Investigación (ETSECCP)

Permanent URI for this collectionhttps://hdl.handle.net/2183/40349

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Neural Network Approach for Modeling Future Natural River Flows: Assessing Climate Change Impacts on the Tagus River
(Elsevier, 2025-04) Fernández-Novoa, Diego; Soares, Pedro M.M.; García-Feal, Orlando; Costoya, Xurxo; Trigo, R M; Gómez-Gesteira, Moncho
[Abstract]: Study region: Tagus River basin (Iberian Peninsula). Study focus: An innovative methodology is developed to analyze the impact of climate change on the hydrological cycle. Initially, natural river flow is reconstructed to address the challenge posed by river regulation, which complicates accurate hydrological modeling and can obscure the true impact of climate change. The Iber+ hydrodynamic model is applied to account for downstream reservoir contributions, which allows reversing their influence. Then, neural networks of varying configurations, with specific requirements such as data bucketing, are trained to replicate river flow utilizing recorded precipitation and temperature datasets, subjected to validation procedures. A multi-model ensemble is constructed to address uncertainties inherent in modeling future hydrological climate scenarios. This ensemble, supplied with climate model data, derives historical and projected river flows, allowing analysis of their temporal evolution. New hydrological insights for the region: The findings affirm the efficacy of the proposed methodology and reveal, for the considered high-risk SSP5–8.5 scenario, the intensification of the Tagus hydrological cycle. Within the inherent uncertainty of climate models, average ensemble outputs indicate a reduction of about −20 % in available water at the end of the century, especially critical during summer, with an almost 600 % rise in dry months. Average ensemble results also indicate an increase in flooding events, with extreme floods that currently have five-year frequency, projected to double by the century’s end.
Machine Learning Predictive Modelling for Sediment Risk Indices within an Urbanized River Channel
(Elsevier, 2025-05) Pimiento, Maria Alejandra; Anta, Jose; Torres, Andres
[Abstract]: Despite the growing application of machine learning (ML) in water quality assessment and pollution source identification, its potential for predicting environmental risk indices in urban stormwater sediments remains largely unexplored. Conventional models struggle to capture complex interactions among hydrological variables, sediments and pollution parameters. This study uses ML techniques to enhance sediment quality assessment to address this gap. The case study focuses on sediments from the Molinos River in Bogotá, Colombia, characterized by particle size distribution (PSD), heavy metal (HM) concentrations, and environmental risk indices. Cohen's Kappa coefficient was used to evaluate the relationship between the enrichment factor (EF) of Ni and Pb, PSD, and hydrological variables as rainfall data. A support vector machine model using an ANOVA kernel, validated through multiple calibration and validation datasets, demonstrated the feasibility of predicting sediment-related risks in urban drainage systems. The best model successfully predicted Pb EF levels for 7 of 8 samples, achieving a Cohen's Kappa coefficient of 0.71 (p = 0.037), indicating substantial agreement. These findings highlight the potential of ML models to predict sediment EF using rainfall data, providing a practical tool for environmental risk assessment. By enabling predictions of contamination levels, this methodology enhances decision-making and promotes more sustainable urban water management strategies.
Design of Safe Light Rail Transit (LRT) Roundabouts
(Collegio Ingegneri Ferroviari Italiani, 2017-02) Novales, Margarita; Marti, Christian M.; Teixeira, Manuel; Schmitt, Dominique; Monti, Franck; Morley, Reddy; Fontaine, Laetitia
[Abstract]: While travelling at-grade in an urban environ- ment, a Light Rail Transit (LRT) system needs to traverse road intersections of various complexities. These intersec- tions, including roundabouts, are major hotspots (risky points) in LRT networks. There are several documents re- lated to the treatment of conventional LRT intersections for guaranteeing safety, but almost no reference to LRT round- abouts design, except for the French guidelines. This paper addresses safety issues related to LRT roundabout design. The paper contains, firstly, the explanation of the differ- ences between the roundabout management without and with an LRT running through it, and the consequences for road vehicle drivers’ behavior. Secondly, the appropriate- ness of using a roundabout in the insertion of an LRT in a specific intersection is discussed. Finally, the main consid- erations for designing a safe LRT roundabout are present- ed, taking into account general aspects such as visibility, perception and protection, and more specific ones such as the adequate insertion of the LRT in the roundabout, its size and number of lanes, as well as some traffic light im- provements that may enhance safety. Additionally, some re- al case examples are presented at the end of the paper to il- lustrate how the safety of a given LRT roundabout can be improved once it has been built.
