Validation of satellite precipitation (TRMM 3B43) in Ecuadorian coastal plains, Andean highlands and Amazonian rainforest

Precipitation monitoring is of utmost importance for water resource management. However, in regions of complex terrain such as Ecuador, the high spatio-temporal precipitation variability and the scarcity of rain gauges, make difficult to obtain accurate estimations of precipitation. Remotely sensed estimated precipitation, such as the Multi-satellite Precipitation Analysis TRMM, can cope with this problem after a validation process, which must be representative in space and time. In this work we validate monthly estimates from TRMM 3B43 satellite precipitation (0.25° x 0.25° resolution), by using ground data from 14 rain gauges in Ecuador. The stations are located in the 3 most differentiated regions of the country: the Pacific coastal plains, the Andean highlands, and the Amazon rainforest. Time series, between 1998-2010, of imagery and rain gauges were compared using statistical error metrics such as bias, root mean square error, and Pearson correlation; and with detection indexes such as probability of detection, equitable threat score, false alarm rate and frequency bias index. The results showed that precipitation seasonality is well represented and TRMM 3B43 acceptably estimates the monthly precipitation in the three regions of the country. According to both, statistical error metrics and detection indexes, the coastal and Amazon regions are better estimated quantitatively than the Andean highlands. Additionally, it was found that there are better estimations for light precipitation rates. The present validation of TRMM 3B43 provides important results to support further studies on calibration and bias correction of precipitation in ungagged watershed basins.Pragu

Análisis de datos funcionales espaciales para regionalizar la estacionalidad y la intensidad de la precipitación en una región escasamente monitoreada: desvelando las dependencias espacio-temporales de la precipitación en Ecuador

Se usa el análisis de datos funcional para identificar regiones de precipitación tanto por estacionalidad como por intensidad. La metodología propuesta resulta ser robusta para detectar áreas homogéneas y compactas con significado físico. Se usa como caso de estudio el Ecuador.The identification of area‐wise homogeneous precipitation regions helps to unveil similar precipitation patterns and amounts, where similar atmospheric processes at diverse temporal scales are likely to occur. However, although scientifically and socially relevant, the regionalization of precipitation is challenging, specially in areas of complex orography and with sparse monitoring. This limits our understanding of complex spatio‐temporal dependencies and hinders any information‐based resource management decision‐making. Gridded satellite precipitation products are useful in this context, even though they contain bias errors. Spatial functional data analysis (sFDA) is a novel technique that considers time as well as space dependencies by means of spatial autocorrelation and complete time functions, one for each spatial point. Therefore, the aim of this study is to evaluate sFDA as a tool to regionalize seasonality and intensity precipitation patterns, having Ecuador as a case study. The Tropical Rainfall Measuring Mission (TRMM 3B43) satellite precipitation is used to create an exhaustive spatial delineation. To the best of our knowledge, this is the first time that a sFDA regionalization approach is performed on gridded satellite precipitation. The complex orography and heat‐driven atmospheric processes in Ecuador's latitude make it a highly non‐trivial case to test the aforementioned technique. As a result, five relevant regions of precipitation seasonality were spatially delineated and temporally characterized. Three of them were zonally oriented, and two meridional‐wise in the coast. In addition, 20 relevant intensity regions across Ecuador were identified specially in regions with sparse monitoring. The regions were related to regional climate processes. However, limitations were found in regions with important orographic precipitation and locally variability patterns, probably due to the shortcomings of TRMM precipitation quantification. After the successful application of hierarchical regionalization using sFDA in a tropical region with sparse monitoring, it is reasonable to conclude that sFDA is a robust method to detect compact and meaningful homogeneous areas

Spatial association to characterize the climate teleconnection patterns in Ecuador based on satellite precipitation estimates

