemporal characteristics of consecutive spells of the same type and the transitions between spells, investigating their frequency and transition times. The application of the framework allowed us to identify over 140,000 spells across all catchments, with 74% classified as HFS and 26% as LFS. HFS of short duration (less than 3 days) and high severity (above 99th percentile) occur more often in catchments located in mountainous areas, while LFS of long duration (over 90 days) and high severity (below 5th percentile) occur more often in Northern France. Our results also indicate that consecutive short-duration HFS occur more often in the dataset studied than consecutive long duration LFS. Rapid transitions (less than 14 days) from LFS to HFS mainly occur in the Mediterranean part of France in the beginning of the winter season. The framework developed to identify spatiotemporal patterns of high and low flow spells can be potentially useful to new generation early warning systems and support first responders in flood disaster and drought management.
This work is funded by Horizon Europe under grant agreement No. 101074075 (MedEWSa project).
How to cite: Guimarães, G. M., Ramos, M.-H., and Pechlivanidis, I.: Using streamflow and baseflow separation to characterize spells of low and high flows and their transitions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8411, https://doi.org/10.5194/egusphere-egu25-8411, 2025.
Quantifying impacts of land-use change on streamflow extremes is challenging, primarily due to the masking effects of other environmental processes. Our current understanding of these impacts on streamflow extremes remains incomplete. Here, we use explainable machine learning techniques to analyse over 1.5 million seasonal 7-day low-flow and high-flow events across 10,717 catchments worldwide between 1982 and 2023. Our model incorporates antecedent meteorological conditions, annual change of six land-use categories, and catchment characteristics (hydrogeological, anthropogenic, and topographic) as explanatory variables. The Shapley additive explanations technique is employed to quantify the contributions of the predictors to low and high flows. Our results indicate that all categories of land-use change exert a greater influence on high flows compared to low flows, although the overall contribution of land-use change to streamflow extremes is far smaller (< 2%) than that of antecedent meteorological conditions (32%–48%) and hydrologic signatures (35%–52%). Contrary to previous studies, our results indicate that land-use impacts are largely independent of catchment size. Notably, urbanization exhibits diverging effects on low flows: enhancing them in arid regions, reducing them in tropical regions, and minimally impacting them in temperate regions. Urbanization nearly always amplifies high flows, except in minimally urbanised catchments of arid regions. Areas with higher forest cover consistently have smaller low flows across all climate zones, and high flows appear generally insensitive to afforestation. Low flows generally are insensitive to cropland expansion but areas with more cropland typically have smaller high flows.
How to cite: Zhang, B., Slater, L., Moulds, S., Wortmann, M., Yu, L., Berghuijs, W., Gu, X., and Yin, J.: Divergent impacts of land-use change on high and low river flow revealed by explainable machine learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11414, https://doi.org/10.5194/egusphere-egu25-11414, 2025.
Hydroclimate variability results in sequencing between wetter and drier periods at both day-to-day and longer timeframes. Variability at the day-to-day scale can result in sudden water surpluses or deficiencies resulting in extreme events such as floods and flash droughts. Longer-term variability, however, can significantly influence water security through the impact of droughts and reduced streamflow. Variability at both timescales poses significant challenges to water resources management, with follow-on impacts on local ecosystems and communities. In this study we investigate changes in day-to-day hydroclimate variability, focussing on the intermittency patterns of rainfall (wet and dry spells).
Our investigation, at the catchment scale, uses rainfall for 467 Hydrological Reference Stations (HRS) catchments from 1950-2022 across the Australian continent. We look at long-term trends in rainfall frequency, duration, and intensity characteristics at annual and seasonal timescales and break down our analysis by similar climatic regions. We find a clear trend towards more dry days per year across most catchments in Australia. Interestingly, there are no consistent trends in annual rainfall totals or annual mean dry spell length, despite the increase in the dry days per year. There are however consistent declining trends in annual mean and maximum wet spell lengths with shorter spells over ~80% and ~50% of catchments respectively, with the majority being in southern and eastern Australia. Northern Australia sees the opposite of this drying trend with fewer dry days per year and more intense rainfall during wet spells. Depending on the season, some regions are experiencing an increase in the number of wet spells, potentially suggesting there are changes to the dominant weather systems delivering rainfall to the region.
The presence of trends towards shorter wet spells and an increase in their frequency aligns with the change towards more episodic rainfall and highlights the need to further investigate both wet and dry spells concurrently. We conclude that wet and dry spell characteristics are changing and will continue to do so under the influence of climate change and need to be considered to manage water security across Australia.
How to cite: Thomas, S., Wasko, C., Guo, D., Bende-Michl, U., and Peel, M.: Changes in wet and dry spell characteristics in Australian catchments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1669, https://doi.org/10.5194/egusphere-egu25-1669, 2025.
Recent extreme hydrological events in the Euro-Mediterranean region have highlighted the urgent need for improved understanding and prediction of floods and droughts. Catastrophic floods, such as those in Austria, the Czech Republic, Poland, Romania, and Slovakia, have resulted in significant socioeconomic losses. More recently, unprecedented flooding in Valencia on October 29th underscores the increasing unpredictability and intensity of such events. Concurrently, Northern Africa has experienced severe, prolonged droughts over the past six years, with southern and eastern Europe facing similar challenges marked by persistent drought conditions and critical water shortages, leading to exacerbated soil moisture deficits and stressed vegetation. While the focus has largely remained on short-term meteorological drought forecasting, many significant impacts—ranging from public water supply to hydropower production—are closely tied to hydrological droughts. Understanding future variations in both flood and drought conditions is then essential for developing robust defence strategies and ensuring resilient infrastructure across the region.
This study investigates the impact of climate change on future hydrological extremes over the Med-CORDEX region. We utilized the ENEA-REG regional coupled model, which downscales historical and CMIP6 scenario simulations (SSP1-2.6, SSP2-4.5, and SSP5-8.5) from the MPI-ESM1-2-HR global model, to drive the CaMa-Flood River Hydrodynamics model for streamflow and river flood simulations. ENEA-REG integrates a coupled atmosphere (WRF) and ocean (MITgcm) components, which enhance our ability to capture complex interactions between sea surface temperatures and extreme hydrological events. Preliminary results indicate notable spatial variability in future flood and drought hazards. Considering floods, changes in their extent, duration, and high-flow frequencies (20-year and 50-year events) suggest a decrease in magnitude in eastern Mediterranean basins under SSP5-8.5, while Spanish northern (Ebro, Duero, Tajo) and southern (Guadalquivir and Andalusian) hydrographic basins, the Po River basin, together with UK and the north of Europe show increases. For droughts, the analysis focuses on changes in magnitude, duration, and trends in streamflow and streamflow drought index, highlighting critical vulnerabilities across the region. These findings emphasize the need for targeted adaptation strategies in response to evolving hydrological extremes.
How to cite: Hamitouche, M., Fosser, G., Anav, A., and Dottori, F.: Projected Changes in the Euro-Mediterranean Hydrological Extremes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-550, https://doi.org/10.5194/egusphere-egu25-550, 2025.
Droughts and floods have large impacts on a wide range of sectors and their frequency is expected to increase in a warming climate. While droughts and floods individually have distinct impacts, the occurrence of compound flood and drought (CFD) events, or vice versa, can cause greater impacts than when these events occur in isolation. This study examines changes in the characteristics and return period of single flood and drought events, as well as changes in CFD characteristics, by analyzing daily streamflow data from the CWatM (CommunityWaterModel) model for four European rivers during both historical and future periods under two climate scenarios (SSP1-2.6 and SSP5-8.5). Floods and droughts were identified using threshold methods and CFD events were determined when floods and droughts occurred within a 7-month interval. Flood and drought characteristics were defined as flood/drought frequency, flood/drought duration, flood magnitude, flood volume, and drought volume. On the other hand, CFD characteristics were analyzed based on frequency, duration, transition time, and empirical compound severity index. Flood and low flow return periods were estimated based on Gumbel’s extreme value distribution. Results show that floods will generally become more frequent and severe under SSP1-2.6, whereas under SSP5-8.5, they will become less frequent but more severe. Drought severity is projected to increase substantially under both scenarios, though the frequency will vary across different basins. Changes in return periods of high- and low-flow events also vary greatly between basins, with more extreme both high and low flows in the Rhone basin. CFD events will be more frequent and severe in the Rhine and Rhone basins, while their frequency will decrease in the Danube and Tagus basins. Rivers with lower baseflow are expected to experience more frequent and severe CFD, due to more extreme variations in rainfall. The Rhone basin, in particular, will experience shorter transitions between flood and drought events, indicating that CFD will be most impacted by climate change.