Prima esperienza tram-treno sulle linee ferroviarie spagnole convenzionali: il tram-treno della Baja di Cadice
(CIFI Collegio Ingegneri Ferroviari Italiani, 2014-02) Novales, Margarita; Conles Barrera, Emilio José
[Abstract]: The article presents a study which examines how several technological challenges were overcome by the tram-train railway project, which is under ownership and management of the Administrador de Infraestructuras Ferroviarias (Adif), in Cádiz Bay, Spain. These challenges include the track gauge, the passenger access and the bogies. The infrastructure, rolling stock, operation and future expansion plans for the project is also discussed.
Integrating Net Rainfall Calculation in Deep Learning-Based Surrogate Modeling Frameworks for 2D Flood Prediction
(Elsevier, 2025-11) Farfán-Durán, Juan F.; Montalvo Montenegro, Carlos Israel; Cea, Luis; Leitão, J. P.
[Abstract]: This study proposes a novel deep learning (DL)-based surrogate model that incorporates the calculation of net rainfall using the SCS-CN method, providing a flexible framework for evaluating the influence of rainfall events under different antecedent moisture conditions (AMC). The proposed framework involves establishing a ground truth model (Iber-SWMM) and defining the necessary terrain features and rainfall patterns for training the surrogate. A benchmark surrogate model using only gross rainfall, replicating methodologies from previous studies, is also developed for comparison. The trained models are then applied to predict water depth maps using test rainfall patterns under different scenarios, both with and without net rainfall. The results demonstrate that the proposed surrogate model reduces the computational times of Iber-SWMM by 2 to 4 orders of magnitude while outperforming the benchmark surrogate in all the measures. It presents satisfactory accuracy in water depth prediction, with 80% to 95% of predictions within a -0.2 to 0.2 m error range and hit ratios between 0.87 to 0.91 in terms of flooded pixels in the more extreme events. These outcomes are comparable to those achieved by a physics-based model on one of the test events. The study also suggests future lines for refinement.
Impact of Fluids on the Mode I Fracture Toughness of Two Granites and One Sandstone
(American Geophysical Union & Wiley, 2025-01) Muñoz-Ibáñez, Andrea; Herbón-Penabad, Miguel; Li, Yan; Delgado Martín, Jordi
[Abstract]: Fluids affect the mechanical behavior of geomaterials, including properties such as unconfined compressive strength and brittleness. However, their impact on mode I fracture toughness (KIc) has been less explored. This study investigates the impact of saturating fluids on the KIc of three rock types: a porous siliceous sandstone (Corvio) and two high-strength, low-porosity granites (Blanco Mera and Blanco Alba). Pseudo-compact tension (pCT) specimens (diameter ∼50–54 mm, thickness ∼25 mm, notch depth ∼16 mm) were saturated with seven different fluids (deionized water, methanol, NaCl-saturated water, mineral oil, diesel fuel, an acidic HCl solution and a caustic NaOH solution) and tested under identical conditions. Results show that all fluids reduce KIc, but the extent varies with rock type and fluid properties. Aqueous fluids caused the most significant reductions, with deionized water having the greatest impact on granites (∼18%–30%) and the acid solution on sandstone (∼70%). Non-polar hydrocarbon fluids, despite their lack of reactivity, caused moderate effects attributed to poro-mechanical effects. Additionally, pH-shift experiments, involving sequential exposure to alkaline and acidic solutions, mitigated fluid-induced weakening. This behavior is hypothesized to stem from silica dissolution in the alkaline phase, followed by rapid nucleation and precipitation during the acidic phase, forming silica-rich coatings on mineral surfaces. Fracture energy was not equally distributed, with higher post-peak energy absorption due to crack bifurcation, grain rotation or friction. These findings underscore the interplay of lithological factors, fluid properties and chemical processes in fracture behavior, with implications for subsurface engineering and modeling of fluid-rock interactions.