Las teleconexiones climáticas muestran relaciones remotas y a gran escala entre puntos distantes de la Tierra. Sus relaciones con la precipitación son importantes para monitorear y anticipar las anomalías que pueden producir en el clima local, como eventos de inundaciones y sequías que impactan la agricultura, la salud y la generación de energía hidroeléctrica. Las teleconexiones climáticas en relación con la precipitación se han estudiado ampliamente. Sin embargo, la asociación espacial de los patrones de teleconexión (es decir, la delimitación espacial de regiones con teleconexiones) ha sido desatendida. Dicha asociación espacial permite caracterizar cuán estable (heterogeneidad / dependiente y estadísticamente significativa) es el fenómeno espacial subyacente para un patrón dado. Por lo tanto, nuestro objetivo fue caracterizar la asociación espacial de los patrones de teleconexión climática relacionados con la precipitación utilizando un enfoque exploratorio de análisis de datos espaciales. Se utilizaron indicadores globales y locales de asociación espacial (I de Moran y LISA) para detectar patrones espaciales de teleconexiones basados ​​en imágenes de satélite de TRMM e índices climáticos. El I de Moran representó una asociación espacial positiva alta para diferentes índices climáticos, y LISA representó dos tipos de patrones de teleconexiones. Los patrones homogéneos se localizaron en las regiones de la Costa y Amazonas, mientras que los patrones dispersos tuvieron una mayor presencia en la Sierra. Los resultados también mostraron algunas áreas que, aunque con influencias de teleconexión moderadas a altas, tenían patrones espaciales aleatorios (es decir, asociación espacial no significativa). Otras áreas mostraron tanto teleconexiones como una asociación espacial significativa, pero con patrones dispersos. Esto señaló la necesidad de explorar las características subyacentes locales (topografía, orientación, viento y microclimas) que restringen (asociación espacial no significativa) o reafirman (patrones dispersos) los patrones de teleconexión.Climate teleconnections show remote and large-scale relationships between distant points on Earth. Their relations to precipitation are important to monitor and anticipate the anomalies that they can produce in the local climate, such as flood and drought events impacting agriculture, health, and hydropower generation. Climate teleconnections in relation to precipitation have been widely studied. Nevertheless, the spatial association of the teleconnection patterns (i.e., the spatial delineation of regions with teleconnections) has been unattended. Such spatial association allows to characterize how stable (heterogeneity/dependent and statistically significant) is the underlying spatial phenomena for a given pattern. Thus our objective was to characterize the spatial association of climate teleconnection patterns related to precipitation using an exploratory spatial data analysis approach. Global and local indicators of spatial association (Moran's I and LISA) were used to detect spatial patterns of teleconnections based on TRMM satellite images and climate indices. Moran's I depicted high positive spatial association for different climate indices, and LISA depicted two types of teleconnections patterns. The homogenous patterns were localized in the Coast and Amazonian regions, meanwhile the disperse patterns had a major presence in the Highlands. The results also showed some areas that, although with moderate to high teleconnection influences, had a random spatial patterns (i.e., non-significant spatial association). Other areas showed both teleconnections and significant spatial association, but with dispersed patterns. This pointed out the need to explore the local underlying features (topography, orientation, wind and micro-climates) that restrict (non-significant spatial association) or reaffirm (disperse patterns) the teleconnection patterns.Santiag

Future meteorological droughts in Ecuador: decreasing trends and associated spatio temporal features derived from CMIP5 models

Droughts are one of the most spatially extensive disasters that are faced by societies. Despite the urgency to define mitigation strategies, little research has been done regarding droughts related to climate change. The challenges are due to the complexity of droughts and to future precipitation uncertainty from Global Climate Models (GCMs). It is well-known that climate change will have more impact on developing countries. This is the case for Ecuador, which also has the additional challenges of lacking meteorological drought studies covering its three main regions: Coast, Highlands, and Amazon, and of having an intricate orography. Thus, this study assesses the spatio-temporal characteristics of present and future droughts in Ecuador under Representative Concentrations Pathways (RCP) 4.5 and 8.5. The 10 km dynamically downscaled products (DGCMs) from Coupled Model Intercomparison Project 5 (CMIP5) was used. The Standardized Precipitation Index (SPI) for droughts was calculated pixel-wise for present time 1981–2005 and for future time 2041-2070. The results showed a slightly decreasing trend for future droughts for the whole country, with a larger reduction for moderate droughts, followed by severe and extreme drought events. In the Coast and Highland regions, the intra-annual analysis showed a reduction of moderate and severe future droughts for RCP 4.5 and for RCP 8.5 throughout the year. Extreme droughts showed small and statistically non-significant decreases. In the Amazon region, moderate droughts showed increases from May to October, and decreases for the rest of the year. Additionally, severe drought increases are expected from May to December, and decreases from January to April. Finally, extreme drought increases are expected from January to April, with larger increases in October and November. Thus, in the Amazon, the rainy period showed a decreasing trend of droughts, following the wetter in wet- and drier in dry paradigm. Climate change causes decision-making process and calls for adaptation strategies being more challenging. In this context, our study has contributed to better mapping the space-time evolution of future drought risk in Ecuador, thus providing valuable information for water management and decision making as Ecuador faces climate change. © Copyright © 2020 Campozano, Ballari, Montenegro and Avilés