How to cite: Sutanto, S. J., Koenen, T., and Zamora, P. R.: From floods to droughts: Climate change impact on compounding streamflow flood and drought in Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3378, https://doi.org/10.5194/egusphere-egu25-3378, 2025.
Rapid transitions between droughts and floods can exacerbate the impacts of the individual events and present a complex challenge for water resource management: sudden or frequent transitions between dry and wet conditions can negatively impact water quality, agricultural productivity, and cause damage to water infrastructure. Despite these potentially severe impacts, such transitions are less comprehensively studied than their component extremes.
Transitions can be defined multiple ways, here we identify transition events as the period between consecutive yet opposite extremes. Firstly, we use a threshold method to demarcate extreme wet and dry events in both streamflow and precipitation to allow for understanding of both hydrological and meteorological transitions. Transitions are then derived from the extreme wet and dry events in pairs, to extract both wet-to-dry and dry-to-wet transitions. The transition events can then be characterised and quantified by transition metrics, namely magnitude, duration, intensity, and frequency. We apply these methods to analyse both historical and future transitions over the UK using national river flow and precipitation projections from the enhanced future Flows and Groundwater (eFLaG) dataset for 1989-2079. We also use the associated physical catchment characteristics to evaluate their influence on transitions.
This work aims to characterise the spatial distribution of transitions in the UK, with a view to identifying any ‘hotspots’ of transitions, as well as assess projected changes in transitions across the UK. We find a difference in transition characteristics between the north-west and south-east UK, a pattern which persists under future projections, and an increase in the frequency of transitions in the north-west into the future.
Our findings will provide valuable insights to support water resource managers in drought and flood preparedness in making informed, sustainable decisions to mitigate the impacts of extreme wet and dry events; and potentially enable improved prediction of hydrological extremes.
How to cite: Armitage, R., Magee, E., Chevuturi, A., Chan, W., and Hannaford, J.: Characterising Historical and Future Transitions in UK Hydrological Extremes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6991, https://doi.org/10.5194/egusphere-egu25-6991, 2025.
The Lancang-Mekong River (LMR) Basin is highly vulnerable to extreme hydrological events, including floods, droughts, and their combinations, such as Drought-Flood Abrupt Alternation (DFAA). The impacts of climate change on these extremes and the efficacy of potential adaptation measures remain poorly understood. This study investigates these dynamics using five Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). It employs the Standardized Runoff Index (SRI) and the Regional Drought-Flood Abruptness Index (R-DFAI) alongside the Tsinghua Representative Elementary Watershed (THREW) model, integrated with a reservoir module. Results reveal that the LMR Basin, particularly its upstream regions, is projected to face heightened susceptibility to drought during the near future (2021–2060) and increased flood risks in the far future (2061–2100). Under SSP126 and SSP245 scenarios, DFAA risks escalate, especially downstream and during the wet season, whereas under SSP585, these risks decline. Reservoirs as a promising adaptation strategy can significantly mitigate extreme hydrological events and DFAA, particularly in regions with higher total reservoir storage. However, their efficacy in controlling downstream floods diminishes in the far future. Reservoir operations reduce DFAA’s intensity, limit multi-peak occurrences, shorten its monthly span, and alleviate risks during critical agricultural periods. These insights offer valuable guidance for effective water resource cooperative management across LMR Basin countries.
How to cite: Zhang, K. and Tian, F.: The mitigation of reservoirs on extreme hydrological events in Lancang-Mekong River Basin under changing climate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2286, https://doi.org/10.5194/egusphere-egu25-2286, 2025.
A wide variety of processes controls characteristics of river flood events. Classifying flood events by their causative processes may assist in understanding the emergence of extremes and support the detection and interpretation of their changes. We show observational evidences of considerable changes in the frequency of different flood generation processes in Europe in the past decades that are likely to manifest in the shifts in the dominant processes by the end of the century under high emission scenario. Furthermore, we show that we can use the information on different event generation processes for diagnosing limitations of conceptual hydrological models and deep learning-powered forecasting tools paving the way to their improvement. Our ongoing work on socio-economic impacts of floods generated by different processes indicates that their future shifts and the limitations of our state-of-the-art models might have dire consequences for the flood preparedness in Europe.
How to cite: Tarasova, L.: Flood generation processes – a tool for understanding hydrological changes and improving predictions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4518, https://doi.org/10.5194/egusphere-egu25-4518, 2025.
Catchment hydrological response is frequently nonlinear (i.e., it varies more-than-proportionally with precipitation intensity) and nonstationary (i.e., it depends on the ambient conditions in the catchment). This nonlinearity and nonstationarity implies that each drop of rain may affect streamflow differently, depending on how it fits into the sequence of past and future precipitation. Thus quantifying the nonlinearity and nonstationarity in hydrological response is critical for understanding how flood behavior is shaped by catchment processes.
The nonlinearity and nonstationarity of rainfall-runoff behavior can be quantified, directly from data, using Ensemble Rainfall-Runoff Analysis (ERRA), a data-driven, model-independent method for quantifying rainfall-runoff relationships across a spectrum of time lags. ERRA combines least-squares deconvolution (to un-scramble each input's temporally overlapping effects) with demixing techniques (to separate the effects of inputs occurring under different antecedent conditions) and broken-stick regression (to quantify nonlinear dependence on precipitation intensity). I show how this approach yields a linearity exponent that quantifies how peak runoff depends on precipitation intensity, and a nonstationarity exponent that quantifies how peak runoff depends on antecedent wetness.
Here I apply this approach to data from experimental catchments and large-sample data sets, including the hourly versions of CAMELS and CAMELS-GB. Results reveal that most catchments exhibit substantial nonlinearity and nonstationarity, but with little evidence of dramatic threshold behavior.
How to cite: Kirchner, J.: Quantifying nonlinearity and nonstationarity in catchment runoff response using Ensemble Rainfall-Runoff Analysis (ERRA), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13741, https://doi.org/10.5194/egusphere-egu25-13741, 2025.
The high temporal and spatial variability of runoff generation processes makes it difficult to identify runoff source areas (partial or variable source areas), which may contribute to flooding, especially to the flood peak. Several methods have been introduced to model runoff process or map dominant runoff processes. However, no method can map areas contributing to the flood peak. This study introduces and defines flood source areas (FSA), presents the Flood Peak Source Area Index (FSAI) for quantification and comparison, and evaluates the effectiveness of classifying these areas by a new law in Germany, which is supposed to improved flood protection and risk reduction.
The distributed process-based hydrological model RoGeR was used to simulate runoff generation processes like Hortonian overland flow, saturation overland flow, subsurface stormflow, and deep percolation triggering groundwater flow to calculate the FSA. We simulated observed flood-generating rainfall-runoff events and design rainfall events with a 50-year return period, three durations (1h, 6h, 24h), and two initial soil moisture conditions (dry and wet) in six meso-scale catchments in south-west Germany representing the main soil types and geological settings in Germany. The analysis has three steps. For each scenario, the peak discharge period was determined based on the time between the "peak value -10%" before and after the peak. The second step finds source areas for each runoff generation process within the defined peak period based on travel times to the catchment outlet. These defined areas were intersected with RoGeR's spatial runoff generation maps for each runoff component and time step in the third step. To define the FSAI, we divided the maps of contributing runoff (mm) for each runoff component by the total catchment runoff (mm) during the flood peak period. This is repeated for all runoff components and added to get the quotient of total runoff to the runoff peak volume. Areas with values >1 significantly contribute to flood peak, while those with values < 1 contribute less. With overall a value of one, the entire catchment would contribute equally to the flood peak.
Results show that FSAI > 1 are occurring on 10-60% of the catchment area, depending on event and catchment. On the other hand, 15% to 90% of the catchment area have an FSAI of zero, indicating no flood peak contribution, but this is highly variable by catchment and event characteristics. FSA vary in size and location depending on the event, making them non persistent in space. The FSA patterns vary depending on initial soil moisture, precipitation intensity and duration, spatial distribution, and flood peak shape. Scale dependence matters too. FSAs vary in extent and location depending on the flood hydrograph reference point (catchment outlet). This study found no clear FSA in a watershed to map. FSA can occur anywhere in a catchment, making retention measures to reduce flood risk difficult to establish. But the study also found that roads, urban areas, and wetlands have a disproportionally higher FSAI, indicating their high sensitivity for flood genesis and making runoff reduction in these areas most effective.
How to cite: Weiler, M. and Kirn, L.: Flood source areas: can we map areas in a catchment contributing to flood peaks?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17281, https://doi.org/10.5194/egusphere-egu25-17281, 2025.
