We welcome contributions that e.g. focus on:
- Using field observations across multiple sites or large sample hydrology datasets, to synthesize process-based explanations of hydrological phenomena
- Connections between residence time and catchment response time
- Theoretical explanations of hydrological phenomena across multiple places or scales, for example, what is the link of event recession timescales to seasonal streamflow patterns?
- Connections among hydrological signatures at different time scales, e.g. connection of the streamflow seasonality to the long term mean flow
- New approaches to use modelling tools to make process and pattern interpretations
- New methods to identify hydrological patterns in data
Sollicited speaker: Shaozhen Liu
Hydrologic processes can be notoriously place-specific and much of our understanding about these processes originates from intensively monitored but small research basins. This project is motivated by a need to connect this small-scale hydrologic process understanding with large-scale model applications, to strengthen the theoretical underpinnings of the models used for water resources planning and prediction of water-related risks across large geographical domains. Here we describe a community-driven synthesis effort that convened multiple virtual workshops, in-person community engagements, and online interactions that bring together water science experts working in various regions across North America. The community expertise was used to develop a hierarchical division of the North American continent into distinct hydrologic domains and provinces, and to describe the dominant hydrologic processes of each landscape.
At the highest level, we recognize five distinct domains: (1) the east, characterized by complex surface-groundwater interaction; (2) the west, with complex topography and resulting climate patterns as a dominant feature; (3) the central domain covering the prairies and plains across landscapes with extensive agriculture; (4) the north, primarily characterized by complex cold-region processes; and (5) the tropical islands, where large gradients in hydrologic drivers occur over relatively short distances. At the second level, we divided the domains into 35 hydrologic provinces. We then developed perceptual models of the hydrologic behaviour of each province using a combination of expert knowledge, literature reviews and data-based quantification of hydrologically relevant landscape characteristics. We envision further development of a third level in the classification that includes progressively more local detail. In parallel, the current perceptual models can be mapped onto computational models, modules and individual equations to support a theory-based large-domain effort to develop appropriate hydrologic models for any location in the wider North American continent. The procedures used in this work are general and could be applied to any geographical domain where expert knowledge of local conditions is available.
How to cite: Knoben, W., McMillan, H., Fan, Y., Wagener, P., Garousi-Nejad, I., Masterman, J., Read, J., Carney, S., van Werkhoven, K., and Clark, M.: Hydrologic Process Synthesis across Diverse Landscapes: Towards a hierarchical classification of North American hydrology, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5729, https://doi.org/10.5194/egusphere-egu26-5729, 2026.
Topography fundamentally regulates how ecosystems access and redistribute water and energy, thereby shaping spatial patterns of vegetation productivity, soil carbon, and nutrient dynamics. Despite its recognized importance, the influence of topography on the spatial heterogeneity of coupled water and carbon processes remains poorly quantified. This is largely because real landscapes confound terrain effects with variability in climate, soil, and vegetation, and because many existing models treat ecohydrological and biogeochemical processes in a decoupled manner. Here, we isolate and quantify the role of terrain complexity by combining synthetic landscapes of varying geomorphic complexity – generated using a landscape evolution model – with meteorological forcings and land cover data from six FLUXNET sites spanning diverse biomes. Using the state-of-the-art, spatially distributed, ecohydrological model T&C-BG-2D, we simulate the distributions of evapotranspiration (ET), gross primary productivity (GPP), and soil organic carbon (SOC) across these landscapes. We find that, on average, ET and GPP decrease as terrain becomes more complex, reflecting enhanced hydrological redistribution and energy limitation. In contrast, SOC exhibits two contrasting response modes that depend on soil texture and hydroclimatic regime, highlighting the interactions between topography-driven processes and local biogeochemical controls. The spatial distributions of ET, GPP, and SOC are well described by lognormal and mixture-lognormal forms, whose shape parameters scale systematically with catchment-scale terrain complexity. An independent analysis of satellite-derived GPP and ET across three different biomes confirms that similar scaling relationships emerge in real landscapes, demonstrating that topography imposes a consistent and measurable constraint on ecohydrological variability. Together, these results provide a physically based framework linking terrain complexity to the spatial organization of coupled water and carbon processes, and offer quantitative guidance for the development of topography-aware parameterizations in large-scale land surface and Earth system models.
How to cite: Bonetti, S. and Lian, T.: Topographic controls on water and carbon cycling: Insights from mechanistic modelling in synthetic landscapes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5402, https://doi.org/10.5194/egusphere-egu26-5402, 2026.
Time-variance in catchment hydrologic function—how rainfall-runoff relationships shift across events, seasons, and years—remains a fundamental yet incompletely understood aspect of catchment behavior. Synthesizing this time-variance across scales is essential for advancing hydrological theory, improving predictions in ungauged basins, and guiding model development. Here, I present a synthesis of recent work spanning local to continental to global scales, integrating fine-resolution mechanistic models with large-sample data-driven methods.
