The new technique, called the Robust Variance-based Event Identification Method, or RVEIM, was developed by Mohammad Masoud Mohammadpour Khoie, Danlu Guo, and Conrad Wasko and published in the journal Hydrology and Earth System Sciences. Its central insight is that a runoff event is best detected not by hunting for peaks in the streamflow record, but by watching for sudden surges in the variance of that record. When streamflow variance briefly and clearly exceeds what is normal for a catchment, the stream is doing something unusual, and that something is almost always a response to rain. By anchoring event detection to this statistical signature of physical process, RVEIM needs only two user-defined parameters, a dramatic reduction from the half-dozen or more that conventional methods demand.

The problem RVEIM addresses is one that has quietly undermined event-based hydrology for years. Because no instrument directly measures where a runoff event begins or ends, researchers must rely on rules: a threshold to filter out trivial flows, a minimum spacing to keep consecutive events independent, a search window to match each flood peak with its causative storm. None of these rules has a ground truth to validate against, so their values are chosen by expert judgment or local calibration. Sensitivity analyses have shown that even within accepted ranges, changing these values can alter the number, length, and volume of identified events by amounts comparable to the climatic differences between regions. In one striking example cited by the team, simply reversing the direction of the pairing search, from runoff to rainfall rather than rainfall to runoff, introduced as much variability as differences in climate itself.

Worse, the conventional two-step workflow, detecting runoff events first and pairing them to rainfall afterward, can produce physically impossible results. When a mismatched pair is created, the calculated runoff coefficient, the ratio of runoff volume to rainfall volume, can exceed one, implying that more water left the catchment than fell on it as rain. Such events are clear flags of identification error, yet some methods generate them routinely. RVEIM sidesteps this by detecting and pairing simultaneously: it identifies independent rainfall events first, then searches for the corresponding streamflow response within a window whose length is not fixed by the user but computed from the catchment’s characteristic rainfall-to-runoff lag plus the duration of each individual storm. This time-variant window mirrors the causal chain of runoff generation and allows the method to capture both brief, sharp responses and long, multi-peak events without extra tuning.

The variance threshold at the heart of the method is also derived rather than imposed. The team first applies the widely used Lyne and Hollick digital filter to estimate baseflow, the slow groundwater-fed component of streamflow. They then use a median absolute deviation test to exclude baseflow values inflated by event conditions, and take the variance of the remaining, baseflow-dominated records as the threshold below which streamflow behavior counts as normal. Because this threshold emerges from each catchment’s own data, it transfers across climates without recalibration. In tests across eight representative catchments spanning desert, grassland, temperate, subtropical, tropical, and equatorial zones, the variability of event characteristics under RVEIM stayed within roughly fifteen percent of the mean, while two benchmarking methods, a local maxima approach and the more elaborate Detrending Moving-average Cross-correlation Analysis, exhibited uncertainties of forty-three to ninety-three percent.

Physical plausibility improved as well. Across the representative catchments, the percentage of events with runoff coefficients exceeding one remained below about four percent under RVEIM, and was essentially zero for the DMCA benchmark, whereas the local maxima method produced consistently higher and more variable rates. The differences mattered most in wet catchments such as those in western Tasmania, where frequent storms and high soil moisture make event separation genuinely difficult. There, the three methods diverged sharply in their pictures of catchment behavior: RVEIM attributed far fewer events to near-zero runoff coefficients than its competitors, a result consistent with the hydrological reality of a saturated, fast-responding landscape.

With its robustness established, the team unleashed RVEIM on all 467 unregulated Hydrologic Reference Stations monitored by the Australian Bureau of Meteorology, catchments with at least thirty years of quality streamflow record and minimal human interference. The resulting atlas reveals a continent organized by water. Runoff coefficients climb toward the coasts and reach their highest values in Tasmania, where abundant rainfall, low evapotranspiration, and saturated soils conspire to send most event rainfall straight into streams. In the arid interior, by contrast, most storms vanish into infiltration and evaporation, leaving runoff coefficients clustered near zero. Northern Western Australia presents an intriguing anomaly: despite modest rainfall event volumes, its catchments yield substantial runoff, a consequence of low evapotranspiration and high antecedent soil moisture that leave little room for losses.