Air can hold more moisture as temperature increases, leading to more extreme precipitation events. Yet, in many locations, this does not result in larger river floods. Here we use global projections to explore differences in the response of the atmosphere and catchments to an increase in global mean temperature. We focus on changes in the amplitude of extreme precipitation events and river floods per °C above pre-industrial levels. We rely on global projections produced as part of the ISIMIP2b and ISIMIP3b projects based on CMIP5 and CMIP6 climate models, respectively. We compute changes in the median of annual maxima based on periods of 31 years on 0.5° global grids.
We find that whilst extreme precipitation is projected to increase over a large majority of the land area, a much smaller fraction of the land area is projected to show an increase in extreme flow magnitude. Importantly, whilst there is high model agreement that extreme precipitation will increase, agreement that future flows will increase is significantly lower. Specifically, ensemble spread for fluvial changes is typically wider and more likely to encompass both increases and decreases than for pluvial changes. We connect these discrepancies to changes in land-surface processes projected by the global hydrological models, highlighting the importance of river flood drivers other than extreme precipitation and illustrating the limits of using a Clausius-Clapeyron narrative to predict future changes in river floods. We compare ISIMIP2b and ISIMIP3b projections to underline the persistence of uncertainties in the magnitude of future river floods and discuss their implications for adaptation.
How to cite: Addor, N., Lord, N., Hoch, J., and Hatchard, S.: Persistent uncertainties in the magnitude of future river floods, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19095, https://doi.org/10.5194/egusphere-egu25-19095, 2025.
Dealing with large uncertainties associated with estimates of extreme floods is a major challenge for risk assessment and mitigation. It is important to understand and quantify the potential sources of these uncertainties to reduce risk and support cost-effective and safe infrastructure design.
In this study, we employ a framework based on a hydrometeorological modeling chain with long continuous simulations to estimate extreme floods (Viviroli et al., 2022). The first element of the modeling chain is the multi-site stochastic weather generator GWEX, which focuses on intense precipitation events. GWEX generates long scenarios that force a bucket-type hydrological model (HBV), which simulates discharge time series. Lastly, a hydrologic routing model (RS Minerve) implements simplified representations of river channel hydraulics, floodplain inundations and regulated lakes.
The main objective of this contribution is to quantify the uncertainty arising from the weather generator and the hydrological model at different return levels, as these two factors are highly relevant for hydrological extremes. To this end, we employ two weather generator parameterizations: the first one is the default parameterization, which serves as a benchmark, whereas specific parameters are conditioned on weather types in the second one. Then, two hydrological model configurations with different response functions are utilized. Varying these elements of the modeling chain allows us to understand their impact on the extreme flood estimates by interpreting the resulting variability as uncertainty. We run our simulations for three representative HBV-model parameter sets to account for model parameter uncertainty. This modeling framework is applied to nine large catchments (> 450 km²) located in different regions of Switzerland to consider the influence of catchment characteristics. The last step of our methodology includes the decomposition of uncertainty in extreme flood estimates using an analysis of variance (ANOVA).
Our results suggest that the contributions of different sources of uncertainty vary between the catchments. The dominant source of uncertainty may vary for different return periods ranging from 1 to 1000 years. These results highlight the challenge of generalizing a priori about the importance of the selected components contributing to the total uncertainty at the catchment scale, as physiographic catchment characteristics play a key role. Overall, this study sheds light on the role of uncertainties in a hydrometeorological modeling chain and will serve as a basis for follow-up studies related to hazard assessment, safety planning, and hydraulic engineering projects.
Reference:
Viviroli D, Sikorska-Senoner AE, Evin G, Staudinger M, Kauzlaric M, Chardon J, Favre AC, Hingray B, Nicolet G, Raynaud D, Seibert J, Weingartner R, Whealton C, 2022. Comprehensive space-time hydrometeorological simulations for estimating very rare floods at multiple sites in a large river basin. Natural Hazards and Earth System Sciences, 22(9), 2891–2920, doi:10.5194/nhess-22-2891-2022
How to cite: Kritidou, E., Kauzlaric, M., Vis, M., Staudinger, M., Seibert, J., and Viviroli, D.: Understanding the impact of precipitation and model uncertainties on extreme flood estimates, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2595, https://doi.org/10.5194/egusphere-egu25-2595, 2025.
Abstract: As urban populations grow and cities expand and develop, the likelihood of natural disasters, such as floods, increases accordingly. Urban centers and residential areas are highly susceptible to flooding. Flooding poses significant risks to urban areas, especially in regions vulnerable to climate change, where developing countries are disproportionately affected. In Erbil, the rapid expansion and urban development, particularly following the 2004 liberation by coalition forces, have resulted in the extensive conversion of agricultural and undeveloped lands both within and beyond the city's municipal boundaries into built-up areas. Compared to rural areas, urban areas are more significantly impacted by natural disasters, particularly flooding. This study explores the influence of surface cover types on runoff and flood risk, focusing on the Italian City-2 and Rizgary neighborhood in Erbil, Kurdistan Region of Iraq. The challenges associated with surface water management are not limited to new neighborhoods but are also prevalent in many older neighborhoods of the city. The Soil Conservation Service Curve Number (SCS-CN) method was employed to model runoff under varying rainfall scenarios. This study aimed to: (1) evaluate the impact of impervious surfaces in residential areas on runoff generation, emphasizing the role of urban design; (2) analyze how varying housing densities influence runoff under different rainfall scenarios, comparing Italian City 2 and Rizgary Neighborhood in Erbil to represent distinct urban typologies; and (3) explore the potential of the SCS-CN method for sustainable hydrological planning. The findings provide insights for optimizing urban planning, mitigating flood risks, and enhancing water resource management in semi-arid regions like Erbil. The results reveal that increasing the proportion of permeable surfaces significantly reduces runoff volumes and mitigates flood risks, as compared to areas dominated by impervious surfaces. These findings underscore the critical importance of integrating permeable materials and green infrastructure into urban design to enhance flood resilience. The study offers valuable insights for urban planners, policymakers, and developers by identifying optimal surface compositions for reducing flood risks in rapidly urbanizing areas. Additionally, the research emphasizes the urgent need for sustainable urban development policies, particularly in regions like Erbil, which face the dual challenges of rapid urbanization and climate change-induced risks.
How to cite: Mustafa, A., Szydłowski, M., and Aziz, S. Q.: Optimizing Impervious Surface Distribution for Enhanced Urban Flood Resilience, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4550, https://doi.org/10.5194/egusphere-egu25-4550, 2025.
Flood frequency estimation is critical for water resource planning and management; however, traditional methods, typically univariate, often underestimate impacts due to several limitations, such as the use of short observational series (Taleb, 2022) and the lack of consideration for the interdependence among key hydrological variables (e.g., precipitation, discharge, and volume) (G. Salvadori et al., 2011; Serinaldi, 2015) Addressing these shortcomings, we present an innovative methodological framework that integrates continuous hydrologic-hydraulic modeling with multivariate analysis techniques (Brunner et al., 2017; Grimaldi et al., 2013, 2021), enabling a more comprehensive representation of flood impacts and extent. This approach encompasses three distinct hydrological modeling strategies:
First, we employ rainfall-based modeling using both observed and synthetic rainfall series to develop rainfall-runoff hydrological models that generate discharge series. These discharge series are used to apply univariate methodologies, resulting in three flood scenarios: one scenario based on discharges derived from observed rainfall, a second scenario using synthetic rainfall, and, finally, an additional scenario derived from continuous hydrologic-hydraulic modeling. A key advantage of the latter approach is the elimination of the need for design hyetographs and hydrographs, which are significant sources of uncertainty in conventional methods (Grimaldi et al., 2012).
Second, we focus on discharge-based modeling, utilizing both observed and synthetic discharge series. This process employs a multivariate methodological framework to generate synthetic discharge series derived from observed data. Univariate methodologies are applied to these series to produce two flood scenarios: one exclusively based on observed series and another on synthetic series. Additionally, continuous discharge series generated through the multivariate framework are incorporated into a continuous hydrologic-hydraulic modeling approach, yielding a third scenario that enables more robust and detailed analysis.
Finally, joint behavior is evaluated through the analysis of joint return periods, accounting for the spatial dependence of precipitation (Urrea Méndez & Del Jesus, 2023) and the interaction between discharge and volume (Brunner et al., 2017; Fischer & Schumann, 2023). This framework explores distinct approaches that complementarily capture the physical processes underlying floods, thereby reducing uncertainty and improving estimations compared to conventional univariate methods. Validation of this framework will be conducted in the Los Corrales de Buelna region, Spain, demonstrating how the combination of multivariate tools and continuous hydrologic-hydraulic modeling enhances the accuracy of extreme event identification and management, offering more robust and effective solutions for engineering and territorial planning.
