Posters virtual: Wed, 6 May, 14:00–18:00 | vPoster spot A
Surface-groundwater interactions (SGI) plays a crucial role in maintaining stream thermal regime and ecological balance, keeping a check on this is logistically and financially challenging. This study utilises multi-temporal Landsat-8 Thermal Infrared Sensor (TIRS) data to compute Stream Surface Temperature (SST), its anomaly (SSTA), Robust Thermal Deviation Index (R-TDI) and further classifies groundwater influence on the Kharun River, a semi-arid urban catchment in India (approximately 4109 km²).
Due to changes in weather and season, surface water is subject to heating and cooling, but the water system beneath the land surface will be at a constant temperature. The stream reach, influenced by groundwater, will show a relatively stable thermal signature across all seasons. Stream Surface Temperature (SST) derived through radiometric calibration and emissivity-adjusted retrieval across pre-monsoon, monsoon, and post-monsoon periods. To isolate localized hydrological processes from regional climatic forcing, we computed Stream Surface Temperature Anomalies (SSTA) by subtracting reach-wise median SST from pixel-scale values. To account for the non-normal nature of SST, a Robust Thermal Deviation Index (R-TDI) framework was utilised which minimizes atmospheric noise and mixed-pixel interference, allowing for the isolation of persistent thermal signals.
Using statistically defined TDI thresholds, a classification approach was finalised putting stream stretches into high, moderate, and low groundwater influence zones. Results identify spatially consistent cold-water anomalies indicative of groundwater discharge primarily during pre-monsoon and warmer-water anomalies during post-monsoon seasons when thermal contrasts are most pronounced. These zones coincide with structurally controlled segments and urbanized stretches, suggesting a complex interplay between hydrogeology and anthropogenic modifications. By leveraging open-access satellite data, this research provides a scalable tool for evidence-based river restoration and climate-resilient water management in rapidly urbanizing regions.
Key Words: Thermal remote sensing; Landsat-8 TIRS; Stream surface temperature; Thermal anomaly; Surface–groundwater interaction; Data-scarce catchments
How to cite: Chandel, R. and K. Singh, C.: Thermal Remote Sensing for Qualitative Analysis of Surface Water and Groundwater Interaction: A Case Study of the Kharun River, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9498, https://doi.org/10.5194/egusphere-egu26-9498, 2026.
Wetlands play a vital role in the hydrologic cycle since they impact stream flow, add to water storage capacity, provide habitat for many species, and provide resiliency in ecosystems. Ondiri Swamp, which is a peatland located in Kenya with approximately an area of 33 hectares and is the headwaters of Nairobi River has very little hydrological understanding, especially regarding subsurface and groundwater contributions since there have not been any continuous in-situ data measurements. This study aims to quantify water storage and investigate potential groundwater presence using an embedded, multi-sensor dataset.
To overcome the limitation of only using traditional optical index methods for surface water detection under dense vegetation, water occurrence data (Global Surface Water), Sentinel-1 SAR and Sentinel-2 multitemporal optical images, DEM images (Copernicus DEM), and NDVI derived vegetation index data will be combined. Measurements of swamp depth and peat thickness will be collected from short-term field campaigns for calibration of volume estimates and provide preliminary data for a preliminary water balance. The precipitation data (CHIRPS) and ET data (FAO WaPOR) will be combined with inflow and outflow estimates to create a preliminary water balance. Surface storage will be estimated, and potential groundwater contributions will be inferred without long-term observatory data sources. The methods used for the quantitative and qualitative assessment of wetland water resources will generate probabilistic wetland water maps using a multi-temporal remote sensing-based classification of existing datasets, as well as using terrestrial calibrations from field data.
The study will be able to quantify total wetland water storage, determine the degree to which groundwater may influence wetlands, and identify the seasonal dynamics of wetland hydrology. Through a combination of remote sensing, existing datasets, and terrestrial calibrations from field studies, the study provides a strong, scalable framework for conducting wetland hydrology research, managing wetland ecosystems and planning wetland water resources in areas where very few, if any, hydrological observations are available.
How to cite: Ouedraogo, A.: Estimating Surface and Subsurface Water in Ondiri Swamp, Kenya, Using Multi-Sensor Embedded Data and Preliminary Water Balance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19536, https://doi.org/10.5194/egusphere-egu26-19536, 2026.
A numerical investigation is conducted to study the steady-state concentration field
when a solute is released from multiple continuous line sources in an ice-covered
channel with an absorbing bed under turbulent flow conditions. The governing
equations are solved using the Crank-Nicolson scheme by adopting a two-power law
velocity and a quartic eddy diffusivity profile, which is influenced by the roughness of
the bed layer and the ice cover. Validation against earlier numerical results for a
specific case reveals strong consistency in the concentration profiles. The findings
highlight how the roughness of the boundaries affects the solute concentration. It
further demonstrates the effect of the bed absorption parameter in the early mixing
stages when solute is released near the bed. For zero bed absorption, the solute
concentration asymptotically attains a uniform far-field value of unity, while any non-
zero bed absorption leads to complete depletion of solute downstream.
How to cite: Paul, S. and Ghoshal, K.: Solute dispersion from continuous point sources in ice-covered turbulent flows with bed absorption, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5160, https://doi.org/10.5194/egusphere-egu26-5160, 2026.
