In hydraulics, flume experiments provide controlled, high-quality datasets but are resource-intensive and limited in scalability. Numerical modeling offers greater flexibility to simulate diverse flow conditions, yet its accuracy is highly sensitive to parameterization, boundary conditions, and discretization schemes. In hydrology, sparse and uncertain field data further complicate model calibration and validation.
Recent advances in artificial intelligence (AI) and machine learning (ML) allow researchers to analyze large and heterogeneous datasets. However, risks arise when dataset adequacy, representativeness, or validation are overlooked, leading to ambiguous outcomes. These issues intensify when experimental, numerical, and AI-driven approaches are not cross-validated or integrated, weakening robustness and transferability.
This session aims to strengthen understanding of data curation and model selection as critical, though often overlooked, components in solving water resource challenges. Topics of interest include:
1. Strategies for data acquisition, handling, and curation across laboratory, field, numerical, and AI/ML approaches.
2. Best practices in optimization, calibration, and hyper-parameterization to improve model performance.
3. Frameworks for integrating laboratory, field, and computational datasets for consistency and cross-validation.
4. Data curation methods that enhance efficiency, reproducibility, and reliability in modeling.
Through interdisciplinary dialogue, the session seeks to generate methodological insights and practical guidelines that enhance accuracy in data handling and model selection. The overarching goal is to advance high-quality, validated, and context-relevant outcomes that strengthen resilience and reliability in water research.
Heatwaves are among the most rapidly intensifying climate extremes over India, yet their evolving spatial characteristics under recent and near future climate change remain inadequately quantified. This study examines the spatio-temporal variability of Heatwave Days (HWDs) across India using daily maximum temperature from the India Meteorological Department (IMD) gridded dataset for the historical period 1975-2024 and extends the analysis to the near future (2025-2044) using CMIP6 climate projections. Heatwave days are identified at each grid point using a calendar day based percentile approach, where daily maximum temperature exceeding the local 95th percentile threshold for the same calendar day, computed over a fixed reference period of 1981-2010, is classified as a heatwave day. Grid wise cumulative and decadal HWDs are analysed to assess long-term exposure and spatial redistribution. To objectively identify dominant heatwave regimes, Self-Organizing Maps (SOMs) are employed using multiple HWD metrics, enabling classification of regions with distinct heatwave characteristics and temporal evolution. Observational results indicate a clear reorganization of heatwave patterns over India. During the late 20th century (1975-1994), HWD accumulation is largely limited to north-western and parts of central India, typically ranging between 26 to 50 days per decade, with most eastern and peninsular regions experiencing fewer than 25 HWDs. From the mid-1990s onward, a pronounced intensification and spatial expansion is evident. By 2005-2014, large parts of central and eastern India exhibit decadal HWDs in the range of 51 to 100 days. The most recent decade (2015-2024) shows widespread moderate to high HWDs accumulation across the country, with several regions of central, eastern, and peninsular India experiencing 101 to 150 HWDs, and localized hotspots exceeding 150 days per decade. Future HWDs for 2025-2044 are derived from daily maximum temperature projections of the MPI-ESM1-2-HR model under the SSP2-4.5 scenario. The near-future decadal projections (2025-2034 and 2035-2044) indicate a continued intensification and spatial expansion of HWDs, with extensive areas of north-western, central, and peninsular India experiencing 151 to 250 HWDs per decade, and emerging hotspots exceeding 250 to 350 days, particularly over parts of north-western and southern India. Eastern India also shows a marked transition toward higher HWDs classes, indicating increasing regional vulnerability. Overall, the combined observational and CMIP6 based analysis demonstrates a transition toward widespread and persistent heatwave exposure across India in both recent decades and the near future. The integration of a grid specific, calendar day based percentile definition with SOM based classification provides a robust framework for identifying evolving heatwave regimes and supports improved heat risk assessment, climate adaptation planning, and early warning strategies under continued warming.
How to cite: Bhoopathi, S. and Pal, M.: Reorganization of Heatwave Day Regimes across India under Recent and Near Future Warming, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16374, https://doi.org/10.5194/egusphere-egu26-16374, 2026.
Combined Sewer Overflows (CSOs) in cities can play a significant role in the morphology and hydraulic performance of streams near urban areas. A complete urban drainage system is often modelled by a dedicated hydrological/hydraulic model (e.g., SWMM or Mike+). However, these models must be calibrated against observations. Especially the flow from CSOs is difficult to estimate. The quality of the data and the drainage models depend on the accuracy of the overall mass balance of the drainage system. If it is not possible to estimate the discharge from, for example, a CSO, the results from other parts of the system become unreliable.
This research evaluates flow dynamics through a multi-methodological approach where the CSO is evaluated by theoretical models, CFD models, experimental work in a laboratory, and a new innovative method where the noise from a CSO is analyzed. The sound is both analyzed directly and by training a machine learning model on the laboratory experiments. The result is a hybrid model filtering all the estimates to one flow estimate. CFD has been used to model the specific CSO to take a Q-h relationship into account, and to generate a so-called catalog method. In this method, multiple variations of geometry are simulated in a free-surface CFD model to cover many different geometries, and general equations are extracted from these simulations.
The hybrid approach opens the door to a new way of estimating interactions between the urban water cycle and the receiving waters. Applying edge processing makes it possible to continuously adapt to local conditions that were not present during the calibration and validation of the model. Edge processing involves signal processing and modeling at the measuring point, where the maximum bandwidth of the sensor data is available and can be used for the most accurate data estimation.
How to cite: Rasmussen, M. R., Jackerott, M. U., Nielsen, J. M., Vestergaard, I. K., and Nielsen, J. E.: Combining different hydraulic methods to estimate the discharge from Combined Sewer Overflows (CSO) into streams., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11280, https://doi.org/10.5194/egusphere-egu26-11280, 2026.
This study investigates wave-induced flow behaviour around vertical breakwaters with retreated crown wall using numerical simulations. Previous experimental work has shown that moving the crown wall landward can reduce wave forces, moments, and overtopping. However, the associated flow mechanisms near the wall and trunk region have not been examined in detail. In this work, the open-source CFD model REEF3D is used to simulate regular wave interaction for crown wall retreat configuration. The model solves the Reynolds-averaged Navier–Stokes equations, with a level set method for free-surface tracking and a k–ω turbulence closure. The numerical results are first validated against published experimental data to ensure accuracy. The simulations provide detailed information on velocity fields, vortex formation, and flow separation during wave impact and overtopping. The results show that retreating the crown wall modifies the local flow structure, leading to a redistribution of momentum and a reduction in direct wave impact on the wall. These findings help to clarify the hydrodynamic role of retreated crown wall in vertical breakwater design.
How to cite: Firoj, S. and Afzal, M. S.: Flow Modulation and Wave Impact Reduction by Retreated Crown Walls in Vertical Breakwaters, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13261, https://doi.org/10.5194/egusphere-egu26-13261, 2026.
