Tesis Doctoral/PHD

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Fog in the Andean Páramo: measurements, dynamics, and its influence on soil hydrology and evapotranspiration processes
(Universidad de Cuenca, 2022-09-15) Berrones Guapulema, Gina Marcela; Célleri Alvear, Rolando Enrique
The páramo ecosystem is characterized by a very moist climate and the continuous presence of fog and low-intensity rainfall. The most important páramo feature is the high water regulation capacity which in part might be related to the high frequency of fog and low-intensity rainfall (drizzle). Therefore, it is essential to understand the hydrological processes that are linked to the ecology of the páramo. This study aimed the following three objectives: (1) to assess fog water estimates derived from three different types of fog gauges, and from them to understand its temporal dynamics and the importance of fog to annual rainfall; (2) to quantify the contribution of fog water deposition to soil moisture; and (3) to analyze the impact of fog on evapotranspiration rates, under different weather conditions (clear, foggy and rainy). Findings of this study show that fog occurs at very low intensities (0.2 mm h-1) reporting events of short term (<3 hours) at wind velocities below 4 m s-1. Most of the time fog appears combined with other type of precipitation (i.e. drizzle, light rain or rain) with fog tending to be more intense in the early morning, and at night. On average, daily fog amounts 1.37 mm. Overall, fog and drizzle are the major water sources to páramo vegetation, especially during late night-time and early mornings, when evaporation is low. The fog water deposition shows that only 4.5% of fog reaches the soil, contributing to soil moisture changes rather low (0.1-0.2 mm), whilst the combination of fog with low-intensity rainfall generate a higher contribution on soil moisture (as high as 4.3 mm). These events are potentially important for both soil moisture and stream flow, because of their long duration and high total amount per-event. Daily evapotranspiration rates are reduced by 43% due to the presence of mixed conditions (fog + lowintensity rainfall) compared with clear conditions (no fog and no rainfall). The net radiation is reduced by 9.2% during foggy conditions (only fog) mainly because its early morning hours occurrence is higher, and when solar radiation peaks fog occurrence is lower. While, during mixed conditions the net radiation is reduced by 33%. At the same time as less humid periods were reported, evapotranspiration was also low; suggesting that fog and drizzle presence can inhibit transpiration, limit water loss by evaporation and also could alleviate water stress.
Causality and climate networks approaches for evaluating climate models, tracing flows, and selecting physically meaningful predictors
(Universidad de Cuenca, 2022-04-14) Vázquez Patiño, Angel Oswaldo; Samaniego Alvarado, Esteban Patricio; Campozano Parra, Lenin Vladimir
Climate consists of many components, for example, atmosphere, hydrosphere, cryosphere, and biosphere. All the components act under mechanisms that relate them in a highly non-linear way, making the climate a complex system. This complexity is a challenge to study the climate and its implications at various spatiotemporal scales. However, the dependence of anthropogenic activities on the climate has encouraged its study in order, for example, to anticipate its periodic changes and, as far as possible, extreme events that may have adverse effects. As climate study is an intricate task, several approaches have been used to unravel the underlying processes that dominate its behavior. Those approaches range from linear correlation analysis to complex machine learning-based knowledge discovery analysis. This last approach has become more relevant after the introduction of sophisticated climate simulation models and high-tech equipment (e.g., satellite) that allow a climate record of greater coverage (spatial and temporal) and that, together, have generated ubiquitous large databases. One of the knowledge discovery approaches based on this big data is based on climate networks. Nevertheless, causal reasoning methods have also been used recently to infer and characterize these networks, which are called causal climate networks. Several studies have been carried out with climate networks; however, the recent introduction of causality methods makes the study of climate with causal climate networks an opportunity to explore and exploit them more widely. In addition, the particularities of the climate make it necessary to understand specific operational issues that must be taken into account when applying networks. This thesis aims to propose new methodologies and applications of causal climate networks following as a common thread the characterization of physical phenomena that manifest themselves at different spatial scales. For this, different case studies have been taken. They are the climate in South America and a large part of the Pacific and Atlantic oceans, then, reducing the scale, the surrounding factors that influence the rainfall of Ecuador, and, finally, the selection of predictors for downscaling models in an Andean basin. Among the main results are the following three. First, a methodology for evaluating global climate models based on what is called here as causal flows. Second, an approach that studies causal flows and helps trace influence paths in flow fields. Third, the presentation of evidence that shows the effectiveness of methods based on causality in selecting predictors for downscaling models. The thesis contributes to efforts to bridge the gap between the climate science and causal inference communities. This through the study and application of causal reasoning and taking advantage of the enormous amounts of climate data available today
Evaluating electrical conductivity as a surrogate tracer to determine the factors controlling event and pre-event water flow partitioning at a tropical montane Andean ecosystem
(Universidad de Cuenca, 2024-09-17) Lazo Jara, Patricio Xavier; Crespo Sánchez, Patricio Javier; Segura, Catalina
