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Keywords = Atrato River

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11 pages, 332 KB  
Proceeding Paper
Water-Level Forecasting Based on an Ensemble Kalman Filter with a NARX Neural Network Model
by Jackson B. Renteria-Mena, Douglas Plaza and Eduardo Giraldo
Eng. Proc. 2025, 101(1), 2; https://doi.org/10.3390/engproc2025101002 - 21 Jul 2025
Viewed by 1304
Abstract
It is fundamental, yet challenging, to accurately predict water levels at hydrological stations located along the banks of an open channel river due to the complex interactions between different hydraulic structures. This paper presents a novel application for short-term multivariate prediction applied to [...] Read more.
It is fundamental, yet challenging, to accurately predict water levels at hydrological stations located along the banks of an open channel river due to the complex interactions between different hydraulic structures. This paper presents a novel application for short-term multivariate prediction applied to hydrological variables based on a multivariate NARX model coupled to a nonlinear recursive Ensemble Kalman Filter (EnKF). The proposed approach is designed for two hydrological stations of the Atrato river in Colombia, where the variables, water level, water flow, and water precipitation, are correlated using a NARX model based on neural networks. The NARX model is designed to consider the complex dynamics of the hydrological variables and their corresponding cross-correlations. The short-term two-day water-level forecast is designed with a fourth-order NARX model. It is observed that the NARX model coupled with EnKF improves the robustness of the proposed approach in terms of external disturbances. Furthermore, the proposed approach is validated by subjecting the NARX–EnKF coupled model to five levels of additive white noise. The proposed approach employs metric regressions to evaluate the proposed model by means of the Root Mean Squared Error (RMSE) and the Nash–Sutcliffe model efficiency (NSE) coefficient. Full article
(This article belongs to the Proceedings of The 11th International Conference on Time Series and Forecasting)
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23 pages, 2629 KB  
Article
Biomonitoring of Mercury and Lead Levels in the Blood of Children Living near a Tropical River Impacted by Artisanal and Small-Scale Gold Mining in Colombia
by Eurípides Palacios-Valoyes, Manuel H. Salas-Moreno and José L. Marrugo-Negrete
Toxics 2024, 12(10), 744; https://doi.org/10.3390/toxics12100744 - 13 Oct 2024
Cited by 5 | Viewed by 3566
Abstract
(1) Background: Mercury and lead contamination resulting from various anthropogenic activities represents a global environmental problem and a considerable risk to the health of the human population. (2) Methods: The objective of this research was to evaluate the concentrations of mercury (Hg) and [...] Read more.
(1) Background: Mercury and lead contamination resulting from various anthropogenic activities represents a global environmental problem and a considerable risk to the health of the human population. (2) Methods: The objective of this research was to evaluate the concentrations of mercury (Hg) and Lead (Pb) in the blood of the child population in the municipalities in the Atrato River basin using a direct Hg analyzer and graphite furnace atomic absorption spectrometry. (3) Results: In total, 171 children (5–14 years of age) were taken into account, and 18.71% (32) of the children had concentrations of Hg and Pb above the permissible values established by the WHO. In the municipality of UN, 19 children had blood Hg concentrations between 5.29 and 17.71 μg/L. In CA, two children had concentrations of 5.03 and 8.43 μg/L, separately. In the case of Pb, seven children showed concentrations between 3.60 and 4.83 μg/dL in the municipality of RQ, three in UN (3.59, 3.61, and 4.60 μg/dL), and one in Carmen de Atrato (5.47 μg/dL). (4) Conclusions: The levels of Hg and Pb in the blood of children living in the riparian areas of the Atrato River basin are related to gold mining activities in the basin and the consumption of contaminated fish. Full article
(This article belongs to the Special Issue Dietary Exposure to Heavy Metals and Health Risks)
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18 pages, 1789 KB  
Article
Multivariate Hydrological Modeling Based on Long Short-Term Memory Networks for Water Level Forecasting
by Jackson B. Renteria-Mena, Douglas Plaza and Eduardo Giraldo
Information 2024, 15(6), 358; https://doi.org/10.3390/info15060358 - 15 Jun 2024
Cited by 14 | Viewed by 4034
Abstract
In the Department of Chocó, flooding poses a recurrent and significant challenge due to heavy rainfall and the dense network of rivers characterizing the region. However, the lack of adequate infrastructure to prevent and predict floods exacerbates this situation. The absence of early [...] Read more.