IberSWMM+: A high-performance computing solver for 2D-1D pluvial flood modelling in urban environments
(Elsevier, 2025-04) Sañudo, Esteban; García-Feal, Orlando; Hagen, L.; Cea, Luis; Puertas, Jerónimo; Montalvo Montenegro, Carlos Israel; Alvarado-Vicencio, R.; Hofmann, J.
[Abstract]: Urban drainage modelling is essential for effective city planning and flood management. The increasing complexity of urban environments and the growing availability of high-resolution data have led to the need to develop more sophisticated and freely accessible urban drainage models. This paper presents the parallel implementation of Iber-SWMM, a freely distributed integrated 2D/1D urban drainage model for modelling surface and sewer flows and their interactions. Iber-SWMM constitutes an advance in the field by incorporating a fully distributed hydrological approach, advanced roof modelling tools, and GIS interoperability, offering a comprehensive solution for urban hydrodynamics. Originally designed for research in small urban drainage models due to CPU limitations, Iber-SWMM has now been enhanced with High Performance Computing (HPC) techniques. This allows for the simulation of high-resolution urban models with fine meshes comprising millions of elements, essential for accurate representation of complex urban geometries. We validated the model through laboratory-scale tests and two city-scale scenarios, providing detailed input data and demonstrating the applicability of the model in real-world situations. Our results show that the GPU-accelerated version achieves simulation speeds up to 200 times faster than the sequential version for large models. For instance, in a city-scale scenario with approximately 6 million cells, 3000 nodes, and 3000 links, simulation time was reduced from 72 h to just 20 min. To ensure result consistency and assess convergence, we conducted simulations using low, medium, and high-resolution computational meshes for each case study. Our findings indicate that both parallel and sequential versions produce consistent results, with convergence typically achieved at medium to high resolutions. Notably, we observed that for very large models, the computation of the drainage network in SWMM can become a bottleneck, suggesting an area for future optimization. By enabling the simulation of high-resolution urban models with millions of elements up to 200 times faster than sequential versions, this study bridges the gap between academic research and practical urban planning, empowering stakeholders to conduct more detailed, city-wide simulations, and ultimately contributing to faster urban flood risk management.
Suction-Induced Strains in Intact Rocks
(Elsevier, 2026-06) Muñoz-Ibáñez, Andrea; Santamarina, J. Carlos
[Abstract]: Suction-induced strains in rocks affect subsurface applications that involve immiscible fluids, including CO₂ sequestration, hydrocarbon extraction and the storage of energy fluids. This study explores the underlying processes and parameters that govern the strains intact rocks will experience during wetting and drying. It combines a synthesis of published data with new experimental results. Macroscale water retention measurements together with nuclear magnetic resonance NMR data show that desaturation proceeds through sequential drainage, beginning with the largest interconnected pores, which empty first due to their lower capacity to sustain capillary pressure. Consequently, the suction at air-entry ψAE is strongly correlated with the characteristic pore size d85. Because the rock remains saturated to the verge of air entry, the nominal strain ε ≈ ψAE/E defined as the ratio between the air entry pressure and the rock stiffness E is an effective indicator of the rock’s susceptibility to suction-induced deformation; this nominal strain can vary from less than 10−6 in stiff igneous rocks to more than 10−4 in clay-rich shales. Suction-induced strains can significantly impact fracture transmissivity, which scales with the cube of the fracture aperture. Then, wetting-induced swelling may reduce aperture and enhance self-sealing, while drying can increase aperture and facilitate leakage. During wetting or drying, changes in suction dominate over osmotic effects, although their impact may be partially masked by concurrent processes such as creep and thermoelastic strains.
ANN and DoME to Predict the Moisture Damage Resistance of HMA with RCA
(CRC Press, 2023) Pasandín, A.R.; Pérez Pérez, Ignacio; Rivero, Daniel; Rabuñal, Juan R.