The Critical Zone, extending from the land surface through the vadose zone to groundwater, can store and transfer substantial carbon as CO2 and dissolved inorganic carbon (DIC). Yet CO2 behavior below the first meters of soil remains poorly constrained, particularly where water-table fluctuations, gas-water exchange, and water-rock reactions interact. In these settings, deep vadose CO2 may exhibit atmospheric and soil-respiration signatures with contributions linked to groundwater degassing and carbonate-system reactions, potentially creating transient subsurface CO2 reservoirs that couple the aquifer and the atmosphere.
We present a repeated sampling design to characterize carbon cycling across the Critical Zone in semi-arid southeastern Spain. We sampled the air columns of 11 boreholes belonging to six groundwater bodies during four campaigns (spring 2022, autumn-winter 2022, spring-summer 2024, and spring-summer 2025). In borehole air, we measured CO2, H2O vapor, and its carbon isotopes composition (δ¹³C-CO2); air was stored in gas-tight bags and analyzed by cavity ring-down spectroscopy (Picarro G2508 and G2201-i). In parallel, groundwater was sampled at each site. In situ, we measured pH, temperature, oxidation–reduction potential (ORP), HCO3-, and electrical conductivity. In the laboratory we analyzed pH, alkalinity, major ions, total organic carbon and total nitrogen, carbon isotopes of dissolved inorganic carbon (δ¹³C-DIC), and water isotopes (δ²H, δ¹⁸O). Water-table position at the time of sampling was used to interpret gas-water contact.
Critical Zone CO2 concentrations in borehole air ranged from 614 to 128700 ppm (pCO2=0.000587-0.102287 atm). Groundwater CO2 was estimated with the PHREEQC software, yielding values between 2240 and 9550 ppm (pCO2=0.002240-0.009550 atm), allowing comparison between the air column and the saturated zone, and evaluation of disequilibrium and exchange potential as the water-table varies. Carbon isotopes signatures constrain sources and transformations: δ¹³C-CO2 ranged from -11.14 to -23.62‰, δ¹³C-DIC from -6.27 to -20.11‰, and host-rock δ¹³C from 2.37 to -7.12‰. All values (δ¹³C‰) are reported relative to VPDB (Vienna Pee Dee Belemnite). Joint interpretation across gas, DIC, and rock enabled discrimination among biogenic CO2 production, atmospheric mixing, carbonate dissolution/precipitation (based on the saturation indices of the main carbonate mineral phases), and CO2 transfer from the aquifer to the deep vadose zone. The multi-campaign design provided a basis for quantifying seasonal and interannual shifts in these boreholes and for identifying hydrogeochemical conditions (e.g., pH-alkalinity evolution and redox state) that promote storage/mineralization versus release of CO2.
Our experimental design characterizes subsurface CO2 storage and transport at the Critical Zone scale. It identifies when the deep vadose environments act as reservoirs, conduits, or sources linking groundwater and the atmosphere. This information is rarely available but critical for improving carbon budgets and models for the Critical Zone.
This work was supported by the Spanish Ministry of Science and Innovation (projects PID2024-158786NB-C21 and PID2024-158786NB-C22, NATURAL), the University of Granada (project PPJIB2024-53), and the Regional Ministry of University, Research and Innovation, the Spanish Government and the and European Union – NextGenerationEU (projects BIOD22_001 and PCBIO).
How to cite: Echeverría-Martín, E., Fernández-Cortés, Á., Sánchez-Cañete, E. P., Serrano-Ortiz, P., Oyonarte, C., Riba Palou, A., Kowalski, A. S., and Domingo, F.: CO2 Dynamics and Carbon Sources in the Critical Zone: An Isotopic Study in Aquifers of Southeastern Spain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7262, https://doi.org/10.5194/egusphere-egu26-7262, 2026.
Understanding hydrological responses to high-intensity rainfall is critical for water resource management in humid tropical regions, where climate change is increasing the frequency and magnitude of extreme storm events. However, runoff generation mechanisms and flow pathway activation in small tropical catchments remain poorly understood. This study investigates hydrological connectivity, flow pathways, and streamflow source contributions in the Acono watershed, Trinidad and Tobago.
A multi-tracer approach combining stable isotopes (δ²H, δ¹⁸O), radioisotopes (³H, ²²²Rn), and major ion geochemistry (SO₄²⁻, Na⁺, Mg²⁺, Ca²⁺, Cl⁻) was applied to characterize water sources and residence times under contrasting hydrological conditions. Periodic sampling was conducted over a 22-month period, complemented by event-based sampling during a minimum of five high-intensity rainfall events. Samples were collected from rainfall, streams, springs, shallow soil water (10–80 cm), and deep groundwater, alongside continuous monitoring of rainfall, soil moisture, and water levels across the catchment. End-member mixing analysis was used to quantify source contributions to streamflow.
Preliminary results indicate that streamflow is predominantly sourced from pre-event (“old”) water under low flow and moderate wet-season conditions, with old water and spring inputs frequently accounting for 60–99% of flow. Direct rainfall contributions are generally limited (average ~7%) and rarely exceed ~30–37%, suggesting strong subsurface buffering and rapid mobilization of stored water rather than dominant overland flow. In contrast, the onset of wetter conditions in early 2025 triggered pronounced, non-linear shifts in source contributions, including sharp increases in deep groundwater and spring contributions (up to ~89% and ~80%, respectively), alongside elevated event water fractions. These patterns suggest threshold-controlled activation of deeper storage and fast-responding subsurface pathways during periods of sustained or intense rainfall.