Watershed hydrodynamics is governed by various hydrological flow processes that occur at different spatiotemporal scales. Most hydrological models couple the surface flow solver with the standard empirical infiltration models for flood propagation modeling. However, the empirical infiltration models are not applicable for heterogeneous and anisotropic soils and shallow groundwater tables, which are most vulnerable to waterlogging problems. Hence, simultaneous and integrated modeling of the surface and subsurface flow processes is essential for the continuous monitoring of watershed hydrodynamics. A physically based unified multi-region, multi-process watershed model integrates the various hydrological flow components in different regions through unique coupling mechanisms at the interfaces. The current work presents a Finite Volume (FV) method-based watershed flow model developed using the OpenFOAM® framework [1]. The developed model framework utilizes the ‘multi-region’ structure from the OpenFOAM® library to integrate the OpenFOAM®-based solvers for the individual processes of surface overland flow [2,3] and saturated-unsaturated subsurface flow [4] through the imposition of appropriate interface boundary conditions or addition of source/sink terms at the interfaces of the flow regions. The surface flow component is modeled using the diffusive wave or the zero-inertia (ZI) approximation of the two-dimensional (2D) depth-averaged shallow water equations (SWE). On the other hand, the flow through the variably saturated subsurface media is modeled using the ‘mixed form’ of the 3D modified Richards Equation. The flux exchange between the surface and subsurface regions (infiltration or exfiltration rate) is modeled using a switching algorithm to impose the boundary condition on the interface between the two regions. The algorithm changes the interface to a Dirichlet or a Neumann type boundary condition based on the rainfall intensity and the saturated hydraulic conductivity of the ground surface. A stabilized and adaptive time-stepping algorithm has been implemented to ensure smooth convergence of the iterative technique used for linearizing the nonlinear governing equations. The developed model is equipped with parallelization strategies to be run on multi-core processors, which is essential for increased computational efficiency while solving regional-scale watershed flow problems. The developed watershed model has been verified and validated against the standard benchmark problems on saturation excess and infiltration excess from the literature. Moreover, the applicability of the developed model has been extended to solve complex hydrological problems on exfiltration occurring over natural catchments, yielding satisfactory results.
References
[1] Jasak, H., A. Jemcov, Z. Tukovic. (2007). OpenFOAM: A C++ library for complex physics simulations. In Vol. 1000 of Proc., Int. Workshop on Coupled Methods in Numerical Dynamics,1–20. Dubrovnik, Croatia: Inter-University Center
[2] Dey, S., Dhar, A. (2024). Applicability of Zero-Inertia Approximation for Overland Flow Using a Generalized Mass-Conservative Implicit Finite Volume Framework. Journal of Hydrologic Engineering, 29(1), 04023042.
[3] Dey, S. (2025). zeroInertiaFlowFOAM – a OpenFOAM®-based computationally efficient, mass-conservative, implicit zero-inertia flow model for flood inundation problems on collocated grid-systems (No. EGU25-17402). Copernicus Meetings.
[4] Dey, S., & Dhar, A. (2022). Generalized mass-conservative finite volume framework for unified saturated–unsaturated subsurface flow. Journal of Hydrology, 605, 127309.
How to cite: Dey, S. and Dhar, A.: An OpenFOAM®-based coupled surface-subsurface flow model for simulating watershed hydrodynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13540, https://doi.org/10.5194/egusphere-egu26-13540, 2026.
Marine sediments are very important for keeping the coast stable and protecting the shoreline naturally. However, anthropogenic activities can greatly change how sediment moves, making their accurate monitoring essential. In marine settings, understanding bedload sediment transport can be challenging due to conventional methods reliant on visual observations or direct sediment sampling tend to be intrusive, spatially constrained, and inadequate for long-term or continuous monitoring. In this situation, passive underwater acoustics is a promising non-intrusive option that can provide continuous monitoring with high temporal resolution. This study investigates the acoustic signatures related to marine bedload transport, focusing particularly on the sounds generated by interparticle collisions of mobile sediments. A series of controlled laboratory experiments are performed utilising simplified experimental arrangements in which artificial sediments (spherical glass beads) are mobilised under oscillatory motion that simulates wave-induced seabed forcing. We use glass beads of different sizes to create idealised bedload conditions, and we use an oscillating plate to control the movement of the particles. Hydrophones placed close to the sediment bed record acoustic pressure signals. The recorded acoustic signals are analyzed in both the time and frequency domains. Individual particle impacts are characterised by short transient acoustic events, and spectral analyses show clear peak frequencies that are linked to sediment motion. The results indicate that the peak frequency of the acoustic spectrum is predominantly determined by particle diameter and is additionally influenced by the amplitude and frequency of the applied oscillatory motion. These observations align with theoretical models, such as those suggested by Thorne (1985), that explain the generation of pressure waves during underwater particle collisions. To further explore the mechanisms of sound generation, experiments are conducted with both smooth and rough beds below the beads layers. The analysis reveals the existence of sediment-specific acoustic signatures, facilitating the differentiation of particle sizes according to their spectral characteristics. This study illustrates the significant potential of passive acoustic methods for the remote monitoring of marine bedload transport. The study offers novel insights into sound generation mechanisms linked to sediment motion across various particle sizes, motion amplitudes, and bed configurations, utilising a combination of laboratory experiments, theoretical frameworks, and comprehensive spectral analysis, with direct implications for intricate coastal and offshore environments.
How to cite: Dutta, D., Jarno, A., Besnard, H., Morvan, B., and Marin, F.: Passive Acoustic Characterization of Marine Bedload Transport Based on Interparticle Collision Dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18906, https://doi.org/10.5194/egusphere-egu26-18906, 2026.
Considering the dearth of gauge-based rainfall observations at desirable resolution, it becomes immensely challenging to quantify and monitor droughts, especially over the developing countries. This can be circumvented by utilizing the high-resolution open-access rainfall products. This study is envisaged with the objective to assess the spatiotemporal variation of meteorological droughts over the Bundelkhand region, India. The multi-source weighted-ensemble precipitation (MSWEP), a blended product of global gauge-based, satellite-based and reanalysis precipitation datasets, is utilized for a period of 44 years (1980-2023). The MSWEP rainfall is bias-corrected with respect to the India Meteorological Department (IMD) gridded observation dataset for the 14 districts in the region. Using the corrected rainfall product, the droughts over each district are characterized by Standardized Precipitation Index (SPI) at three different timescales, i.e., the SPI-3, SPI-6 and SPI-12 are used to model short-term, intermediate-term and long-term droughts, respectively. A drought severity index (DSI) is proposed considering the probability of droughts in different severity classes (i.e., near-normal, moderate, severe and extreme). Further, the trend analysis of SPI at different timescales is carried out using Modified Mann-Kendall (MMK) test. The results reveal the MSWEP dataset’s problems in capturing higher quantiles, which affects the probabilistic distribution used for quantifying drought events. However, the bias-corrected MSWEP product showed an excellent match with the IMD gridded data, thereby substantiating its applicability over the Bundelkhand Region. The region is found to be prone to droughts with an increasing trend of dryness. The novel approach of DSI is found to distinguish the drought severity levels at district-scale, which can be helpful for planning and management of droughts. Overall, this study provides critical insights on the drought characterization using state-of-the-art datasets and innovative approaches, which can also be extended to other drought-prone regions of the world.