In the Department of Chocó, flooding poses a recurrent and significant challenge due to heavy rainfall and the dense network of rivers characterizing the region. However, the lack of adequate infrastructure to prevent and predict floods exacerbates this situation. The absence of early warning systems, the scarcity of meteorological and hydrological monitoring stations, and deficiencies in urban planning contribute to the vulnerability of communities to these phenomena. It is imperative to invest in flood prediction and prevention infrastructure, including advanced monitoring systems, the development of hydrological prediction models, and the construction of hydraulic infrastructure, to reduce risk and protect vulnerable communities in Chocó. Additionally, raising public awareness of the associated risks and encouraging the adoption of mitigation and preparedness measures throughout the population are essential. This study introduces a novel approach for the multivariate prediction of hydrological variables, specifically focusing on water level forecasts for two hydrological stations along the Atrato River in Colombia. The model, utilizing a specialized type of recurrent neural network (RNN) called the long short-term memory (LSTM) network, integrates data from hydrological variables, such as the flow, precipitation, and level. With a model architecture featuring four inputs and two outputs, where flow and precipitation serve as inputs and the level serves as the output for each station, the LSTM model is adept at capturing the complex dynamics and cross-correlations among these variables. Validation involves comparing the LSTM model’s performance with linear and nonlinear Autoregressive with Exogenous Input (NARX) models, considering factors such as the estimation error and computational time. Furthermore, this study explores different scenarios for water level prediction, aiming to utilize the proposed approach as an effective flood early warning system. Full article
(This article belongs to the Special Issue Real-World Applications of Machine Learning Techniques)
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21 pages, 107967 KB  
Article
Detection of Coastal Erosion and Progradation in the Colombian ‘Atrato River’ Delta by Using Sentinel-1 Synthetic Aperture Radar Data
by Rubén Darío Vásquez-Salazar, Ahmed Alejandro Cardona-Mesa, Juan Valdés-Quintero, César Olmos-Severiche, Luis Gómez, Carlos M. Travieso-González, Jean Pierre Díaz-Paz, Jorge Ernesto Espinosa-Ovideo, Lorena Diez-Rendón, Andrés F. Garavito-González and Esteban Vásquez-Cano
Remote Sens. 2024, 16(3), 552; https://doi.org/10.3390/rs16030552 - 31 Jan 2024
Cited by 13 | Viewed by 4851
Abstract
This paper presents a methodology to detect the coastal erosion and progradation effects in the ‘Atrato River’ delta, located in the Gulf of Urabá in Colombia, using SAR (Synthetic Aperture Radar) images. Erosion is the physical–mechanical loss of the soil that affects its [...] Read more.
This paper presents a methodology to detect the coastal erosion and progradation effects in the ‘Atrato River’ delta, located in the Gulf of Urabá in Colombia, using SAR (Synthetic Aperture Radar) images. Erosion is the physical–mechanical loss of the soil that affects its functions and ecosystem services while producing a reduction in its productive capacity. Progradation is the deposition of layers in the basinward direction while moving coastward. Other studies have investigated these two phenomena using optical images, encountering difficulties due to the persistent presence of clouds in this region. In order to avoid the cloud effects, in this study, we used 16 Sentinel 1 SAR images with two different polarizations between 2016 and 2023. First, each image was rescaled from 0 to 255, then the image was despeckled by a deep learning (DL) model. Afterwards, a single RGB image was composed with the filtered polarizations. Next, a classifier with 99% accuracy based on Otsu’s method was used to determine whether each pixel was water or not. Then, the classified image was registered to a reference one using Oriented FAST and Rotated BRIEF (ORB) descriptor. Finally, a multitemporal analysis was performed by comparing every image to the previous one to identify the studied phenomena, calculating areas. Also, all images were integrated to obtain a heatmap that showed the overall changes across eight years (2016–2023) in a single image. The multitemporal analysis performed found that the newly created mouth is the most active area for these processes, coinciding with other studies. In addition, a comparison of these findings with the Oceanic Niño Index (ONI) showed a relative delayed coupling to the erosion process and a coupling of progradation with dry and wet seasons. Full article
(This article belongs to the Special Issue Coastal and Littoral Observation Using Remote Sensing)
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9 pages, 452 KB  
Proceeding Paper
Multivariable NARX Based Neural Networks Models for Short-Term Water Level Forecasting
by Jackson B. Renteria-Mena, Douglas Plaza and Eduardo Giraldo
Eng. Proc. 2023, 39(1), 60; https://doi.org/10.3390/engproc2023039060 - 5 Jul 2023
Cited by 8 | Viewed by 2577
Abstract
In this work a novel application for multivariable forecasting is presented, applied to hydrological variables and based on a multivariable NARX model. The proposed approach is designed for two hydrological stations located at the Atrato River in Colombia where the variables of water [...] Read more.
