Facultad de Ingeniería Tesis Maestrías

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Pronóstico de la generación de potencia en un parque eólico a través de modelos de aprendizaje automático basado en datos históricos
(Universidad de Cuenca, Facultad de Ingeniería, 2025-11-18) Astudillo Calle, Jorge Eduardo; Minchala Ávila, Luis Ismael
This work presents an advanced hybrid model for wind power generation forecasting that inte-grates feature engineering, seasonality analysis, and signal decomposition techniques. Initially, an exhaustive study of annual, monthly, and daily seasonality is carried out using sine and co-sine functions, which effectively capture regular cyclic patterns. However, when analyzing the complete wind power generation signal over an extended horizon, it becomes evident that it is not fully stationary. To address this nonlinear and non-stationary behavior, the CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) technique is imple-mented, decomposing the signal into Intrinsic Mode Functions (IMFs) at different temporal sca-les. This decomposition allows the specialized LSTM model to focus on learning specific high-and low-frequency dynamics independently. Validation is performed using operational data from the Huascachaca wind farm; the tuning stage employs time-series cross-validation (TSCV ), and the final evaluation uses a rolling-origin scheme with metrics expressed in physical units. Overall, the model achieves RMSE values between 546 and 680 kW and an R2 between 0.74 and 0.80 for a 48-hour forecasting horizon, demonstrating the effectiveness of the proposed approach in real-world energy forecasting applications.
Unveiling groundwater recharge elevations in a tropical Andean catchment: Insights from nine-year isotopic records
(Universidad de Cuenca, Facultad de Ingeniería, 2025-10-08) Tuba Guaman, Damian Francisco; Ramón Flores, Jorge David
Research on páramo ecosystems have demonstrated that groundwater contributions to baseflow are both permanent and substantial, particularly during periods of low rainfall. However, advancing this knowledge requires identifying the spatiotemporal variability of groundwater recharge in order to clarify the mechanisms that sustain baseflow. This study addresses this knowledge gap by identifying the groundwater recharge elevations and the temporal dynamics of groundwater recharge in the Quinuas Eco-hydrological Observatory, a páramo catchment located in Southern Ecuador. For this purpose, we utilized a unique nine-year dataset (2014-2023) of stable water isotopes ( 𝛿 18𝑂 ) and meteorological records. Groundwater recharge elevations were estimated by comparing 𝛿 18𝑂 in rainfall and groundwater samples collected across an altitudinal gradient (3218-4055 m a.s.l.). The temporal dynamics of recharge were assessed by applying cluster analysis to the groundwater isotope data and by estimating rainfall thresholds required to initiate recharge. Results indicate that groundwater recharge predominantly occurs above 4100 m a.s.l. Rainfall exceeding 110 mm per month is required to initiate effective recharge. Notably, this threshold corresponds to the most humid months of April and May (Cluster 1). These findings highlight the role of high-altitude zones in sustaining groundwater recharge and suggest that groundwater recharge is a near-continuous process throughout the year, except during dry months. This study underscores the utility of stable isotopes as powerful tools to understand the hydrological connectivity between rainfall and groundwater, provides essential insights for improving water resource management and conservation strategies in páramo ecosystems.
Assessment of metal concentrations in High Andean Tropical rivers of southern Ecuador
(Universidad de Cuenca. Facultad de Ingeniería, 2025-10-02) Guamán Chalco, Gloria Verónica; Crespo Sánchez, Patricio Javier
High Andean tropical streams play a critical role in water provision. Although these ecosystems are generally pristine, few studies have quantified their water quality. This study assessed spatial variability and concentration–discharge (c–Q) relationships of major and minor solutes, as well as heavy metals concentrations in streams of southern Ecuador, using data collected between 2008 and 2021 across 28 monitoring sites. Major ions revealed a general trend of downstream enrichment. The Zhurucay catchment exhibited the highest concentrations of several heavy metals at Alumbre stream, which exceeded both national and international standards for drinking water and aquatic life. Principal Component Analysis (PCA) and k-means clustering identified three hydrochemical water types: (1) weakly mineralized waters, primarily in headwater sites, reflecting cation-poor lithology (2) Fe–Mn-rich waters related to wetlands, and (3) mineralized waters, primarily associated with downstream sites, likely influenced by groundwater and cation-rich lithology. Concentration– discharge relationships exhibited dilution behavior for Ca, Mg, Na, K, Sr, Ba, Rb, and electrical conductivity, whereas Al and Fe displayed mobilization patterns. In contrast, As, Pb, and Cd did not show a clear c–Q pattern. Elevated concentrations are likely associated with the volcanic origin of the region, influenced by both recent and past volcanic activity, including the presence of organic-rich soils and hydrothermally altered geological formations. Although Páramo ecosystems are widely recognized for their high-quality water, this research demonstrates that natural geological anomalies can introduce elevated metal concentrations. Therefore, it is crucial to establish baseline concentrations and assess natural variability for water management.