The most consequential finding is a systematic climate gradient in the shape of the runoff coefficient distributions. In desert and grassland catchments, the empirical distribution rises steeply at near-zero values, indicating that the vast majority of events produce negligible runoff, a signature pointing to infiltration-excess processes in which rain falls faster than parched soils can absorb it only during intense bursts. In temperate, subtropical, and equatorial regions, the distributions rise gradually toward higher coefficients, the hallmark of saturation-excess runoff from already-wet catchments. Tropical catchments occupy an intermediate, mixed regime. Moving from dry to wet climates, the distributions also become less skewed and more uniform, echoing patterns previously documented in Austria and the European Alps and suggesting the gradient is a global hydrological regularity rather than an Australian curiosity.

The implications reach well beyond academic taxonomy. Flood estimation, infrastructure design, and projections of how catchments will respond to a changing climate all depend on event-scale runoff coefficients, and biased event identification can distort all of them. By capturing the full spectrum of event magnitudes rather than privileging large floods or short responses, RVEIM offers a consistent yardstick for comparing catchments across regions and for tracking how runoff generation shifts as droughts, land-use change, and warming reshape the water cycle. The method has been released as a function in the open-source hydroEvents R package, and its developers argue that because its parameters are unlikely to require adjustment between climates, it should transfer readily to continents beyond Australia. If it does, hydrologists worldwide may finally agree on where one storm ends and the next river begins.

Subject of Research: A parsimonious rainfall-runoff event identification method applied across 467 Australian catchments to characterize event-scale runoff processes

Article Title: Characterising runoff processes for Australia: insights from a parsimonious rainfall-runoff event identification method

Article References: Mohammadpour Khoie, M. M., Guo, D., & Wasko, C. (2026). Characterising runoff processes for Australia: insights from a parsimonious rainfall-runoff event identification method. Hydrology and Earth System Sciences, 30(18), 5947-5970. https://doi.org/10.5194/hess-30-5947-2026

Image Credits: AI Generated

DOI: 10.5194/hess-30-5947-2026

Keywords: hydrology, rainfall-runoff, runoff coefficient, event identification, catchment response, Australia, baseflow separation, flood estimation, climate gradient, streamflow, RVEIM, large-sample hydrology

The study, led by Roel Dijksma and colleagues at Wageningen’s Hydrology and Environmental Hydraulics group, took advantage of a rare natural experiment. Since 2009, the university’s Master course in Catchment and Climate Hydrology has culminated in an intensive eight-day excursion across Iceland, where students learn to read complex, largely undisturbed landscapes and reconcile what they see with the simplified hydrological models they have built in class. When pandemic restrictions halted all outdoor teaching in 2020 and 2021, a professional video team produced a virtual version of the excursion, filmed on location with the teaching staff. The cohorts of 2020 and 2021, some 105 students in total, completed the course using only this digital material.

Then came the twist. In April 2022, once restrictions lifted, the university offered an additional voluntary excursion to Iceland for those same students. Roughly half, 54 of the 105, were able to join. That created three distinct groups within a single student population: those who had only attended the real excursion, those who had only studied the virtual version, and those who first worked through the virtual materials and later stood on Icelandic soil themselves. The researchers seized the opportunity to send a detailed questionnaire to excursion participants spanning every cohort from 2011 to 2025, asking how the experience had shaped their careers, their scientific thinking, and their views on virtual versus real fieldwork.

The response was striking. Of 134 questionnaires sent to a randomly selected 20 percent of the 676 total participants, 104 were completed, a response rate of 78 percent. Respondents ranged from current Master students to senior scientists with more than fifteen years of professional experience. More than half strongly agreed that planning and fieldwork remain an important part of their current job or study, and the average response across all respondents was moderately agree. Even among the most senior alumni, whose careers have drifted toward modelling and management, the excursion’s contribution to their scientific development was still clearly recognized, though its perceived intensity softened slightly with the passing years.