Brunner, M. I., Viviroli, D., Sikorska, A. E., Vannier, O., Favre, A.-C., & Seibert, J. (2017). Flood type specific construction of synthetic design hydrographs. Water Resources Research, 53(2), 1390–1406. https://doi.org/10.1002/2016WR019535
Salvadori, C. De Michele, & F. Durante. (2011). On the return period and design in a multivariate framework. Hydrology and Earth System Sciences, 15(11), 3293–3305. https://doi.org/10.5194/hess-15-3293-2011
Grimaldi, S., Nardi, F., Piscopia, R., Petroselli, A., & Apollonio, C. (2021). Continuous hydrologic modelling for design simulation in small and ungauged basins: A step forward and some tests for its practical use. Journal of Hydrology, 595, 125664. https://doi.org/10.1016/j.jhydrol.2020.125664
Grimaldi, S., Petroselli, A., Arcangeletti, E., & Nardi, F. (2013). Flood mapping in ungauged basins using fully continuous hydrologic–hydraulic modeling. Journal of Hydrology, 487, 39–47. https://doi.org/10.1016/j.jhydrol.2013.02.023
How to cite: Urrea Méndez, D. A., Gomez Rabe, D. V., and del Jesus Peñil, M.: Advancing Flood Impact Estimation: Comparing Multivariate Continuous Hydrologic-Hydraulic Models with Traditional Approaches, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6833, https://doi.org/10.5194/egusphere-egu25-6833, 2025.
Canada has a long history of recurrent flooding, which has resulted in significant damage and large government disaster assistance disbursements. The most expensive flood in Canada was the 2013 Alberta flood, which resulted in total estimated losses of over five billion dollars, according to the Canadian disaster database. There is an increasing body of literature, suggesting that future climate change will alter precipitation and streamflow characteristics, snowpack, and snowmelt timing and magnitude. Extreme inflows that exceed dam discharge and storage capacity can lead to dam breach, posing significant risks to lives and properties on the downstream. Dams constructed decades ago are specifically vulnerable to unprecedented flood events. Therefore, in addition to other actions, an important step for enhancing and assessing climate-resilience of dams is to develop climate change informed approaches for estimating design floods and associated guidelines. For the development of design flood estimation guidelines, a variety of literature was explored, including journal articles, national and international guidelines, technical reports, and documents pertaining to regional climate change and catastrophic events. In addition, outcomes from a number of targeted dam vulnerability assessment case studies, involving development of physics-informed non-stationary flood frequency relationships and flood envelop curves, were also considered. Through a systematic review of traditional design practices, careful examination of regional climate change vulnerabilities, and outcomes of targeted dam vulnerability assessment case studies, it was realized that a variety of approaches will be required to ensure future climate-resilience of dams of all sizes, ranging from low-risk small dams to high-risk large dams. Therefore, traditional design flood estimation methodologies need to be innovated, following new design philosophies, advances in climate change science, and improved understandings of regional flood generating mechanisms. This presentation will discuss the steps taken to develop design flood estimation guidelines and the outcomes of various research activities, including the development of physics-informed non-stationary flood frequency analyses and creation of regional flood envelop curves to support design of critical water infrastructure.
How to cite: Khaliq, M.: Climate-Resilience of Dams: Canadian Perspectives and Design Flood Estimation Guidelines, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7330, https://doi.org/10.5194/egusphere-egu25-7330, 2025.
Large floods regularly cause loss of life and substantial economic damage. In a warmer climate, increased precipitation variability and extremes, combined with reduced snowmelt, are expected to alter flood characteristics, but how the dynamics of large floods across Europe will evolve under climate change remains unclear. Many existing grid-based and catchment-based studies lack the capacity to systematically identify widespread floods associated with larger impacts. This study addresses these gaps by identifying large, spatially connected floods in Europe based on the spatio-temporal connectivity of runoff extremes, which is derived from daily routed runoff simulations driven by five CMIP5 models under various warming levels. Further, a comprehensive set of flood metrics—including frequency, timing, extent, and volume—is quantified to assess future flood changes. Additionally, the underlying drivers of these changes are investigated. We show that earlier snowmelt generally leads to earlier floods, while increasing precipitation contributions attenuates flood seasonality. In western and central Europe, projected increases in precipitation amplify flood extents and volumes, particularly for the most extreme floods. In contrast, reduced snowmelt dominates flood changes in northern Europe. Interestingly, floods of different magnitudes exhibit varied responses to global warming. For example, while the extent of average large floods in southern Europe are projected to decrease, the most extreme floods remain nearly unchanged, warranting continued attention. Overall, our findings demonstrate that the impact of climate change on the dynamics and magnitude of large floods is strongly region-specific. These insights provide essential information for regional flood risk management and could help mitigate the impacts of particularly large floods in Europe.
How to cite: Fang, B., Rakovec, O., Bevacqua, E., Kumar, R., and Zscheischler, J.: Future evolution of large floods in Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9464, https://doi.org/10.5194/egusphere-egu25-9464, 2025.
Flash Droughts characterized by their rapid onset and development are a growing concern because of the threats it poses to agriculture and ecosystems (O and Park, 2023) caused by the rapid decline in soil moisture. Despite that little is known about how they will develop under different warming levels.
This study aims to bridge that gap in our understanding of flash drought development by examining the frequency and extent of flash droughts across Europe under 1.0°C, 1.5°C, 2.0°C and 3.0°C global warming levels relative to pre-industrial time. This study uses mesoscale hydrologic model (mHM) (Samaniego et al., 2010; Kumar et al, 2013) to simulate soil moisture using the data from bias corrected climate projections from the Inter-Sectoral Impact Model Intercomparison Project Phase 3b (ISIMIP3b) derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) (O’Neill et al., 2016). Flash droughts are identified using percentiles-based criteria detecting rapid decline in soil moisture content (Shah et al., 2022).
Results indicate the area under flash droughts are expected to increase by 50% at 3°C warming compared to 1°C in the entire Europe with the effect being more prominent in the Northern parts of Europe going as high as three times at 3°C compared to 1°C. Frequency of such events is expected to double as the climate heats up from 1 °C to 3 °C, with the effects again getting reflected more in the Northern region of the Europe and diminishing as we move down South towards the Mediterranean. Results also indicate that areas such as France, Spain and Norway which were already facing flash droughts historically are expected to have more such events with new areas also getting affected thus making the event more widespread.
These findings indicate the effect of climate change and how it can affect the agricultural systems and the need for proactive adaptation measures to mitigate the effects.
Keywords: Flash drought, mHM, CMIP6, Warming levels, soil moisture, pre-industrial
Kumar, R., Samaniego, L. and Attinger, S., 2013. Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations. Water Resources Research, 49(1), pp.360-379.
O, S., Park, S.K., 2023. Flash drought drives rapid vegetation stress in arid regions in Europe. Environ. Res. Lett. 18, 014028. https://doi.org/10.1088/1748-9326/acae3a
O’Neill, B.C., Tebaldi, C., van Vuuren, D.P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G.A., Moss, R., Riahi, K., Sanderson, B.M., 2016. The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev. 9, 3461–3482. https://doi.org/10.5194/gmd-9-3461-2016
Samaniego, L., Kumar, R., Attinger, S., 2010. Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res. 46. https://doi.org/10.1029/2008WR007327
Shah, J., Hari, V., Rakovec, O., Markonis, Y., Samaniego, L., Mishra, V., Hanel, M., Hinz, C., Kumar, R., 2022. Increasing footprint of climate warming on flash droughts occurrence in Europe. Environ. Res. Lett. 17, 064017. https://doi.org/10.1088/1748-9326/ac6888
How to cite: Yadav, D., Kumar, R., Shah, J., Hanel, M., and Rakovec, O.: Projected flash drought evolution across Europe at different global warming levels , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-727, https://doi.org/10.5194/egusphere-egu25-727, 2025.
Design flood quantile estimation at critical locations in a river basin is essential for various hydrological applications. Regional flood frequency analysis using the L-moment-based approach offers a robust and efficient method for estimating flood quantiles at ungauged and sparsely gauged sites. The literature suggests that LH moments—higher probability-weighted moments—place greater emphasis on the tail of the distribution. This study explores the performance of the LH-moment-based approach for regions modeled using the Log Pearson Type III (LP-III) distribution, applying techniques such as the method of moments, maximum likelihood estimation, L-moments (a special case of LH-moments), and LH-moment parameter estimation. A Monte Carlo simulation experiment was conducted to assess the accuracy and reliability of these parameter estimation techniques for design flood estimation. The analysis was applied to four river basins in South India to evaluate the ability of the LP-III distribution to model annual maximum series across different climate zones (arid, temperate, and tropical). The findings have significant implications for flood risk management, infrastructure design, and policy-making, especially in regions undergoing rapid environmental changes. This research enhances the understanding of regional flood dynamics and provides a framework for more accurate flood risk assessments and improved management strategies.
