University of Cuenca

Understanding how streamflow is generated across spatial scales is crucial for enhancing regional hydrological models and effective water management. However, knowledge on how different geomorphic characteristics, landscape structure and subsurface properties influence streamflow remains limited, particularly in tropical Andean catchments. To address this gap, we investigated streamflow responses and generation processes across six nested tropical Andean catchments (6-91 km2), characterized by permeable fractured bedrock, interconnected lake systems, wetlands and complex geomorphology within the Quinuas Ecohydrological Observatory in southern Ecuador. Using nearly a decade of hydrometric, stable isotopes and hydrogeochemical data, we applied a multi-criteria approach that combined mixing models, transit times modelling, young water fractions estimation, and principal component analysis to identify dominant flow paths and controls on streamflow generation. Our findings reveal that, despite relatively uniform rainfall distribution across the catchments, streamflow responses are shaped by catchment structure, particularly geological controls and subsurface water storage. Small headwater catchments (6-19 km2) exhibited rapid discharge responses to rainfall, with MTTs as low as 41 weeks, where wetlands and high-altitude lakes regulated flows by slowly releasing stored water during dry periods. In contrast, larger downstream catchments (54-91 km2) showed increasing dependence on deep groundwater storage within the permeable bedrock, with MTTs exceeding 100 weeks. Young water fraction estimates further revealed that fast, well-connected flow paths persist across all catchment scales, coexisting with the progressive increase in groundwater storage and longer transit times observed downstream. The PCA revealed three groups driven by geology, topography and land cover that jointly shape MTT variability across scales. These results highlight the dominant role of geological and geomorphological variability in governing how water is generated and transported throughout complex terrain, providing new insights into structure-dependent hydrological behaviour in tropical Andean catchments.

PurposeThis study aims to examine the gender gaps in intergenerational educational mobility across 23 OECD countries and identify whether and to what extent cognitive and noncognitive skills contribute to these.Design/methodology/approachUsing PIAAC II Cycle data, this study builds four mobility measures and applies the Oaxaca-Blinder decomposition to assess the role of skills in gender differences in mobility.FindingsMen display lower educational mobility than women in nearly all countries. In the explained component of the gap, cognitive skills, particularly numeracy, are the main contributors, generally favoring men. Noncognitive traits like conscientiousness and open-mindedness follow, typically contributing to women's mobility.Originality/valueTo the best of the authors' knowledge, this is the first cross-country study to jointly examine the role of cognitive and noncognitive skills in shaping gender gaps in educational mobility, highlighting the relevance of skill-building.

The physics of many natural systems can be represented by partial differential equations. Physics-informed neural networks (PINNs) solve these equations using artificial intelligence (AI) and automatic differentiation (AD) to approximate derivatives. However, AD is not appropriate for all kinds of partial differential equations. In this article, we present VANFID (variable modification finite-difference neural network), a modification of the classical PINN in which the finite-difference method replaces AD and a prior variable modification is applied. The PINN used in this study also incorporates VANFID's variable modification. Both VANFID and the PINN are applied to reference and real-world cases (cascade and step pool). For the real-world cases, two strategies are tested to handle varying cross-sections: (i) an equivalent cross-sectional representation and (ii) an additional neural network. Moreover, a methodology for handling transcritical flow is evaluated in both PINN and VANFID. Results show that the tanh activation function performs better across reference and real scenarios; VANFID outperforms PINN in reference cases, while PINN performs better in most real cases. Adding a neural network to represent cross-sectional properties in real cases has a limited impact on cascade high flow.HIGHLIGHTSAn alternative methodology to PINN called VANFID has been developed for solving reference cases in open-channel flow and real cases in mountain river reaches. The activation function providing the best results for reference and real cases is tanh. The use of an equivalent cross-section to represent non-prismatic cross-section characteristics improves model performance in only one real case.

This study presents the first systematic regional assessment of how the Historic Urban Landscape (HUL) approach has been understood and applied in Latin American and Caribbean (LAC) cities between 2011 and 2022. The HUL approach is framed as a socio-spatial perspective shaped by historical layering, cultural practices, ecological structures, and contemporary development pressures. A systematic review of academic publications and institutional gray literature (Scopus, Google Scholar, and municipal repositories) was conducted to evaluate both conceptual understanding and methodological implementation aligned with the six steps of the 2011 HUL Recommendation. Findings reveal a clear implementation gap: although awareness of the HUL approach has increased across the region, its practical application remains partial. Steps 1 and 2 focused on value identification and participatory engagement show the highest adoption, while steps 4 and 6 which require interinstitutional coordination and integration into statutory planning instruments exhibit limited progress. Academic and research institutions play a more prominent role than local governments in leading or supporting HUL-related actions, indicating persistent institutional and governance constraints. Results highlight the need to strengthen municipal capacities, integrate HUL-based diagnostics into urban planning systems, and consolidate participatory, interdisciplinary, and multilevel governance mechanisms to close the gap between conceptual uptake and operational implementation.

Implementing psychosocial health interventions in new target groups in different cultures requires rigorous training. The 'Circle of Friends' (CoF) model has proven to be effective for helping lonely older adults. The aim of this article is to describe in detail how professionals' training in using the CoF model was modified to create the 'Friends in Nature (FiN)' intervention in the EU-funded 'RECETAS' project for use in five other countries (Spain, France, Czech Republic, Australia, and Ecuador) and how and why the original training model changed in various cultural contexts. RECETAS was tailored to suit the local context and specific target populations. The training required several stages of modification: 1) changing from face-to-face training to online training for key facilitators in each country, 2) key facilitators adapting the training for local facilitators at each study site, and 3) local facilitators applying learning outcomes in the intervention groups. The CoF training model was modified at each stage, but its essential elements were largely maintained during the process. Loneliness is a stigmatized topic in many cultures, two study sites incorporated reflections on loneliness indirectly through a focus on social connection. The same study sites used an adapted version of learning diaries when mentoring their facilitators for group dynamics. Key facilitators at all study sites brought up the challenges of group dynamics. Planned outcome analyses will be used to evaluate how these adaptations influence the efficacy of the intervention. This article may help educators to understand the challenges of a multi-country educational project.