Articles publicats (Grup de Recerca de Dinàmica Fluvial (RIUS))

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    Disclosing the effects of climate, land use, and water demand as drivers of hydrological trends in a Mediterranean river basin
    (Asociación Ibérica de Limnología, 2024) Córdoba-Ariza, Gabriela; Batalla, Ramon J.; Sabater, Sergi; Mas-Pla, Josep
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    Losing flow in free-flowing Mediterranean-climate streams
    (Wiley, 2024) Carlson, Stephanie M.; Alvarez, Derry; Bogan, Michael T; Hazard, Cleo Wolfle; Ayers, Jessica; Grantham, Theodore E.; Batalla, Ramon J.; Garcia, Celso
    Stream drying is happening globally, with important ecological and social consequences. Most examples of stream drying come from systems influenced by dam operations or those with highly exploited aquifers. Stream drying is also thought to be driven by anthropogenic climate change; however, examples are surprisingly limited. We explored flow trends from the five recognized Mediterranean-climate regions of the world with a focus on unregulated (non-dammed or non-diverted) streams with long-term gauge records. We found consistent evidence of decreasing discharge trends, increasing zero-flow days, and steeper downward discharge trends in smaller basins. Beyond directional trends, many systems have recently undergone shifts in flow state, including some streams that have transitioned from perennial to intermittent flow states. Our analyses provide evidence of stream drying consistent with climate change but also highlight knowledge gaps and challenges in empirically and statistically documenting flow regime shifts. We discuss the myriad consequences of losing flow and propose strategies for improving detection of and adapting to flow change.
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    Analysis of probability distributions for modelling extreme rainfall events and detecting climate change: insights from mathematical and statistical methods
    (MDPI, 2024)
    Exploring the realm of extreme weather events is indispensable for various engineering disciplines and plays a pivotal role in understanding climate change phenomena. In this study, we examine the ability of 10 probability distribution functions-including exponential, normal, two- and three-parameter log-normal, gamma, Gumbel, log-Gumbel, Pearson type III, log-Pearson type III, and SQRT-ET max distributions-to assess annual maximum 24 h rainfall series obtained over a long period (1972-2022) from three nearby meteorological stations. Goodness-of-fit analyses including Kolmogorov-Smirnov and chi-square tests reveal the inadequacy of exponential and normal distributions in capturing the complexity of the data sets. Subsequent frequency analysis and multi-criteria assessment enable us to discern optimal functions for various scenarios, including hydraulic engineering and sediment yield estimation. Notably, the log-Gumbel and three-parameter log-normal distributions exhibit superior performance for high return periods, while the Gumbel and three-parameter log-normal distributions excel for lower return periods. However, caution is advised regarding the overuse of log-Gumbel, due to its high sensitivity. Moreover, as our study considers the application of mathematical and statistical methods for the detection of extreme events, it also provides insights into climate change indicators, highlighting trends in the probability distribution of annual maximum 24 h rainfall. As a novelty in the field of functional analysis, the log-Gumbel distribution with a finite sample size is utilised for the assessment of extreme events, for which no previous work seems to have been conducted. These findings offer critical perspectives on extreme rainfall modelling and the impacts of climate change, enabling informed decision making for sustainable development and resilience.
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    Comparative analysis and evaluation of seismic response in structures: perspectives from non-linear dynamic analysis to pushover analysis
    (MDPI, 2024-03-15) Rodríguez, César A.; Rodríguez Pérez, Ángel Mariano; López Alonso, Raúl; Caparrós Mancera, Julio Jose
    This study presents a detailed comparative analysis of different methods for evaluating seismic response in structures, focusing on maximum displacements and collapse assessment. The results obtained through modal spectral analysis, non-linear dynamic analysis, and the incremental pushover analysis applied to a specific structure are compared. It has been found that the choice of time step and the consideration of ductility are critical for obtaining accurate predictions. The results of the non-linear dynamic analysis of the building's response indicate that an earthquake equivalent to the one that affected the city of Lorca (southeast Iberian Peninsula) in 2011 would have a devastating impact on the studied structure, highlighting the importance of the finite element method modelling in predicting the formation of plastic hinges and assessing structural safety. These findings highlight the importance of utilising multiple analysis approaches and detailed modelling to fully understand the seismic behaviour of structures and ensure adequate resistance and stability to extreme events.
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    Evaluation of 2D hydrodynamic-based rainfall/runoff modelling for soil erosion assessment at a seasonal scale
    (Elsevier, 2024) Costabile, Pierfranco; Cea, Luis; Barbaro, Gabriele; Costanzo, Carmelina; Llena, Manel; Vericat Querol, Damià
    Badlands are often the source of a significant fraction of the sediment reaching the river network due to the exposure of the bare soil to the impact of rain drops and to the bed shear stress generated by the surface runoff. Hence, a correct understanding of the soil erosion and sediment transport processes inside badlands can help to a better characterisation of the suspended sediment production at the catchment scale. In this work we study the suitability of a two-dimensional (2D) physically-based event-scale erosion model as a tool to represent soil erosion and sediment transport in badlands at a seasonal scale. The model solves the 2D shallow water equations, including infiltration and rainfall, in order to compute the generation and routing of surface runoff within the badland. Coupled to the hydrodynamic equations, the model solves a 2D suspended sediment transport equation with source terms that account for rainfall- and runoff-driven erosion and sediment deposition. Based on this model, an overall procedure was developed and tested considering, as case study, a badland located in El Soto catchment (central Pyrenees, Iberian Peninsula). For the analysed badland, several high-resolution topography surveys were available, which allowed for the estimation of the soil loss and the spatial distribution of erosion patterns for periods of 3–4 months over two years. These data sets were used to calibrate and validate the proposed modelling approach, and to analyse its capabilities and limitations for the assessment of soil erosion at the seasonal scale.