Person:
Célleri Alvear, Rolando Enrique

Birth Date

1975-04-07

ORCID

0000-0002-7683-3768

Scopus Author ID

15060963700

Afiliación

Universidad de Cuenca, Cuenca, Ecuador
Universidad de Cuenca, Departamento de Recursos Hídricos y Ciencias Ambientales, Cuenca, Ecuador
Universidad de Cuenca, Facultad de Ingeniería, Cuenca, Ecuador
Universidad de Cuenca, Facultad de Ciencias Agropecuarias, Cuenca, Ecuador

Organizational Units

Organizational Unit

Facultad de Ingeniería

La Facultad de Ingeniería, a inicios de los años 60, mediante resolución del Honorable Consejo Universitario, se formalizó la Facultad de Ingeniería de la Universidad de Cuenca, conformada por las escuelas de Ingeniería Civil y Topografía. Esta nueva estructura permitió una mayor especialización y fortalecimiento en áreas clave para el desarrollo regional. Cuenta con programas académicos reconocidos internacionalmente, que promueven y lideran actividades de investigación. Aplica un modelo educativo centrado en el estudiante y con procesos de mejora continua. Establece como prioridad una educación integra, la formación humanística es parte del programa de estudios que complementa a la sólida preparación científico-técnica. Las actividades culturales pertenecen a un programa permanente y activo al interior de nuestras dependencias, a la par de proyectos que desde el alumnado y bajo la supervisión de docentes cumplen con servicios de apoyo a nivel local y regional; promoviendo así una vinculación estrecha con la comunidad.

Job Title

Profesor (T)