The starkest contrasts emerged when the virtual-only cohort was compared with everyone who had physically travelled to Iceland. Students who had only studied the video materials were neutral about whether the modelling concepts discussed during the excursion echoed into their later work, while their peers who had made the journey were clearly positive. On the contribution to understanding undisturbed hydrological systems and to overall scientific development, the virtual-only group scored substantially lower, falling to the slightly-to-moderately-agree range, whereas the field participants were strongly to fully in agreement. When asked to distribute ten points between the virtual and the real excursion, the students who had experienced both allocated 8.9 points to the real trip and just 1.1 to its digital counterpart.

Why does the difference run so deep? The students themselves pointed to several factors that a camera, however professional, cannot replicate. They missed the active, location-based learning in a landscape of undisturbed catchments, the direct and inspirational interaction with teaching staff, and the chance to bond with peers into a professional network that lasts well beyond graduation. One participant captured the sentiment in a reflection quoted in the paper: you can learn a lot in a classroom, but an excursion makes you remember. Another described the trip as capturing the very essence of studying, being curious, feeling passionate, and loving the process of learning. The virtual-only group also remained neutral on whether a trip to a more heavily managed area closer to home could substitute for Iceland, while the field participants firmly disagreed, suggesting that the visceral experience of an unmanaged landscape shaped their judgment in ways the video never could.

The choice of Iceland is no accident, and the paper devotes considerable attention to why the island is such a powerful teaching environment. Straddling the Mid-Atlantic Ridge and fed by a mantle plume, Iceland is the only place on Earth where an oceanic ridge rises above sea level thanks to a hotspot, producing young mafic rocks roughly 20 million years old with strikingly different hydraulic properties from older formations. The Gulf Stream warms the southwest while cold Arctic air dominates the north, and the mountains and ice caps boost precipitation by about 40 percent, generating a rainfall gradient from under 400 millimetres per year in the dry northeast to more than 4,000 on some glaciers, and locally even above 7,000. The result is a compact natural laboratory of groundwater-fed rivers, direct runoff rivers and glacier-fed streams, braided and meandering channels, and catchments that remain relatively free of human management.

Climate change is written into that landscape in real time. Glaciers cover about 11 percent of the country, and all of them face strong net ablation, so the share of glacier meltwater in river discharge is rising, with rivers below the large ice caps carrying visibly more meltwater than before, while streams fed by small glaciers are losing their summer melt signal altogether. For students trained to conceptualize precipitation-runoff relationships, flow generation processes, drought propagation and flood forecasting, seeing these processes unfold across such contrasting settings, and then confronting how crudely their computer models represent them, appears to leave a lasting imprint. The survey found that all respondents, regardless of cohort, strongly agreed that the excursion deepened their grasp of undisturbed hydrological systems.

The findings come with honest caveats. The authors, all of whom teach on the excursion, acknowledge their own attachment to the course and took steps to limit bias by keeping the survey anonymous and examining the results from multiple angles. Response rates for the pandemic cohorts were lower than hoped, with only 40 percent of contacted students completing the questionnaire, and some declined because the memory of that stressful period remained too raw. One participant noted that although grateful for the effort behind the virtual excursion, the combination with lockdown was devastating. The authors also note that opinions on flying may have shifted over the years, though the survey showed no trend across cohorts. Still, 74 percent of respondents considered it acceptable to fly to Iceland for the excursion, only 13 percent disagreed, and the researchers argue that careful, selective travel for transformative field learning remains defensible.

The overall conclusion is measured but firm. Virtual excursions, especially as production quality improves and tools like animations and artificial intelligence mature, can be a valuable addition to the teaching toolbox, useful for preparation, revision, or reaching students who cannot travel. But as a replacement for the real thing, they fall short. The students who lived through both versions are unambiguous: the field trip fostered relatedness with peers and teachers, boosted intrinsic motivation across the whole course, and delivered learning that no classroom or screen could match. As the paper’s closing sentiment from a participant suggests, the essence of geoscience education still lies in standing before a river, feeling the wind off an ice cap, and working out for yourself how the water got there.