How to cite: Singh, A. and Chavan, S.: Assessing the uncertainty in parameter estimation of Log Pearson type III Distribution, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-972, https://doi.org/10.5194/egusphere-egu25-972, 2025.
While nature-based drought mitigation measures (DMM), such as removing drainage and abstractions and raising stream bed levels, are a possible solution to combat droughts by targeting raised groundwater levels, they can also reduce the available storage capacity to buffer storm events, creating potential trade-offs with flood risk management objectives. However, the effects of floods and droughts are rarely assessed jointly. We demonstrate a coupled groundwater-surface water modeling approach in a shallow groundwater system of the Dutch sandy soils region that has shown vulnerability to droughts. We simulate the effects of DMM on both long-term averages of groundwater levels and short-term groundwater and surface water responses during heavy rainfall events. The DMM raise long-term summer groundwater levels, thereby compensating climate change induced summer groundwater storage deficits. However, during wetter winter months, groundwater levels are also raised significantly. As a result of reduced available flood storage capacity, peak streamflow increases following heavy winter rainfall events. We conclude that it is crucial to design and plan drought and flood mitigation strategies jointly. This also requires tailoring land management to prevalent environmental conditions. To this end, developing modeling approaches for a joint assessment of hydrological effects is key to inform the formulation of integrated strategies.
How to cite: Wittmann, C., de Louw, P., Schoonderwoerd, E., Kingma, V., Dahm, R., Peerdeman, K., and Penning, E.: Evaluating the effects of drought mitigation measures during floods, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1152, https://doi.org/10.5194/egusphere-egu25-1152, 2025.
In this paper, we propose a new approach for multivariate drought frequency analysis. It combines extreme value statistics of magnitude, duration and deficit volume of annual streamflow drought events. Drought magnitude is represented by the annual minimum flow. It is modeled by the mixed distribution approach of Laaha (2023a) based on annual summer and winter minimum series, where possible seasonal correlations are modeled by a copula approach (Laaha 2023b). Duration and deficit volume of annual drought events are estimated by Yevjevich’s threshold level approach, using a constant threshold level. To this end, the dependence structure of magnitude (M), duration (D) and deficit volume (V) with seasonality characteristics is evaluated. The joint probability of occurrence of multiple drought characteristics is modeled using a Vine copula approach, thereby extending bivariate drought frequency analysis of Mirabbasi et al. (2012). The multivariate frequency model allows marginal and total frequencies or return periods of drought events to be calculated. We anticipate that the multivariate low-flow frequency analysis is more comprehensive, and thus more effective in capturing drought severity compared to the univariate analyses. We suggest that the method can be used for drought monitoring in various hydrological settings including strongly seasonal climates.
References:
Laaha, G., 2023a. A mixed distribution approach for low-flow frequency analysis–Part 1: Concept, performance, and effect of seasonality. Hydrology and Earth System Sciences, 27(3), pp.689-701.
Laaha, G. 2023b. A mixed distribution approach for low-flow frequency analysis–Part 2: Comparative assessment of a mixed probability vs. copula-based dependence framework. Hydrology and Earth System Sciences, 27(10), 2019-2034.
Mirabbasi, R., Fakheri-Fard, A. and Dinpashoh, Y., 2012. Bivariate drought frequency analysis using the copula method. Theoretical and applied climatology, 108, pp.191-206.
How to cite: Firoozi, F., Laimighofer, J., and Laaha, G.: Low flow frequency analyses: A new approach integrating seasonality and multivariate characteristics of drought, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3052, https://doi.org/10.5194/egusphere-egu25-3052, 2025.
Abstract
Extreme low flow is a critical component of the river flow regime, posing significant risks for water management by impacting water availability and quality. Addressing these challenges requires accurate information on design low flow corresponding to specific non-exceedance probabilities. Traditional low-flow frequency analysis assumes stationarity and process homogeneity; however, these assumptions become questionable under the influence of climate change and varying generation processes for low flows, such as in seasonal snow climate that the annual extreme series will be a mixture of both summer and winter low-flow events. The study aims to extend regional low flow frequency analysis to non-stationary conditions and account for seasonal variation for a better statistical description of extreme events.
First, we analyse temporal trends in the study area separately for annual minimum winter and summer series and investigate whether they can be related to temperature increase or other climate trends. Then, we apply modelling concepts to extend the mixed distribution model of Laaha (2023) to non-stationary conditions using a conditional Generalized Extreme Value (GEV) distribution. This allows us to consider the detected trends in low flow frequency analysis. The results of the study provide a new perspective on low flow processes and impact chains in river systems.
Keywords: Non-stationary frequency analysis, low flow, drought, climate change, seasonality
Reference
Laaha, G. (2023). A mixed distribution approach for low-flow frequency analysis – Part 1: Concept, performance, and effect of seasonality. Hydrol. Earth Syst. Sci., 27(3), 689-701. https://doi.org/10.5194/hess-27-689-2023
How to cite: Fitriana, F. S., Fischer, S., Weigelhofer, G., and Laaha, G.: Non-stationary low-flow frequency analysis with Mixture Generalized Extreme Value (GEV) distribution, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5996, https://doi.org/10.5194/egusphere-egu25-5996, 2025.
In the second decade of September 2024, after a long-lasting above-average temperature period without widespread precipitation, an extraordinary precipitation event occurred, affecting mainly the west and northwest of Slovakia. Cumulative precipitation amounts ranged from 120 to 250 mm, locally significantly more on the windward sides of the mountains. Extraordinary high precipitation totals were also recorded in surrounding countries, especially in Austria, Czech Republic, Romania and southern Poland. This precipitation event resulted in a flood situation. We observed the highest level of flood activity on all hydro-prognostic profiles of the rivers Morava and Danube. Direct hydraulic interaction between surface water and groundwater in the Záhorská nížina Lowland, Žitný ostrov Island and areas along right bank of the Danube River has caused a significant increase of the groundwater level during the flood wave in these areas. Based on the measured data from the state groundwater monitoring network of the Slovak Hydrometeorological Institute, we assessed the state of the groundwater level in the affected areas during the flood situation. We also identified and analyzed in more detail the areas where groundwater reached the terrain.
How to cite: Radič, S., Gavurník, J., and Slivová, V.: Flood situation on the rivers Morava and Danube in September 2024 and its impact on the groundwater level, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4334, https://doi.org/10.5194/egusphere-egu25-4334, 2025.
Droughts and floods are natural phenomena in the Amazon, arising from the spatial and temporal variability of rainfall distribution. However, anthropogenic climate change and forest degradation, summed to large-scale climatic events, have intensified their frequency, intensity and onset, pushing the Amazon region to a critical tipping point. The Madeira River, the largest and most significant tributary of the Amazon River, is particularly vulnerable to these extremes. Notable droughts in 2005, 2010, 2015-2016 and 2023-2024, alongside major floods in 2014 and 2021, highlight the increasing variability of hydrometeorological patterns, severely impacting water resources, ecosystems and communities. This study evaluates the environmental and social impacts of climate change on the Madeira River Basin, emphasizing changes in hydrometeorological patterns and their repercussions in droughts and flood events. Daily observed data on precipitation, streamflow, and water level from stations operated by the National Water and Sanitation Agency (ANA) were analyzed. A 50-year historical dataset (January 1975 to August 2024) across 14 locations was used to calculate the Standardized Precipitation Index (SPI) and the Standardized Streamflow Index (SSI) to assess the magnitudes, duration, and period of occurrence of flood-drought events. The findings reveal escalating impacts of hydrological extremes on ecosystems and communities. Rising temperatures and extreme events disrupt the basin’s ecological recovery processes, reducing soil moisture, altering evapotranspiration rates, and stressing biodiversity. Communities face reduced water availability, compromised hydroelectric energy production, and restricted transportation for riparian populations reliant on river systems for livelihoods. Correlations between SPI and SSI were analyzed to understand the interactions between climatic and hydrological variables, offering insights into the basin’s response mechanisms to drought and flood events. These insights are critical for guiding adaptive strategies and managing water resources in a changing climate. Furthermore, the study highlights the importance of developing and refining early warning systems to mitigate risks, enhance resilience and support sustainable management in the face of hydrological extremes.