Last Name

Célleri Alvear

First Name

Rolando Enrique

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Now showing 1 - 10 of 23

Quantification of rainfall interception in the high Andean tussock grasslands
(2018) Ochoa Sanchez, Ana Elizabeth; Célleri Alvear, Rolando Enrique; Crespo Sánchez, Patricio Javier
The páramo ecosystem provides most of the water for the tropical Andean highlands in South America. Although the comprehension of this environment has increased lately, there remains an urgent need to quantify the processes involved in the hydrological cycle. Interception loss (IL) is one of the least studied processes in the páramo, and more generally, in grasslands globally. The main objective of this study was to quantify IL at event scale by estimating it indirectly from precipitation (P) and effective rainfall (ER). Furthermore, the following questions were assessed(a) how much of the P becomes ER?(b) what is the impact on IL calculations of using a rain gauge instead of a disdrometer?(c) which meteorological variables are related to the IL process? and (d) is it possible to estimate IL from meteorological variables? High percentages of IL in relation to P were found (10 …
Probabilistic forecasting of drought events using Markov chain- and Bayesian network-based models: A case study of an Andean regulated river basin
(MDPI AG, 2016-01-01) Avilés Añazco, Alex Manuel; Célleri Alvear, Rolando Enrique
The scarcity of water resources in mountain areas can distort normal water application patterns with among other effects, a negative impact on water supply and river ecosystems. Knowing the probability of droughts might help to optimize a priori the planning and management of the water resources in general and of the Andean watersheds in particular. This study compares Markov chain- (MC) and Bayesian network- (BN) based models in drought forecasting using a recently developed drought index with respect to their capability to characterize different drought severity states. The copula functions were used to solve the BNs and the ranked probability skill score (RPSS) to evaluate the performance of the models. Monthly rainfall and streamflow data of the Chulco River basin, located in Southern Ecuador, were used to assess the performance of both approaches. Global evaluation results revealed that the MC-based models predict better wet and dry periods, and BN-based models generate slightly more accurately forecasts of the most severe droughts. However, evaluation of monthly results reveals that, for each month of the hydrological year, either the MC- or BN-based model provides better forecasts. The presented approach could be of assistance to water managers to ensure that timely decision-making on drought response is undertaken.
Evaluation of Markov Chain Based Drought Forecasts in an Andean Regulated River Basin Using the Skill Scores RPS and GMSS
(KLUWER ACADEMIC PUBLISHERS, 2015-01-01) Avilés Añazco, Alex Manuel; Célleri Alvear, Rolando Enrique
On behalf of the decision-makers of Andean regulated river basins a drought index was developed to predict the occurrence and extent of drought events. Two stochastic models, the Markov Chain First Order (MCFO) and the Markov Chain Second Order (MCSO) model, predicting the frequency of monthly droughts were applied and the performance checked using two skill scores, respectively the ranked probability score (RPS) and the Gandin-Murphy skill score (GMSS). Data of the Chulco River basin (3200–4300 m.a.s.l.), situated in the Ecuadorian southern Andes, were employed to test the performance of both models. Results indicate that events with greater drought severity were more accurately predicted. The study also revealed the importance of verifying the quality of the forecasts and to have an assessment of the likely performance of the forecasting models before adopting any model and accepting the resulting information for decision-making.
Rain gauge inter-comparsion quantifies differences in precipitation monitoring
(2020) Padrón Flasher, Ryan Sebastián; Feyen Null, Jan Null; Córdova Mora, Mario Andrés; Crespo Sánchez, Patricio Javier; Célleri Alvear, Rolando Enrique
Efforts to correct precipitation measurements have been ongoing for decades, but are scarce for tropical highlands. Four tipping-bucket (TB) rain gauges with different resolution that are commonly used in the Andean mountain region were compared-one DAVIS-RC-II, one HOBO-RG3-M, and two TE525MM TB gauges (with and without an Alter-Type wind screen). The relative performance of these rain gauges, installed side-by-side in the Zhurucay Ecohydrological Observatory, south Ecuador, at 3780 m a.s.l., was assessed using the TB with the highest resolution (0.1 mm) as reference, i.e. the TE525MM. The effect of rain intensity and wind conditions on gauge performance was estimated as well. Using 2 years of data, results reveal that (i) the precipitation amount for the reference TB is on average 5.6 to 7.2% higher than the rain gauges having a resolution of 0.2 mm and 0.254 mm respectively; (ii) relative underestimation of precipitation from the gauges with coarser resolution is higher during low-intensity rainfall mounting to a maximum deviation of 11% was observed for rain intensities ≤1 mm h−1 ; (iii) precipitation intensities of 2 mm h−1 or less that occur 75% of the time cannot be determined accurately for timescales shorter than 30 minutes because of the gauges’ resolution, e.g. the absolute bias is >10%; and (iv) wind has a similar effect on all sensors. This analysis contributes to increase the accuracy and homogeneity of precipitation measurements throughout the Andean highlands, by quantifying the key role of rain-gauge resolution.
Dynamic mapping of evapotranspiration using an energy balance-based model over an andean páramo catchment of southern ecuador
(MDPI AG, 2016-01-01) Carrillo Rojas, Galo José; Célleri Alvear, Rolando Enrique; Córdova Mora, Mario Andrés
Understanding of evapotranspiration (ET) processes over Andean mountain environments is crucial, particularly due to the importance of these regions to deliver water-related ecosystem services. In this context, the detection of spatio-temporal changes in ET remains poorly investigated for specific Andean ecosystems, like the páramo. To overcome this lack of knowledge, we implemented the energy-balance model METRIC with Landsat 7 ETM+ and MODIS-Terra imagery for a páramo catchment. The implementation contemplated adjustments for complex terrain in order to obtain daily, monthly and annual ET maps (between 2013 and 2014). In addition, we compared our results to the global ET product MOD16. Finally, a rigorous validation of the outputs was conducted with residual ET from the water balance. ET retrievals from METRIC (Landsat-based) showed good agreement with the validation-related ET at monthly and annual steps (mean bias error <8 mm. month-1 and annual deviation <17%). However, METRIC (MODIS-based) outputs and the MOD16 product were revealed to be unsuitable for our study due to the low spatial resolution. At last, the plausibility of METRIC to obtain spatial ET retrievals using higher resolution satellite data is demonstrated, which constitutes the first contribution to the understanding of spatially-explicit ET over an alpine catchment in the neo-tropical Andes.
Evaluation of the Penman-Monteith (FAO 56 PM) Method for Calculating Reference Evapotranspiration Using Limited Data
(INTERNATIONAL MOUNTAIN SOCIETY, 2015-08-01) Córdova Mora, Mario Andrés; Carrillo Rojas, Galo José; Célleri Alvear, Rolando Enrique; Crespo Sánchez, Patricio Javier