Data collect is ongoing and additional analyses are expected to improve our understanding of the translation from rainfall to streamflow. This research provides a novel approach to understanding hydrological processes in small island developing states (SIDS).
How to cite: Ramjohn, P. and Farrick, K.: High Intensity Rainfall Event Contributions to Stormflow and Stream Residence Time in the Acono Watershed, Trinidad., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15744, https://doi.org/10.5194/egusphere-egu26-15744, 2026.
Global water security can be achieved by the systematic assessment of available water resources in both large and small river basins. This study investigated the stable isotopic composition of river water in the Yamuna basin, India to fingerprint the major contributing sources of water and their spatial variability along the main river channel. The Yamuna river originates at an altitude of about 6300 m asl in Yamunotri glacier near Bandarpunch, Uttarakhand Himalayas and flows through several states of India like Haryana, Punjab, Madhya Pradesh, Rajasthan and Uttar Pradesh. In this study, the Yamuna river water samples have been collected along main channel from Yamunotri to its confluence with Ganga river during pre-monsoon and post-monsoon seasons of the year 2024. The measured stable isotope ratios of oxygen (δ18O) and hydrogen (δ2H) in river water are in the range of -2.7 – -11.2 ‰ and -23.4 – -75.2 ‰ respectively for the sampling period. This study reports for the first time that there is a significant spatial variability in the source water of Yamuna river as fingerprinted by the stable isotopic composition. The Yamuna river at upper reaches receives water from sources that are depleted in heavier isotopic content mainly from glacial melt. The higher amount of water diversion to canal networks at different stages as well as water mixing from industrial and urbanized regions have led to relative water degradation of Yamuna river in middle reaches. The downstream isotopic composition reflects possible interaction with groundwater, higher water influx from Peninsular tributaries, and evaporation effect. Seasonality in source water contribution to Yamuna river discharge along the entire stretch has also been traced using stable isotopic composition of water.
How to cite: Tripti, M., Khobragade, S. D., and Rao, S. M.: Stable isotopic fingerprinting of hydrological variability along the Yamuna river, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10986, https://doi.org/10.5194/egusphere-egu26-10986, 2026.
The application of isotopic tracers provides a powerful means to unravel complex hydrological systems, including groundwater (GW)-surface water (SW) connectivity. This study investigates the interacting hydrological and geochemical processes within a temperate volcanic lake basin in west-central Mexico, with the objective of assessing hydrogeological connectivity between groundwater and the lacustrine system. Spatially distributed sampling was conducted for major ions, nitrate, strontium, and stable water isotopes (δ¹⁸O and δ²H) across multiple water sources, including precipitation, rivers, lakes, wells, and springs.
Results indicate that direct infiltration of precipitation constitutes the dominant groundwater recharge mechanism in high-elevation, forested zones, where waters exhibit a Ca–Mg–HCO₃⁻ hydrochemical facies. Mixing with deeper groundwater components is also evident, as reflected by elevated temperatures and isotopic compositions indicative of enhanced water-rock interaction. Surface waters, particularly lakes, display pronounced evaporative enrichment, while elevated nitrate concentrations in shallow groundwater point to anthropogenic inputs associated with irrigation return flows and urban activities.
Although sampling was conducted during the dry season and therefore may not capture the full range of annual hydrological variability, the identification of local and regional recharge zones provides a robust framework for future investigations of precipitation-driven recharge and GW-SW interactions. Additionally, strontium concentrations proved effective for tracing subsurface flow paths and fluid exchange along fault-controlled structures, offering valuable insights into hydrogeological processes in tectonically active volcanic settings. The integrated use of hydrochemical and isotopic tracers highlights their critical role in supporting sustainable water-resource management and protecting groundwater quality in complex temperate, semi-arid lake systems increasingly impacted by anthropogenic pressures.
How to cite: Ramírez González, L., Olea Olea, S., Sánchez Murillo, R., Villanueva Estrada, R. E., González Mejía, M. A., González Hita, L., Morales Casique, E., Zamora Martínez, O., Gómez Vasconcelos, M. G., Denis Ramón, A., and Ramírez Serrato, N.: Tracing Groundwater-Surface Water Mixing Using Isotopes in a Semi-Arid Volcanic Lake Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15165, https://doi.org/10.5194/egusphere-egu26-15165, 2026.
Understanding catchment behaviour is essential for effective water resources planning and sustainable watershed management. Traditional model evaluation approaches based solely on time-series performance metrics often fail to capture the full spectrum of hydrological functioning. This study employs a hydrological signature–based evaluation framework to assess the capability of the Soil and Water Assessment Tool (SWAT) model in reproducing the dominant hydrological processes in the Bharathapuzha River Basin, a monsoon-dominated river system in southern India. The SWAT model was implemented using spatial datasets of topography, land use, and soil characteristics, together with long-term hydro-meteorological inputs, and calibrated and validated against observed daily streamflow. Beyond conventional performance indices, key hydrological signatures including flow duration curves, runoff ratio, baseflow index, seasonal flow patterns, and characteristics of low- and high-flow events were extracted from both observed and simulated datasets. Comparison of observed and simulated signatures provided a process-oriented evaluation of model behaviour, offering key insights into how well runoff generation, seasonal variability, and hydrological extremes are represented. These perspectives are not readily evident from traditional model performance metrics alone. This study demonstrates the value of hydrological signatures as diagnostic tools for enhancing model realism and improving confidence in hydrological simulations for climate impact assessment and water resources management in monsoon-driven catchments.