How to cite: Camarano Lüdtke, J., Melo Brentan, B., and Ferreira Rodrigues, A.: Investigating the Impacts of Climate Change on Hydrological Extremes in The Madeira River Basin, Amazonia: an emphasis on the unprecedented drought-flood transitions over the last decade, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4574, https://doi.org/10.5194/egusphere-egu25-4574, 2025.
Floods are a recurring and devastating hazard in West Africa, with significant socio-economic and environmental impacts. A better understanding of their frequency and magnitude is crucial for effective flood risk mitigation, infrastructure design, and water resource management. The lack of reliable hydrometric datasets has hitherto been a major limitation in flood frequency analysis at the scale of West Africa. We combine insights from historical flood frequency analysis and future climate-driven flood projections to provide a more complete description of flood hazards in West Africa. Using a newly developed African hydrological database, annual maximum flow (AMF) time series from 246 river basins (1975–2018) were analyzed with the Generalized Extreme Value (GEV) and Gumbel distributions. The GEV distribution, paired with the Generalized Maximum Likelihood Estimation (GMLE) method, yielded the best results for quantile estimation, enabling the generation of regional envelope curves for the first time in West Africa. Future flood trends have been assessed from the OS LISFLOOD and the HMF-WA large-scale distributed hydrological models, driven by five bias-corrected CMIP6 climate projections under the SSP2-4.5 and SSP5-8.5 scenarios. Both hydrological models consistently projected increases in flood frequency and magnitude across West Africa, despite their differences in hydrological processes representation and calibration schemes. Flood magnitudes are projected to increase in 94% of stations, with some areas experiencing increases exceeding 45%. Significant trends are already observable in many basins as early as the 1980s, emphasizing the robust climate change signal in this region. This combined approach, integrating historical flood frequency analysis with future climate-driven projections, offers critical regional-scale insights into the evolving flood hazards in West Africa.
How to cite: Diop, S. B., Ekolu, J., Tramblay, Y., Dieppois, B., Grimaldi, S., Bodian, A., Blanchet, J., Rameshwaran, P., Salamon, P., and Sultan, B.: Flood frequency analysis in West Africa in a climate change context, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10427, https://doi.org/10.5194/egusphere-egu25-10427, 2025.
Climate change-induced fluctuations in the hydrological cycle are expected to increase the frequency of hydrological extremes and the transitions between them, namely, drought-flood and flood-drought transitions. While much research has focused on these events individually, their interactions remain less explored despite significant implications for water management, requiring a balance between water availability and safety.
This study investigates the interplay of hydro-meteorological drivers—precipitation (P), temperature (T), and streamflow (Q)—during drought-flood and flood-drought transitions across selected catchments in Europe with diverse climates, using long-term observational datasets. Drought and flood events are defined based on extreme wet and dry meteorological conditions (extending the methodology developed in Hariharan Sudha et al., 2024), and the duration and magnitude of their hydro-meteorological characteristics are quantified. The analysis examines how an opposite hydrological event as a precondition influences the propagation speed, timing, and severity of the subsequent event compared to events without a precondition. Propagation speed is assessed by the time lag between meteorological (P/T) and hydrological (Q) drivers of events, while correlations between the hydro-meteorological characteristics of successive events are used to evaluate the severity of transitions.
Through this study, regional patterns and trends in the propagation, timing, and severity of drought-flood and flood-drought transitions are identified, highlighting the role of climate and catchment characteristics in shaping these dynamics. The findings provide a basis for understanding hydrological transitions under future climate scenarios, contributing to improved risk assessment and adaptive water resource management.
Reference:
Hariharan Sudha S, Ragno E, Morales-Nápoles O and Kok M (2024) Investigating meteorological wet and dry transitions in the Dutch Meuse River basin. Front. Water 6:1394563. doi: 10.3389/frwa.2024.1394563
How to cite: Sudha, S. H., Ragno, E., van der Ent, R., and Morales Nápoles, O.: Interactions Between Hydrological Extremes: Analysing drought-flood and flood-drought transitions in Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11452, https://doi.org/10.5194/egusphere-egu25-11452, 2025.
The transition from droughts to floods poses significant challenges to socio-environmental systems, as these extremes often occur in rapid succession, leaving little time for recovery. These abrupt transitions exacerbate disaster risk, also resulting in complex interaction between drivers and impacts. The Standardized Precipitation Evapotranspiration Index (SPEI) from 1901 to 2023 at multiple timescales is used to better understand these dynamics in Pakistan, a highly vulnerable country. Southern Pakistan, especially Sindh and Baluchistan, is the most affected area as the analysis reveals more frequent dry events with shorter interarrival times and high drought intensity. The decreasing interval between dry and wet periods highlights increasingly rapid transitions from dry to wet conditions over time. These results underscore the limited potential for sustained recovery after drought events, which not only poses significant challenges for water resource management and agriculture but also amplifies the severity of subsequent flood impacts. To better understand these dynamics, we analysed the drought-to-flood transition that occurred between 2020 and 2022. Results highlight spatiotemporal interaction between risk components, impacts and management of cascading extremes exacerbating vulnerabilities. This underscores the pressing need for comprehensive and adaptive mitigation strategies that address the interconnected nature of these events.
How to cite: Ridolfi, E., Moccia, B., Russo, F., and Napolitano, F.: Accelerating transitions between dry and wet periods in Pakistan: interconnected impacts and exacerbated vulnerabilities, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13402, https://doi.org/10.5194/egusphere-egu25-13402, 2025.
Extreme floods exceeding historical records have become more frequent globally in recent years due to climate change, signaling an increasing non-stationarity in flood patterns. Traditional design floods, based on the assumption of stationarity, are no longer sufficient to ensure engineering safety and human welfare, necessitating a re-evaluation and revision of design flood standards. The Lancang-Mekong River Basin (LMRB) is both climate-sensitive and a high-risk area for flood disasters. To better manage future flooding in the LMRB, six hydrological stations along the mainstream are focused to analysis flood non-stationarity. In this study, a GAMLSS model based on temporal covariates is developed and nine global climate models and two SSPs-RCPs scenarios are designed for flood peaks frequency analysis. The results show that annual maximum flood peak series exhibit significant non-stationarity, with a noticeable increasing trend across the entire basin under the BCC, CCCMa, and MIRCO climate models. In contrast, the remaining models show an increasing trend in the upstream and a decreasing trend in the downstream. When non-stationary models are constructed, the flood peak series at most stations follow log-normal and gamma distributions under different future scenarios, with both the mean and variance showing a strong linear relationship with time. Compared with traditional stationary models, future design floods present heterogeneous deviations from upstream to downstream. At the upstream Chiang Saen station, flood estimates shift from overestimation to underestimation over time, with a 5% underestimation of the 100-year flood by 2065. This suggests that additional flood control infrastructure will be needed to withstand more frequent extreme floods. Conversely, at the downstream Kratie station, an opposite trend is observed, with a 7% overestimation of the 100-year flood by 2065, suggesting that some existing infrastructure may become redundant in the future. This study providing a more accurate scientific basis for flood risk forecasting and offering new support for flood management and disaster risk reduction in the basin.
How to cite: Li, Y., Zhang, J., and Zhou, H.: Non-Stationarity flood frequency analysis in the Lancang-Mekong River Basin under Climate Change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14235, https://doi.org/10.5194/egusphere-egu25-14235, 2025.
Droughts are among the most devastating natural hazards, driving conflict, migration, and socioeconomic changes worldwide. Compound droughts – where meteorological, hydrological, and soil moisture (agricultural) drought co-occur – have greater ecological and socio-economic impacts than individual drought types. However, existing knowledge about global-scale compound droughts is limited, as research is mostly focusing on smaller areas and the propagation of meteorological drought to other types, typically considering just two different drought types.
Here, we use an ensemble of 9 model outputs from the ISIMIP3a experiment (H08, WaterGAP 2.2e, Miroc-Integ-Land, forced with 20CRv3-ERA5, 20CRv3-W5E5, GWSP3-W5E5 reanalysis datasets) with daily outputs of precipitation, soil moisture and discharge to compute empirical drought indices. Focusing on severe drought events with index value (intensity) below -1.5, we analyse event characteristics as well as probability and duration of compounding for 1961–2020.