At the local scale, process-based modeling reveals how subsurface physical structure—including subsurface lateral permeability pattern—mediates the climate-induced time-varying partitioning of water between long-term storage, shallow and deep flow paths, and evapotranspiration. At continental to global scales, large-sample analyses across more than five thousand gauged catchments and 80,000 ungauged catchments expose systematic patterns in functional complexity (or time-variance): most catchments exhibit strongly time-varying rainfall-runoff behavior, with climate (particularly rainfall persistence and aridity) providing the dominant control, while geology and topography modulate outcomes locally.
To enable these syntheses, we developed new data-driven methodologies for extracting catchment hydrologic function and quantifying its temporal variation from observational records. These methods provide a transferable framework for diagnosing functional behavior in gauged systems. These findings advance process-based explanations of hydrological phenomena across places and scales, connect event-scale dynamics to seasonal and long-term patterns, and offer new tools for identifying hydrological signatures in data. The implications extend to model structure selection, monitoring network design, and the development of a unifying hydrological theory that accommodates—rather than assumes away—functional time-variance.
How to cite: Ameli, A.: Synthesizing Time-Variance in Catchment Hydrologic Function: Patterns, Controls, Methodological Advances and Global Extrapolation to Ungauged Basins, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8753, https://doi.org/10.5194/egusphere-egu26-8753, 2026.
Potential evaporation is central to hydrology, ecohydrology, and drought/climate-impact studies, yet “potential evaporation / evaporative demand” remains fragmented across definitions, implementations, and complementary relationship (CR) formulations. This fragmentation complicates intercomparison, obscures physical interpretation, and can lead to conflicting conclusions even when analyses use the same underlying data. Here I present a synthesis framework that unifies CR curve families and clarifies which aspects of inferred behavior arise from definitional choices versus land–atmosphere adjustment physics.
I recast CR theory in a nondimensional phase space defined by x ≡ Ep0/Epaand y ≡ E/Epa, where E is actual evaporation, Epa is “apparent potential” evaporation diagnosed from the drying environment, and Ep0 is a wet-environment benchmark. In this atlas, physically admissible behavior occupies a constrained region and diverse CR formulations become directly comparable. Remaining differences among curve families can be summarized with a small set of geometric descriptors (e.g., wet-limit slope, dry-end location, and curvature), enabling a compact “fingerprint” of CR behavior.
To prevent definitional artifacts from masquerading as physical inference, I introduce definition-consistency tests that isolate the impact of the wet benchmark choice on the x-axis mapping. I show that inconsistent wet-benchmark definitions can primarily induce horizontal remapping in x, biasing inferred asymmetry/curvature and thereby altering conclusions about coupling regimes. To interpret geometry physically, I connect atlas descriptors to a minimal coupled mixed-layer model that links curve shape to a small set of drivers controlling land–atmosphere feedback strength and adjustment timescales (e.g., ventilation and boundary-layer mixing).
Finally, I demonstrate the framework using eddy-covariance evaporation and meteorological time series from NEON sites, showing how inter-site differences emerge largely through differences in the distribution of x and in the curvature of the median y(x) response. The atlas provides a transparent pathway to compare, interpret, and select potential evaporation metrics for ecohydrological and hydroclimatic applications, while reconciling apparently divergent results across the CR literature.
How to cite: Pettijohn, J.: A nondimensional atlas for potential evaporation and the Bouchet–Morton complementary relationship: separating definition choices from land–atmosphere adjustment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2831, https://doi.org/10.5194/egusphere-egu26-2831, 2026.
Water years have been used by water resource managers for more than a century to align hydrological phenomena with the annual precipitation cycle. The central idea is to start a new water year when specific hydrological conditions are met, so that precipitation carry-over from the preceding 12-months period is minimised. With the increase in global hydrological data and analysis, it is vital to understand first how to best determine the start of water years across the globe and to understand their effect on evaluating interannual changes.
The only global analysis of the water year to date defines its start by the month of lowest stream discharge. While this definition works well in seasonal climates, it neglects snow dynamics, as the snowfall does not immediately contribute to discharge. In snow-dominated catchments, the lowest discharge often occurs just before the spring melt; consequently, precipitation from the previous water year significantly influences the discharge in the following water year.