How to cite: Krishnan Sreelatha, G., Anupama Rajith, A., Sreekumar, A., Girish, G., and Reghunath, G.: Signature-Based Evaluation of Hydrological Processes Using the SWAT Model in the Bharathapuzha River Basin, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9647, https://doi.org/10.5194/egusphere-egu26-9647, 2026.
Developing hydrological models, which are process-aware and reliably transferable across diverse environments remains a challenge. We benchmark Shyft – an open-source, fully FAIR (findable, accessible, interoperable and reusable) flexible modeling framework, across 109 catchments in mainland Norway to evaluate how model structure, forcing uncertainty and calibration objective jointly shape streamflow simulation performance. We adopt large sample hydrology perspective to probe five models “stacks”, providing alternative process choices, such as evapotranspiration (Penman-Monteith vs Priestley-Taylor), snowmelt (temperature-index vs semiphysical) and runoff response (Kirchner vs HBV tank and soil) with multiple goal functions drawn from KlingGupta Efficiency (KGE) and Nash-Sutcliffe Efficiency (NSE), with and without catchment specific precipitation correction. We use a suite of evaluation metrics targeting bias, hydrograph dynamics, low flows and interannual variability. We move beyond crude mean-flow benchmarks toward simple climatological benchmarks, providing an objective context for model skill evaluation, given the seasonal nature of Norwegian catchments.
The evaluation revealed that configurations containing temperature-index snow simulation and Kirchner runoff offer the greatest robustness and generality across all hydrological regimes. In terms of objective functions, KGEbased targets outperform NSE-based targets, with metric combining KGE and box-cox transformed KGE (KGE_bcKGE) identified as a promising generalist objective, which performs well across diverse metrics, including low-flow targeted (KGE(1/Q)) and interannual NSE. Furthermore, precipitation correction was found to be essential for improving performance in Mountain and Inland regimes, suggesting snow undercatch as a primary source of precipitation uncertainty. Among simple benchmarks, daily mean was found to be best predictor setting model expectations for future model intercomparisons in the region. Our results demonstrate the need for balance of structural adequacy, forcing uncertainty and equifinality.
This project is supported by Norwegian Research Council NFR project 336621.
How to cite: Silantyeva, O., Huang, S., and Xu, C.-Y.: Benchmarking flexible modelling framework Shyft across mainland Norway, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22432, https://doi.org/10.5194/egusphere-egu26-22432, 2026.
Water balance modeling plays a pivotal role in sustainable water management, as it underpins the understanding of hydrological processes that govern resource distribution, ecosystem stability, and long-term environmental planning. Accurate and efficient computational tools are essential to capture the spatial and temporal dynamics of water balance, particularly in complex geological and urban environments. WaterpyBal is an innovative modeling framework specifically designed to construct spatial-temporal water balance models. It effectively integrates multiple stages of hydrological assessment-including data interpolation, evapotranspiration estimation, and infiltration computation-while accounting for soil heterogeneity and components of the urban water cycle. The tool demonstrates robust performance when applied to both synthetic and experimental datasets, providing reliable and scalable results.
In the context of the exascale era, where data-intensive environmental models demand unprecedented computational power, High-Performance Computing (HPC) frameworks are essential to ensure scalability and efficiency. To this end, WaterpyBal has been enhanced through its integration with PyCOMPSs, the Python binding of the COMPSs programming model. PyCOMPSs enables the transparent parallelization of Python applications by identifying task-level parallelism through annotated methods and dynamically constructing a task-dependency graph during runtime. This graph-driven execution model allows efficient scheduling and data management across distributed computing infrastructures such as clusters and cloud platforms.
The integration of WaterpyBal with PyCOMPSs significantly improves its computational performance, enabling the simulation of large-scale, high-resolution water balance models within feasible timeframes. This work demonstrates the potential of combining advanced hydrological modeling with state-of-the-art parallel computing frameworks to address emerging challenges in environmental modeling and resource management at scale.
How to cite: Castillo Reyes, O., Li, J., Hassanzadeh, A., and Vázquez-Suñé, E.: High-performance task-based water balance modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5899, https://doi.org/10.5194/egusphere-egu26-5899, 2026.
Most studies on estuarine compound flooding patterns and processes either utilize paired station data of streamflow and sea level (or simulated data), readily available at national, continental and global scales, or are confined to one estuary system and specific events, where detailed water level observations exist. These approaches do not provide a full understanding of the processes underlying the compound events, as reflected in observed spatial patterns and temporal variation.
We call for revised observational strategies for integrating estuary-scale process and the manifestation of compound water level extremes in the estuary with larger-scale patterns and trends. Proving methodological insights from a review of existing compound flooding literature and our multi-scale analysis in Europe, we establish recommendations for such a setup.