We found significant variability in duration and probability across different hydrological regions (hydrobelts) and drought indices, with results sensitive to the drought type used as basis for the comparison. The largest differences in duration and probability between hydrobelts occurred with soil moisture drought as the basis of analysis, while meteorological drought as the base showed the smallest differences. Compound drought durations were longer in the Southern Hemisphere, particularly near the equator. Soil moisture and hydrological droughts had longer median durations than meteorological droughts and therefore higher probabilities of compounding. The high probabilities were concentrated in northern latitudes and Asia for soil moisture drought and were globally more evenly distributed for hydrological. Analysing the influence of ENSO revealed longer durations and higher probabilities globally during El Niño compared to La Niña months. The uncertainty in the probability of compounding shows large spatial variation and was found to depend on the model, climate forcing, drainage basin size and the hydrobelt.
Our results may help prepare regional or national drought management plans by providing insights into the spatial characteristics and probability of compound droughts. However, until the uncertainty in global modelling is addressed, and new methods or simulations are provided, the benefit is limited.
How to cite: Seppälä, P., Kallio, M., Ahopelto, L., Fallon, A., Kinnunen, P., Heino, M., and Kummu, M.: Global models show strong spatial variation in compound drought occurrence, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18679, https://doi.org/10.5194/egusphere-egu25-18679, 2025.
Traditional hydrologic design has focused on using annual maximum values. However, numerous significant hydrologic events such as active and break spells during monsoons, heat waves, and flash floods from snowmelt occur over days to weeks. These events require daily or even finer resolution data for accurate characterization. Often, impactful events result from multiple hydrologic variables exhibiting extreme behaviour concurrently - known as compound extremes - leading to different occurrence probabilities and impacts than those extreme events identified through univariate analyses. Characterizing these extreme events is challenging due to the need for the joint consideration of multiple variables. This study introduces a novel multivariate approach using a time-varying interval-censored estimation method for copula models. This method enables the determination of design magnitudes and associated risks with compound extremes when hydrologic data exhibit (i) strong dependence, and (ii) significant ties. The method's effectiveness is demonstrated in the Godavari River Basin, India, using daily precipitation and temperature data over the monsoon seasons between 1977 and 2020. A conservative approach is recommended for estimating design magnitudes in multivariate contexts. The study examines the importance of ties and temporal dependence between precipitation and temperature data in estimating the design magnitudes of cold-wet compound extremes at specified exceedance probabilities across various spatial scales. The results show that ties and temporal dependence significantly affect design estimates. Since these characteristics are common in hydrologic data, this framework is broadly applicable for characterizing other compound extremes in hydrology.
How to cite: Subhadarsini, S., Kumar, D. N., and Govindaraju, R. S.: Analyzing Compound Extremes in Hydrology: A Multivariate Approach Using Correlated Time Series, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20701, https://doi.org/10.5194/egusphere-egu25-20701, 2025.
Droughts are traditionally associated with warmer, arid climates. However, recent events such as the European droughts of 2018 and 2022, have also highlighted the vulnerability of temperate regions such as Northern Europe. For example, in Denmark the 2018 summer drought led to severe soil water degradation with reported crop failures, surface water degradation, and infrastructural damages due to soil subsidence. Furthermore, climate change studies point towards increasing frequency and intensity of severe droughts.
These events have underscored the importance of understanding how meteorological droughts propagate through the hydrological cycle, transforming into soil moisture and hydrological droughts with distinct response times and magnitudes in different compartments of the hydrological cycle. Due to the close coupling of groundwater to surface waters, and the reliance on groundwater for water supply, drought analysis in Denmark must encompass the entire hydrological cycle in a coupled, integrated manner.
Drought propagation is influenced by numerous factors, including topography, soil types, vegetation, hydrogeology, and human interventions, leading to high spatial variability. While much research has focused on streamflow and soil moisture droughts, the drought propagation across the entire hydrological cycle, where groundwater and its coupling to surface hydrology plays a critical role, remains understudied due to data limitations, particularly at larger scales.
This study leverages the National Hydrological Model of Denmark (DK-model), an integrated, distributed hydrological model, to evaluate drought propagation across all hydrological compartments, from precipitation to soil moisture, streamflow, and shallow and deep groundwater. The DK-model’s nature as an integrated distributed model covering the entirety of Denmark with diverse hydrogeological settings, combined with high observation data availability across the hydrological compartments, provides a unique opportunity to evaluate the model’s ability of reproducing drought events and propagation.
By analyzing model outputs against a large dataset of long-term observations of streamflow, groundwater levels and soil moisture, we comprehensively assess the model’s capability to simulate drought propagation and identify correlations, lag times, and response magnitudes. This work improves understanding of drought dynamics in temperate regions and supports sustainable water resource management in Denmark.
How to cite: Schneider, R., Karlsson Seidenfaden, I., F. T. Hansen, M., Koch, J., Andreasen, M., Nilsson, B., and Stisen, S.: Validating drought propagation through the entire hydrological cycle simulated with an integrated national-scale hydrological model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10370, https://doi.org/10.5194/egusphere-egu25-10370, 2025.
In hydrology, streamflow droughts and floods are typically studied as events that are independent from one another, however, this assumption is not necessarily valid. From a physical perspective, for instance, streamflow can be autocorrelated, with signatures of past flow volumes reflected in present streamflow conditions. From a management perspective, rapid drought to flood transitions can leave strategies designed for one event counter-effective when dealing with the other extreme. Furthermore, impacts of rapid drought to flood transitions have the potential to be highly destructive.
The definition of drought and flood events can unintentionally bias detection of transitions in particular regions or for certain types of hydrological regimes or events. This can potentially alter the attributes of detected events, a problem which in a context of transitions has not yet been addressed. Thus, we aim to improve extreme event detection, with a particular focus on hydrologic transitions. We assess the sensitivity of transitions detection to different methodological choices, and we evaluate their appropriateness for various applications. We use eight global case study catchments to examine how existing methodological and parameter variation choices influence transition detection using the threshold level method. The case studies cover different hydroclimatological regimes ranging from a heavily snow driven catchment in Norway, to a semi-arid catchment in Texas, a flashy sub-alpine catchment in Switzerland, and a monsoonal regime in Australia, among others. We examine the impact of threshold type, its level, data aggregation window, and temporal transition window.
Using a combination of quantitative and qualitative analyses applied to these case studies, we demonstrate the following. First, the choice of event detection approach and parameters can alter the detection and duration of events, resulting in some methods detecting “transitions” where others will not. For instance, fixed thresholds are more likely to capture dry conditions, while daily varying thresholds are better at identifying anomalous conditions as compared to the normal flow regime These characteristics point to different aspects of drought to flood transitions e.g. changes in the hydrophobicity of soil or context-specific aspects of water management. Second, less extreme drought and flood thresholds than those used in the study of individual events may be appropriate because the probability of transition occurrence within a specified time period can be very low, even if the independent events are probable. This, however, can be highly regime-dependent and careful consideration of what a transition “means”, in context, is essential for meaningful interpretation of hydrologic transitions across regime types. Finally, the selected time lag between the end of a drought and the beginning of a flood event is important for determining the presence of transition periods in the time series of different hydrological regimes. We highlight the potential pitfalls of different threshold level choices to aid future research in this field, representing the first ever set of methodology guidelines for hydrological transitions research.
How to cite: Anderson, B., Muñoz-Castro, E., Tallaksen, L. M., Matano, A., Magee, E., Armitage, R., Götte, J., and Brunner, M. I.: Pitfalls and recommendations for event detection of drought to flood transitions , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16941, https://doi.org/10.5194/egusphere-egu25-16941, 2025.
The record-breaking 2023 Amazon drought, considered a once-in-a-century event, was not generally due to a moisture deficit from either remote sources or from the Amazon Basin itself. Rather, it was caused by the almost complete absence of atmospheric instability which inhibited convection and therefore precipitation in this region and by extremely high temperatures. Although atmospheric moisture was anomalously high, it was insufficient to compensate for high temperature, which led to reduced relative humidity values and enhanced atmospheric evaporative demand. Furthermore, the moisture that did not precipitate in the region due to atmospheric stability was transported to areas where there was sufficient instability for convection (i.e. moisture sinks), resulting in very high precipitation and floods in La Plata river basin in September 2023. The temperature anomaly over the target region presents two sources, a local one contributing to warming and an external one contributing to cooling. The results show the importance of adiabatic warming due to subsidence in the region itself (atmospheric stability) and also outside (anticyclonic circulation).
How to cite: Gimeno, L., Fernandez-Alvarez, J. C., Nieto, R., Carvalho, D., and Vicente-Serrano, S.: Unearthing the source of anomalous moisture and temperature excesses for the record-breaking 2023 Amazon drought , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8090, https://doi.org/10.5194/egusphere-egu25-8090, 2025.