Aplicación de aprendizaje por refuerzo en la planificación de la expansión de los sistemas de transmisión
(Universidad de Cuenca, 2025-09-18) Llivisaca Mejia, Mateo David; Astudillo Salinas, Darwin Fabian; Torres Contreras, Santiago Patricio
Transmission Expansion Planning (TEP) is, from a mathematical point of view, a complex optimization problem and, in practice, a key tool for planning the efficient growth of the Electric Power System (EPS). With the constant increase in demand and generation capacity, if the transmission bottleneck is not solved, a proper operation of the system cannot be guaranteed. In this research, Reinforcement Learning (RL) is applied to solve the TEP through three approaches: the use of Q-learning, a learning-guided metaheuristic and deep reinforcement learning. In this framework, both Q-learning and RL-based metaheuristics learn online and use that knowledge locally. On the other hand, deep reinforcement learning methods, such as Deep Q-Network (DQN) and REINFORCE, allow reusable general policies to be learned, although they require a better representation of the state. This is achieved by modeling the power grid as a complex network and evaluating nodes using centrality-based metrics. The results show that the use of RL in the metaheuristic improves the exploration of the solution space. As for the deep learning approach, this first approach offers promising results: although in some cases optimal topologies are not reached, feasible plans are obtained that can serve as initial solutions in classical optimization schemes.
Extreme temperature events in the tropical Ecuadorian Andes: a comparative study of 2014-2022 vs 2023 and 2024
(Universidad de Cuenca, 2025-09-19) Acurio Vargas, Holguer Emmanuel; Córdova Mora, Mario Andrés; Célleri Alvear, Rolando Enrique
The rapid advance of climate change has made 2023 and 2024 the warmest years on record. However, global averages can mask marked contrasts at regional scales, especially in mountain ecosystems where complex topography modulates the thermal signal. The tropical Andes, key to biodiversity and water supply, are among the most sensitive and at the same time have short records that reveal these local variations. This study assessed recent variability in extreme temperature events along an altitudinal gradient (2600–3955 m a.s.l.) in the southern Ecuadorian Andes, comparing data from 2023–2024, the hottest years on record, with a reference period (2014-2022). Using daily temperature data derived from four automatic weather stations, we analyzed distributional characteristics, extreme temperature variability through ETCCDI indices, and changes in the frequency and intensity of warm and cold spells. Results revealed a positive shift in temperature distributions, with urban areas experiencing elevated nighttime minimums and upland sites showing stronger increases in daytime maximums. Extreme temperature indices showed a marked decrease in cold extremes (TN10p, TX10p) and an increase in warm events (TN90p, TX90p), particularly in 2024. In 2024 warm nights nearly tripled at the urban station (Balzay), while higher-altitude rural sites recorded over 100 days above the 90th percentile. Diurnal temperature range was higher in rural sites but lower in the city due to enhanced nocturnal heat retention. Heatwaves were more intense, while cold spells were weaker. These findings underscore the spatial heterogeneity of warming in mountain environments and highlight the role of elevation and urbanization.