[Abstract]: The production of hot-mix asphalt using recycled concrete aggregates from construction and demolition debris as raw material could support the circular economy and the development of more environmentally friendly infrastructure. A crucial characteristic of HMA manufactured with RCA is its moisture resistance. Careful research should be done to ensure satisfactory performance. The experimental inquiry might be perfectly complemented by a mathematical approach. To predict the indirect tensile strength value and the tensile stress ratio as a function of the study parameters (wet or dry state, bitumen per-centage, and RCA percentage), three models—linear, artificial neural networks (ANN), and development of mathematical expressions (DoME)—were proposed. It was possible to get mathematical expressions. The key finding of this study is that the DoME approach led to more accurate estimations of the ITS values. DoME’s primary advantage is that it returns a simpler expression.
Assessing Compound Flooding Hazards in Estuaries by Integrating a Climate Emulator and a Hybrid Metamodel
(Springer, 2026) Ortiz-Angulo, Jared; Camus, Paula; Pérez-Díaz, Beatriz; Cagigal, Laura; Jiménez, Mirian; Castanedo, Sonia; Pozo, Andrea; Cea, Luis; Farfán-Durán, Juan F.; Méndez, Fernando
[Abstract]: Compound flooding in estuaries results from the interaction of multiple forcings, including tides, storm surges, waves, precipitation and river discharge. These events present significant challenges for dynamic modeling due to their computational requirements. To address this, we present a hybrid statistical-dynamical framework for efficiently assessing compound flooding hazards. The framework incorporates a new version of the climate-based emulator TESLA, which generates synthetic extreme multivariate events by linking them to weather types that represent atmospheric pressure patterns. A multiscale approach considering Regional Weather Types (RWT) and Local Weather Types (LWT) captures the spatial variability of oceanographic and land drivers. TESLA is coupled with a hydrodynamic metamodel, enabling fast predictions of water levels and inundation under various forcing conditions while significantly reducing computational demands. Using flood proxies based on water volume, the framework identifies events associated with specific return periods. High-resolution simulations of these events provide detailed assessments of compound flooding hazards. Applied to the Asón River estuary in northern Spain, this approach demonstrates its ability to analyze historical climate variability, predict flood risks, and define mitigation strategies. It offers an efficient tool for exploring low-probability, high-impact scenarios in estuarine environments under current and future climate conditions.
Bond Behavior Between Steel Reinforcement and Concrete with Recycled Fine Aggregate under Different Confinement Levels
(Elsevier, 2026-04) Eiras López, Javier; Berrocal, Carlos G.; Fernández, Ignasi; Carro-López, Diego
[Abstract]: This paper identifies the trends on the bond behavior of concrete with recycled fine aggregate (RFA). This was analyzed replacing natural fine aggregate with recycled fine aggregate at different percentages (20%, 50% and 100%). Using a real-case fine recycled aggregate from a decommissioned bridge and keeping constant the mix proportion, the w/c ratio. The bond strength was measured in three different confinement levels with 16 mm rebars, and the bond was confirmed to be reduced compared with conventional concrete. The results indicate a reduction trend of the bond strength as the proportion of recycled fine aggregate increases for the and both in splitting and pull out failure modes. Finally, when using the Model Code 2020 to predict bond strength, the ratio of experimental values to theoretical predictions may decrease by up to 40%, therefore, to maintain design conservatism, the anchorage length should be increased in this case.
Nanocellulose Fibers and Crystals as Emulsifying Agents
(Woodhead Publishing, 2025) Pasandín, A.R.; Orosa, Pablo; Pérez Pérez, Ignacio
[Abstract]: The most prevalent biopolymer on Earth is cellulose. Plants and trees are the primary sources of cellulose used in industry. Different sizes of cellulose can be extracted, depending on the intended purpose. Micro and nanocellulose are the two types of cellulose that are most frequently used in industrial settings. Most studies distinguish between three primary forms of nanocellulose: bacterial nanocellulose, cellulose nanofibers, and cellulose nanocrystals. Numerous researchers have extensively employed two of them, cellulose nanofibers (CNF) and nanocrystals (CNC), as emulsifiers. These nanoparticles can be used as emulsifiers, either molecularly dissolved or not (Pickering emulsions). Usually, oil in water (o/w) emulsions are stabilized by unmodified, while water in oil (w/o) emulsions or multiple emulsions are stabilized by modified nanocelluloses. Most researchers and industrial applications use nanocellulose particles as food industry emulsion stabilizers. Nevertheless, their application in construction materials remains relatively scarce to date. In this regard, nanocellulose is currently employed in the construction sector as an emulsion stabilizer for manufacturing bituminous emulsions and forming Pickering emulsion systems stabilized by nanocellulose to be used as templates to create nanocomposite foams. Because cellulose is widely available, environmentally friendly, and has shown previous successful applications, using it as an emulsifying agent for bio-materials in the construction industry is an alternative with great development potential. In particular, exploring the potential of using waste biomass as a source of nanocellulose for bio-based materials is highly interesting.