Uav monitoring for enviromental management in galapagos islands

In the Galapagos Islands, where 97% of the territory is protected and ecosystem dynamics are highly vulnerable, timely and accurate information is key for decision making. An appropriate monitoring system must meet two key features: on one hand, being able to capture information in a systematic and regular basis, and on the other hand, to quickly gather information on demand for specific purposes. The lack of such a system for geographic information limits the ability of Galapagos Islands' institutions to evaluate and act upon environmental threats such as invasive species spread and vegetation degradation. In this context, the use of UAVs (unmanned aerial vehicles) for capturing georeferenced images is a promising technology for environmental monitoring and management. This paper explores the potential of UAV images for monitoring degradation of littoral vegetation in Puerto Villamil (Isabela Island, Galapagos, Ecuador). Imagery was captured using two camera types: Red Green Blue (RGB) and Infrarred Red Green (NIR). First, vegetation presence was identified through NDVI. Second, object-based classification was carried out for characterization of vegetation vigor. Results demonstrates the feasibility of UAV technology for base-line studies and monitoring on the amount and vigorousness of littoral vegetation in the Galapagos Islands. It is also showed that UAV images are not only useful for visual interpretation and object delineation, but also to timely produce useful thematic information for environmental management.Pragu

Mobility modes of school-age children: incidence exploration of socioeconomic, perception and urban mesoscale factors using Random Forest

El análisis y comprensión de la incidencia de los factores socioeconómicos, de percepción y de mesoescala urbana sobre los modos de movilidad de los niños y niñas en edad escolar es fundamental para fomentar el uso de modos más sustentables. Este estudio explora la relación entre factores socioeconómicos, de percepción y de mesoescala urbana sobre los modos de movilidad diaria de niños y niñas en edad escolar (6 a 12 años) en la ciudad intermedia de Cuenca (Ecuador, América Latina). Se utilizó la herramienta Random Forest, como método de aprendizaje automático supervisado, para clasifcar los modos de movilidad en: “caminar”, “autobús” y “automóvil”, y para identifcar la importancia de los factores en cada modo. Los datos se obtuvieron de una encuesta de movilidad realizada en hogares de Cuenca en el 2019. A pesar de que buseta es un modo de movilidad usual para escolares, no pudo ser considerado en este estudio ya que no se contemplaba en la encuesta original utilizada. Los resultados mostraron que el mejor modelo para los modos de movilidad “caminar” y “autobús” fue con todos los grupos de factores (socioeconómicos, de percepción y de mesoescala urbana), mientras que para “automóvil”, como se esperaba, fue el modelo con factores socioeconómicos el más relevante. Si bien los factores más importantes fueron el número de vehículos por familia y nivel socioeconómico, también encontramos que los factores de percepción son relevantes para incentivar el caminar como un modo de movilidad cotidiana . Del mismo modo, para fomentar el uso del autobús, deben tenerse en cuenta los factores urbanos de mesoescala. Este estudio aporta datos y un enfoque metodológico para contribuir a la política pública en materia de movilidad activa en edad escolar.Analyzing and understanding the incidence of socioeconomic, perception and urban mesoscale factors on mobility modes of school-age children is essential to motivate a more sustainable mobility. This study explores the relationship between socioeconomic, perception and urban mesoscale factors on the daily mobility modes of school-age boys and girls (6 to 12 years old) in the intermediatesized city of Cuenca (Ecuador, Latin America). Random Forest, as a classifcation machine learning method, was used to classify the mobility modes into walk, bus and car, and to identify factor importance in each mode. The data were obtained from a mobility survey carried out on Cuenca households in 2019. Even if school bus is a usual mobility mode for schoolchildren, it could not be accounted in this study because it was not contained in the original survey. The results showed that the best model for walk and bus mobility modes was with all the factor groups, while for Car, as expected, was the socioeconomic model. Even if the most important factors were cars´ number per family and socioeconomic level, we also found that, in order to encourage walking as the mobility mode, the perception factors are relevant. Similarly, in order to encourage bus mobility mode, the urban mesoscale factors should be accounted for. This study contributes with data and a methodological approach that could infuence public policy regarding scholar-aged active mobility

Altitudinal and temporal evapotranspiration dynamics via remote sensing and vegetation index-based modelling over a scarce-monitored, high-altitudinal Andean páramo ecosystem of Southern Ecuador