Unraveling the Role of Groundwater in the Andean Páramo
(Universidad de Cuenca, 2025-09-15) Jerves Ramirez, Mateo Josue; Pesántez Vallejo, Juan Patricio
The Andean páramo is a critical ecosystem for regional downstream water supply. Understanding the often neglected role of groundwater in the páramo is challenging due to measurement constraints at depth in the rock. Drilling monitoring wells, collecting samples, and analyzing samples often require substantial economic resources. This study examines the connectivity between groundwater and surface water by integrating hydrometric and hydrochemical measurements from measured sources into a Bayesian mixing model. Results reveal that groundwater flows through bedrock fractures, contributing up to 12% of the total annual streamflow. Additionally, in terms of the contribution of groundwater to other hydrological units, groundwater makes 16–41% of the water in springs and 37–62% in Histosols during our study period. We also found that Histosols can be differentiated into groundwater-fed, receiving water from below 20 meters, and rainfall-fed, receiving contributions from hillslope flow. Groundwater is crucial in regulating baseflow in the study catchment, accounting for up to 12.3% of streamflow at the catchment outlet via direct contribution during dry periods. Groundwater also sustains groundwater-fed Histosols and springs during dry periods, accounting for up to 62% and 41% of their total water mixture. Considering the contribution of groundwater-fed Histosols and springs to streamflow during dry periods, the total contribution of groundwater to streamflow results in 49.8%. Due to critically sustained baseflow during dry periods, a holistic understanding of the hydrological system, which includes both deep and shallow groundwater, is necessary to address the increasing water scarcity, prolonged droughts, and changing precipitation patterns.
Modelamiento aproximado de sistemas dinámicos a través del operador de Koopman
(Universidad de Cuenca, 2025-06-23) Villarreal Esquivel, Marcos Lenin; Minchala Ávila, Luis Ismael; Durán Siguenza, Juan Francisco
Systems modeling has enabled better understanding and solving of complex real-world problems, which are computationally expensive. In this context, data-driven modeling employs surrogate modeling approaches to reduce problem dimensionality and improve computational efficiency. This work focuses on data-driven modeling of nonlinear dynamic systems, to obtain models that allow the detection and diagnosis of faults in dynamic multiple-input multiple-output (MIMO) systems. The starting point of the research is the Koopman operator, whose application is explored in combination with different Dynamic Mode Decomposition (DMD) approaches. The modeling methodology of this research involves evaluating methods such as Hankel Alternative View of Koopman (HAVOK) and Hankel-DMDc, to obtain a correct model for fault detection in MIMO systems. The results obtained from this research, in a test system composed of a system of two interconnected tanks, show that the developed model achieves an adequate adjustment concerning the real behavior of the system and allows not only an effective prediction of its dynamics but also a correct leak detection.
Desarrollo de un sistema de control centralizado aplicado a la marcha bípeda de un exoesqueleto robótico de extremidades inferiores
(Universidad de Cuenca, 2025-05-05) Garcia Reino, Sebastian Alejandro; Minchala Ávila, Luis Ismael; Calle Siguencia, John Ignacio
The development of robotic exoskeletons has experienced remarkable progress in recent years, beco-ming a key technology for the assistance and rehabilitation of people with reduced mobility. However, one of the main challenges remains ensuring a stable and natural bipedal gait. This requires the design of robust and accurate control algorithms, as well as the efficient integration of sensors and actuators for real-time estimation and control. In this work, a centralized nonlinear model predictive control (NMPC) system was simulated and validated. Multibody modeling in Simulink was used to represent the exos-keleton’s dynamics. Additionally, experimental validation of inertial sensors designed by the Research Group on Electronics and Control at the University of Cuenca was carried out. The results show that the NMPC controller significantly outperforms the PID controller in tracking the hip and knee joint references, achieving lower values for mean squared error (MSE), mean absolute error (MAE), and cumulative error metrics (IAE and ISE). Notably, NMPC demonstrated greater adaptability to temporal variations in the gait cycle, maintaining high accuracy even under demanding conditions, which highlights its potential for future applications in real-world environments.