The results of this thesis showed that electrical conductivity could be used as an alternative to Oxygen-18 as a tracer for event and pre-event water flow partitioning analyses which highly increases the temporal resolution of tracer concentrations while reducing the uncertainty of the tracer-aided model. The results showed great similarity under a large range of flow conditions, reassuring the consistency of the estimated fractions with 89% of the monitored events showing differences lower than 20% in pre-event water fraction regardless of the antecedent moisture and rainfall conditions. The use of electrical conductivity was possible due to a quasi-conservative behavior related with the presence of organic-rich riparian soils (peat-type) overlying compact bedrock across the catchment. This highlights the potential of electrical conductivity to obtain high temporal frequency data while lowering the costs needed to implement and keep tracer data collection up for long time periods. In addition, results from the comparison of models with different complexities also showed great similarity in their estimations of the event and pre-event water fractions as long as appropriate concentrations of event (Ce) and pre-event (Cp) water for the simpler model are set. In fact, Cp showed to be the most important factor for improving accuracy while Ce had little influence on the results. Hence, the best way to determine Cp was the concentration of a streamflow sample taken before the beginning of each event. These findings will allow to reduce the logistical and economical resources needed to adequately assess hydrograph separation and to carry out quasi-continuous assessments of flow partitioning with high accuracy in high-Andean montane ecosystems. The previous results led to the analysis of several spatial and temporal factors controlling event and pre-event water fractions. This allowed us to obtain tracer and hydrometeorological high-frequency data from a large number of rainfall-runoff events (n=72). The correlations showed that the main temporal controlling factor was rainfall amount with a strong (i.e., r>0.7) and significant (i.e., p<0.05) positive correlation with the event water fraction, whereas, soil type, vegetation cover, and topography were highly correlated when considering the spatial factors. These results suggested an enhanced shallow subsurface hydrological connectivity between hillslopes and riparian wetlands which follow in an increase of event water fraction for events that show higher peak flows while a threshold is exceeded. Overall, our findings suggests that high temporal resolution data is extremely necessary to adequately assess event and pre-event water fraction flow partitioning as it helps to obtain a complete understanding of catchment hydrological behavior at scale event. This improved understanding could aid in the implementation of science-based water management strategies that includes many processes that are often overlooked.
Towards an efficient and functional design of constructed wetlands systems for wastewater and sludge treatment in high altitude tropical regions
(Universidad de Cuenca, 2024-09-05) Arévalo Durazno, María Belén; Alvarado Martínez, Andrés Omar
The treatment of wastewater and sludge through decentralised natural systems, such as the French System, represents a sustainable and effective strategy. This system uses two stages of vertical flow constructed wetlands (VFCWs) to treat raw wastewater, eliminating sludge generation. Despite its extensive use in France, its application in Latin America, particularly in high-altitude Andean regions, has been limited. The main objective of this thesis was to investigate the feasibility of applying the French System for the treatment of domestic wastewater and septic sludge under the climatic conditions of the Andean Region, at 2500 meters above sea level, through a pilot study in Cuenca, Ecuador. Results showed that VFCWs can continuously handle extreme hydraulic loads of diluted wastewater, with proper feeding and resting periods, reducing the required treatment area and minimizing sludge accumulation. It was also determined that septic tanks remain common in both urban and rural areas, making the treatment of fecal sludge necessary. By using VFCWs for this type of sludge, it was observed that the use of multiple beds allows for adequate treatment, and that retaining the percolate for seven days significantly improves the removal of COD and TS without increasing the treatment area. The French System shows great potential for use in areas with climates similar to the Andean region for the treatment of domestic wastewater and septic sludge.
Ultraviolet disinfection of water with UV-LED technology: study of inactivation kinetics and reactivation processes
(Universidad de Cuenca, 2024-04-25) Duque Sarango, Paola Jackeline; Pinos Vélez, Verónica Patricia; Samaniego Alvarado, Esteban Patricio; Sánchez Cordero, Esteban Remigio; Romero Martínez, Leonardo
Access to safe drinking water is crucial for human well-being, but the lack of this resource represents a significant global challenge. Consumption of contaminated water greatly increases the disease risk, making water disinfection essential to eliminate pathogenic microorganisms. Ultraviolet (UV) light-emitting diode (LED)-based systems emerge as an up- and-coming option to address this issue. These semiconductor devices emit light in the ultraviolet range and present a design and materials that allow efficient applications in disinfection and other fields, standing out for their environmental friendliness and overcoming the limitations associated with mercury lamps. This research uses different wavelengths and reactors for UV disinfection to evaluate the inactivation efficiency of various microorganisms, including indicator bacteria, fungal spores, cyanobacteria, and microalgae. Significant challenges are addressed, such as variability in bacterial response and resistance of emerging microorganisms. In addition, the possibility of reactivation of microorganisms after treatment is investigated. This comprehensive approach contributes to understanding the versatility of UV-LED technology in water disinfection. It promotes compliance with quality standards, public health preservation, and sustainable water treatment innovation.