As a baseline, our analysis uses regional-scale patterns and long-term trends in compound flooding potential in three contrasting countries in Europe (Norway, Finland and Spain, differing in terms of tidal amplitude, seasonality and relative sea level trends), quantified with state-of-the-art methods. We then document the availability of direct estuarine water level data for validating the inferred flooding potential. Finally, three different field setups in northern Norway, central Finland and northern Spain are used to test how compounding streamflow and sea level conditions inferred from national stations are visible in different parts of the estuary. Unlike previous studies, we also examine the manifestation of low water conditions to maximize the usefulness of the acquired data for extreme-event studies. Moreover, we test how robust the state-of-the-art infrastructure is in extreme conditions, including meso-tidal variation, river ice, snowmelt-induced flooding and drying up of estuaries.
This multi-scale study allows us to present recommendations for robust observational strategies that allow inference of processes governing compound water level extremes at multiple scales, and explaining the observed patterns and trends. Such strategies have potential in improving our understanding of current and future compound hazards. Accommodating low-water conditions and hydrometeorological extreme conditions facilitates continental and global comparative studies.
How to cite: Nylén, T. and Tolvanen, H.: Revisiting the observational strategy: Toward more robust inference of compound water level extreme processes in estuaries, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20425, https://doi.org/10.5194/egusphere-egu26-20425, 2026.
The intensification of hydrological cycle driven by global warming leads to an increase in extreme precipitation events, prolonged droughts and higher rates of evaporation. This global change has altered the global hydrological cycle and effect on the long term water availability in many watersheds worldwide. The impact of climate change is usually assessed by using ratio of stream flows and climate variables, which are formally defined as the climate elasticity of water availability This study examines how the hydrological cycle is intensifying over the Kabul Watershed and how this affects water availability using the water balance (P–E) approch. Here, we used ERA5 land data of annual total precipitation (P) and total surface evaporation (E) from 1976 to 2024 to understand how the land and atmosphere interacted. The climate elasticity of (P-E) to annual water availability is determined for 1976-2010 and validated for 2011-2024. The results reveal 0.8 °C rise in temperature, 12% decline in annual precipitation, and 7% increase in evaporation in the past 25 years. This caused 15% reduction in the P–E balance, which directly reduced the annual water availability. The climate elasticity factor of 0.55 has been determined to water availability in Kabul for the period of 1976-2010. By using this elastic factor, the average water availability of 19.54 MAF is predicted for the period of 2011-2024 whereas the observed water availability is 20.43 MAF. This finding reflects the sensitivity of a watershed to P-E alteration for water availability and underscore the urgent need of climate resilient water management strategies to mitigate the future impacts of climate change in the Kabul watershed.
How to cite: Kosar, T., Rahim, A., Yaseen, M., Naz, R., Mamoor, M., and Akif, A.: Climate Driven Hydrological Intensification and Its Implications for Water Availability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6269, https://doi.org/10.5194/egusphere-egu26-6269, 2026.
Flood hazard assessments are commonly based on rainfall magnitude and frequency; however, flood responses to similar rainfall intensities may change over time due to evolving land use, river morphology, and hydraulic controls. This study investigates temporal changes in flood inundation patterns between 2014 and 2024 over a highly flood prone urban coastal catchment in India under comparable rainfall forcing, with the objective of improving understanding of non-stationary flood behavior. Rainfall events were identified and grouped based on intensity and duration using long-term precipitation records. For each selected event, flood extents were mapped using satellite-based inundation detection implemented on cloud computing platforms, and, where appropriate, complemented by physically based hydraulic modeling. This combined rainfall–flood framework enables consistent inter-annual comparison of flood patterns under equivalent meteorological conditions. The methodological approach focuses on isolating the influence of landscape and hydraulic evolution on flood response by analyzing spatial characteristics of inundation independent of rainfall variability. By integrating remote sensing and hydraulic modeling within a long-term analysis, the study provides a transferable framework for assessing how flood behavior evolves in response to environmental and anthropogenic changes. This work is relevant to flood risk management and climate adaptation, particularly in rapidly changing river basins where traditional stationary assumptions may no longer be valid. The approach supports improved interpretation of historical floods and more robust planning under future uncertainty.
How to cite: Ghosh, M. and Karmakar, S.: Assessing changes in flood inundation patterns using rainfall-controlled event analysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15655, https://doi.org/10.5194/egusphere-egu26-15655, 2026.
Hydroclimatic extremes have extensive social, economic and ecological impacts, thereby making it highly imperative to develop disaster assessment and mitigation strategies. The frequency of extreme events like heatwaves and droughts is intricately linked with the rising temperature trends and the changing precipitation patterns worldwide. Moreover, lagged responses amongst such extremes can occur across temporal scales due to the existing large-scale climate linkages. However, the association between present-day occurrences of concurrent high temperature and low precipitation days (HTLPs) with the frequency of heatwaves and droughts of a subsequent period is not fully explored. In this global analysis, we estimate the frequency of heatwaves and droughts based on 1-year temporally lagged HTLPs. Our results reveal a significant rising trend in the average number of heatwaves with an increase in the number of HTLPs of the previous year, while no significant trend is observed for droughts. However, a high number of HTLPs (over 100 events) is associated with a slight reduction in the number of heatwaves (5.9 to 5.6) but a pronounced increase in the number of droughts (1.8 to 2.4). During a 10-year validation period, 81% of heatwaves and 85% of droughts globally remain consistent with the HTLP–conditioned behavior inferred from the 34-year training period of the model. Our findings thus demonstrate the applicability and effectiveness of HTLPs in predicting heatwaves and droughts. This study can be used to develop stochastic models to predict heatwaves and droughts with HTLP as a predictor, and hazard-specific probabilistic assessments that can support and improve resource allocation at regional and global scales.
