Examinando por Autor "Morales, Yerel"

Mostrando 1 - 3 de 3
  • Miniatura
    Ítem
    A self-identification Neuro-Fuzzy inference framework for modeling rainfall-runoff in a Chilean watershed
    (Elsevier, 2021) Morales, Yerel; Querales, Marvin; Rosas, Harvey; Allende-Cid, Hector; Salas, Rodrigo
    Modeling the relationship between rainfall and runoff is an important issue in hydrology, but it is a complicated task because both the high levels of complexity in which both processes are embedded and the associated uncertainty, affect the forecasting. Neuro-fuzzy models have emerged as a useful approach, given the ability of neural networks to optimize parameters in a fuzzy system. In this work a Self-Identification Neuro-Fuzzy Inference Model (SINFIM) for modeling the relationship between rainfall and runoff on a Chilean watershed is proposed to reduce the uncertainty of selecting both the rainfall and runoff lags and the number of membership functions required in a fuzzy system. The data comes from the Diguillín river located in Ñuble region and average daily runoff and average daily rainfall recorded from years 2000 to 2018, according to the Chilean directorate of water resources (DGA). In addition, we worked with the Colorado River basin, located in the Maule region, to validate the method developed. The experimental results showed a good adjustment using the last 3 years as validation set, further improvement was achieved using only the last year was used as validation test, obtaining 84% of and Kling Gupta Efficiency, higher than other forecasting models such as Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial neural networks (ANN), and Long Short-Term Memory (LSTM) approach. In addition, Nash-Sutcliffe efficiency and percent BIAS indicate the method is a promising model. On the other hand, even better results were obtained in the validation basin, whose adjustment was 94% and an efficiency of 97%. Therefore, the proposed model is a solid alternative to forecast the runoff in a given watershed, obtaining good performance measurements, managing to predict both the low and peak runoff values from rainfall events, avoiding the requirement to determine a priori the lags of time series and the number of fuzzy rules.
  • Miniatura
    Ítem
    Addressing the Effects of Climate Change on Modeling Future Hydroelectric Energy Production in Chile
    (MDPI, 2021) Gil, Esteban; Morales, Yerel; Ochoa, Tomás
    Despite the growing scientific evidence, the electricity market models used in Chile do not consider the effects of climate change on hydroelectric energy production. Based on a statistical analysis of the historical hydro-energy inflow dataset and a revision of the scientific literature, we suggest a set of technical and statistical criteria to determine an alternative representation of the hydro-energy uncertainty in the Chilean electricity market. Based on these criteria, we then propose an alternative range of historical hydrological data, which is built by shedding the first 35 years of the historical dataset (out of 59 years) and using only a reduced subset of 24 years. Additionally, we propose to capture the potential impacts of even more prolonged droughts on the Chilean electricity system by repeating the last nine years of data at the end of the 24 year-long series. The resulting extended subset of 33 hydro-years is approximately 10% drier on average than the original dataset of 59 years. The proposed range of hydrological data captures some of the anticipated effects of climate change on Chilean hydro-uncertainty reported in the literature and also preserves most of the intra-annual and spatial diversity of the original data.
  • Miniatura
    Ítem
    Uso del modelo QDM modificado en una cuenca con escasa información hidrometeorológica en el sur de Chile
    (Universidad de Chile. Departamento de Ingeniería Civil, 2021) Morales, Yerel
    El análisis sobre la disponibilidad de recursos hídricos es una constante en la actualidad y para dar respuesta a las preguntas asociadas a ello, la modelación hidrológica es una herramienta de gran utilidad. Hoy en día existe una gran variedad de modelos hidrológicos, cada vez más detallados y específicos, pero ¿qué pasa cuando la información disponible es escaza o el tiempo de puesta en marcha es acotado? En el presente artículo se describe el modelo QMD Modificado, un modelo agregado, conceptual y que representa el proceso precipitación escorrentía a nivel diario, el cual se utilizó para simular los caudales de la cuenca del río Lirquén en Cerro El Padre utilizando 2 años de calibración y una validación que comprende 10 años consecutivos, entregando resultados de NS en torno a los 0.7 tanto para calibración como para validación. A partir de lo anterior se concluye que el modelo QMD es una alternativa viable en cuencas con morfología regular.