Impact of the conservation mechanism to supply water to community drinking water systems and irrigation systems in rural Andean regions and its relationship with the Sustainable Development Goals
(Universidad de Cuenca, 2025-04-07) Carvajal Arizábala, Johanna Gabriela; Sucozhañay Calle, Adrián Esteban; Célleri Alvear, Rolando Enrique; Timbe Castro, Luis Manuel
The conservation of ecosystems is key to ensuring the availability of natural resources like water, a critical service for sustaining human activities. However, the impact of conservation on human well-being remains uncertain. This study explores the links between water provision, local activities, and Sustainable Development Goals (SDGs), focusing on the rural Andean community of El Carmen de Jadán, Azuay, Ecuador. This community, located downstream of the Aguarongo Protected Forest (APF), depends on water from headwaters for agriculture, livestock, and daily needs. Conservation efforts since the 1990s have helped secure this resource. We developed a storyline to build a conceptual framework integrating water provision, respondents’ activities, and personal and community goals. Then, we surveyed 55 water users and analyzed the results using two indices: Level of Support for Contribution (LSC) and Importance of Contribution (IC). A network analysis of high LSC and IC values revealed co-occurrences among components. Results show that the activities most linked to water are human consumption (44–52 responses), followed by livestock (29–37), agriculture (24–29), and ancestral health practices (28). Human consumption was related to SDG targets 2.4, 6.1, 6.4, 6.6, 12.8, 13.3, 15.2, and 15.4 (346–416 connections). Agriculture, livestock, and ancestral health practices were linked to all targets analyzed, including 1.1, 1.2, 2.1, and 2.4 (253–308, 220–427, and 286 connections). These findings underscore the connection between ecosystem conservation, livelihoods, and global goals. Strategies such as irrigation optimization, water monitoring, and community participation can enhance water management and promote local well-being.
Efectos de las condiciones meteorológicas extremas en los patrones de los ciclos diarios de los árboles de Polylepis reticulata
(Universidad de Cuenca, 2025-03-25) Poma Tene, Byron Rodrigo; Carabajo Hidalgo, Aldemar Emmanuel
Polylepis forests grow in the high Andes, forming the world's highest tree line while adapting to extreme climatic conditions. Despite their ecological significance, the daily patterns of stem cycles remain understudied. From 2018 to 2022, we monitored a Polylepis reticulata forest in the Ecuadorian Andes, utilizing high-resolution dendrometers to assess stem cycle responses to climatic events in large (LD) and small (SD) diameter classes. A peak threshold approach identified extreme events based on vapor pressure deficit (VPD). We employed multiple linear regression (MLR) to pinpoint key environmental factors influencing daily maximum stem shrinkage (MDS) and used random forest (RF) and regression tree (RT) techniques to determine growth drivers. During cold events, stem shrinkage was minimal, contributing 30% to annual growth, whereas warm events exhibited pronounced shrinkage, contributing less than 1%. The primary driver of MDS was maximum daily VPD, followed by precipitation. VPD is the main driver in radial growth, when VPD is <0.048 kPa higher growth rate was observed. The various responses to extreme conditions and the drivers of stem fluctuation provide key information on the possible impacts on these forests, affecting their development and adaptive capacity in the future.
Socio-hydrological strategies for drought management in Andean irrigation systems
(Universidad de Cuenca, 2025-03-17) Bermeo Avendaño, María Augusta; Célleri Alvear, Rolando Enrique
Using a combination of soft data from water user association members and water management modeling, several low-effort actions have been identified (e.g., implementing sprinkler irrigation, installing micro-reservoirs, or switching from unlined open channels to pipelines) that significantly improve irrigation conditions in critical situations. Water savings would allow an increase in the irrigated area between 6% to 42% if these actions are implemented individually and in combination with increasing between 15% and 187%. Prioritizing community involvement in developing irrigation solutions enhances sustainability and ensures that these solutions are practical and more likely to be embraced by the community.
Modelo optimización robusta para la planificación de la topología de un sistema de distribución a gran escala
(Universidad de Cuenca, 2025-03-10) Cando Naula, Diego Jonnathan; Torres Contreras, Santiago Patricio
The integration of technologies such as distributed energy resources, microgrids, and smart grids has significantly transformed the design and operation of distribution networks, requiring new planning models that ensure efficiency and continuity of supply. The lack of access to detailed data from real distribution networks motivates this project, which proposes synthetic networks that replicate real-world characteristics without exposing sensitive information. To achieve this goal, geographic information systems, graph theory, and network statistics are employed to design both secondary and primary distribution systems. In this context, the algorithms define service drops, locate and size distribution transformers, secondary network layouts, structure primary feeders, and position support elements. Within the secondary system, length and proximity constraints are enforced using a KD-Tree to optimize spatial organization, alongside a DFS-P algorithm that merges depth-first search with tree pruning. This methodology places transformers under spatial constraints and avoids unrealistic configurations. For the primary distribution system, minimum spanning trees and optimal routes are devised based on distances among substations, load nodes, and distribution transformers. The distribution system design incorporates street and load maps, processed to correct geometric and attribute inconsistencies. Finally, the algorithms were implemented in an area served by Empresa Eléctrica Regional Centro Sur C.A., demonstrating that this methodology yields realistic and robust networks with statistics comparable to realistic systems.