Fracture Performance of HWMRA Made With Waste Lignin
(CRC Press, 2023) Miró-Recaséns, R.; Martínez-Reguero, A. H.; Pasandín, A.R.; Valle Corte, Jorge del; Pérez Pérez, Ignacio
[Abstract]: A readily available and sustainable biomass resource that could be used as a bi-tumen extender or modifier is the biopolymer lignin. Nevertheless, there isn’t much agreement regarding how well lignin-based bituminous mixtures crack. The fracture performance of half-warm mix recycled asphalt (HWMRA), made with 100% reclaimed asphalt pavement (RAP) and 5% lignin-rich industrial waste in place of bitumen emulsion, was examined in the current research in this regard. The Fénix test was carried out with this goal in mind. The results were compared to those obtained for a control mixture (HWMRA with 0% of lignin rich industrial waste). At 20ºC the results were slightly better for the control mixture. But at -5ºC and 5ºC the results were similar for both mixtures. Therefore, it can be concluded that replacing 5% of the bitumen emulsion with lignin-rich industrial waste will not be detrimental to the cracking performance of half-warm mix recycled asphalt.
Fracture Topology in Mafic Formations: Implications for Geological Carbon Storage
(American Chemical Society, 2025) Muñoz-Ibáñez, Andrea; Santamarina, J. Carlos
[Abstract]: Carbon mineralization pilot projects have demonstrated effective CO2 sequestration, yet uncertainties persist for large-scale deployment, particularly regarding the role of fracture networks and evolving fracture-matrix interactions. In this study, we integrate field data, numerical simulations and gravimetric-volumetric analyses to investigate the fracture characteristics of basalt formations and their implications for CO2 storage. Fracture aperture is shown to be proportional to block size, governed by thermal contraction during lava cooling, with the aperture-to-block size ratio β ranging from ∼0.7·10–2 to 6·10–2 depending on mineralogy. Network modeling reveals that initial aperture variability is amplified by dissolution near the injection zone (high Peclet and low Damköhler numbers); however, the hexagonal fracture topology enhances mixing and delays hydrochemical feedback and flow localization. Chemo-gravimetric analysis indicates that mineralization can sequester 0.2–0.3 g CO2 per gram of rock, significantly exceeding pore-space storage via supercritical or dissolved CO2. However, volume-positive mineralization eventually reduces fracture transmissivity. Aperture shut-off depends on the aperture-to-block size ratio β and the mineralization expansion factor ε. The reacted volume fraction at shutoff can range from 7 to 24%. Mineralogy emerges as a primary control on fracture topology, chemical reactivity and storage capacity. Results underscore the need for careful reassessment of CO2 storage capacity in mafic rocks.
Flooded With Potential: Urban Drainage Science as Seen by Early-Career Researchers
(IWA Publishing, 2025) van der Werf, Job Augustijn; Pons, V.; Smyth, Kelsey; Shi, B.; Lechevallier, P.; Naves, J.; Regueiro-Picallo, Manuel
[Abstract]: This opinion paper reflects on the current challenges facing urban drainage systems (UDS) research, along with solutions for fostering sustainable development. Over the course of a year-long project involving 92 participants aged 24–38, including PhD candidates, post-doctoral researchers, and early-career academics, we identified critical challenges and opportunities for the sustainable development of UDS. Our exploration highlights four key challenges: limited public visibility leading to resource constraints, insufficient collaboration across subfields, issues with data scarcity and data sharing, and geographical specificities. We emphasise the importance of raising public and political awareness regarding UDS's vital role in climate adaptation and urban resilience, advocating for blue-green infrastructure and open data practices. Additionally, we address systemic academic barriers that hinder innovative research. We call for a shift away from metrics that prioritise quantity over quality. We recommend establishing stable career pathways that empower early-career researchers. This paper aims to catalyse a broader community dialogue about the future of UDS research, uniting voices from various career stages. By presenting actionable recommendations, we aim to inspire fundamental changes in research conduct, evaluation, and sustainability, ensuring the field of UDS is prepared to meet pressing urban water management challenges worldwide.