Bridging the gap between hydrological and biogeochemical processes in a high Andean catchment: a comprehensive tracer-aided model framework
(Universidad de Cuenca, 2023-09-29) Pesántez Vallejo, Juan Patricio; Crespo Sánchez, Patricio Javier; Birkel, Christian; Célleri Alvear, Rolando Enrique
The Andean mountains satisfy the vital needs of the Andean population and its lowlands. However, they are projected to experience significant impacts attributed to land-use change and climate change. Despite our understanding of the hydrology in these areas, to date, there has been no modeling framework that incorporates direct data acquisition, simple models, and extends to a distributed modeling framework. Such a framework should be able to elucidate hydrological and biogeochemical processes in a manner comprehensible to decision-makers. Therefore, the primary objective of this thesis is to spatially and temporally assess the production and distribution of water and dissolved organic carbon (DOC) in a páramo catchment using tracer-aided models. To achieve this, we have monitored hydrometeorological and biogeochemical parameters, as well as water stable isotopes. In combination with field observations and perceptual knowledge of these catchments, we evaluated them within a comprehensive hydrological modeling framework. We found that DOC and other solutes can be estimated through in-situ spectrometry. Using these solutes as tracers made it possible to compare different hydrological pathways and was the only way to identify that streamflow response consisted of near-surface rapid flow, more mixed flow through the two main soil types, as well as flow from shallow fractured rock, especially under base flow conditions. Based on the hydrological processes found, a new module was developed to simulate DOC production and incorporate it into a spatially distributed hydrological model at a high spatial (10 x 10 meters) and temporal (1 hour) resolution. This model allowed us to identify DOC hots pots and hot moments. The results showed increased hydrological connectivity between hillslopes and valleys with increasing precipitation. Wetter conditions also favored DOC production, especially in valleys (Histosols), and DOC transport to the river. Our findings suggest that minor changes in meteorological conditions directly affect water dynamics in páramo soils and its biogeochemistry. These conclusions will enable informed decisions to be made regarding water security, taking into account the effect of carbon loss from the soils to the rivers in the páramo.
Towards the improvement of machine learning peak runoff forecasting by exploiting ground- and satellite-based precipitation data: A feature engineering approach
(Universidad de Cuenca, 2023-05-10) Muñoz Pauta, Paul Andrés; Célleri Alvear, Rolando Enrique; Orellana Alvear, Johanna Marlene
Peak runoff forecasting in complex mountain systems poses significant challenges in hydrology due to limitations in traditional physically-based models and data scarcity. However, the integration of machine learning (ML) techniques offers a promising solution by balancing computational efficiency and enabling the incorporation of satellite precipitation products (SPPs). However, debates have emerged regarding the effectiveness of ML in hydrology, as its black-box nature lacks explicit representation of hydrological processes, hindering performance improvement and result reproducibility. To address these concerns, recent studies emphasize the inclusion of FE strategies to incorporate physical knowledge into ML models, enabling a better understanding of the system and improved forecasting accuracy. This doctoral research aims to enhance the effectiveness of ML in peak runoff forecasting by integrating hydrological concepts through FE techniques, utilizing both ground-based and satellite-based precipitation data. For this, we explore ML techniques and strategies to enhance accuracy in complex macro- and mesoscale hydrological systems. Additionally, we propose a FE strategy for a proper utilization of SPP information which is crucial for overcoming spatial and temporal data scarcity. The integration of advanced ML techniques and FE represents a significant advancement in hydrology, particularly for complex mountain systems with limited or inexistent monitoring networks. The findings of this study will provide valuable insights for decision-makers and hydrologists, facilitating effective mitigation of the impacts of peak runoffs. Moreover, the developed methodologies can be adapted to other macro- and meso-scale systems, with necessary adjustments based on available data and system-specific characteristics, thus benefiting the broader scientific community.
Dynamics of Precipitation Anomalies in Tropical South America: A Multiscale Approach
(Universidad de Cuenca, 2023-05-08) Córdova Mora, Mario Andrés; Célleri Alvear, Rolando Enrique
This PhD thesis aims to study the dynamics of precipitation anomalies and extreme precipitation events in tropical South America (TrSA). Precipitation anomalies in TrSA are influenced by a complex climate variability resulting from the superposition of various phenomena acting on different temporal and spatial scales, as well as several geographical features. The study uses interpolated gridded global datasets and climate reanalysis to understand dynamics of precipitation anomalies, while weather radar data and last-generation reanalysis datasets were employed to investigate extreme precipitation events. The study applied data analysis techniques and machine learning algorithms and incorporated process knowledge to select the input data and interpret the results. Three objectives were executed to understand precipitation anomalies and extreme precipitation events in TrSA using a multiscale perspective: 1) understanding the dynamics of precipitation anomalies in tropical South America in annual to monthly scales, 2) understanding the dynamics of precipitation anomalies in the tropical Andes in seasonal scale, and 3) understanding the dynamics of extreme precipitation at event scale in the southern Ecuadorian Andes. The study found that precipitation anomalies are mainly influenced by the intensity and position of the South Atlantic Convergence Zone (SACZ), El Niño Southern Oscillation (ENSO), the meridional position of the Intertropical Convergence Zone (ITCZ), and the strength of the South American Monsoon System. Moreover, Convective Available Potential Energy (CAPE), the vertical integral of divergence of moisture flux, and SSTbased oceanic indices were found to be important variables that influence precipitation anomalies in different regions of the tropical Andes. Finally, the study found distinct patterns of circulation anomalies for extreme events in the southern Ecuadorian Andes.