Aplicación de algoritmos de agrupamiento para la optimización de tiempos de ejecución y eficiencia en algoritmos relacionados a problemas de planificación de sistemas de suministro de energía eléctrica
(Universidad de Cuenca, 2025-02-21) Cando Naula, Paúl Marcelo; Sanango Fernández, Juan Bautista
In the context of increasing electrical demand and the integration of new technologies, planners must adapt and optimize the grid to ensure efficient and reliable distribution. However, the complexity of so- lution methods used in electric power system planning (EPSP) at all stages can result in excessive execution times. To mitigate these challenges, this study presents a comparison of different clustering algorithms through an approach that restricts the number of groups based on a group weight limit. The evaluated algorithms include hierarchical, partitional, and density-based approaches. The methodology is applied to distribution expansion planning (DEP) at medium voltage and sub-transmission levels th- rough substation expansion planning (SEP), which employs a binary integer linear programming (BILP) model. Additionally, a partitional algorithm is used to address the problem of assigning load nodes to electrical infrastructures. For both contexts, synthetic case studies extracted from specialized literature are adopted. The results demonstrate that these size-restricted clustering techniques significantly opti- mize solution times by reducing the size of the input data set, usually composed of load nodes, through the application of technical criteria.
Propuesta de un modelo de planificación óptima de redes inteligentes (Smart Grids) incluyendo integración eficiente de recursos energéticos distribuidos (DER), aplicada a una red de distribución de la CENTROSUR
(Universidad de Cuenca, 2024-11-06) Villacrés Enríquez, Luis Ricardo; Pesántez Sarmiento, Patricio Antonio
The grid has been overwhelmed with extreme weather events occurring with increasing frequency, with the only practical solution being to de-energize lines and interrupt power supply to many customers. Recent advances in the distribution grid, including the integration of Distributed Energy Resources (DER) and Microgrids, provides potential means to improve the operational resilience of the grid. For this reason, in this thesis it was proposed to develop an Electric Distribution Planning Methodology considering the efficient integration of Distributed Energy Resources (DER), especially related to Charging Stations for Electric Vehicles, Induction Stoves and Distributed Generation. It was supported by Stochastic Models, Optimization Techniques, Geographic Information Systems, and Technical Analysis Systems, in order to optimize the investment and perform an adequate operation of the electric grid. In this new expansion planning, a long-term time frame was defined with a projected number of electric vehicles, which was divided by means of scenarios, where the optimal location, capacity and number of Fast Charging Stations and Distributed Generation installed in the feeder's medium voltage were obtained, that is, the expansion operation of the Smart Grid was analyzed. This methodology was applied to a test network and then to a use case of the network of Empresa Electrical Regional CENTROSUR, and some alternatives were proposed to evaluate and make the best decision.
Implementación en ATP de benchmark IEEE 39 barras incluyendo modelos genéricos de generación fotovoltaica para estudios de integración de energías renovables a la red
(Universidad de Cuenca, 2024-10-07) Dután Amay, Paúl Iván; Dután Amay, Walter Javier
The increase in electrical energy consumption requires the study and development of different generation technologies that allow supplying demand with efficiency, quality and safety. The work presents a contribution to the analysis of the dynamic response of an electrical power system to the input and output of photovoltaic generation in the Alternative Transients Program (ATP) software, which is of the EMT (Electromagnetic Transient) type, considering an adequate level detail of its components that allow analysis using effective values - RMS. For this, the 39-bar IEEE test model is implemented with the respective control systems of the synchronous machines, using IEEE models implemented through TACS. The approach of this work allows us to analyze the response of an electrical system that has conventional generation units, to the entry of generation based on sources that are connected by inverters. The entry of large blocks of this type of generation reduces the inertia of the system and power reserves which, in dynamic events, can lead to a loss of the system due to frequency. From this point of view, frequency response analysis is important to determine the amount of inverter-based generation that can be connected to a grid. A simulated power system in the ATP software allows it to be studied at a high level of detail and precision, obtaining response signals in the phase domain. This allows the model to be used for the analysis of slow transients and fast transients, contributing to the research of new technologies in generation. Photovoltaic systems are currently more accessible, so their integration into the SEP requires appropriate models for research and studies. Having the models, as well as the system and its integration in this type of software, allows having a detailed reference scenario for EMT studies of a power system.