Keywords: Bias-correction; Bundelkhand; DSI; MSWEP; MMK; SPI
How to cite: Swain, Dr. S.: A statistical approach of mapping drought severity using bias-corrected blended dataset over a semi-arid region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18814, https://doi.org/10.5194/egusphere-egu26-18814, 2026.
Small watersheds play a crucial role in sustaining river hydrology, ecological flows and local water security. However, they are increasingly threatened by climate change, rapid transformations of land use and escalation of anthropogenic pressures. These problems are worse in areas with little data, where few hydrological observations, sparse monitoring networks, and inconsistent long-term datasets make it hard to accurately assess vulnerability and make plans. To address this critical gap, this study introduces a unique and data-efficient Criteria Importance Through Intercriteria Correlation- Group Method of Data Handling (CRITIC-GMDH) hybrid framework, specifically developed to accurately assess watershed vulnerability in regions where large, continuous, or high-resolution datasets are unavailable. This interpretable decision-support approach integrates CRITIC for objective indicator weighting with the nonlinear modelling capability of the GMDH, enabling robust vulnerability prediction under constrained data conditions, overcoming key limitations of conventional hydrological models and black-box machine learning techniques. The framework incorporates eleven hydro-meteorological, geomorphological, and socio-economic parameters, including rainfall, temperature, runoff, watershed area, watershed length, water quality index, average slope, forest area, impervious area, population density, and highest flood level. The approach is demonstrated across four major river basins in Northeast India, such as Gomati, Haora, Khowai, and Manu, which represent highly sensitive and partially transboundary catchments. Future climate projections from CMIP6 SSP1-2.6 and SSP5-8.5 scenarios were used to compute the Vulnerability Index across decadal periods (2005–2065). Results show a significant escalation in vulnerability, particularly under SSP5-8.5, with Haora and Gomati exhibiting Vulnerability Index > 0.85, indicating extreme exposure to climate extremes, and urbanization stress. Sensitivity analysis identifies rainfall, runoff, and temperature as dominant controlling parameters, and validation through the Falkenmark indicator and green-blue water stress indices confirms emerging scarcity risks. The study provides a scientifically grounded pathway for watershed prioritization and climate-resilient planning, offering an adaptable methodological foundation for sustainable management of small river systems in data-scarce regions.
How to cite: Rudra Paul, A. and Kumar Roy, P.: Climate-Induced Vulnerability Assessment of Small Watersheds Using a CRITIC–GMDH Hybrid Model: A Methodology Tailored for Data-Scarce Regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4175, https://doi.org/10.5194/egusphere-egu26-4175, 2026.
This study investigates the coastal-region impacts of climate change on rice yield in Goa, India, a monsoon-driven agroecosystem highly dependent on paddy cultivation and vulnerable to rainfall variability, salinity intrusion, and rising temperatures. The study aims to (i) estimate future crop evapotranspiration (ETc) and rice yield projections under different Shared Socioeconomic Pathways (SSP 2.6, SSP 4.5, and SSP 8.5), and (ii) assess the effectiveness of adjusting planting dates, along with the integration of drought-resilient cultivars, alternate wetting and drying (AWD) irrigation, and soil management practices, as adaptation strategies to mitigate yield reductions. To achieve these objectives, the CropWat and AquaCrop models were employed, using statistically downscaled CMIP6 CESM2 climate data.
The AquaCrop model was calibrated using data from 1994 to 2004 and validated for the period 2005–2014, demonstrating strong performance metrics (Nash–Sutcliffe Efficiency = 0.86, RMSE = 278.5, r² = 0.93). Our findings indicate that projected climatic changes pose a significant threat to rice yield stability in the region. Rising temperatures and shifting monsoon patterns are expected to elevate evapotranspiration demand by 10–14%, thereby intensifying irrigation requirements even in high-rainfall areas.
In response, adjusting planting dates emerged as a promising adaptation strategy. Specifically, delaying planting by 5 days until 2070 and by 10 days from 2071 to 2099 significantly mitigated yield declines across all SSP scenarios. An optimum 10-day delay in planting was found to recover up to 17% of yield losses under SSP 2.6 and SSP 4.5. Furthermore, compound strategies—including drought-tolerant rice cultivars, AWD irrigation, and improved soil management—provided up to 25% additional yield gains. These integrated approaches not only improved crop water productivity but also stabilized yields under moderate emission pathways. However, under the high-emission SSP 8.5 scenario, yield reductions remained substantial (up to 20%) due to increased temperature stress and shortened grain-filling duration, underscoring the limits of adaptation under extreme climate conditions.
The results highlight the importance of temporally optimized sowing schedules, integrated irrigation management, and improved soil practices for enhancing the resilience of coastal rice systems. This study further demonstrates that reliable data curation, model calibration, and parameter selection are essential to improving predictive accuracy in agro-hydrologic modelling. The findings emphasize the need for consistent methodological frameworks that couple climate projections with process-based crop models to assess adaptation effectiveness under uncertain future conditions.
Overall, the study provides actionable insights for strengthening the accuracy and reliability of water- and climate-based agricultural modelling frameworks. The outcomes contribute to developing climate-resilient strategies for paddy cultivation in coastal India, reinforcing the broader understanding of model validation, uncertainty reduction, and data-driven adaptation in hydrologic and agricultural research.
How to cite: Balvanshi, A., Kv, J., and Desai, V. R.: Evaluating Climate Change Impacts and Adaptation Options for Paddy Yield Using Data-Curated Modelling in Goa, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12001, https://doi.org/10.5194/egusphere-egu26-12001, 2026.