Investigating the relationships between precipitable water vapor estimations and heavy rainfall over the Eastern Pacific Ocean and Ecuadorian regions
(Universidad de Cuenca, 2023-03-20) Serrano Vincenti, María Sheila Fabiola; Villacís Erazo, Marcos Joshua; Condom, Thomas; Campozano Parra, Lenin Vladimir
Among the weather phenomena, rainfall is difficult to forecast, despite the theoretical and technical challenges inherently related to its prediction, its impact in economic and everyday activities, clearly justify its study. Numerical Weather Prediction Models are widely used to predict rainfall, such as the Weather Research & Forecasting Model (WRF), However, they underperform when is set to predict intense events and when working with complex and steep topographies. Recent studies have proposed the estimation of Precipitable Water Vapor PWV, as a tool that can help predict and understand the mechanisms that trigger intense rainfall. PWV is mainly sourced from satellite products and from indirectly measurements which derive it through the delay of the Global Navigation Positioning System (GNSS) signals quite accurately. Thus, the present work studies the relationship between intense rain and satellite sourced PWV over the ocean, the relationship of PWV-GNSS over the Coast, Sierra and Amazon of Ecuador, and the comparison of the PWV-GNSS with the data modeled in WRF. As main results, we point an empirical model between the satellite PWV and the maximum values of rainfall over the ocean. In addition, PWV-GNSS loading and unloading periods related to the diurnal cycle of rainfall over the land, and relationships with intense rain events were identified; and finally, the main discrepancies between the observed PWV-GNSS data and rainfall with WRF modeled data over areas of the Equatorial Andes.
Comparative assessment of a mountain river flow resistance – 1D-: sensitivity and prediction using data-based approaches
(Universidad de Cuenca, 2022-11-21) Cedillo Galarza, Juan Sebastián; Alvarado Martínez, Andrés Omar
Mountain -rivers are, by far, the most challenging case to model because of its bed characteristics and their energy dissipation mechanisms depending on its irregular morphology. Resistance, roughness, or friction parameter are equivalent terms. It plays an important role in 1-D open channel models to estimate different variables. Moreover, this parameter contains all the dissipative processes in a mountain river, and it is usually valued through field measurements, existing different methodologies to estimate it. Consequently, it is essential to determine which methodology is the most adequate to predict it. The resistance parameter determined in field is not always the same as the one used in a hydrodynamic model. In this thesis; cascades, plane bed, and step-pool has been studied in the Quinuas river (Ecuador). “Non-dimensional hydraulic geometry equations” (NDHG) were the best option to predict velocity in all the mountain river reaches. The parameters of NDHG varies depending on the author, therefore a methodology based on some field measurements to estimate the NDHG parameters was developed. The differences between model and field resistance coefficient depends on the morphology and flow magnitude. A machine learning technique using the system physics was develop providing optimal results to predict water depths and to calibrate resistance parameter.
Mathematical programming for the support of river water management: water allocation and reservoir location
(Katholieke Universiteit Leuven, 2022-05-20) Veintimilla Reyes, Jaime Eduardo; Van Orshoven, Jos; Cattrysse, Dirk; Vanegas Peralta, Pablo Fernando; Cisneros Espinoza, Felipe Eduardo
Surface and ground water availability is variable in space and time and the spatio-temporal pattern of this variability often does not match with the distributed use pattern of sectors and individual consumers. This mismatch can become controversial when overall water availability decreases, e.g., due to climate change, and competition for water increases. It is in this context that the so called WEF-nexus between water for human consumption and industrial use, water for Energy (hydropower) and water for Food (irrigated agriculture) (WEF) has gained increasing attention in research, business and policy spheres, especially in regions with more arid climate. An additional dimension of this nexus is the water required for sustainable functioning of ecosystems in general and wetlands in particular. Allocation of scarce water has challenged water managers for decades. The construction and operation of reservoirs is the typical solution put forward. In this research we addressed the optimization of the allocation of water available in a river-with-reservoir system towards multiple users as a network flow optimization (NFO) problem. There are two classes of methods to tackle NFO problems: heuristic models and mathematical models. Heuristic models are able to provide a feasible solution within reasonable computation time whereas mathematical models are able to come up with the optimal solution but often requiring longer computation times. Since for strategic decisions computation times are less crucial, the latter, i.e. linear programming (LP) models and mixed integer linear programming (MILP) models were the subject of this research. LP and MILP models were formulated to optimize the flow and storage of water through Water Supply Networks (WSN) created from geographic information describing the river basin under study. A WSN encompasses a set of oriented lines connected in georeferenced nodes whereby the lines represent river segments and the nodes represent reservoirs, natural water bodies, inflow points and abstraction points. Whereas inflow and abstraction points are characterized by time series of incoming and required water volumes, the water volume available in river segments, reservoirs and other water bodies, each having predetermined capacities, is updated throughout the simulation period.