Estrategia para el modelamiento de productos y servicios financieros sostenidos en tecnologías de la información para la Cooperativa de Ahorro y Crédito Jardín Azuayo
(Universidad de Cuenca, 2024-10-02) Ávila Calle, José David; Pesántez Salas, Pablo Leonardo
Services in the Ecuadorian financial market maintain the traditional goal of capital: maximizing profits. With our proposal, we seek to consolidate fair distribution and redistribution. Financial service and product offerings in areas distant from urban centers do not generate profits; therefore, they have not grown and have caused economic and social imbalance. In the second stage of our thesis, we gather the real needs in these sectors; this essential input supports the participatory analysis and design of a model coherent with the context, to consequently incorporate people and economies into the cooperative financial system. Technology and information technology create sufficient possibilities for the distribution of services; undoubtedly, financial services through computer and mobile applications allow for significant coverage, adapting business and service modeling as the main focus of our next stage, and concluding with a method technically modeled and adjusted to the contextual characteristics of our country, the territorial idiosyncrasy, and the organizational structure of the common good for the sustainable construction of financial services mainly, and that contribute to social inclusion through economic inclusion; our model, from its conception, is free to use to incorporate services and products aimed at reducing gaps. With the knowledge acquired in the Master’s program, the experience in Technology Management at the work level, and the validation of the method by the tactical area of Jardín Azuayo, the Self-Service ATM was built. Its impact and growth over time corroborate the initial expectations; there is another way to do cooperation as an alternative to the traditional economic, financial, and social system.
Satellite precipitation prediction using GOES-16 data and Convolutional Neural Networks
(Universidad de Cuenca, 2024-09-30) Vélez Hernández, Efraín Mateo; Muñoz Pauta, Paul Andrés; Célleri Alvear, Rolando Enrique
Real-time precipitation information is critical for effective basin monitoring and responding to hazardous events like storms, floods, and landslides. In regions with a complex topography and limited ground-based measurements, reliable real-time data is scarce, hindering decision-making. Satellite Precipitation Products (SPPs) have emerged as valuable data to overcome these limitations, offering precipitation estimates in instances where information is either insufficient or unavailable. Despite their utility, SPPs are constrained by latency, typically spanning several hours. Latency causes the omission of possible precipitation events during this interval. This study addresses the latency gap challenge by developing a model that predicts near-instantaneous IMERG-ER SPP using a U-Net-based Convolutional Neural Network (CNN) and infrared data from the GOES-16 geostationary satellite. Five years of hourly data (2019-2023) were used, with the first four for training and the last year for testing. The used band combination was 6.2, 6.9, 7.3, 8.4, and 11.2 μm wavelengths. The model yielded predicted SPPs with an approximate latency of 11 minutes, exhibiting an RMSE of 0.46 mm/h, a Pearson Correlation Coefficient of 0.60, a bias of -0.007 mm/h, and a Critical Success Index of 0.53. While the model performed well in predicting frequent low-intensity precipitation, it struggled with high-intensity values. These shortcomings can be attributed to data imbalance and model regularization procedures. The results highlight the potential of the proposed approach for providing a timely spatial precipitation prediction, particularly in regions where ground-based data is scarce.