(Figure Presented) Reference evapotranspiration (ETo) is often calculated using the Penman-Monteith (FAO 56 PM; Allen et al 1998) method, which requires data on temperature, relative humidity, wind speed, and solar radiation. But in high-mountain environments, such as the Andean páramo, meteorological monitoring is limited and high-quality data are scarce. Therefore, the FAO 56 PM equation can be applied only through the use of an alternative method suggested by the same authors that substitutes estimates for missing data. This study evaluated whether the FAO 56 PM method for estimating missing data can be effectively used for páramo landscapes in the high Andes of southern Ecuador. Our investigation was based on data from 2 automatic weather stations at elevations of 3780 m and 3979 m. We found that using estimated wind speed data has no major effect on calculated ETo but that if solar radiation data are estimated, ETo calculations may be erroneous by as much as 24%; if relative humidity data are estimated, the error may be as high as 14%; and if all data except temperature are estimated, errors higher than 30% may result. Our study demonstrates the importance of using high-quality meteorological data for calculating ETo in the wet páramo landscapes of southern Ecuador.
Near-surface air temperature lapse rate over complex terrain in the Southern Ecuadorian Andes: Implications for temperature mapping
(Institute of arctic and alpine research, 2016-11-01) Córdova Mora, Mario Andrés; Abril Orellana, Olmedo Andrés; Carrillo Rojas, Galo José; Célleri Alvear, Rolando Enrique; Orellana-Alvear, J
Near-surface air temperature variation with altitude (Tlr) is important for several applications including hydrology, ecology, climate, and biodiversity. To calculate Tlr accurately, a dense monitoring network over an altitudinal gradient is needed. Typically, meteorological monitoring in mountain regions is scarce and not adequate to calculate Tlr correctly. To overcome this problem in our region, we monitored temperature over a gradient ranging 2600-4200 m a.s.l. during an 18 month period. Using these data, we calculated Tlr for the first time at this altitude in the Andes and tested the impact of using the standard Tlr values instead of the observed ones to map temperature by means of the MTCLIM model. We found that annual lapse rate values (6.9 °C km-1 for Tmean, 5.5 °C km-1 for Tmin, and 8.8 °C km-1 for Tmax) differ significantly from the MTCLIM default values and that temperature maps improved vastly when measured Tlr was entered, especially for Tmax and Tmin. Our results may be representative of the broader area, as Tlr in our study period is not affected by microclimatic conditions generated by differences in topography and land cover between our monitoring sites; moreover, observed temperature during our study period was found to be representative of the longer-term annual climatology of the region.
Wavelet analyses of neural networks based river discharge decomposition
(2020) Palacio Baus, Kenneth Samuel; Crespo Sánchez, Patricio Javier; Célleri Alvear, Rolando Enrique; Mosquera Rojas, Giovanny Mauricio; Mendoza Sigüenza, Daniel Emilio; Campozano Parra, Lenin Vladimir
The problem of discharge forecasting using precipitation as input is still very active in Hydrology, and has a plethora of approaches to its solution. But, when the objective is to simulate discharge values without considering the phenomenology behind the processes involved, Artificial Neural Networks, ANN give good results. However, the question of how the black box internally solve this problem remains open. In this research, the classical rainfall‐runoff problem is approached considering that the total discharge is a sum of components of the hydrological system, which from the ANN perspective is translated to the sum of three signals related to the fast, middle and slow flow. Thus, the present study has two aims (a) to study the time‐frequency representation of discharge by an ANN hydrologic model and (b) to study the capabilities of ANN to additively decompose total river discharge. This study adds knowledge to the open problem of the physical interpretability of black‐box models, which remains very limited. The results show that total discharge is adequately simulated in the time frequency domain, although less power spectrum is evident during the rainy seasons in the ANN model, due to fast flow underestimation. The wavelet spectrum of discharge represents well the slow, middle and fast flow components of the system with transit times of 256, 12–64 and 2–12 days, respectively. Interestingly, these transit times are remarkably similar to those of the soil water reservoirs of the studied system, a small headwater catchment in the tropical Andes. This result needs further research because it opens the possibility of determining MMT on a fraction of the cost of isotopic based methods. The cross‐power spectrum indicates that the error in the simulated discharge is more related to the misrepresentation of the fast and the middle flow components, despite limitations in the recharge period of the slow flow component. With respect to the representation of individual signals of the slow, middle and fast flows components, the three neurons were uncapable to individually represent such flows. However, the combination of pairs of these signals resemble the dynamics and the spectral content of the aforementioned flows signals. These results show some evidence that signal processing techniques may be used to infer information about the hydrological functioning of a basin.
The breathing of the andean highlands: net ecosystem exchange and evapotranspiration over the páramo of southern Ecuador
(2019) Carrillo Rojas, Galo José; Silva, Brenner; Rollenbeck, Rütger; Célleri Alvear, Rolando Enrique; Bendix, Jorg
Atmospheric carbon (CO 2) exchange, evapotranspiration (ET) processes, and their interactions with climatic drivers across tropical alpine grasslands are poorly understood. This lack of understanding is particularly evident for the páramo, the highest vegetated frontier in the northern Andes, the main source of water for inter-Andean cities, and a large carbon storage area. Studies of CO 2 and ET fluxes via the standard Eddy Covariance (EC) technique have never been applied to this region, limiting the understanding of diurnal / nocturnal exchanges and budget estimations. In this paper, we report the first EC analysis conducted on the Andean páramo (3765 m a.s.l.); this analysis measured CO 2, ET, and micrometeorological variables over two years (2016–2018) to understand their interactions with climatic / biophysical controls. The páramo was found to be a source of CO 2 and exhibited a net positive exchange …
Evaporation dynamics and partitioning in Andean tussock grasslands
(Ed, 2022) Célleri Alvear, Rolando Enrique; Ochoa Sánchez, Ana Elizabeth; Crespo Sánchez, Patricio Javier; Carrillo Rojas, Galo José; Sucozhañay Calle, Adrián Esteban; Marín Molina, Franklin Geovanny; Ochoa Sánchez, Ana Elizabeth
The paramo biome, located above 3300 m a.s.l. and covered mainly by tussock grasslands, provides ecosystem services for Andean cities, especially water resources used for drinking water, agriculture, hydropower generation and sustaining aquatic ecosystems. Even though research about the main components of the water cycle has increased substantially in the last decade, evaporation has remained unknown. In this study, we quantified for the first time daily, monthly and annual evaporation, its components (i.e. interception and transpiration) at event scale and its climatic drivers at a representative páramo catchment in Southern Ecuador (Figure 1). We used the eddy-covariance method to quantify evaporation. We additionally compared those measurements with lysimeters, water balance, energy balance, hydrological models (HBV-light and PDM) and the calibration of the Penman-Monteith equation in order to find easier and cheaper alternatives for estimating evaporation at the páramo