Hydrodynamic assessment of different UASB reactor’s influent distribution systems to improve granulation
(Universidad de Cuenca, 2022-05-17) Cisneros Ramos, Juan Fernando; Alvarado Martínez, Andrés Omar
Wastewater treatment systems are implemented to remove wastewater pollutants before discharge into receiving water bodies. Wastewater can negatively affect the ecosystem of the receiving water body if proper treatment is not conducted. Despite its importance, small coverage of wastewater treatment systems has been achieved worldwide mainly due to the related high construction and operating costs. According to the Food and Agriculture Organization, about 80% of the world’s wastewater generation is discharged into the environment without any treatment, especially in low-income countries. Anaerobic biological wastewater treatments could be an answer to reduce treatment costs. Anaerobic technologies offer advantages over competing technologies such as reduced land footprint, small reactor volume, reduced excess sludge production, and the ability to recover energy through methane capture. The most widespread anaerobic technology worldwide is the Upflow Anaerobic Sludge Blanket (UASB) reactor. The UASB reactor uses an upward flow to produce granular sludge capable of treating high organic loads. Although there is extensive information on the microbiology of these granules and their efficiency in treating different wastewater qualities, further research is required to better understand the relationship between granule formation and reactor hydrodynamics. Flow hydrodynamics, almost entirely controlled by the reactor's Influent Distribution System (IDS), is key to consider during the UASB reactor’s design since it modules the substrate distribution inside the reactor and the formation of stagnant and short-circuited zones. The IDS role is critical, especially during the reactor's start-up stage when the granular sludge starts to form. This thesis aimed to advance our understanding of the flow hydrodynamics impact on the operation and efficiency of the UASB reactor during its startup stage. The research was divided into two main stages. The first stage was dedicated to physically modeling the reactor using a Froude dynamic similitude scaled reactor and developing an automated tracer testing system. This system allowed us to determine the importance of controlling the test water's conductivity, temperature variation, and surface tension during the tracer tests. The second stage was devoted to numerically modeling the hydrodynamics of the UASB reactor using computational fluid dynamics (CFD) simulations. Initially, the research focused on finding the turbulence closure model that best reproduced the reactor’s hydrodynamics. Thus, CFD simulations were conducted using the realizable k-epsilon model to assess the potential volume of granule generation for IDS configurations commonly used in the literature. The simulations confirmed that the IDS configuration recommended by the design guidelines has a high performance in reducing stagnant and short-circuited zones. This research proposed a novel IDS configuration that generated a granulation volume 22% larger than the recommended IDS configuration, potentially reducing UASB reactor start-up time. The research demonstrates the potential of using physical and numerical techniques as a basis for the model-based design approach to solve problems specific to UASB reactors, an approach that could be extrapolated to other types of reactors.
Sediment transport in steep Andean rivers with coarse bed material
(Universidad de Cuenca, 2022-05-05) Carrillo Serrano, Verónica Margarita; Timbe Castro, Luis Manuel; Cisneros Espinoza, Felipe Eduardo
To improve the understanding of bedload sediment transport with the aim of proposing estimations of its transport rates with greater accuracy, a comprehensive analysis was developed. To investigate the former process, three rivers typical of the southern Ecuadorian mountainous region with longitudinal slopes ranging from 0.8% to 10% were characterized based on the hydraulic geometry (HG) theory. Dimensional and dimensionless downstream HG relations were obtained for top width, average flow depth, average flow velocity, and channel bed slope. The correlation coefficients (𝑅 2 ) of these HG relations indicated that the dimensionless equations adequately represented the observed data of each parameter with a single relation for all three rivers except for slope. Slope relation behavior indicates that slope is not dependent on discharge. Therefore, the non-dimensional HG relations were reformulated using dimensionless discharge and bed slope as independent variables. These new relations showed improved performance (high 𝑅 2 ) and demonstrated the role of slope in determining channel hydraulic and geometric variables. This might also indicate that slope would play an important role in the determination of bedload transport rates. A physical model of a characteristic high-gradient river was implemented to study bedload sediment transport. Several scenarios of channel slope, discharge, and bed material configuration were tested. The most relevant variables from a set of independent variables considered were selected based on a stepwise regression. Additionally, sediment characteristic diameter was also considered as an independent variable replicating the analysis for four different characteristic diameters (𝑑16, 𝑑50, 𝑑84, and 𝑑90). Linear and potential models were obtained with each characteristic diameter. Potential models showed more consistent behavior throughout the entire range of the data considered. Linear models performed better for medium to high transport rates. However, higher dispersion in the estimations was obtained for the lower transport rates. Better performance was observed for the models corresponding to the 𝑑50 and 𝑑84 characteristic diameters. For a validation analysis, higher prediction capacity was obtained for potential models (for 𝑑50 and 𝑑84) with 96% of the data falling within ½ order of the magnitude bands. Based on 𝑅 2 , the 𝑑84 potential model can be selected as the one with the better overall behavior for the laboratory-based models. Using field and laboratory data and considering additional independent variables that could describe better bedload sediment transport, a stepwise procedure was applied to determine the more relevant variables to estimate bedload transport rates. Laboratory data was used to validate field data behavior. Through the use of a State Dependent Parameter (SDP) technique, the nonlinear relations between each of the relevant variables identified and the bedload transport rate were established. From these relations, nonlinear models were built to estimate bedload transport rates. Based on the relevant variables, potential (linear through logarithmic transformation) models were also obtained for comparison. Similar performances were reported for potential and nonlinear models for the data used to calibrate the models. For validation of the models with an independent set of data, the nonlinear 𝑑50 showed a higher level of accuracy. Considering the high level of uncertainty in the estimations of bedload transport rates the 𝑑84 nonlinear model can be also considered as acceptable. For the estimation of bedload transport rates in steep Andean rivers with coarse bed material, the 𝑑50 and 𝑑84 nonlinear models can be applied with an acceptable level of confidence for parameters with values within the range of those corresponding to the data used to build the models. For extrapolation, the application of this model must be subject to a verification process.