Evolución de la modelización numérica bidimensional del flujo en lámina libre a través del software Iber
(Universitat Politècnica de València - Fundación para el Fomento de la Ingeniería del Agua, 2025-04) Sanz-Ramos, Marcos; Sañudo, Esteban; López-Gómez, David; García-Feal, Orlando; Bladé, Ernest; Cea, Luis
[Resumen]: Iber es una herramienta de simulación hidráulica bidimensional surgida desde la academia para dar solución a problemas de ingeniería hidráulica y ambiental. Desde su nacimiento en 2010 se ha convertido en un software ampliamente aceptado para simular procesos hidrodinámicos de flujo en lámina libre. Este trabajo presenta la evolución de Iber y analiza las mejoras llevadas a cabo que actualmente permiten realizar simulaciones, completamente acopladas con la hidrodinámica, de transporte de sedimentos y calidad de aguas, de procesos hidrológicos a nivel de cuenca rural y urbana, de eco-hidráulica, etc. Los módulos y capacidades de cálculo implementados, así como las líneas de trabajo futuras, demuestran que la modelización hidrodinámica bidimensional todavía tiene un gran margen para el desarrollo de nuevas aplicaciones y mejoras. Iber sigue unas líneas de desarrollo con un enfoque eminentemente práctico, permitiendo a usuarios y usuarias realizar simulaciones cada vez más fidedignas al proceso físico a representar.
Enhancing Flood Risk Management: A Review on Numerical Modelling of Past Flood Events
(MDPI, 2025-05) González-Cao, José; Barreiro-Fonta, Helena; Fernández-Novoa, Diego; García-Feal, Orlando
[Abstract]: Recent scientific literature has consistently highlighted a significant increase in both the frequency and intensity of flood events, primarily attributed to the effects of climate change. Projections suggest that this trend will likely intensify in the coming decades. In this context, enhancing our understanding of flooding dynamics becomes not only necessary but urgent. A critical component of this advancement lies in the numerical analysis of historical flood events, which provides valuable insights into flood behaviour across extended temporal and spatial scales. This approach enables two key outcomes: a significant improvement in conventional methods for estimating return periods and a reduction in the uncertainties associated with historical flood events by simulating multiple plausible scenarios to identify the most likely one. This paper presents a comprehensive review of the scientific literature focused on the numerical simulation and reconstruction of past flood events. Two main conclusions emerge from this review: First, the temporal scope of the studies is notably wide, covering events ranging from glacial periods to those occurring in the mid-20th century. Second, there exists a pronounced spatial imbalance in the geographical distribution of these studies, with certain regions significantly underrepresented. This review provides a valuable resource for researchers and practitioners working in flood risk assessment and hydrological modelling. By consolidating existing knowledge, it supports the development and refinement of decision-support tools aimed at improving mitigation strategies to reduce the impact of flooding on both populations and infrastructure.