Subject of Research: Comparing the perceived educational impact of real versus virtual hydrology field excursions among Master students

Article Title: Field or virtual? Perceived impact of academic excursions through the eyes of (future) hydrologists

Article References: Dijksma, R., Teuling, A. J., Melsen, L. A., Bense, V. F., & van der Ploeg, M. J. (2026). Field or virtual? Perceived impact of academic excursions through the eyes of (future) hydrologists. Geoscience Communication, 9(4), 437-450. https://doi.org/10.5194/gc-9-437-2026

Image Credits: AI Generated

DOI: 10.5194/gc-9-437-2026

Keywords: hydrology education, field excursions, virtual field trips, Iceland, Wageningen University, geoscience communication, COVID-19, catchment hydrology, climate change, student survey, fieldwork, scientific development

The review, led by Muhammad Shareef Shazil of the University of Campania Luigi Vanvitelli together with Thom Bogaard of Delft University of Technology and Roberto Greco of the University of Campania, analyzed 235 studies drawn from an initial pool of 470 records in the Scopus database. The authors found that previous major reviews, including landmark syntheses from 1988 and 2002 and more recent assessments, have concentrated overwhelmingly on the geomorphological factors of dam formation and failure. Yet the processes that actually kill these dams, overtopping, seepage-induced piping and slope failure, are all activated by water. Rainfall, snowmelt and glacier melt control how fast a dammed lake fills, how much pressure builds against the dam body, and how quickly internal erosion channels can carve their way through loose material.

The stakes are far from academic. The historical record contains chilling examples. In 1786, the catastrophic failure of a landslide dam on the Dadu River in China sent a flood wave roughly 1,400 kilometers downstream and killed an estimated 100,000 people. More recently, the 2010 Attabad landslide in northern Pakistan blocked the Hunza River, killed 20 people and submerged several villages under a growing lake. Classic analyses reported that about half of all landslide dams fail within ten days of formation, and inventories compiled in recent years show that roughly 7 percent collapse within a single day, about 11 percent within a month, while just over 20 percent survive longer than 20 years. But longevity is notoriously hard to predict: the Kummer dammed lake in South Tyrol, Italy, held for 370 years before it failed, destroying parts of the city of Merano.

The failure mechanisms themselves are well documented. Overtopping, in which rising lake water spills over the dam crest and erodes the downstream face, accounts for more than 90 percent of recorded failures. Piping occurs when water infiltrating through the porous dam body enlarges internal channels until the structure collapses, a process especially dangerous in fine-grained dams. Slope failure arises when rapid water level changes alter pore pressures within the dam, triggering sliding along internal failure surfaces. What these mechanisms share is a hydrological trigger: each one is set in motion by high water levels, extreme inflows, or sudden shifts in the water balance of the upstream catchment. A dam’s geometry and material composition matter, but without knowing how much water arrives, and when, the probability of failure remains deeply uncertain.

To illustrate the danger of ignoring hydrology, the review points to the Ram Creek landslide dam in New Zealand. Geomorphic indices, empirical formulas built from dam volume, catchment area and valley geometry, had classified the dam as stable. It failed after just a few hours of intense rain. Such indices, from early volume-to-catchment ratios proposed in the 1980s to the widely used dimensionless geomorphic index combining dam height, volume and catchment area, remain valuable first-order screening tools. But they are static. They cannot capture the dynamic, seasonal and extreme hydrological forcing that so often flips a dam from stable to unstable. The review notes one partial exception: the Hydromorphic Dam Stability Index, which integrates discharge and fluid density, represents one of the first attempts to bridge geomorphology and hydrology in stability assessment.

Geotechnical research has added its own layer of insight. Particle size distribution has emerged as a key control on dam behavior: dams built from coarse, blocky rock-avalanche debris tend to be highly permeable, allowing rapid seepage that can actually reduce overtopping risk, while dams of unconsolidated fine material are far less stable. Heterogeneous deposits containing weak layers of contrasting permeability are particularly prone to internal erosion. Newer quantitative tools, including the Material-based Morphological Index, the Dam Composition Index and a dimensionless parameter describing material distribution, attempt to fold these material properties into stability predictions. Discrete element simulations have shown that longer sliding paths, higher base friction and gentler valley slopes increase the internal heterogeneity of dam deposits. Yet even these sophisticated indices suffer from a chronic shortage of material data from real, heterogeneous natural dams.