Root-zone Soil Moisture (RZSM; 10–102 cm) is a critical variable for land–atmosphere interactions, plant water availability, groundwater recharge, and hydrological extremes; however, its reliable estimation at deeper layers over large spatial scales remains challenging. Ground-based monitoring networks such as the International Soil Moisture Network (ISMN) provide accurate multi-depth soil moisture observations, but their utility is constrained by sparse station distribution, high installation and maintenance costs, and limited spatial coverage (Dorigo et al. 2011). In contrast, microwave remote sensing based satellite missions, including Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Sentinel-1, offer frequent and spatially continuous SM observations but are sensitive only to near-surface conditions (top ~5 cm), leaving deeper soil layers unobserved. This disparity between depth-limited in-situ observations and surface-focused satellite measurements motivates the present study to develop a machine learning based framework to estimate RZSM from satellite-derived surface SM by incorporating temporal memory and forcing. This approach effectively captures persistence effects and vertical moisture transfer, which are essential for accurate prediction of deeper SM layers (Pal &Maity, 2019). Multi-depth SM observations from 5 to 102 cm, obtained from ISMN stations and categorized according to USDA Hydrologic Soil Groups (HSG A–D; four stations per HSG), account for differences in soil water movement and retention behaviour (Ross et al. 2018). For each soil group, Support Vector Regression (SVR) and Random Forest (RF) models were trained using a sequential, depth-wise prediction strategy comprising four depth transitions: 5–10 cm, 10–20 cm, 20–51 cm, and 51–102 cm. Model evaluation demonstrates strong predictive performance across all depth intervals (R² = 0.85–0.95 for RF and 0.63–0.95 for SVR at validation sites), indicating that HSG classification effectively captures soil-specific SM dynamics. The trained models successfully generate comprehensive RZSM profiles using satellite-derived SM from the SMAP mission.These profiles are rigorously validated against ground-based observations and demonstrate strong applicability across diverse landscapes lacking direct subsurface measurements.
How to cite: Bakka, S. and Narayanan, S.: Machine Learning-Based Root-Zone Soil Moisture Estimation Using Satellite-Derived Surface Soil Moisture, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10741, https://doi.org/10.5194/egusphere-egu26-10741, 2026.
Urban roads in fast-growing cities fall apart quickly, and everyone feels the impact—traffic slows down, accidents happen, and the city’s economy takes a hit. The old way of checking roads—sending people out to inspect them on foot—just doesn’t cut it anymore. It’s slow, expensive, and puts workers in harm’s way. So, we’ve built something better: an automated system that uses drones and AI to keep an eye on road conditions.
Here’s how it works. Drones fly over city streets, snapping high-resolution images that pick up everything from big potholes to tiny cracks. We run these images through our analytics pipeline. First, we use classic machine learning to weed out the stretches of road that are still in good shape. That way, the system doesn’t waste time on areas that don’t need attention.
Next, we use a deep learning model—based on YOLO, which stands for “You Only Look Once”—to hunt down and label the actual problem spots. We’ve trained this model using annotated drone photos, so it can handle tricky lighting or weird road surfaces. The model doesn’t just spot the defects—it also nails down where they are, how big they’ve gotten, and how bad the damage is.
But spotting problems isn’t enough. City agencies need to see this info and act on it, fast. So, we’ve built a web portal using OpenLayers and PostGIS that maps out every defect. Maintenance crews can sort issues by type or severity, pull up interactive maps, and even generate reports to plan repairs.
This whole setup is practical, affordable, and scales up easily for any city that wants to take road maintenance seriously. By bringing together drones, AI, and smart mapping, we’re giving city managers the real-time, reliable data they need to keep roads safe and traffic moving. And honestly, this system can help any city make smarter decisions about their roads and urban development.
How to cite: Manu, H. and Bhoopathi, S.: UAV-Based Road Defect Detection Using Hybrid Machine Learning Approach with Web GIS Visualization, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6705, https://doi.org/10.5194/egusphere-egu26-6705, 2026.
The purpose of the talk is to discuss spatially adapted cross-validation methods that maintain sufficient separation between training and validation sets, thus providing more accurate estimates of model risk. We begin by reviewing various spatial cross-validation techniques, including spatial blocked cross-validation and spatial leave-one-out, under scenarios of low to strong spatial dependence. We then propose a practical framework for determining an optimal “buffer size” for spatial leave-one-out that reduces autocorrelation between training and validation subsets. This framework is further enhanced by a parametric bootstrap approach designed to approximate the true risk in single-realization settings. Simulation experiments confirm that these methods effectively capture the underlying spatial structure, leading to more reliable risk estimation.
How to cite: Chavez Chong, C. O., Hardouin, C., and Fermin Rodriguez, A. K.: Strategies for spatial leave-one-out cross-validation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12042, https://doi.org/10.5194/egusphere-egu26-12042, 2026.
Posters virtual: Thu, 7 May, 14:00–18:00 | vPoster spot 1b
EGU26-5098 | ECS | Posters virtual | VPS23
A Geospatial and AHP-Based Approach for Delineating Groundwater Potential Zones in Vulnerable Groundwater SystemsThu, 07 May, 14:33–14:36 (CEST) vPoster spot 1b
Groundwater is the second largest reserve of fresh water and is an important resource that supports agriculture, industrial and domestic water supplies. Groundwater is facing unsustainable impacts by human activities over the years in different forms. The situation is aggravated by climate change which aggravates groundwater stress through variable precipitation leading to reduced recharge. Thus, highlighting the importance of assessing aquifer potential for sustainable groundwater management. The analysis was carried out in the Manjra and Maner sub-basins, of Godavari river basin, India where data-driven assessments remain limited. In this regard, the present research employs a Multi-Criteria Decision Analysis (MCDA) framework that integrates Geographic Information Systems (GIS) and the Analytical Hierarchy Process (AHP) to define groundwater potential zones (GWPZ) in the Manjra and Maner sub-basins. In a GIS environment, eight thematic layers—geology, land use/land cover, lineament density, drainage density, rainfall, soil, and slope—were examined. These factors were weighted using AHP, and combined using weighted overlay analysis. Area under the Curve (AUC), Receiver Operating Characteristic (ROC) analysis, and groundwater inventory data were used to validate the final GWPZ map. Five classifications of groundwater potential were identified for the research area: very low, low, moderate, high, and very high. The research region's predominance of moderate (45%) to high potential (28%) zones suggests that groundwater availability is generally fair to good. Priority locations for sustainable groundwater development and management are indicated by the high and very high potential zones.
How to cite: Belluti Nanjundagowda, P. and Vema, V. K.: A Geospatial and AHP-Based Approach for Delineating Groundwater Potential Zones in Vulnerable Groundwater Systems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5098, https://doi.org/10.5194/egusphere-egu26-5098, 2026.