We present a new definition to be used in the global water year estimations. It utilizes the areal mean of snow water equivalent collected in upstream catchments and discharge of the target catchment to determine the starting month. This definition mirrors the dynamics of terrestrial water storage and aligns more closely with various national definitions. Applying this methodology across ERA5 Land variables and a combination of MSWEP, GLEAM, GRADES, and SWEML datasets, reveals significant differences in trends and coefficients of variation for annual hydrological fluxes when compared to the standard calendar year. Additionally, our snow-and-discharge-based definition minimizes water balance closure errors. Given these findings, we suggest that global interannual hydrological analysis should, at minimum, consider water years for a physically sound assessment.
How to cite: Kunadi, A., Kallio, M., and Kummu, M.: A Water Year Definition that Works Everywhere , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9586, https://doi.org/10.5194/egusphere-egu26-9586, 2026.
The body of research on large wood (LW) dynamics in rivers has been gaining momentum in line with the increasing recognition of the multifaceted morphological and ecological roles that wood exerts on fluvial systems. Although processes constituting LW dynamics (e.g., recruitment, mobility, storage, and export) have been extensively explored at the reach scale, understanding remains scarce at the catchment scale, which requires a systematic, landscape-level approach to identifying broader risks and developing targeted action plans. This contribution synthesizes a three-decade scholarly corpus and presents a nuanced meta-analysis on catchment-scale LW dynamics across different geographical and climatic regions. The final database encompasses 248 distinct catchments globally, classified according to the specific LW process documented and indexed with a common parameter for each process: recruitment per channel area (m3 ha-1) for recruitment, stability index– equal to wood length to channel width ratio (m m-1)– for mobility, LW load (m3 ha-1) for storage, and unit LW export rate (m3 ha-1 a-1) for export. Regression modelling was rigorously employed, with the aforementioned LW parameters from the four processes as response variables. Meanwhile, predictor variables were systematically chosen to represent the effect of catchment characteristics and hydrological forcing on the LW parameters, thereby adopting a large-sample hydrology perspective across diverse environmental settings. Quantitative results from the regression analyses suggest that drainage area, mean catchment slope, mean annual precipitation, and percentage forested area are statistically significant predictors of LW parameters across the studied LW processes. For the recruitment phase, higher mean annual precipitation and steeper slope are generally associated with greater LW recruitment. In terms of mobility, an increase in drainage area corresponds to a decrease in the stability index, suggesting lower LW stability in larger catchments. LW storage patterns show that higher mean annual precipitation is linked to a greater LW load, while smaller catchments generally exhibit lower stored LW volumes. Finally, the unit LW export rate is significantly influenced by the percentage forested area and slope within each catchment, with both higher percentages of forestation and steeper slopes leading to greater LW export per unit drainage area. These results highlight the extent to which catchment-scale characteristics affect LW processes in a way that studies conducted at the reach scale could easily overlook. This meta-analysis also represents the first systematic attempt to quantify catchment-scale variability in LW parameters at a global level, a dimension that previous reviews have not explored. Finally, the analyses suggest that a disproportionate number of studies on LW dynamics are concentrated on catchments in temperate and continental climatic regions. This highlights a profound need for more studies on LW patterns in underrepresented areas, including tropical catchments in the Southern Hemisphere and the boreal and Arctic rivers in high latitudes– all of which are increasingly altered and subjected to anthropogenic pressures as well as climate change ramifications.
How to cite: Casasola, H., Ravazzolo, D., Persi, E., Petaccia, G., and Sibilla, S.: A global large-sample synthesis of large wood (LW) dynamics based on catchment descriptors and hydrological drivers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-418, https://doi.org/10.5194/egusphere-egu26-418, 2026.
Understanding the complexity of hydrological systems is still a major challenge in the field of hydrology, despite advances in observations, large-sample datasets and analytical methods. Improving this understanding is important for addressing water-related challenges, including hydrological extremes such as floods and droughts.
In this study we use more than 7000 catchments in Europe from the EStreams dataset (Nascimento et al., 2024) to identify hydrologically similar catchments and to assess their relative climate and landscape controls. Across the wide spatial and temporal gradients of the study catchments, 10 hydrological response types (HRTs) could be identified using 40 hydrological streamflow signatures.
The dominant controls of hydrological streamflow behaviour across the HRTs were identified using 84 climate- and landscape attributes with a Random Forest classification model. Climate emerges as the primary control of hydrological streamflow behaviour at the continental scale. However, in 4 out of 10 HRTs, landscape was found to be at least as strong, or even stronger, a control on the hydrological streamflow response.
To further identify the climatic and landscape controls on a regional scale, the hydrological variability was analysed within the HRTs and across several major river basins by identifying subgroups within these hydrological and spatial groupings based on the 40 hydrological signatures. Using the same climate and landscape attributes, the drivers of hydrological streamflow behaviour were assessed for these subgroups. The results further support that climate and landscape jointly shape the hydrological streamflow behaviour.