The heart of the review is its argument that upstream catchment hydrology deserves equal billing. Inflow from rainfall, snowmelt, glacier melt and groundwater directly controls how quickly the lake fills and how much load presses on the dam. Evidence for this link comes from multiple directions. Discriminant and logistic regression analyses of Japanese landslide dams identified historical peak flow as a critical stability factor. In Italy, a potentially unstable dam survived a period of high river flows only because a pre-existing hydropower bypass diverted 80 percent of the peak discharge. Bayesian lifetime analysis showed that catchment area, together with dam shape, controls dam longevity, and machine learning studies have recently confirmed the importance of hydrological factors. In the Karakoram, the Attabad dam, initially judged highly vulnerable because of its size and enormous catchment, has now stood for more than 16 years, aided by an excavated spillway and by a hydrological regime in which precipitation falls mainly as snow and meltwater is released gradually, damping discharge peaks and limiting overtopping potential.

Because most landslide dams form in remote, high mountain regions where gauges are sparse or absent, the review devotes considerable attention to how remote sensing and modelling can fill the data gap. Satellite imagery can track the surface area and volume of dammed lakes over time; researchers used Sentinel-2 images processed in Google Earth Engine to detect and monitor new lakes formed after the 2011 Kaikōura earthquake in New Zealand. Radar technologies such as Sentinel-1 SAR and the SWOT satellite altimetry mission promise measurements of water surface elevation and even discharge in ungauged catchments. Reanalysis products and snow and glacier datasets supply the meteorological inputs needed for water balance calculations. On the modelling side, parsimonious lumped models such as the Budyko framework and the GR6J rainfall-runoff model can simulate catchment response where data is limited, while general circulation models allow exploration of future climate scenarios, though uncertainties from coarse spatial resolution and complex topography remain a challenge.

The review also warns that climate change is poised to reshape the entire hazard landscape. Warming temperatures accelerate snowmelt and glacier retreat, shifting the timing of inflows so that lake level peaks arrive sooner after dam formation and increasing the risk of early failure. More intense rainfall extremes raise both landslide occurrence and overtopping probability. Glacier retreat exposes new valley walls and debris sources, creating conditions for future dams, while meltwater can accelerate lake filling or destabilize existing barriers through increased seepage. Even vegetation dynamics play a role: loss of cover through drought or wildfire enhances runoff generation, altering the volume and timing of water reaching dammed lakes. Because climate change acts mainly through hydrological processes, the authors argue, it amplifies the very mechanisms that existing stability assessments most often overlook.

The authors close with a set of recommendations aimed at turning hydrology from an afterthought into a core component of landslide dam hazard assessment. They call for continuous monitoring of lake area, volume, inflows and outflows; systematic use of remote sensing products for evapotranspiration, snowmelt, runoff and terrestrial water storage; hybrid approaches that combine physically based hydrological models with machine learning trained on satellite, reanalysis, geotechnical and geomorphological data; dedicated field campaigns to measure discharge, sediment dynamics, infiltration rates and dam composition; and, crucially, the expansion of global landslide dam inventories to include hydrological information. No single hydrological variable, the review stresses, can predict dam stability across all environments, but integrating multiple dynamic variables offers the clearest path toward reliable early warning systems. For the communities living downstream of mountains that hold thousands of these natural time bombs, that shift in perspective could not come soon enough.

Subject of Research: Hydrological controls on the formation, stability and failure of landslide dams

Article Title: Hydrological perspective of landslide dams: a review

Article References: Shazil, M. S., Bogaard, T., & Greco, R. (2026). Hydrological perspective of landslide dams: a review. Natural Hazards, 122(18), Article 620. https://doi.org/10.1007/s11069-026-08393-2

Image Credits: AI Generated

DOI: 10.1007/s11069-026-08393-2

Keywords: landslide dams, hydrology, dam stability, overtopping, seepage, remote sensing, dammed lakes, outburst floods, climate change, snowmelt, catchment hydrology, natural hazards