How to cite: Sinha, D. and Rajulapati, C.: The role of High Temperature-Low Precipitation conditions in shaping heatwaves and droughts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8393, https://doi.org/10.5194/egusphere-egu26-8393, 2026.
Although drought indices can be evaluated employing linear and non-linear algorithms, most contributions in the literature have not adequately quantified geospatial-temporal volatility, leading to Type II errors. This study addresses these gaps by comparing ten drought indices across the Colorado and Louisiana regions of the United States over 75 years, examining non-linear and spatio-temporal patterns to ensure a robust assessment of drought. High-resolution European Centre for Medium-Range Weather Forecasts (ECMWF) gridded monthly total precipitation data for 75 years (1950-2024) were used to evaluate the drought indices. The spatial clustering of precipitation patterns was quantified using the second-order semi-parametric eigen-decomposition geospatial autocorrelation to geolocate hot and cold spots of precipitation. We employed the Autoregressive Integrated Moving Average (ARIMA) model, coupled with the Generalized Autoregressive Conditional Heteroscedastic (GARCH) model, and compared five ARIMA-GARCH variants across nine error distributions to address non-asymptotic conditional volatility and temporal persistence in precipitation. Drought indices were examined across five temporal scales and contrasted with simulated parameters derived from the Community Earth System Model (CESM). The temporal lag relationship between meteorological and agricultural droughts was evaluated using the non-parametric Time-Varying Distance Cross-Correlation Function (TV-DCCF). The findings revealed that the ARIMA-eGARCH(1,1) model with a Student’s t distribution precisely detected the non-asymptotic conditional volatility in the precipitation time series. The Standardized Precipitation Index (SPI), China Z Index (CZI), and Z-Score Index (ZSI) were the most applicable indices for drought monitoring in both regions. TV-DCCF revealed that meteorological droughts significantly influenced agricultural droughts, with a lag of up to four months. CESM-derived drought indices were mainly within the ERA5-Land uncertainty range, except for CZI and aSPI, attributable to CESM’s lower spatial resolution and limited sensitivity to localized extreme events.
Keywords: Standardized Precipitation Index (SPI); Global Moran’s Index; Autoregressive Moving Integrated Average (ARIMA); Generalized Autoregressive Conditional Heteroscedastic Model (GARCH); ERA5-Land; Community Earth System Model (CESM).
How to cite: Choudhari, N., Elshorbany, Y., Jacob, B., and Collins, J.: Prognosticative De-Volatility Modeling for Empirically Quantifying CESM and ECMWF Space-Time Heterogeneity of Drought Indices Across Colorado and Louisiana Regions of the USA, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14649, https://doi.org/10.5194/egusphere-egu26-14649, 2026.
Hydrodynamic processes strongly influence coastal and estuarine landscapes, especially in low-lying deltaic regions like the Meghna Estuary. Islands in the lower Meghna and at the Padma-Meghna confluence face increased risk of submergence due to sea-level rise and intensified precipitation under future climate scenarios. This study analyzes the long-term hydrodynamic changes in the Meghna Estuary using Delft3D simulations for 2000, 2024, and 2050, focusing on islands such as Nijhum Dwip, Moulovi Char, Domar Char, Char Kukri Mukri, Rajrajeshwar, Hatiya, and Manipura. The model covers the area from Baruriya Transit to the sea, integrating tidal and riverine dynamics. Future discharge for 2050 was generated from MIROC6 climate projections under SSP2-4.5 and SSP5-8.5 scenarios, bias-corrected and simulated via HEC-HMS. HEC-HMS was calibrated using 2022 data and validated with 2023 discharge records from Bhairab Bazar, while Delft3D was calibrated and validated using observed water level data from Daulatkhan over the same period. Results show rising tidal amplitudes and water levels, with high tides near Char Kukri Mukri increasing by 30 to 35 cm by 2050. Tidal inundation is expected to expand during monsoons, increasing flood risk in low-lying areas. Islands like Char Kukri Mukri and Hatiya are losing relative elevation, heightening their vulnerability to flooding and storm surges. Hydrodynamic projections indicate an average increase in water depth of 0.5 to 0.8 m around Rajrajeshwar, Hatiya, and Manipura by 2050, suggesting enhanced tidal energy and flow velocities that are likely to accelerate shoreline erosion and land loss, particularly along their southern and eastern margins. These findings highlight the increasing vulnerability of the Meghna Estuary’s islands to climate change–driven hydrodynamic shifts, emphasizing the urgent need for targeted adaptive management, improved flood risk mitigation, and resilience-building measures to protect the region’s communities and ecosystems from future inundation and erosion risks.
How to cite: Ahmed Dipu, S. U., Gemintang, E., Haque Laskor, Md. A., Bhuiyan, F., Galib Fardin, M. A., Rahman, Md. M., Rabbany, Y., and Islam Fahim, S.: Hydrodynamic Changes of Estuarine Islands in the Meghna River under Future Climate Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17766, https://doi.org/10.5194/egusphere-egu26-17766, 2026.