Overall, this analysis shows that European streamflow behaviour can be classified into a limited number of hydrological response types using streamflow signatures alone. While climate is the dominant control at the continental scale, landscape exerts considerable influence and often becomes equally strong or a stronger control at regional scales. These findings highlight the need to understand climate and landscape as joint drivers within a co-evolutionary perspective to advance our understanding of hydrological systems.
The presentation will be based on Rudlang et al. (2025) as well as new analysis.
References
do Nascimento, T. V. M., Rudlang, J., Höge, M., van der Ent, R., Chappon, M., Seibert, J., Hrachowitz, M., & Fenicia, F. (2024). EStreams: An integrated dataset and catalogue of streamflow, hydro-climatic and landscape variables for Europe. Scientific Data, 11(1), 879. https://doi.org/10.1038/s41597-024-03706-1
Rudlang, J. M., do Nascimento, T. V. M., van der Ent, R., Fenicia, F., and Hrachowitz, M.: Climate and landscape jointly control Europe's hydrology, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-6372, 2025.
How to cite: Rudlang, J. M., do Nascimento, T. V. M., van der Ent, R., Fenicia, F., and Hrachowitz, M.: The spatially variable relative influences of climate and landscape on European streamflow behaviour , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12170, https://doi.org/10.5194/egusphere-egu26-12170, 2026.
Synoptic baseflow campaigns use spatially distributed snapshot measurements of discharge and streamwater chemistry to characterize spatial and temporal patterns of baseflow generation across river networks. Despite growing insights from individual studies, transferring process understanding across catchments remains limited by the lack of a comprehensive synthesis. Here, we present a global meta-analysis of synoptic baseflow campaign applications that examine streamflow sources, scaling, and groundwater flow paths. We identified 52 peer-reviewed studies focusing on 71 catchments worldwide. For each catchment, we assessed monitoring approaches and study objectives. We evaluated outcome metrics including Representative Elementary Area (REA) thresholds, baseflow source identification, and the main drivers of groundwater flow paths. Our synthesis shows that synoptic baseflow campaigns have mainly been applied in temperate regions and in small (< 10 km²) to medium-sized (< 100 km²) catchments, with limited representation of arid, tropical, and high-latitude environments. REA analyses from synoptic baseflow campaigns revealed scale-dependent behavior consistent with the fractal organization of hydrological processes, in which the REA, ranging from 0.5 to 75 km², increases with catchment area (ρ = 0.78, p-value = 0.003) and is driven by the aridity index for catchments larger than 20 km² (ρ = −0.90, p-value = 0.037). Geology emerged as a key driver of regional groundwater flow paths, where permeability controls deep groundwater contributions, highlighting the importance of explicitly accounting for geology in hydrological models. Synoptic campaigns are an efficient alternative for investigating hydrological processes in data-scarce regions, supporting the design of long-term monitoring networks, and helping transfer process understanding to ungauged catchments.
How to cite: Innocente dos Santos, C., Glaser, C., Klaus, J., and Chaffe, P. L. B.: From synoptic baseflow campaigns to hydrological processes understanding: a meta-analysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10592, https://doi.org/10.5194/egusphere-egu26-10592, 2026.
Forested catchments represent major hydrological hotspots worldwide, supplying a large proportion of global freshwater resources while delivering the highest water quality among land-cover types and a wide range of water-related ecosystem services. Understanding the controls on runoff processes in forested catchments is therefore essential for land, water, and forest management. Despite nearly a century of experimental and modelling research on the hydrological functioning of forested catchments, existing knowledge is largely derived from individual sites or limited intercomparison studies, and a coherent global synthesis of runoff processes has been lacking.
Here, I compiled a global database comprising data of 691 forested catchments extracted from 267 peer-reviewed studies published between 1993 and 2024. I used this new and extensive dataset to identify and synthesize the dominant climatic, hydrological, pedological, vegetational, and geological/geomorphological controls on runoff generation, streamflow response, and streamflow prediction. I tested seven classic hypotheses in forest hydrology at the global scale, alongside an original one addressing the dominance of climate as an overarching control and its variability across humid and less humid regions.
The synthesis reveals that threshold behaviors are widespread across forested catchments globally, with soil moisture—often interacting with rainfall—emerging as the dominant driver of nonlinear runoff responses. Tracer-based studies confirm that pre-event water dominates streamflow generation, with groundwater constituting the largest fraction of this contribution, while soil water plays a secondary role. Subsurface flow, often involving preferential flow through macropores and soil pipes, is identified as the most frequent runoff mechanism. Contrary to conventional assumptions, overland flow is not rare in forested catchments: infiltration-excess overland flow, typically associated with arid and/or scarcely vegetated environments, occurs in many of the documented studies, particularly in catchments with low mean annual precipitation and with strong pedological control.