Multi-scale monitoring and modelling for the analysis of the hydrologic response of southern Ecuadorian Andean páramos
(Katholieke Universiteit Leuven, 2017-09-24) Iñiguez Moran, Vicente Mauricio; Bauwens, Willy; Wyseure, Guido
The present research is focused on an “alpine” Neotropical grassland ecosystem, situated between ca. 3500 and 4500 m a.s.l. –locally known as “páramo”– which covers the Andean mountains. Below the páramo, the study area hosts other types of high-altitude Andean ecosystems, such as: tropical montane cloud forest and grasslands. The study area is located in the south-west highlands of the Paute River basin that drains to the Amazon River. These highlands form part of the western Cordillera in the Ecuadorian Andes with a maximum altitude of 4420 m a.s.l. The study area comprises a mountain range from 2647 to 3882 m a.s.l. Two neighbouring basins have been selected from this region: Portete (24.4 km2) and Cumbe (44.0 km2). In addition, a small headwater catchment located in the highlands of the Rircary River basin, a neighbour catchment to Portete (Jordanita, 2.70 km2), is also part of the research area. The overall objective of the research is to show how a multi-scale monitoring set-up for experimental research catchments can be implemented and used to establish the foundations of a hydrological observatory in the southern Ecuadorian Andean region. In addition, the research presents a thoughtful approach to catchment modelling and the interaction between modelling and experimental hydrology. A detailed characterization of the weather of three high-altitude Andean ecosystems (i.e. páramo, tropical montane cloud forest and grasslands) was carried out. As a result, the air temperature patterns recorded in both ecosystems –forest and páramo– were the same. Therefore, it is possible to conclude that the land cover has no influence over the lapse rate air temperature as compared with the effect of the altitude. The altitudinal range analysed was of ca. 1000 m. In addition, the water balance at catchment scale allowed to conclude that the land cover has no significant effect on the Ea as compared with the amount of rainfall that actually receives each ecosystem (páramo or tropical montane cloud forest). Hydrological modelling with TOPMODEL By comparing the results of the implementation of TOPMODEL (a TOPography based hydrological MODEL) for the páramo catchments, it was found that the effective parameters, which reflect the characteristics of the catchments, increase in magnitude as a function of the size of the catchment (which increased from 0.21 km2 up to 4.39 km2). Reliable predictions of TOPMODEL were confirmed by field measurements but, the implicit assumption used to calculate the topographic index (i.e. the upslope contributing area “” should be constant for any point) is not fully valid. This has to be reviewed in future applications of TOPMODEL for páramo, which is suffering more frequent drought events. In this context, the drought analysis allowed to conclude that at the plot scale, the differences between the recovery of the soils were relatively large. The measured water content in páramo soils showed a quicker recovery compared to the mineral soils located below the páramo. At the catchment scale, though, the differences in the speed of recovery derived from the soil water storage simulated by the Probability Distributed Moisture model and the drought analysis was not as pronounced. Only for the prolonged drought event of 2009-2010 were the differences larger. The difference between the precipitation and the potential evapotranspiration has been shown to have more impact on the regional difference in hydrologic behaviour than the difference between the water storage capacities of the soils. Policy makers and researchers will be able to compare these baseline results with future hydrological and soil monitoring data, to track changes in the páramo ecosystem.
Impacts of climate change on catchment runoff for the Paute river basin in the southern Ecuadorian Andes (invloed van klimaatsverandering op de neerslagafstroming van het Paute-rivierbekken in de Zuid-Ecuadoriaanse Andes)
(Katholieke Universiteit Leuven, 2013-10-23) Mora Serrano, Diego Esteban; Willems, Patrick; Wyseure, Guido
The objective of this research is the evaluation of climate change scena rios and the impact it will have in water quantity and quality parameter s for future analysis actions of mitigation and adaptation. The evaluation will be performed at different spatial and temporal resol ution with the development of a calibrated and validated Lumped Co nceptual Hydrologic Model The research consist in three workpackages: 1. Model Development: Consistencies between a detailed local scale model and a regional scale conceptual model. < /UL> Research activities will consist in conducting the assessment of a regio nal scale model VHM (Generalized lumped conceptual and parsimonious mode l structure-identification and calibration, according to the Dutch abbre viation), reported as a draft publication of Dr. Prf. Patrick Willems, c oncerned in the analysis of hydrological processes and water quality imp rovement of the model< //UL> a) Improvement and advance of the existing model of Dr. Rolando Celleri, for the basin upstream of River Tomebamba in Monay 1260 km2 (meso-scale riverbasin) b) Same activity at subbasin scale level: Matadero basin 300 km2 and Llaviuco Basin 52 km2), and analysis of regio nal differences (in catchment properties and model parameters) 2 Scenario Development:< /UL> Analysis of trends and oscillations in climatic and hydrologic series< //UL> a) Analysis of rainfall and climatic series of long term weather station s: Analysis of rainfall series; Analysis of temperature and/or ETo series; Analysis of flow series of long term f low gauging stations. < /UL> The downscaling of the IPCC-SRES for the construction of the future clim ate use will be made of the downscaling of regional climate models, for which assistance will be searched for by INAMHI (Instituto Nacional de M eteorología en Hidrología, Quito-Guayaquil, Ecuador), also experience of the Laboratory of Hydraulics, Katholieque Universiteit Leuven)< //UL> a) Assessment and selection of available GCM simulations for rainfall, t emperature, ETo, and other relevant variables b) Development, implementation and evaluation of methodology to do wnscale GCM simulation results c) Consistency check of climate change scenarios with trends ident ified in Activity 2 for rainfall, temperature and ETo series 3 Climate change impact on hydrology: < /UL> Hydrologic impact analysis of climate change in the Tomebamba< //UL> a) Simulation of climate change scen arios developed in Activity 3 in the regional hydrologic models develope d in Activity 1 b) Statistical evaluation of climate chang e impact results c) Consistency check of climate change sce narios with trends identified in Activity 2 for rainfall, temperat ure and ETo series It is believed that the proposed research in the assessment of local and regional models of water quantity and quality and the effects of climat e change in the southern Ecuador Andes region which is of scientific but also relevant for the socio-economy aspects for the region.