EGU26-4200 | ECS | Posters virtual | VPS23
Performance of Tapered Submerged Vanes in Mitigating Local Scour Around Bridge PiersThu, 07 May, 14:36–14:39 (CEST) vPoster spot 1b
Scour, defined as the erosion or removal of sediment from around bridge piers due to flowing water, remains one of the primary causes of hydraulic structure failures worldwide. Local scour around bridge piers poses a serious threat to bridge stability, particularly during high-flow events, as the development of downflow, horseshoe vortices, and wake vortices at the pier base leads to intense sediment removal and foundation instability. To address this challenge, the present study investigates the hydrodynamic behaviour and scour reduction performance of tapered submerged vanes installed upstream of a cylindrical bridge pier as an effective countermeasure against local scour. A combined numerical and experimental approach was adopted to evaluate the influence of tapered submerged vanes on flow structure and scour characteristics. Numerical simulations were carried out using FLOW-3D Hydro to analyse the three-dimensional flow field around the pier–vane system under steady clear-water conditions. The simulations focused on assessing velocity distribution, near-bed shear stress, vortex dynamics, and secondary flow patterns generated by the tapered vanes. Particular attention was given to the formation of leading-edge vortices (LEVs) and their role in modifying erosive flow structures near the pier foundation. Based on the numerical insights, a series of physical model experiments were conducted in a laboratory flume to quantify the scour reduction achieved by the tapered vanes. The experiments aimed to optimize the longitudinal and transverse placement of the vanes relative to the pier. The vanes were installed at a fixed longitudinal distance upstream of the pier, while transverse spacing was systematically varied to examine its effect on sediment transport and scour depth. Bed elevation profiles and maximum scour depths were measured after equilibrium scour conditions were attained. The results demonstrate that tapered submerged vanes significantly alter the near-bed flow field by generating localized leading-edge vortices that effectively deflect high-energy flow away from the pier base. This flow redirection weakens the horseshoe vortex and reduces near-bed shear stress in the vicinity of the pier. Among the tested configurations, the vane arrangement with a longitudinal spacing of 1.5D and transverse spacing of 2D exhibited the best performance, resulting in a 56% reduction in maximum scour depth compared to the no-vane case. Additionally, localized sediment deposition was observed upstream and downstream of the pier, indicating favourable redistribution of sediment induced by the vane-generated secondary currents. By integrating numerical modelling with experimental validation, this study provides valuable insights into the flow mechanisms and optimal placement strategies of tapered submerged vanes. The findings highlight their potential as a practical, efficient, and sustainable solution for mitigating local scour around bridge piers in alluvial channels.
Keywords: Scour, Submerged Vane, Horseshoe Vortices, Wake Vortices, Leading-Edge Vortex (LEV)
How to cite: Karmishtha, K., Behera, R. K., and Singhal, G. D.: Performance of Tapered Submerged Vanes in Mitigating Local Scour Around Bridge Piers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4200, https://doi.org/10.5194/egusphere-egu26-4200, 2026.
EGU26-4184 | ECS | Posters virtual | VPS23
A Multi-Criteria GIS Framework for Socio-Economic Drought Risk Assessment across IndiaThu, 07 May, 14:39–14:42 (CEST) vPoster spot 1b
Socio-economic drought represents the stage at which water stress translates into tangible disruptions to livelihoods, infrastructure, and economic systems, often preceding severe physical water shortages. In India, pronounced climatic variability combined with extreme physiographic heterogeneity leads to strong spatial contrasts in socio-economic vulnerability to drought. Despite this, most drought assessments in the country remain dominated by hydro-meteorological indicators, with limited integration of socio-economic exposure, sensitivity, and adaptive capacity.
This study develops a spatially explicit socio-economic drought risk assessment framework for India by integrating multi-dimensional climatic, environmental, and socio-economic indicators within a Geographic Information System (GIS). Thirteen indicators capturing water availability, agricultural productivity, infrastructure, population pressure, economic activity, and social deprivation are compiled from multi-source datasets and harmonized to a common spatial resolution. The indicators include available soil water, agricultural yield, livestock density, road density, population density, biomass, electricity consumption, Gross Domestic Product (GDP), global surface water availability, digital elevation model, groundwater availability, land use/land cover, and relative deprivation. Indicator weights are objectively derived using the Analytic Hierarchy Process (AHP), with consistency of expert judgments ensured through the consistency ratio criterion (CR < 0.1). A GIS-based weighted overlay approach is then employed to generate a composite socio-economic drought risk index, which is classified into four risk categories to identify spatial patterns and hotspots.
The resulting risk map reveals pronounced regional disparities, highlighting drought-prone agrarian and socio-economically marginalized regions as areas of elevated risk. The proposed framework offers a transferable and scalable decision-support tool for integrating socio-economic dimensions into drought monitoring and preparedness. By explicitly linking water stress to livelihood and infrastructure vulnerability, the study provides actionable insights for risk-informed planning, targeted mitigation, and long-term drought resilience in India.
How to cite: Beerkur, A. K. and Palagiri, H.: A Multi-Criteria GIS Framework for Socio-Economic Drought Risk Assessment across India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4184, https://doi.org/10.5194/egusphere-egu26-4184, 2026.
EGU26-4951 | ECS | Posters virtual | VPS23
CFD-Based Comparative Analysis of Conventional and Modified Piano Key Weirs for Improved Discharge EfficiencyThu, 07 May, 14:42–14:45 (CEST) vPoster spot 1b
The Piano Key Weir (PKW) has earned recognition for its adaptability for large discharges across weir types of varying heights and with small footprints. Therefore, it has the potential to be a substitute for linear weirs (space being a factor), Ouamane and Lempérière, (2006). Even with the above-mentioned advantages of PKWs, other geometries leave much to be desired. The rectangular PKW and the trapezoidal PKW illustrate a most common inefficiency example. Standard literature describes construction and operational shortfalls such as flowing separation at the inlet key, varying discharge and uneven velocities along the crest, vortex shedding and formation at the key intersections, dead zones in the inlet-outlet, zones of intensified energy dissipation, and lowering weir versatility at high flows. These challenges are combined to mean loss of efficiency in weir discharge capability. In response to these challenges, the present study introduces the Modified Piano Key Weir (MPKW) to assess its performance using 3D computational hydraulic modeling. The Volume of Fluid (VOF) methodology for free surface tracking and the Reynolds-Averaged Navier Stokes (RANS) for turbulence closure modeling characterize pressure gradients, flow accelerations in the several dimensions, and eddies. A systematic numerical investigation was conducted to compare the discharge efficiency of RPKW, TPKW, and MPKW across a range of steady inflow discharges: 0.030, 0.060, 0.090, 0.120, and 0.160 m³·s⁻¹. The MPKW demonstrated consistently superior discharge efficiency over both RPKW and TPKW for all tested cases, without requiring an increase in structural footprint or crest length. The highest relative improvement was observed at 0.060 m³·s⁻¹, which was therefore selected as a representative discharge for in-depth flow diagnostics. Discharge at 0.060 m³·s⁻¹ was applied to determine vorticity structures, turbulent kinetic energy (TKE), and energy dissipation to better understand the flow mechanisms that explain the efficiency of the weir. The MPKW design, with refined geometry and improved inlet–outlet design, rounded key transitions, and adjustable wall skew, was successful in mitigating flow separation at the key inlets and reducing the large-scale vortex formation at the key junctions. The modified sidewall skewed the internal recirculation, and as a consequence, TKE in the stagnation zones was less, and recirculation was more along the crests of the weir, thereby nullifying turbulent structures. While the breakdown of turbulence resulted in localized energy dissipation, the stabilization of the approach flow was improved because the process converted rotational energy of large eddies with a low energy loss to rapidly decaying eddies which do not sustain and produce a recycling of energy. Thus, less energy was concentrated in the vortex cells at the key junctions, the loss due to flow contraction was less, and the nappe cohesion over the crests was improved. MPKW, relative to other configurations, was characterized by a lower level of turbulence and vorticity at the junctions, a greater effective utilization of the crest, and improved pressure recovery. The results confirm MPKW as a hydraulically efficient and economically feasible solution for both new installations and retrofit applications under head or footprint constraints.