The Syr Darya River Basin is a highly glacierized transboundary system where future water availability is strongly influenced by climate change, reservoir operations, and population growth. This study investigates the role of reservoirs in regulating water supply under future climate scenarios using the Water Evaluation and Planning (WEAP) model. Climate projections from the ISIMIP framework under Shared Socioeconomic Pathways SSP1-2.6, SSP3-7.0, and SSP5-8.5 are used to drive hydrological inputs, including streamflow, precipitation, and temperature, while population growth projections represent evolving water demands.
Results indicate a strong increase in summer unmet demand by 2050, intensifying further by 2090, with peak deficits occurring in July–August. Reservoir refilling remains seasonal across all scenarios but becomes more variable and less reliable by 2090, with deeper drawdowns and reduced buffering capacity under higher-emission pathways.
How to cite: Abdul Jalil, U., D'Haeyer, B., Prakash, S., and Huang, J.: The Role of Reservoirs in a Glacierized Basin Under Climate Change: An Analysis Using the WEAP Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21606, https://doi.org/10.5194/egusphere-egu26-21606, 2026.
Extreme hydrological events have become increasingly frequent in Ukraine in recent decades due to climate change and structural weaknesses in water resources management. According to the Water Strategy of Ukraine up to 2050, inadequate governance practices remain a major source of anthropogenic pressure on water bodies, while climate change creates additional risks through prolonged droughts interrupted by intense rainfall events, leading to flooding. These challenges are particularly critical for southern Ukraine, where limited water resources require extensive hydrotechnical regulation and adaptive management.
Flash floods represent one of the most dangerous manifestations of hydrological extremes. Characterised by rapid water-level rise and high flow velocities, they pose severe risks to settlements, infrastructure, and agriculture due to their sudden onset.
The north-western part of the Black Sea region has experienced several severe flash flood events over the past decade. One of the most significant cases occurred in September 2013 in the Kogilnyk River basin., when anomalously high precipitation totals of 41 - 270 mm were recorded from 10 and 14 September. These extreme rainfall conditions were associated with a stationary cold atmospheric front linked to the Asia Minor depression, resulting in prolonged convective rainfall with thunderstorms, squalls and wind gusts of up to 22 m/s in the southern districts of the Odesa region.
The total volume of storm rainfall during this event is estimated at approximately 250 million cubic meters, which exceeded the mean annual runoff of the Kogilnyk River by a factor of 5.5. Precipitation affected an area of about 1,400 km², corresponding to 35% of the total river basin area. As a result, flash flooding impacted multiple settlements, located in the south-western part of Odesa Oblast as well as extensive agricultural lands in there.
Another notable episode occurred in early August 2019, when unstable atmospheric conditions and active cyclones caused intense rainfall across southern and eastern Ukraine. On 3 - 4 August, precipitation amounts reached 130–220% of the monthly norm in several locations. In the Odesa region, rainfall totals of up to 126 mm - equivalent to nearly three months of precipitation—met the criteria for hazardous meteorological phenomena and triggered debris flows and localized flash flooding, particularly in the village of Moloha (Bilhorod-Dnistrovskyi district).
More recently, in September 2025, an urban flash flood in Odesa highlighted the increasing vulnerability of urban areas to extreme rainfall. Prolonged heavy rains caused widespread flooding, significant damage, and human losses, prompting large-scale rescue operations..
The analysed events indicate a clear increase in flash flood intensity and impacts in the north-western Black Sea region. Under continued climate change, enhanced hydrological monitoring, early warning systems, climate-adaptive urban planning, and integrated water resources management are urgently required in southern Ukraine.
ACKNOWLEDGEMENTS
This contribution builds on the conceptual framework of the applied research project “Sustainable Development of Water Resources Management and Modelling in the North-Western Black Sea Region under Conditions of Increasing Climate Extremes and Anthropogenic Pressure”, approved for funding by the Ministry of Education and Science of Ukraine (Order No. 23, 9 January 2026, see https://surl.li/omqxph).
How to cite: Ovcharuk, V. and Khomenko, I.: Flash Flood Events in the Northwestern Black Sea Region under Climate Change , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14233, https://doi.org/10.5194/egusphere-egu26-14233, 2026.
Over the past decade, droughts have drawn increasing attention due to their substantial agricultural and economic consequences, particularly in the U.S. Great Plains area (e.g., the 2012 Central US event and the 2017 Northern Plains event). Although certain large-scale atmospheric and oceanic patterns are necessary for drought development, land- atmosphere interactions can play an important role in the intensification of drought conditions, especially for flash drought. This study aims to predict drought conditions over the U.S. Great Plains at 1-3-week lead times using a convolutional neural network (CNN) model. To forecast drought categories derived from the US Drought Monitor (USDM), the models are trained using multi-source atmospheric and land-surface variables, including 500 hPa geopotential height, precipitation, wind speed, surface radiation, humidity, and temperature from ERA5, soil moisture from Global Land Evaporation Amsterdam Model (GLEAM) and North American Land Data Assimilation System (NLDAS), and Normalized Difference Vegetation Index (NDVI) from satellite products. Model performance is evaluated to unravel the atmospheric and land-surface processes that drive droughts at different lead times and identify their relative contributions to drought development and intensification.