The analysis further shows that hillslope–stream hydrological connectivity is more strongly governed by topographic and vegetation patterns than by climate alone, highlighting the importance of landscape structure in forested environments. Streamflow response magnitude is primarily controlled by geomorphological characteristics and antecedent wetness conditions, in addition to meteorological forcing. Streamflow modelling performance is influenced by a broad combination of controls, with topography and geology exerting slightly stronger effects than soil, vegetation, or climate, reflecting both landscape dominance and model structural assumptions.
Overall, the results reveal the interaction of multiple factors on runoff processes in forested catchments across the planet, highlighting the larger role played by geological/geomorphological, pedological, and hydrological factors in certain processes compared to climate, while the relative importance of vegetation increases under humid conditions. This global synthesis provides new process-based insights, revises long-standing theories, and offers an empirical foundation for advancing our understanding of catchment functioning and improving hydrological modelling in forested catchments worldwide.
How to cite: Penna, D.: Controls on runoff processes in forested catchments: a global synthesis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11133, https://doi.org/10.5194/egusphere-egu26-11133, 2026.
Land cover affects the runoff response of catchments. However, such land-cover effects remain difficult to decipher because experimental studies reveal site-specific effects, while large-sample analyses are often confounded by other factors, such as climate gradients that obscure the role of land cover. Empirical methods that do not consider differences in antecedent wetness may overestimate runoff responses in forested catchments due to their typically humid climate. We quantify runoff responses to a unit precipitation input and examine how this varies across 252 U.S. catchments with different land covers. For comparable antecedent wetness conditions, peak runoff responses decline as forest cover increases, with peaks in forested catchments being 16-63% lower than those in catchments dominated by cropland or grassland. By accounting for climate-driven differences among sites, our approach isolates the influences of forest cover on reducing peak flows, which is often masked by climate in large-sample analyses.
How to cite: Liu, S., Kirchner, J. W., Slater, L. J., Floriancic, M. G., van Meerveld, I., and Berghuijs, W. R.: Forest impacts on peak runoff revealed by accounting for the effects of climate, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23084, https://doi.org/10.5194/egusphere-egu26-23084, 2026.
Between 2019 and 2024, South Sudan experienced prolonged and widespread flooding that existing early-warning systems did not anticipate, largely because flood forecasting models were conditioned on short-term rainfall variability and did not reflect the basin’s long hydrological memory. This study examines the physical processes underlying this forecasting mismatch and shows how limited representation of upstream storage, wetland dynamics, and multi-season antecedent conditions constrained the skill of anticipatory flood information. Using daily lake levels, river discharge, CHIRPS rainfall, and MODIS flood extent, we quantified floodwave travel time from Lake Victoria to the Sudd Wetland to identify the mechanisms shaping this multi-year flood response.
The analysis shows that the mean upstream-to-downstream floodwave transit time is approximately 16.8 months, rather than the often-assumed five months, revealing a fundamentally slow system controlled by lake storage, floodplain buffering, and wetland attenuation. This long delay explains why downstream hydrological signals evolved differently from local rainfall patterns. Flooding in the central and western Sudd was shaped by the gradual movement of stored water through the Victoria–Kyoga–Albert–Sudd corridor, where each lake and wetland unit progressively reshapes and delays the floodwave. In contrast, eastern sub-catchments such as the Baro–Akobo–Sobat responded more directly to local rainfall, reflecting weaker connectivity to the lake–wetland system. The extensive inundation observed in 2022, including around Bentiu, therefore resulted from cumulative multi-year storage initiated by the 2019 positive Indian Ocean Dipole and reinforced by successive anomalous rainy seasons both up- and downstream, rather than from local rainfall downstream alone.
These findings highlight the limitations of flood forecasting modelling approaches that emphasise short-term precipitation forcing while under-representing storage, routing, and long hydrological memory in large lake–river systems. By identifying system-scale transit times and the spatial structure of storage-driven response, this work provides a physical basis for improving the interpretation of flood forecasts and for extending effective lead times for anticipatory action. Explicit recognition of long-memory dynamics can help distinguish precipitation-driven from storage-driven flooding, supporting more timely and proportionate preparedness decisions along the White Nile corridor.
How to cite: Mulangwa, D., Naturinda, E., Koboji, C., Zaake, B., Black, E., Cloke, H., and Stephens, E.: Why did South Sudan experience unprecedented flooding in 2022? The role of upstream storage and hydrological memory in the White Nile., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8825, https://doi.org/10.5194/egusphere-egu26-8825, 2026.