En los Andes tropicales, el ecosistema de páramo se conoce como torres de agua y el principal proveedor de agua para las ciudades de la región andina. Sin embargo, teniendo en cuenta que la evapotranspiración (ET) es la principal pérdida de agua y la falta de mediciones de evapotranspiración in situ en ecosistemas de páramo de altitud elevada, la dinámica de ET en la regulación hidrológica permanece en gran parte inexplorada. Por lo tanto, para cerrar esta brecha, nos centramos en un enfoque de detección remota. Este estudio abordó la dinámica altitudinal y temporal de la evapotranspiración real utilizando un coeficiente de cultivo basado en un modelo de Índice de Vegetación (VI). Se evaluaron el índice de vegetación mejorado (EVI), el índice de vegetación de diferencia normalizada (NDVI) y el índice de vegetación ajustado al suelo (SAVI) recuperados de las imágenes de Landsat. Se utilizaron cuatro imágenes de teledetección y datos meteorológicos a nivel del suelo durante un período de 10 meses para crear mapas ET de cada VI. Se usó una interpolación spline cúbica para obtener series de tiempo ET diarias entre dos fechas de paso elevado por satélite. Se utilizaron valores mensuales agregados para validar contra ET calculado a partir del balance hídrico. Los resultados revelaron que el ET basado en EVI superó al otro ET basado en VI. Los resultados mostraron 30% de subestimación (Pbias%) en relación con el balance hídrico. Para obtener resultados mejorados, se necesita una serie temporal de imágenes satelitales extendidas y una calibración fina. Con respecto a la variabilidad altitudinal, ET exhibió una fuerte dependencia de las características de la cubierta terrestre. Nuestro trabajo proporciona un método plausible para estimar ET en ecosistemas de páramo en ausencia de mediciones ET y con la escasez de imágenes de cielo despejado, es necesaria una evaluación adicional para mejorar las estimaciones de ET utilizando la teledetección en el futuro.In the tropical Andes, the paramo ecosystem is known as water towers and the main water supplier for the cities of the Andean region. Nevertheless, considering that evapotranspiration (ET) is the major water loss and the lack of in situ evapotranspiration measurements in high altitudinal paramo ecosystems, ET dynamics on the hydrological regulation remains largely unexplored. Therefore, to close this gap, we focused on a remote sensing approach. This study addressed the altitudinal and temporal dynamics of actual evapotranspiration using a crop coefficient based on a Vegetation Index (VI) model. Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) retrieved from Landsat imagery were evaluated. Four remote sensing images and ground-level meteorological data for a 10-month period were used to create ET maps from each VI. A cubic spline interpolation was used to obtain daily ET time series between two satellite overpass dates. Aggregated monthly values were used to validate against ET calculated from water balance. Results revealed that EVI-based ET outperformed the other VI-based ET. The results showed 30% of subestimation (Pbias%) in relation to the water balance. For upgraded results, an extended satellite images time series and a fine calibration are needed. Regarding the altitudinal variability, ET exhibited a strong dependence on land cover characteristics. Our work provides a plausible method to estimate ET in paramo ecosystems in the absence of ET measurements and with a scarcity of clear sky images, further evaluation is necessary to improve ET estimations using remote sensing in the future

Virtual control volume approach to the study of climate causal flows: identification of humidity and wind pathways of influence on rainfall in Ecuador

Unraveling the relationship between humidity, wind, and rainfall is vitally important to understand the dynamics of water vapor transport. In recent years, the use of causal networks to identify causal flows has gained much ground in the field of climatology to provide new insights about physical processes and hypothesize previously unknown ones. In this paper, the concept of a virtual control volume is proposed, which resembles the Eulerian description of a vector field, but is based on causal flows instead. A virtual control surface is used to identify the influence of surrounding climatic processes on the control volume (i.e., the study region). Such an influence is characterized by using a causal inference method that gives information about its direction and strength. The proposed approach was evaluated by inferring and spatially delineating areas of influence of humidity and wind on the rainfall of Ecuador. It was possible to confirm known patterns of influence, such as the influence of the Pacific Ocean on the coast and the influence of the Atlantic Ocean on the Amazon. Moreover, the approach was able to identify plausible new hypotheses, such as the influence of humidity on rainfall in the northern part of the boundary between the Andes and the Amazon, as well as the origin (the Amazon or the tropical Atlantic) and the altitude at which surrounding humidity and wind influence rainfall within the control volume. These hypotheses highlight the ability of the approach to exploit a large amount of scalar data and identify pathways of influence between climatic variables