Difference in the amount and meteorological patterns in the highlands and lowlands in the Galápagos Archipelago
(Universidad de Cuenca, 2024-10-01) Tenelanda Patiño, Pablo Andrés; Célleri Alvear, Rolando Enrique; Orellana Alvear, Johanna Marlene
Precipitation variability in the Galápagos Islands is crucial for climate change adaptation, biodiversity conservation and water resource management. This study aims to compare the event-scale precipitation characteristics (ESPC), such as intensity, duration and rainfall accumulation at different altitudes during ENSO from 2022 to 2024 on Santa Cruz Island. Precipitation data were used from a new network of automatic weather stations (AWS) installed at five sites: 2, 422 and 849 m a.s.l. on the windward side, and 22 and 619 m a.s.l. on the leeward side. The analysis included two phases: La Niña (April 2022 - January 2023) and El Niño (June 2023 - April 2024). Comparisons was made in two ways: first, the different altitudes within each phase were compared, and second, the two phases were compared at each altitude. For comparison, the distribution of each ESPC and the Mann-Whitney U-test were used to determine whether the differences were significant. For each ENSO phase, less intense and longer duration events occurred at the highest altitude of 849 m a.s.l. Outliers in each ESPC were significantly higher and more frequent during El Niño, especially on the windward side. This study provides a detailed analysis of precipitation characteristics and their variation according to ENSO phases, providing valuable insights for biodiversity conservation and water resource management on the island.
Assessing the Effectiveness of the Three-Cornered Hat Data Fusion Technique for Satellite Precipitation Data and Its Impact on Runoff Forecasting
(Universidad de Cuenca, 2024-10-01) Luna Abril, Patricio Javier; Muñoz Pauta, Paul Andrés; Célleri Alvear, Rolando Enrique
Runoff forecasting remains a critical challenge in complex basins around the world, where data scarcity and detection problems limit the forecasting performance. Data fusion offers a promising alternative, with the potential to generate enhanced satellite precipitation datasets for use in data-driven runoff forecasting models. This study investigates the effectiveness of the Three-Cornered Hat (TCH) method for fusing satellite precipitation datasets and its impact on runoff forecasting. The TCH method was applied to three satellite precipitation products (SPP), creating a fused dataset that was compared to two benchmark products: IMERG-ER and MSWEP. While the TCH method demonstrated suitability for forecasting in data-scarce regions, it did not outperform the benchmark products, showing comparable results to IMERG- ER. Interestingly, MSWEP exhibited superior performance across different lead times, suggesting that the fusion of multiple precipitation data sources may enhance the performance of runoff forecasting models. The study highlights a key limitation of the TCH method at fine temporal scales. In certain conditions, data may be considered statistically dependent, which could have an adverse effect on the effectiveness of the method. Future research should focus on resolving these limitations and exploring the potential of integrating diverse data sources to unlock further improvements in runoff forecasting.
Modified irrigation sustainability index for the assessment of irrigation systems in low impact agricultural schemes
(Universidad de Cuenca, 2024-09-30) Moreno Contreras, Elizabeth Fernanda; Rivas Tabares, David Andrés; Célleri Alvear, Rolando Enrique
Water is vital for sustainability, supporting life, agriculture, and ecosystem balance. Sustainable irrigation is crucial for conserving environmental resources such as soil and water. Thus, accurately measuring irrigation sustainability is imperative. The Irrigation Sustainability Index (ISI) is a method designed to quantify this effectiveness, enabling comparisons and adaptability across various systems. However, it overlooks a critical aspect of sustainability: irrigation technology. To address this gap, the Modified Irrigation Sustainability Index (MISI) has been developed. MISI incorporates four components: i) Biogeographic Data: Includes information on catchment areas, slope, land use, and irrigation zones, ii) Socio-Demographic Data: Covers potential and existing water-related social conflicts, social organization issues, irrigation shifts, payments, and water rights, iii) Institutional Data: Encompasses administrative support, financing, and related projects, and iv) Technological Data: Details the system type, irrigation methods, reservoir infrastructure, and network materials. The MISI calculation customizes the weights of factors and components for specific systems, enhancing accuracy and adaptability. This index offers a more precise evaluation for different systems, particularly in the realm of low-impact agriculture, which has been underexplored. The results showed that most MISI values fell into the low to medium range. Comparisons with the adapted ISI revealed significant differences, highlighting MISI's value in identifying irrigation system deficiencies. By reflecting the true state of irrigation sustainability and considering intermediate factors, MISI offers crucial insights for decision-making. Its inclusion of the technological component proved instrumental in refining the evaluation. MISI is thus a valuable for monitoring and addressing irrigation challenges, supporting the Sustainable Development Goals (SDG).

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