A spatially explicit approach to the site location problem in raster maps with application to afforestation (Een ruimtelijk expliciete aanpak voor het locatieprobleem in rasterkaarten met toepassing op bebossing)
(Katholieke Universiteit Leuven, 2010-09-02) Vanegas Peralta, Pablo Fernando; Cattrysse, Dirk; De Schreye, Daniel
Environmental conservation and land use planning usually need to automatically identify geographical sites satisfying particular criteria. The identification of sites becomes more complex when spatial configurations of the sites are part of the requirements since topological relations need to be considered in the analysis of digital geographical data. The present research develops heuristic methods and mathematical approaches to automatically identify contiguous and compact sites to be afforested. In addition to spatial configurations, other criteria related to the identification of sites are part of this research: maximization of environmental performance, sediment fow reduction by means of afforestation of compact sites and budget restrictions in afforestation. One of the results of the AFFOREST project (EU 5th Framework Programme for Research and Technological Development) was a Decision Support System (DSS) that is capable to identify high quality sites to be afforested (transformation of agricultural land into forest). Those sites maximize the Environmental Performance (EP) in terms of three Environmental Impact Categories (EIC): carbon sequestration to be maximized, nitrate leaching to be minimized and ground water recharge to be maximized. To this end every EIC is represented by means of a map composed by a grid of cells (raster map), hence the objective is to identify a site made up of a subset of cells maximizing the EP. The cells identified by means of the AFFORESTDSS form a fragmented site, nevertheless it is also useful to identify sites that are contiguous and compact. Compactness facilitates to articulate efficient policies to manage the afforested areas, in order t0 achieve not only environmental but also economical benefits. This research develops new approaches to locate compact sites for maximizing EP.
Data-based local rainfall modeling through global climate information
(Universidad de Cuenca, 2022-03-28) Mendoza Sigüenza, Daniel Emilio; Samaniego Alvarado, Esteban Patricio
Climate is a global system whose subsystems interact complexly. Deterministic models are capable of describing the climate phenomena with physical detail around the globe. Nonetheless, the several concurrent global climate patterns make the numerical modeling challenging for tropical regions. This is because of inadequate parameterizations and systematic errors, typical of physics-based models. Additionally, the morphology of the mountains in the tropical Andes generates complex spatial patterns for the fluxes. A strategy to circumvent the climate modeling complexity in tropical mountain systems is based on the following considerations. 1) Although complex, the climate in the tropical Andes is strongly seasonal. 2) The climate is a network system in which global patterns greatly influence that seasonality. Both considerations seem to be rational criteria to devise a simplified but meaningful modeling process. This research thesis is about the modeling of local monthly rainfall signals using global climate patterns. It is assumed that global climate signals are crucial drivers for the local seasonal features. A signals’ decomposition using the well-known Dynamic-HarmonicRegression (DHR) helps determine which global climate signals influence the local climate. The DHR technique allows the rainfall to be separated into non-stationary trends and quasi-periodical signals. On the one hand, trends are used to find out inter-annual connections with global patterns. On the other hand, the non-stationary amplitudes of periodical components allow finding intra-annual connections. In a second stage, the identified global signals are included as exogenous variables in a harmonic model for simulating the monthly local rainfall. Global patterns determine the non-stationary properties of trends and periodical components through non-linear functions. The non-linearity is attained by the State-Dependent (SDP) technique, which infers non-parametrical functions between the harmonic’ parameters and global climate states. A preliminary evaluation reveals a model with abilities to accurately predict monthly rainfall signals, which points to potential fundamental climate mechanisms and conceptual links between the local seasonal behavior and global climate states. Finally, the model is data-driven in principle, synthesizing local seasonal features driven by global climate patterns, providing the model with a process-driven flavor. Because of this, the model’s evaluation requires a more comprehensive perspective, responding to both the data-driven and process-driven nature. In that sense, a predictability evaluation of the proposed model in contrast to other empirical alternatives is carried out. This predictive-based evaluation is typical for data-driven techniques. In addition, this work considers a process-oriented assessment based on the model’s capacity to mimic intrinsic seasonal and temporal characteristics. This reveals a model with better predictive accuracy than its alternatives in statistical terms and other attributes. It is argued that the predictability of the proposed model is attributed to its capacity for mimicking local rainfall features driven by global climate patterns.