How to cite: Kumar, A., Padhi, E., and Mishra, S. K.: CFD-Based Comparative Analysis of Conventional and Modified Piano Key Weirs for Improved Discharge Efficiency, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4951, https://doi.org/10.5194/egusphere-egu26-4951, 2026.
EGU26-7917 | ECS | Posters virtual | VPS23
Unveiling integrated geo-hydraulic assessment of river meandering, bank erosion and sandbar dynamics in Alluvial channelsThu, 07 May, 14:45–14:48 (CEST) vPoster spot 1b
Predictability of river bank erosion in sinuous alluvial channels requires a combined study of the planform processes, hydraulics processes, sediment transportation, and the geotechnical properties of riverbanks. The research paper provides a detailed analysis of the evolution of channels within the Nabadwip-Kalna stretch of the Bhagirathi-Hooghly River (1990-2020). This analysis combines the synthesis of remote sensing, on-field surveys, lab experiments, and numerical model analysis into a multidimensional analysis. GIS was used through the Digital Shoreline Analysis System (DSAS) to measure changes on the bank-lines using historical satellite images of the same period of time. A two-dimensional migration coefficient (MC) model was used to model spatial-temporal changes in channel centrelines, and an RVR Meander was used to develop a model that takes into consideration depth-averaged flow velocity and reach-averaged hydraulic parameters. The characterisation of cross-sectional bathymetry and near-bank hydraulics was based on ADCP. The results of the geotechnical analysis showed that stratified streambanks showed critical shear stresses of 7.1-7.7 kPa, internal frictional angles of soils less than 30°–34°, and were predominantly affected by either cantilever collapse or piping as a result of varying maximum heights of streams between 5.7 and 6.8 metres. Bank stability through both BSTEM and BEHI was assessed, whereas sediment forecasting combined with SWAT to predict overbank flow and a Genetic Algorithm (GA) to estimate the total load. DSAS analysis on bank-line displacement revealed different erosion patterns within 170 transects, showing different RMSE of 0.090 to 0.162 in predicting zone boundaries. The MC method was able to model the 24-year centreline migration patterns, recording changes in the centreline-geometry parameters. Analysis of five cross-sections instrumented found instability and a factor-of-safety ratio of 0.81-0.95, resulting in 4.07-5.85m/yr and 4.35-7.15 km2/yr, respectively, lateral retreat and the eroded areas. Mean collapse rates were 0.125 to 0.198 m/yr, and the failure angle was 81°–87°. The maximum bank-failure mass was 41.24 kg (seasonal maximum), and the calibrated toe-scour mass was 0.28 kg. The GA model was tried using ten parameterisations and demonstrated the best prediction ability with the coefficient set at ten, where R2 = 0.96 and mean relative error (MRE) = 42% gave significantly better performance than the traditional regression analysis (R2 = 0.87 and MRE = 40%). There were also considerable changes in the area behind sandbar dynamics, that is, Nandai-Hatsimla increased by 11.87 ha in 1990 to 19.05 ha in 2020; Media by 39.7 ha to 57.68 ha; Char Krishnabati by 82.52 ha to 81.07 ha. Land-use/land-cover (LULC) predictions for 2040 indicated settlement expansion from 13.61% (2020) to 20.19%, with validation accuracy (RMSE = 0.253) confirming model reliability. This combined model shows that the combination of remotely sensed, field, laboratory, and model data provides quantitatively sound estimations of fluvial risks and forms the basis of evidence-based management of high-suspended riverine areas. The modular design can be applied to monsoon-dominated alluvial basins throughout the globe, which will promote adaptive land-use planning and long-term infrastructure development in the vulnerable riparian societies.
How to cite: Ghosh, A.: Unveiling integrated geo-hydraulic assessment of river meandering, bank erosion and sandbar dynamics in Alluvial channels, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7917, https://doi.org/10.5194/egusphere-egu26-7917, 2026.
EGU26-8975 | ECS | Posters virtual | VPS23
Flood Hazard Analysis and Risk Assessment of Koshi River, Bihar (India) using Remote Sensing, GIS and AHP TechniquesThu, 07 May, 14:48–14:51 (CEST) vPoster spot 1b
Rising flooding, which is exacerbated by both climate change and human behavior, demands proper identification of vulnerable zones. Conventional hydrological analysis can neglect geographical variability. In this study, a combined geospatial and decision-making process is used to determine the levels of vulnerability and risk of flooding in the Koshi River Basin in the state of Bihar. The research work has developed a susceptible, vulnerable and risk map by integrating GIS, Remote Sensing and AHP. Weightings of eleven physical and hydrological factors and five socio-economic indicators were carried out in a systematic manner using a multi-criteria decision-making framework that allowed appropriate consideration of their relative contributions to flooding. Flood susceptibility, vulnerability and risk maps were created using the GIS environment's Weighted Overlay technique. According to the analysis, population density (41.6%) and literacy rate (24%) are controlling factors for flood vulnerability in the basin, whereas rainfall (23.9%), elevation (14.7%) and drainage density are the main elements that influence flood susceptibility. The Koshi basin is largely covered by the low and moderate classes of flood susceptibility, whereas a very minor amount (0.03%) comes under the high susceptibility classes, according to results from flood susceptibility maps. A significant section (42.87%) of the basin has moderate flood susceptibility due to a combination of exposure and socioeconomic characteristics, according to the results of the flood vulnerability analysis. According to the flood risk results, a significant amount of the basin (84.18%) has moderate flood risk, while a tiny portion has high flood risk in the low-lying, heavily inhabited areas close to the basin's riverbanks. ROC-AUC for model validation yielded an accuracy of 66.3% and proved that the proposed GIS-AHP model was a reliable. Conclusion from this study underscore an integrating role in both physical and socio-economic considerations with prospects of enhancement through climate scenarios in flood mitigation and planning/early warning maps.
How to cite: Chaudhary, P. and Padhi, E.: Flood Hazard Analysis and Risk Assessment of Koshi River, Bihar (India) using Remote Sensing, GIS and AHP Techniques , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8975, https://doi.org/10.5194/egusphere-egu26-8975, 2026.