Understanding how dominant hydrological processes vary across hydroclimatic gradients remains a central challenge in hydrology, particularly because model structures embed assumptions about which processes matter and how they interact, limiting transferability beyond individual catchments. Intensively instrumented research basins provide a unique opportunity to link long-term observations, hydrologic signatures, and model behaviour in a controlled yet climatically diverse setting. Here, we report progress on a comparative analysis of a broad set of intensively monitored research basins that represent considerable hydroclimatic diversity, including arid, semi-arid, temperate rainforest, humid continental, snow-dominated, and humid subtropical environments. These basins are characterized by long-term records of discharge, snow, soil moisture, groundwater, and surface–atmosphere fluxes, as well as open data policies that facilitate inter-comparison.
For each basin, we combine a synthesis of existing process understanding from the literature with a data-driven analysis of long-term observations and a benchmark modelling experiment. Hydrologic signatures derived from hydro-meteorological records are used as proxies for dominant processes, enabling characterization of long-term fluxes and storages, including snow dynamics, evapotranspiration patterns, soil and groundwater storage, baseflow, and streamflow behaviour. In parallel, we implement a common set of model structures within the physically-based SUMMA framework, complemented where appropriate by conceptual models (e.g. FUSE). Model setups are harmonized as far as feasible, including meteorological forcing and spatial discretization, to isolate the influence of process representation rather than data availability and model configuration choices. Calibration results are evaluated using multi-state diagnostics and hydrologic signatures.
The anticipated outcomes are (i) an empirical synthesis of how dominant hydrological processes vary across well-instrumented basins, and (ii) evidence of systematic differences (or lack of such differences) in which model structures and process representations are most suitable under contrasting hydro-climatic conditions. These results are a step on the path towards targeted model development and testing within flexible modelling frameworks, supporting more transferable and process-consistent hydrological models.
How to cite: Wagener, P., Knoben, W. J. M., and Clark, M. P.: From Signatures to Structures: Comparing Dominant Hydrologic Processes and Models Across North America, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14035, https://doi.org/10.5194/egusphere-egu26-14035, 2026.
Reliable estimation of river discharge is constrained by uncertainties in stage-discharge rating curves, particularly in steep, high-gradient catchments where channel morphology is highly dynamic. Conventional approaches often fail to capture the complexity of these systems. To synthesize a more robust understanding of Rating Curve generation, this study evaluates three methods, the conventional power law, spline interpolation, and Bayesian inference, across multiple sites within a mountainous headwater catchment.
We use two years of high-frequency stage data and corresponding gauged discharge measurements from a primary field site, with ongoing validation at two additional sites. The methods are compared in terms of different performance metrics (e.g., RMSE, NSE), their ability to extrapolate low and high flow conditions, and their treatment of uncertainty.
Initial results show that the Bayesian approach substantially outperforms deterministic power law and spline methods in simulating discharge time series. Its strength lies in explicitly accounting for measurement error and structural uncertainty, which are pronounced in high-gradient environments. Posterior parameter distributions further provide physically meaningful insights linked to reach characteristics such as roughness and bed slope. Testing across additional sites will enable synthesis of generalized patterns: if consistent Bayesian priors prove effective across geomorphologically similar reaches, this suggests common hydraulic-hydrological controls operating within this catchment type.
This comparative study advances a probabilistic framework for Rating Curve generation in steep river systems. By demonstrating the transferability of Bayesian methods across multiple sites, we highlight a pathway for operational hydrology to move beyond deterministic curve fitting toward more robust, uncertainty-aware, and physically grounded discharge estimation.
How to cite: Saxena, N. and Sen, S.: Advancing Rating Curve Generation in High-Gradient Rivers: Comparing Power Law, Spline, and Bayesian Approaches of Rating Curve Generation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1079, https://doi.org/10.5194/egusphere-egu26-1079, 2026.
Distinct effects of land use and topography on runoff metrics are well established at small scales, yet their identification in large sample studies remains challenging, as they are often masked by other dominant catchment features. Here, we systematically investigated the drivers of runoff response across a rich dataset of catchment properties from 152 Swiss catchments using runoff metrics derived from non-linear Ensemble Rainfall-Runoff Analysis (ERRA).
We show that catchment area exhibits the strongest control on both the timing and magnitude of streamflow response to precipitation. We found that across Switzerland runoff response is not related to catchment slope (neither mean slope nor fraction of steep or flat terrain), even when clustering catchments of similar area. Thus, contrary to widely circulating assumptions, steeper catchments do not exhibit faster or stronger runoff response. We also tested the differences between forest and agriculture dominated catchments and found no statistical differences in timing and magnitude of streamflow response to precipitation when using the entire dataset. Thus, our Swiss wide analysis does not show the expected buffering effect of forests and faster responses in agricultural landscapes. Land use effects only emerged when stratifying catchments by area and assessing the runoff response for different precipitation intensities. In agriculture dominated catchments, we observed higher peak flow with intense precipitation compared to forest dominated catchments. Thus, the buffering effects of streamflow response to precipitation in catchments with different land use are non-linear and dependent on rainfall intensity.