Disentangling water transport and tracer mixing mechanism in mountainous environments influenced by volcanic features
(Universidad de Cuenca, 2020-06-16) Mosquera Rojas, Giovanny Mauricio; Crespo Sánchez, Patricio Javier
Landscape features of volcanic origin influence the transport of water and solutes across high-elevation environments. Nevertheless, knowledge regarding how these features affect subsurface hydrological behavior at different spatial scales (from plot to catchment) is scarce. The effect of the soils originated from volcanic ash, such as Andosols (or Andisols), and the influence of highly fractured geology of volcanic origin on subsurface hydrological behavior and water flow path delineation are poorly understood. To fill this knowledge gap, I took as the main objective in the doctoral project the analysis of how Andosols and fractured volcanic geology influence flow transport and tracer mixing mechanisms. Laboratory, experimental, and field measurements of the water retention curve (WRC) of Andosols in combination with data extracted from the published literature shows that standard laboratory methods resemble well a small portion of the wet range of the WRC, specifically, from saturation to the matric potentials 3 to 5 kPa (pF 1.5-1.7). For higher matric potentials, standard laboratory methods substantially overestimate the water content of the soils in comparison to experimental and field measurements. Further, a unique set of hydrometric, stable isotope, and soil hydraulic properties data were evaluated to investigate how Andosols influence water transport and tracer mixing mechanisms at a steep tropical hillslope. The results from this analysis point to the dominance of vertical flow paths within the soil matrix, despite the formation of a perched water layer below the root zone, which mimics the hydraulic behavior of a wet, layered sloping sponge. Last, I used a tracer-aided hydrological model (TraSPAN) calibrated for the stable isotopes of water and electrical conductivity (or specific conductance) during a rainstorm event for the analysis of the role of the fractured volcanic geology on flow transport and tracer mixing at the catchment scale. The model structure that best simulated the streamflow hydrograph and the tracers concentrations during a rainfall event consisted of two water reservoirs representing the soils with high infiltration capacity and the groundwater system formed in the fractured bedrock. During the monitored event, only 13% of total precipitation was converted into runoff, with a major proportion (75-81%) corresponding to pre-event water stored in the catchment prior to the event. These findings indicate a large water storage capacity of the system in the fractured volcanic geology.
Integrated water system modelling to support water management in the Cuenca Basin
(Ghent University, 2020-01-17) Jerves Cobo, Rubén Fernando; Goethals, Peter; Nopens, Ingmar
In this chapter is evaluated the biological water quality in relation to chemicals discharged through sewage outfall during doth dry and rainy season. The lowland area of the Cuenca River basin in the southern Andes of Ecuador, including the city of Cuenca, constituted the study area. To perform an integrated water quality assessment, date were collected of macroinvertebrates, physicochemical conditions and morphological characteristics in 43 sites in the Cuenca River and its tributaries. The Andean Biotic Index (ABI) and the Biological Monitoring Working Party adapted to Colombia (BMWP-Col) were used to evaluate the biological water quality. Both biological indexes were higher upstream than downstream form the city. Moreover. These indexes indicated better conditions during the rainy season than in the dry season, based on the presence of more sensitive families. The biological indexes related more to the oxygen saturation than to the five-day biological oxygen demand (BOD5), nutrients and chloride concentrations. The relationship between BOD5 and nutrient concentrations with the variation of both biological indexes was clearer in the dry season than in the rainy season. However, in some sites, these indexes were influenced more by morphological aspects than by pollutants. Both biological indexes shoed similar patterns along the rivers, generally the BMWP-Col scored higher than the ABI index. The later index was shown to be more suitable for the high Andes region as an indicator of water quality. These results could be used to monitor the implementation of river restoration actions, such as determining priorities for splitting sewer and precipitation water transport systems and needs for improved wastewater treatment facilities in specific locations.
Statistical spatial and temporal analysis of historical rainfall and evapotranspiration behavior for Ecuador
(Katholieke Universiteit Leuven, 2019-11-26) Tobar Solano, Vladimiro Alexis; Wyseure, Guido; Willems, Patrick
Statistical analysis of temporal and spatial data: example of rainfall, temperature and evapotranspiration in Ecuador Many studies in Ecuador had taken the endeavor of climate characterization, mainly referred to rainfall and temperatures, and some others to estimating evapotranspiration based on data availability. Such studies have only had local application and had focused on the rainfall gauging stations; fewer stations that have temperature records and even lesser that have information of the various parameters required for the widely used Penman - Monteith equation for estimating evapotranspiration. The main challenge in modeling climate in Ecuador comes from its location in the Intertropical convergence zone, the marine currents in the Pacific, the Amazon basin and the Andes. Therefore, characterization of climate is a first step in order to understand its spatial and temporal variability, and from here to undertake the task of generalizing meteorological elements to the whole country. There needs to be a compromise between data availability that sets boundaries to what can be done and the research objectives of spatial climate patterns. Regarding information, monthly data is available referred to rainfall, for a lesser number of stations temperature is also available; and other elements like wind speed, relative humidity, dew point, pressure, and solar radiation, are only available for a selected set of stations, making it difficult to count on them. GIS spatial data features are also available, like the SRTM DEM 90m, from which morphological characteristics can be derived. First step towards analysis is data validation. Many unforeseen circumstances affect meteorological elements measure and record until final presentation of raw data, and one of the most widely used technique to detect systematic errors is the double mass curve analysis, which will be applied mainly to rainfall information, time series plots may also help identifying errors in other elements like temperatures. Spatial distribution of rainfall will be addressed by means of distribution and seasonal rainfall patterns that will enable categorizing climatic regions. Correlation analysis will be used to estimate missing values and also to estimate ungauged parameters. The main aim is to contribute to a better understanding of climate in Ecuador; by means of models including Andes mountain range and Amazon and coastal regions, for the estimation of various elements like rainfall, temperature and evapotranspiration. Spatial regions with different behavior in rainfall, temperatures and evapotranspiration will be identified. Last but not least, since Ecuador is heavily affected by the extreme anomalies of ENSO, whose presence causes long term heavy rainfalls, and floods, climate characterization should consider its influence.

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