EGU26-8813 | ECS | Posters virtual | VPS23
Assessment of Partial Blockage in Urban Drains for Flood Risk ReductionThu, 07 May, 14:51–14:54 (CEST) vPoster spot 1b
Partial blockage in open channels and urban drainage systems is a common issue arising from debris accumulation, sediment deposition, and inadequate maintenance, often resulting in reduced flow capacity and increased flood risk. Despite its practical relevance, the hydraulic effects of partial blockage on flow behaviour are not well quantified through controlled experimental studies. This work aims to investigate the influence of partial blockage on flow characteristics in open channels and explore its implications for urban stormwater drainage systems.Laboratory experiments are carried out in a rectangular open-channel flume under steady flow conditions. Velocity measurements are obtained at multiple depths for unblocked conditions and for different partial blockage configurations. Blockages of varying size and location are introduced manually to represent realistic obstructions commonly observed in urban drains. The changes in velocity distribution, water depth, and flow-carrying capacity due to partial blockage are analysed to understand the hydraulic response of the system.
Based on these observations, relationships between blockage extent and hydraulic performance are developed to identify critical blockage conditions.The study framework is applied to urban stormwater drainage networks using SWMM modelling to extend the experimental findings to real-world applications. Blockage scenarios are simulated in selected channels to assess their impact on system performance and flooding behaviour.
The outcomes of this study provide experimental insight into blockage-induced hydraulic effects and highlight the importance of considering partial blockage in urban drainage analysis. The combined experimental and modelling approach offers a practical basis for improving flood risk assessment and maintenance planning in urban stormwater systems.
How to cite: Mishra, A. K., Kumar, H., and Vinnarasi, R.: Assessment of Partial Blockage in Urban Drains for Flood Risk Reduction , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8813, https://doi.org/10.5194/egusphere-egu26-8813, 2026.
EGU26-13831 | ECS | Posters virtual | VPS23
From Empirical Assumptions to Data-Informed Decisions: A Reliable Water Storage Soil Depth Estimation MethodThu, 07 May, 14:54–14:57 (CEST) vPoster spot 1b
Efficient water use in agriculture is crucial for sustainable water resource management, especially in areas experiencing increasing water scarcity. A critical yet often oversimplified component of irrigation planning is the estimation of water storage soil profile depth, commonly assumed to be 1-1.5 m as the root-zone depth based on practitioner experience rather than validated soil-water dynamics. Such assumptions introduce uncertainty and limit the reliability of irrigation scheduling decisions. This study presents a novel framework for estimating soil profile depth to store maximum water by integrating Richards’ equation, geotechnical soil column concepts, and the Soil Conservation Service Curve Number (SCS-CN) technique to derive an optimal soil profile depth that maximizes storage capacity based on measurable hydraulic and retention soil properties. By linking the water storage soil column depth with the SCS-CN parameter, for practical field applications such as irrigation scheduling and planning. The proposed framework improves model reliability and interpretability by replacing fixed-depth assumptions with soil-specific storage behaviour, thereby reducing uncertainty in irrigation water estimation. It enables consistent evaluation of field capacity, average soil moisture content, and maximum storage potential across soil types, leading to improved irrigation efficiency. By emphasizing physically constrained model selection, data-informed parameterization, and transparent decision-making metrics, this work enhances the reliability of hydrologic modeling and supports robust irrigation management under water-scarce conditions.
Keywords: Water storage soil profile depth, Richards’ equation, Irrigation water management, Data-informed parameterization, SCS-Curve Number method.
How to cite: Sharma, D., Mishra, S. K., and Pandey, R. P.: From Empirical Assumptions to Data-Informed Decisions: A Reliable Water Storage Soil Depth Estimation Method, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13831, https://doi.org/10.5194/egusphere-egu26-13831, 2026.
EGU26-16403 | ECS | Posters virtual | VPS23
Assessing the Impact of Digital Elevation Model Selection on Hydrological PredictionsThu, 07 May, 14:57–15:00 (CEST) vPoster spot 1b
Digital elevation models (DEMs) play a fundamental role in hydrological modeling by controlling watershed delineation, stream networks and runoff generation processes. This study assess the impact of global DEM product provided by Shuttle Radar Topography Mission SRTM and the Indian national CartoDEM developed by ISRO-Bhuvan (Indian Space Research Organisation-Bhuvan) on streamflow simulation using the Soil and Water Assessment Tool (SWAT) in the Ong River watershed (4650 sq. km), India. The study area is characterized by forest and cropland. Both DEMs, resampled to 30m resolution, were used as inputs to SWAT, along with meteorological data (IMD), land use/land cover data (Sentinel-2), and soil data (FAO). Streamflow data was sourced from Global Flood Awareness System discharge data (GloFAS). Model calibration (2011-2017) and validation (2018-2020) were performed using SWAT-CUP with the SUFI2 algorithm. Model performance was evaluated using Willmott's index of agreement, Nash-Sutcliffe Efficiency (NSE), R², PBIAS, and RSR. Results showed that both DEMs performed satisfactorily, with CartoDEM exhibiting slightly better performance (higher NSE and R², lower PBIAS and RSR) during both calibration and validation periods. Sensitivity analysis revealed that the runoff curve number was the most sensitive parameter, highlighting the impact of DEM selection on surface runoff simulation. The study concluded that CartoDEM is a preferable choice for hydrological modeling in similar catchments, though further research on stream accuracy and catchment delineation in diverse topographies can be explored.
How to cite: Prashant, P., Kumar Mishra, S., and Kumar Lohani, A.: Assessing the Impact of Digital Elevation Model Selection on Hydrological Predictions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16403, https://doi.org/10.5194/egusphere-egu26-16403, 2026.
EGU26-18007 | ECS | Posters virtual | VPS23
Effects of Flow Depth and Sediment Size on Near Bed Hydraulics and Sediment Mobility in Open Channel FlowThu, 07 May, 15:00–15:03 (CEST) vPoster spot 1b
Accurate prediction of sediment mobility in open channel flows is essential for effective river engineering and sediment management. This study examines the combined influence of flow depth and sediment grain size on near bed hydraulics and sediment mobility using high-resolution Acoustic Doppler Velocimeter (ADV) measurements in a controlled laboratory flume. Experiments were conducted over uniform sand beds with median grain sizes of d₅₀ = 0.321 mm and d₅₀ = 0.81 mm under four different flow depths (12cm, 15cm,18cm,21cm) and a range of flow velocities. Three dimensional velocity components were measured at multiple vertical locations throughout the flow depth, while water surface elevations were continuously monitored. Depth resolved ADV data were used to compute mean streamwise velocity, Reynolds shear stress, friction velocity, and turbulent kinetic energy for each sediment size and flow depth. Sediment mobility was assessed using the Shields parameter, estimated from ADV-derived bed shear stress, and compared with the critical Shields parameter at multiple velocity points for each depth. The results indicate that coarser sediment beds exhibit increased near-bed turbulence intensity and higher friction velocity across all flow depths, while yielding lower Shields parameter values relative to finer sediment beds. Comparisons across the four flow depths reveal that sediment mobility transitions from stable to mobile conditions depending on the combined effects of flow depth, sediment size, and local velocity magnitude. At lower velocities, Shields parameter values remain below the critical threshold, indicating stable bed conditions, whereas higher velocities at the same depth result in Shields values exceeding the critical limit, signifying active sediment motion. Depth wise velocity and turbulence profiles demonstrate that both flow depth and sediment roughness significantly modify near-bed hydraulic structure and bed shear stress distribution. The findings highlight the importance of accounting for depth-dependent flow structure and sediment characteristics when evaluating sediment mobility. This study provides a robust experimental framework for identifying stable and mobile sediment regimes and estimating sediment transport potential using high-resolution ADV measurements without direct sediment transport observations.