Effects of Confining Pressure on Mode I Fracture Toughness Considering Jacketed and Unjacketed Conditions
(Springer, 2026) Li, Yan; Herbón-Penabad, Miguel; Muñoz-Ibáñez, Andrea; Alejano, Leandro R.; Alvarellos Iglesias, José; Canal-Vila, J.; Segura-Serra, José María; Delgado Martín, Jordi
[Abstract]: Accurate assessment of mode I fracture toughness (KIc) in rocks under in-situ stress conditions is critical for analyzing various geomechancial problems in underground rock engineering. Typically, KIc is determined through unconfined tests. Under confining pressure, researchers often refer to the apparent mode I fracture toughness (KIc*), where specimens are typically jacketed to isolate from confining fluids. Although rocks are porous media that naturally contain fluids, relatively few studies have investigated the toughness behavior of unjacketed specimens under confining pressure, a scenario prone to rock-fluid interactions. In this study, we measured the KIc and KIc* of pseudo-compact tension (pCT) specimens of granite, limestone, sandstone, and polymethyl-methacrylate (PMMA) under two conditions: covered with a waterproofing rubber (jacketed) or directly exposed to the confining fluid (unjacketed). PMMA served as an impermeable reference material. Tests were conducted at room temperature and confining pressures ranging from 0.1 to 25 MPa. Results show that KIc* is material-dependent for both jacketed and unjacketed specimens. Jacketed specimens generally exhibit significantly higher KIc* values compared to unjacketed ones. However, KIc* values obtained from unjacketed specimens better reflect the actual stress state and fracture behavior under in-situ conditions, as both the mechanical and hydraulic properties of the rock interact concurrently during the development of the fracture process zone. These findings emphasize the importance of selecting appropriate testing conditions for accurately assessing fracture toughness in rocks, which has implications for the evaluation of stability, fracturing and fluid flow in rocks in underground environments.
Dataset on the Impacts of Sand and Leaf Litter on the Hydrological Performance of Green Roofs as Surrogate for Infiltration-Based Blue-Green Infrastructure (BGI)
(Elsevier, 2025-04) Joshi, Prabhat; Naves, Juan; Anta, Jose; Maurer, Max; Leitão, J. P.
[Abstract]: This dataset contains raw and processed data from controlled experiments conducted in a rainfall simulator to quantify the impacts of incremental sand and leaf litter accumulation on the hydrological performance of blue-green infrastructure (BGI). The tests were conducted in a controlled indoor environment using two BGI boxes (approximately 3.84 m² each), representing a typical infiltration-based BGI setup with vegetation, a 6-cm deep substrate, and storage layers. Soil moisture sensors and tipping buckets were installed to measure underdrain flow. In one box, sand was incrementally added (2–18 kg.m−²); in the other, leaf litter accumulation ranged from 0.3 to 1.725 kg (total). Each scenario received rainfall (16.66 mm.h−1 for Box 1; 18.66 mm.h−1 for Box 2) for 30 minutes, with intervals larger than four hours between tests. The dataset can be used to understand the impact of shock events that introduce high pollutant loads to the BGI surface and subsurface, affecting their hydrological performance. It can also be used to study the maintenance needs of BGI to sustain their hydrological functionality.
Can Dominant Runoff Generation Mechanisms Be Disentangled Through Hypothesis Testing? Insights From Integrated Hydrological-Hydrodynamic Modeling
(Wiley, 2025-04) Perrini, Pasquale; Iacobellis, Vito; Gioia, Andrea; Cea, Luis; Savenije, Hubert H. G.; Fenicia, Fabrizio
[Abstract]: Identifying flood-inducing processes remains a challenge in catchment hydrology due to the complex runoff dynamics, particularly in semi-arid regions where surface and subsurface mechanisms alternatively drive streamflow across seasons. Tracer data can help identify hydrograph sources, but they are often unavailable or lack sufficient temporal resolution. To aid process identification at the event-scale, we developed an integrated hydrological-hydrodynamic framework and compared multiple model hypotheses informed by hydrological signatures. We systematically tested these hypotheses through falsification, meta-evaluation, spatial validation, and posterior diagnostics, using the semi-arid Salsola nested catchment in southern Italy as case study. While all model structures performed well on common calibration metrics, differences emerged in spatial transferability tests and alternative diagnostic assessments. Some models, despite strong performance, exhibited inconsistent representations of internal runoff mechanisms, indicating that they achieved good results for the wrong reasons. Furthermore, the choice of routing schemes significantly influenced high peak estimations and overall model performance, particularly when Horton-type overland flow was considered. This underscores the need to treat routing methods as a key component in event-scale modeling. Our findings reveal that during consecutive storm events in the study catchment, surface processes dominate the initial stages, whereas subsurface processes become more influential in later events, providing valuable insights that may be applicable to similar semi-arid regions. Overall, we emphasize the importance of hypothesis testing in runoff process identification, which can compensate for the absence of hydrochemical data for hydrograph separation. Additionally, our results highlight the value of a landscape-based modeling approach for distinguishing alternative runoff generation processes.

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