Climate change is driving significant changes in the frequency and intensity of extreme hydrological events such as floods and droughts. Events like the 2021 Ahrtal flood, 2010 Pakistan flood, and 2020 Gloria flood underscore the growing vulnerability of regions to these extreme events. Spectral nudging is used to reproduce observed conditions in a climate model system, thus enabling the representation of extreme events in the historical and climate change scenarios. In this study, we utilize high-resolution storyline simulations derived through spectral nudging of the IFS-FESOM global climate model to force the global mesoscale hydrological model mHM (mhm-ufz.org). Currently, the IFS-FESOM storyline simulations operate at a spatial resolution of 10 km and an hourly temporal resolution, thus allowing us to study diurnal variability in the flood events. The first part of this study involves the validation of historic event using observation based datasets like ERA5. In the second part the same event is recreated in a 2K warmer climate. By analyzing the event in a warmer world, this study provides critical insights into regional vulnerabilities and informing adaptation planning and strategies to mitigate the impacts of climate extremes in a rapidly warming world.
How to cite: Chandrasekar, A., Marx, A., Kelbling, M., Lüdke, V. S., Grayson, K., John, A., Leal Rojas, J. J., Mueller, S., and Thober, S.: Analyzing Extreme Flood Events in a Warming Climate: Insights from High-Resolution Storyline Simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6954, https://doi.org/10.5194/egusphere-egu25-6954, 2025.
Traditional flow-irrigation systems relying on water canals – primarily used for supporting agriculture purposes – supply multiple ecosystem services (ES). However, their capacity to deliver ES is threatened by climate change. The Veneto region, located in the northeast of Italy, is experiencing severe increases in drought periods followed by intense rainfall, which are undermining its dense and complex network of flow-irrigation canals. Despite the urgency of this situation, the exposure of risk and the consequences on the irrigation systems remains unknown, and so its impact on ES. Spatially explicit models become prominent to evaluate future climate-induced events and potential consequences on ES provided by flow-irrigation systems. Results from those models can inform decision makers and planners to prepare better and efficient adaptation strategies, which will include protecting and maintaining ES.
The aim of this study is to identify and localize areas where ES are more likely to be affected by flood and drought risk in future scenarios (years 2050 and 2100). The model has been built by using k.LAB technology of ARIES (Artificial Intelligence for Environment and Sustainability), an open-source artificial intelligence (AI) modeling framework. By leveraging semantics and machine reasoning, k.LAB enables the integration of independent models and datasets. Moreover, it automatically assembles spatially explicit models into the spatial scale most appropriate for the context of analysis. By conceptualizing risk as a function of hazard, exposure and vulnerability, our methodology uses spatial multi-criteria analysis to aggregate multi-dimensional information into a single parameter output map.
The study resulted in three major findings. First, the model outputs predicted the impact of droughts and floods on ES provided by the irrigation system. Second, risk maps show the future distribution of both hazards at the level of the water canal spatial unit. Third, hotspot maps identify where ES will be more likely threatened by floods and droughts. We conclude our study by discussing how policy makers and planners can effectively use these analyses to guide better plans.
How to cite: Santini, A., Balbi, S., Casali, Y., and Masiero, M.: A spatially explicit risk model to evaluate future drought and flood impacts on ecosystems services provided by flow-irrigation systems: a case study in northeast Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17099, https://doi.org/10.5194/egusphere-egu25-17099, 2025.
Drought is one of the costliest natural hazards of widespread occurrence and long-lasting economic, social, and environmental consequences. Droughts are gradual phenomenon with far-reaching effects that develop over time. Therefore, understanding how drought conditions spread through the terrestrial compartments is essential for predicting impacts, adjusting mitigation strategies, and enhancing climate adaptation. Here, we analyze and characterized drought propagation from meteorological to streamflow and groundwater observations in more than 500 selected river catchments (areas below 300 km2), hosting 13,500 shallow and deep groundwater wells in Germany using the variable threshold level method. We use daily meteorological and streamflow data from CAMELS-DE (Loritz et al.,2024) and a biweekly dataset of groundwater observation compiled from German water authorities, covering the period 1980 to 2020. Among near-natural German river catchments (with no noticeable direct human influence on river flow through reservoir storage and or abstractions), we find four main drought propagation archetypes that evidence the strong coupling or decoupling of surface and subsurface waters: (1) catchments with very reactive groundwater but unresponsive streamflow, where groundwater droughts onset almost immediately in response to meteorological droughts, while the response of streamflow is delayed; (2) fast reactive catchments with delayed response of groundwater droughts; (3) slow reactive catchments characterized by the delayed propagation of groundwater droughts and long recovery times; and (4) very resilient catchments where only the most severe meteorological droughts manifest in either streamflow or groundwater droughts. Our results provide insights on the spatial variability of drought propagation mechanisms at a national scale that can be used to pinpoint the hotspots of rapid drought onset and slow recovery that require targeted mitigation and adaptation strategies.
Loritz, R., Dolich, A., Acuña Espinoza, E., Ebeling, P., Guse, B., Götte, J., Hassler, S. K., Hauffe, C., Heidbüchel, I., Kiesel, J., Mälicke, M., Müller-Thomy, H., Stölzle, M., and Tarasova, L.: CAMELS-DE: hydro-meteorological time series and attributes for 1582 catchments in Germany, Earth Syst. Sci. Data (2024) Vol. 16 Issue 12. DOI: 10.5194/essd-16-5625-2024
How to cite: Peña-Guerrero, M. D., Wang, Z., Ebeling, P., Siebert, C., Merz, R., and Tarasova, L.: Pathways of drought propagation in near-natural catchments across Germany , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6931, https://doi.org/10.5194/egusphere-egu25-6931, 2025.
Droughts occur at larger spatial and longer temporal scale than most hydroclimatic processes. More than for other natural hazards, a thorough understanding of the spatio-temporal dynamics of droughts is essential in monitoring, projecting, and adapting to future drought conditions. However, the long characteristic time scale of droughts severely limits their observation in the historical record, hampering our ability to track how extreme drought events evolve in space and time. This study investigates the statistical characteristics of extreme droughts using simulations from the Paleoclimate Modelling Intercomparison Project Phase 4 (PMIP4) and the Coupled Model Intercomparison Project Phase 6 (CMIP6). By analyzing historical and paleo-hydrological data, we assess the frequency, intensity, and duration of extreme drought events over multiple geographic locations and across different time scales. An advanced non-asymptotic statistical approach, which explicitly separates intensity and occurrence of the process, is employed to capture the variability and the frequency of extreme drought characteristics in space and in time. Our findings reveal significant regional differences in extreme drought properties, with pronounced variations across different climate states and time periods.
How to cite: Caruso, M. F., Villarini, G., and Marani, M.: Space-time variability in extreme drought statistical characteristics, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7656, https://doi.org/10.5194/egusphere-egu25-7656, 2025.
Posters virtual: Fri, 2 May, 14:00–15:45 | vPoster spot A
EGU25-705 | ECS | Posters virtual | VPS11
Enhanced Modulation of Rapid/Flash Drought in India: An Elegant FrameworkFri, 02 May, 14:00–15:45 (CEST) | vPA.8
The land system dries up quickly and intensely during rapid/flash droughts under climate warming are of widespread concern owing to their adverse impact on nation’s economy. During these periods, reduction in precipitation deficits is frequently followed by abrupt increases in evaporative demand, which causes significant drops in soil moisture and discernible effects on agricultural production and the environment. The need for a better knowledge on rapid drought conditions to effectively manage its effects has been highlighted in several recent publications; Nevertheless, the lack of consistent definitions have limited progress toward its assessment. There are several factors and climatic forces that are typically connected to the development of flash droughts, thus it's conceivable that no one definition will fully encapsulate the phenomenon. But it's imperative to ensure that flash droughts (lasts for short duration) can be recognized and differentiated from more traditional drought occurrences (longer duration) due to their quick onset, quick intensification, and severe character. With the increasing use of rapid /flash drought term within the research community, this study explores the extent to which pentad-scale precipitation series across India can be used to represent historical flash droughts, providing a simple framework for the phenomenon. The result shows the categorization of rapid/flash drought at various hotspot location in India and explain it’s causing and triggering factor linked with acute precipitation deficits, one of meteorological variable. The findings of this study can be further utilized in the accurate prediction of flash/rapid drought with the robust evidence from precipitation series in identifying flash drought episodes across the nation. Consequently, our findings indicate that constant monitoring of rapid drought conditions and drivers is crucial for effective preparedness.
How to cite: Kumari, P. and Vinnarasi, R.: Enhanced Modulation of Rapid/Flash Drought in India: An Elegant Framework, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-705, https://doi.org/10.5194/egusphere-egu25-705, 2025.