How to cite: Rippeteau, L. and Chen, L.: Drought prediction and understanding the drivers of drought development using a machine learning approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12345, https://doi.org/10.5194/egusphere-egu26-12345, 2026.
Agriculture poses severe impacts on water quality and health due to diffuse pollution via pesticide use. In this study, the impact of pesticide use on water quality in the Polatlı district—a region of intensive agriculture within the Ankara River Watershed—was assessed using the Grey Water Footprint (GWF) methodology. The study analyzed 34 active ingredients utilized in the 2023 production cycle of wheat, barley, onion, and sugar beet. District-level data on cultivated areas (ha) for each crop were obtained from the Turkish Statistical Institute (TURKSTAT) for 2023. For the GWF calculations, the natural background concentration was assumed to be zero, while the maximum allowable concentrations for each pesticide were retrieved from local regulations. A watershed-scale hydrological model, namely Soil and Water Assessment Tool (SWAT) were constructed for the study area and calibrated against observed streamflow data to ensure reliable simulation of pesticide transport. Pesticide applications were integrated into the model based on actual usage data. The pollutant loads transported from the Polatlı district to the Ankara River were calculated and subsequently utilized in the grey water footprint equation.
Our findings reveal that pesticide impacts vary significantly with respect to crop and active ingredient levels. For example, SWAT model simulation results for deltamethrin reveal a high environmental transport efficiency despite its low application rate (250 ml/ha) compared to other pesticides. This pesticide has an extremely high affinity for soil particles as clear from the organic carbon-water partition co-efficient value (Koc = 1,000,000 L/kg); it binds strongly to soil rather than dissolve in water. The transport of deltamethrin is entirely driven by soil erosion, leading to its accumulation in riverine sediments. Due to its extreme Koc value, the pesticide remains associated with suspended solids and bed sediments, posing a significant long-term threat to benthic organisms and aquatic biodiversity. This sediment-related pollution indicates that the GWF of the basin is not only a function of dissolved pollutants, but it can be heavily influenced by sediment quality. No leaching to groundwater or dissolved transport was observed, confirming its strong soil-binding behavior. This substantial variability in GWFs underscores the necessity for region-specific water quality standards to more accurately assess and manage the environmental impact of pesticide use. Our analysis addresses the complexities of mixed cropping systems typical of semi-arid regions, where water scarcity and intensive pesticide use converge to create critical water quality challenges. This study provides a framework for similar assessments in other agricultural regions, aiding in the development of more informed pesticide management strategies to enhance water resource sustainability. Our results highlight specific pesticides requiring priority attention: replacing or limiting high-GWF pesticides is essential for progress toward sustainable water management in the Ankara River basin.
How to cite: Dogan, F. N. and Capar, G.: Assessment of Pesticide-Related Water Pollution in the Ankara River Watershed: A Combined SWAT and Grey Water Footprint Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16687, https://doi.org/10.5194/egusphere-egu26-16687, 2026.
Terrestrial water availability in India is increasingly affected by both climate variability and human activities such as groundwater extraction, reservoir operations, and the expansion of irrigation. However, the observed trends in these factors and their future changes at the river basin level are still not well quantified, making it difficult to plan effective water management strategies. In this study, we assess the individual and combined impacts of climate change and human interventions on the water budgets of major Indian river basins using an ensemble framework that includes the Community Water Model (CWatM) hydrological models. We specifically analyze the changes in sectoral water demands, including agricultural, domestic, and industrial, analyzing their historical progression and projected changes from 1951 to 2100. Based on IMD datasets and CMIP6 scenarios, we identify key regions likely to face water stress in the future and estimate uncertainties in water availability. These findings support the development of sustainable water management plans in response to evolving sectoral trends and climate-related challenges across the Indian subcontinent.
How to cite: Kushwaha, A. P. and Mishra, V.: Dynamics of Sectoral Water Demand and Future Water Stress Hotspots in Indian River Basins, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16329, https://doi.org/10.5194/egusphere-egu26-16329, 2026.
Climate change is driving a marked intensification of hydrological extremes, including both droughts and floods. When these opposing conditions occur in close succession, known as hydrological whiplash, they generate compounded impacts on ecosystems, infrastructure, and human livelihoods. We analyze hydrological whiplash across India using observed streamflow data and simulations from the validated H08-CaMa-Flood model. The results indicate that nearly 90% of streamflow stations experienced at least one whiplash event, with drought-to-flood transitions being both more common and more abrupt than flood-to-drought shifts. These events are concentrated primarily during the monsoon season, but their occurrence has increased in the non-monsoon months in recent decades, particularly in high-elevation regions. Moreover, we find that whiplash events are becoming more frequent and more intense, while the interval separating dry and wet extremes is shrinking, signaling an escalation of hydrological volatility across the country. Together, these patterns underscore the need for strengthened monitoring, early warning capabilities, and adaptive water management strategies to reduce the growing risks associated with rapid hydrological transitions under a warming climate.
How to cite: Sharma, P. and Mishra, V.: Hydrological Whiplashes Over India: Patterns, Drivers, and Recurrence, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16235, https://doi.org/10.5194/egusphere-egu26-16235, 2026.