How to cite: Banothu, J. and Devi, K.: Effects of Flow Depth and Sediment Size on Near Bed Hydraulics and Sediment Mobility in Open Channel Flow, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18007, https://doi.org/10.5194/egusphere-egu26-18007, 2026.
EGU26-18481 | ECS | Posters virtual | VPS23
Assessing urban surface flood resilience using hydrodynamic modelling under extreme rainfall conditions in urban catchment of NepalThu, 07 May, 15:03–15:06 (CEST) vPoster spot 1b
Urban flooding poses a growing challenge for rapidly urbanizing cities, where climate change–driven increases in extreme rainfall, expanding impervious surfaces, and limited drainage capacity collectively exacerbate the frequency and severity of surface water inundation. In this context, understanding urban surface flood resilience, defined as the capacity of stormwater drainage systems to withstand, convey, and recover from intense rainfall events, remains essential for effective flood risk management and climate adaptation planning. The present study investigates urban surface flood resilience in Janakpur Sub-Metropolitan City, Nepal, a fast-growing urban center increasingly exposed to pluvial flooding. The study develops an integrated modelling framework using a 3-way coupled MIKE+ hydrodynamic model, integrated with intense spatial analysis using GIS, to evaluate the performance of the existing stormwater drainage system under extreme rainfall conditions. The model represents the urban drainage network and surface flow processes using drainage infrastructure data obtained from field surveys, terrain information derived from a high-resolution digital elevation model, and delineated urban catchments. To characterize rainfall extremes, the analysis employs long-term observed hourly rainfall records spanning 25 years to generate design storm events corresponding to multiple return periods. The modelling framework simulates system response for a representative extreme rainfall event and quantifies inundation dynamics across the urban landscape. The results shows that the coupled approach effectively captures critical flood hazard characteristics, including inundation depth, flow velocity, and the depth–velocity product, allowing for the spatial identification of highly vulnerable catchments and drainage bottlenecks. The findings provide actionable insights into the limitations of existing stormwater infrastructure and support the development of targeted adaptation strategies aimed at enhancing urban surface flood and drainage resilience. Overall, the study underscores the value of integrated hydrodynamic modelling for resolving location-specific flood behaviour and strengthening urban flood resilience assessments under evolving climatic and urbanization pressures.
How to cite: Singh, P., Deopa, R., and Mohanty, M. P.: Assessing urban surface flood resilience using hydrodynamic modelling under extreme rainfall conditions in urban catchment of Nepal, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18481, https://doi.org/10.5194/egusphere-egu26-18481, 2026.
EGU26-20031 | ECS | Posters virtual | VPS23
Evaluation of Penman-Monteith estimates of evapotranspiration derived using field-collected stomatal conductance observationsThu, 07 May, 15:06–15:09 (CEST) vPoster spot 1b
Accurate estimation of evapotranspiration (ET) is critical for various applications in hydrology and agricultural water management. However, direct observations of ET, specially its spatial variation, in time-consuming and cumbersome, thus necessitating the need to use of indirect methods for its estimation. In this study, stomatal conductance data is used in conjunction with bio-physical parameters of wheat crops for deriving the spatially varied estimates of ET (ETSC) for different irrigation treatments using the Penman-Monteith equation. For this, five treatments, including drip (DI) and flood (FI) irrigated treatments were used in the study, namely fully irrigated (DI)), 50% MAD (maximum allowable deficit) (DI), 50% MAD (FI), farmer fields replication (FI) and rain-fed treatment.
The ETSC estimates are also compared to the ET estimates derived using a method based on field water balance (ETWB). When compared with the ETWB values, the ETSC estimates compared well particularly for the irrigated treatments. The average root mean square error (RMSE) of ETSC estimates in comparison to ETWB values are 0.11, 0.2, 0.23 and 0.26 mm/day for fully irrigated, 50% MAD (FI), 50% MAD (DI) and farmers field replication treatments, respectively. The corresponding RMSE value (0.47 mm/day) for the rain-fed treatment are found significantly higher than the irrigated treatments indicating the limitation of the approach in high water stress conditions. The differences between ETSC andETWB values also increase significantly during the end-season stage when the wheat crop is close to maturity. Overall, the results demonstrate the robustness of the proposed approach in estimating the spatial variation of ET using the Penman-Monteith method in conjunction with the on-field field stomatal conductance observations.
How to cite: Upreti, H. and Yadav, M.: Evaluation of Penman-Monteith estimates of evapotranspiration derived using field-collected stomatal conductance observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20031, https://doi.org/10.5194/egusphere-egu26-20031, 2026.
EGU26-22153 | Posters virtual | VPS23
Spacing Effect on the Equilibrium Scour and Flow Pattern around Four-Pier group in Different ConfigurationsThu, 07 May, 15:09–15:12 (CEST) vPoster spot 1b
Present-day practices of bridge piers design often employ group arrangements of piers in various configurations to modify flow dynamics and mitigate subsequent scour formation around the piers. These group arrangement configurations may vary in aspects of spacing ratio, number of piers, and orientations to alter the flow-structure interaction, and hence the scour development. Investigating the turbulent flow behaviour around various common group arrangements has been a topic of interest for researchers for a few years now. This study presents an experimental investigation aimed at comparing the equilibrium scour depth caused by various four-pier group arrangements. To assess the impact of spacing, the face-to-face distance between piers (G) was taken to values of D, 2D, and 3D, where D refers to the diameter of the circular pier. The scour patterns reveal that the maximum scour depth occurred when spacing G was equal to D. The equilibrium scour depth decreased with an increase in the pier spacing to 2D and 3D, corresponding to an approximate flow intensity of 0.9. The scour contours exhibit the impact of neighbouring piers and how it differs with an increase in pier spacing. Instantaneous velocity data were collected to derive the flow characteristics in the flow field. Velocity vectors depict the influence of different configurations on the flow pattern. The study provides an insight into the spacing effects on equilibrium scour, which can be useful in the design of pier group arrangements.
How to cite: Sahu, C.: Spacing Effect on the Equilibrium Scour and Flow Pattern around Four-Pier group in Different Configurations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22153, https://doi.org/10.5194/egusphere-egu26-22153, 2026.