Our results caution against generalized assumptions in large sample hydrology, because effects of topography and land use are strongly modulated and often veiled by other catchment properties or climate and dependent on rainfall intensity.
How to cite: Pulli, R. and Floriancic, M.: Catchment area veils land use and topographic controls on runoff generation in Swiss catchments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1741, https://doi.org/10.5194/egusphere-egu26-1741, 2026.
The choice of unit hydrograph (UH) shape remains a long-standing problem in rainfall–runoff modelling, with widely used forms such as the Gamma, triangular and other hydrographs often adopted without explicit validation. Here we present a calibration-free, moment-based framework to objectively test UH shape assumptions using observed rainfall–runoff events.
Treating time as a random variable and rainfall and runoff as probability weights, we exploit the additivity of central moments under convolution to directly estimate the first three temporal moments of the UH from data. For each event, UH moments are obtained as differences between runoff and rainfall moments, without fitting hydrographs or calibrating model parameters. For two-parameter unit hydrograph shape families, such as the Gamma (Nash) and triangular hydrographs, the first two temporal moments uniquely determine the shape parameters. The third central moment is therefore not a fitting target but an independent prediction, allowing systematic errors from the assumed shape to be identified.
The framework is applied to hourly data from 431 UK catchments from the CAMELS-GB dataset, using the 50 largest events per catchment. Event- and catchment-level diagnostics highlight systematic differences between alternative unit hydrograph shape families, including Gamma and triangular representations. By comparing moment-based consistency across shapes and response time scales, the analysis provides an objective basis for identifying the most appropriate unit hydrograph form for different hydrological conditions.
Overall, the proposed moment-based framework offers a physically interpretable and calibration-free approach for evaluating and comparing unit hydrograph shapes, with clear potential for application in catchment classification and regionalisation.
How to cite: Yin, Y., Rosolem, R., and Woods, R.: A Moment-Based, Calibration-Free Evaluation of Unit Hydrograph Shape Across UK Catchments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7154, https://doi.org/10.5194/egusphere-egu26-7154, 2026.
Understanding long-term hydro-climatic variability is essential for contextualising present and future water stress in semi-arid regions. In the Levant, instrumental observations are short and paleoclimate reconstructions remain spatially coarse, leaving large gaps in knowledge of past drought and flood dynamics. This study explores the potential of historical documentary evidence to reconstruct hydro-meteorological variability across the Levant between 200 and 1850 CE, with a detailed focus on Damascus, one of the best-documented cities in the region.
We compiled and harmonised 3,507 hydrometeorological records extracted from major historical databases and scholarly compilations based on Arabic, Greek, Syriac, and Latin sources. Events were standardised by type, timing, location, and intensity using a common classification scheme, enabling consistent temporal and spatial analyses. Event frequencies were aggregated at decadal resolution to assess documentation density, biases, and long-term variability across the region. While the resulting dataset spans more than 1,600 years and 50 locations, coverage is highly uneven, with a strong concentration in major urban centres after the thirteenth century. Damascus emerges as the only site with sufficiently continuous records to support quantitative analysis.
For Damascus, we analyse long-term precipitation and flood events between 1250 and 1520 CE, the period of highest documentary density. A semi-quantitative dryness index derived from historical descriptions was constructed and compared with the Palmer Drought Severity Index (PDSI) from the Old World Drought Atlas. Both datasets were aggregated into decadal bins, and drought frequencies were statistically evaluated. Results reveal pronounced multi-decadal hydro-climatic fluctuations, including persistent dry phases in the late fourteenth and early fifteenth centuries, punctuated by episodic but severe flood clusters. The documentary-based dryness index shows a moderate and statistically significant correlation with PDSI at the decadal scale, indicating broad coherence between independent historical and tree-ring-based reconstructions.
Seasonal analysis of historical records further highlights the vulnerability of Damascus to precipitation deficits during autumn and winter, the city’s primary rainy seasons. These findings demonstrate that, despite fragmentation and strong spatial biases, historical documents can provide robust, locally grounded indicators of past hydro-climatic variability when systematically harmonised and analysed.
The study also underscores key limitations, including uneven spatial coverage, source availability, and interpretive uncertainty, reinforcing the need for close collaboration between historians and climate scientists. Integrating documentary evidence with paleoclimate proxies offers a valuable pathway for improving reconstructions in data-sparse regions and for linking hydro-climatic variability to societal impacts in the long term.
How to cite: Moussa, R., Merheb, M., Hamelin, G., Lemoine, N., and Cudennec, C.: Hydro-meteorological variability in the Levant (200–1850 CE) reconstructed from historical documentary evidence, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9893, https://doi.org/10.5194/egusphere-egu26-9893, 2026.
Hydrological drought is commonly described using standardized indices derived from observed streamflow. While such indices are useful for monitoring purposes, they often rely on empirical distribution fitting and fixed thresholds, which makes their physical interpretation and transferability across climates and time periods difficult. In particular, it remains unclear how changes in climate forcing or catchment properties are reflected in drought characteristics defined by these indices.
In this study, hydrological drought is examined from a process-based probabilistic perspective, starting from stochastic rainfall–runoff dynamics. Daily rainfall is represented as a marked Poisson process, with storm arrivals occurring at a constant frequency and rainfall depths following an exponential distribution. Infiltration produces random increments of soil moisture, while evapotranspiration leads to continuous moisture losses from the root zone. These losses vary linearly with soil moisture between the wilting point and an upper threshold associated with soil water holding capacity. When this threshold is exceeded, runoff pulses are generated, with their occurrence and magnitudes described by stochastic processes. The resulting runoff feeds a lumped catchment storage, which is drained through the river network according to a nonlinear storage–discharge relationship that reflects the combined contribution of different flow components.
Based on this framework, the stationary probability distribution of streamflow is analytically derived, allowing hydrological drought to be interpreted as a left-tail behavior of the flow distribution rather than as an empirical anomaly. By mapping this theoretical distribution into a standardized probability space, drought conditions can be evaluated in a way that remains comparable with conventional approaches, while keeping an explicit link to physically meaningful parameters. The emphasis of this work is therefore not on defining a new drought index, but on improving the physical understanding of why and how hydrological drought characteristics change under different climatic and catchment conditions.
How to cite: Wang, H.-J.: A Process-Based Probabilistic View on Hydrological Drought Formation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16859, https://doi.org/10.5194/egusphere-egu26-16859, 2026.
Snowmelt-driven streamflow is often highly seasonal and supports ecosystems and human water use. Climate-driven changes in snow accumulation and melt alter the timing and rates of liquid water input to catchments, thereby reshaping seasonal streamflow patterns. However, shifts in streamflow seasonality under climate change (e.g. snow fraction) remain uncertain. Here, we employ directional statistics to quantify streamflow seasonality (i.e., center of mass timing and concentration) and their sensitivity to annual snow fraction for 239 snow-affected CONUS catchments. While the snowfall-fraction sensitivity of streamflow timing and concentration is relatively weak in individual catchments, consistent and distinguishable patterns emerge at the regional scale. We demonstrate and explain an apparently opposite regional response of seasonal streamflow to between-year variations in snowfall fraction. In years with less snowfall, we identify regions of the USA where seasonal streamflow occurs later (Eastern Rockies and Great Plain-western Great Lakes) and where the flow becomes more concentrated in time (Pacific Northwest). These effects are precisely the opposite of the expected behaviour (observed in other snow-affected parts of the USA), which would be that less snowfall leads to earlier and less concentrated seasonal streamflow. The climate context, particularly precipitation seasonality, provides a mechanistic explanation for these unexpected behaviours. Further, trends from 1980 to 2022 show that changes in streamflow seasonality do not always match the expected effects of declining snow. Our results imply that climate change will not affect snow-affected water resources in the same way everywhere. Water managers in snow-affected regions will need to adapt their strategies to local climate conditions, taking into account not only changes in snow but also shifts in precipitation.
How to cite: Wang, Z., Berghuijs, W., Howden, N., and Woods, R.: Diverse yet Surprisingly Weak Influence of Snow-Fraction Changes on Regional Streamflow Seasonality Shifts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20328, https://doi.org/10.5194/egusphere-egu26-20328, 2026.
The hydrology of snow-influenced catchments is characterized by streamflow seasonality resulting from snow and ice accumulation and melt effects. Given how strongly these processes are connected to topography, it is tempting to think that the main streamflow characteristics can be inferred from topography and information on the statistical properties of precipitation and air temperature alone. In this study, we analyze streamflow distributions, interannual and interseasonal water carry-over, and precipitation properties from the CAMELS-CH data set to synthesize the dominant controls on streamflow variability in high-alpine catchments. A key focus is on understanding the interplay between water input (as modulated by air temperature) and groundwater (derived from baseflow analysis) to understand the seasonal streamflow cycle. Ultimately, the proposed analysis should provide a framework to synthesize high-alpine catchment behavior and to assess their sensitivity to climatic variability and change.
How to cite: Müller, T. and Schaefli, B.: From snowfall to streamflow: synthesizing the hydrology of high alpine catchments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23227, https://doi.org/10.5194/egusphere-egu26-23227, 2026.