In this work a novel application for multivariable forecasting is presented, applied to hydrological variables and based on a multivariable NARX model. The proposed approach is designed for two hydrological stations located at the Atrato River in Colombia where the variables of water level, water flow and water precipitation are correlated by using the NARX model based on a neural network structure. The structure of the NARX-based neural network is designed in order to consider the complex dynamics of hydrological variables and their corresponding cross-correlations. A short-term water level forecasting is designed based on the NARX model, to be used as an early warning flood system. The validation of the proposed approach is performed by comparing the estimation error with an ARX dynamic model. As a result, it is shown that a NARX model structure is more suitable for water level forecasting than simplified structures. Full article
(This article belongs to the Proceedings of The 9th International Conference on Time Series and Forecasting)
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26 pages, 3364 KB  
Article
Health Risk Assessment for Human Exposure to Heavy Metals via Food Consumption in Inhabitants of Middle Basin of the Atrato River in the Colombian Pacific
by Gabriel Caicedo-Rivas, Manuel Salas-Moreno and José Marrugo-Negrete
Int. J. Environ. Res. Public Health 2023, 20(1), 435; https://doi.org/10.3390/ijerph20010435 - 27 Dec 2022
Cited by 24 | Viewed by 6249
Abstract
The Atrato river basin is one of the world’s most biodiverse areas; however, it is highly impacted by mercury gold mining, which generates air, water, and soil pollution. (1) Background: The concentrations of persistent heavy metal pollutants, mercury (Hg), lead (Pb), cadmium (Cd), [...] Read more.
The Atrato river basin is one of the world’s most biodiverse areas; however, it is highly impacted by mercury gold mining, which generates air, water, and soil pollution. (1) Background: The concentrations of persistent heavy metal pollutants, mercury (Hg), lead (Pb), cadmium (Cd), and arsenic (As) in the fish, fruits, and vegetables most consumed by the riverside inhabitants of the middle basin of the Atrato river represent a danger to public health; (2) Methods: A total of 154 samples of different fruits and vegetables and 440 samples of fish were analyzed by atomic absorption spectroscopy. A sample of 446 people were surveyed to evaluate food consumption and carcinogenic and non-carcinogenic risk; (4) Conclusions: High concentrations of As, Hg, Pb, and Cd were identified in fish, fruits-tubers, and vegetables-stems commonly consumed by inhabitants of the middle basin of the Atrato River, which exceeded the Codex limits and the limits established by the WHO/FAO, especially for carnivorous fish species. A high carcinogenic and non-carcinogenic risk was evidenced amongst inhabitants of the middle basin of the Atrato River due to the consumption of fish contaminated with high concentrations of As, MeHg, and THg. The risk due to the consumption of vegetables was very low. Full article
(This article belongs to the Topic Environmental Toxicology and Human Health)
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23 pages, 8851 KB  
Article
Streamflow Variability in Colombian Pacific Basins and Their Teleconnections with Climate Indices
by Teresita Canchala, Wilmar Loaiza Cerón, Félix Francés, Yesid Carvajal-Escobar, Rita Valéria Andreoli, Mary Toshie Kayano, Wilfredo Alfonso-Morales, Eduardo Caicedo-Bravo and Rodrigo Augusto Ferreira de Souza
Water 2020, 12(2), 526; https://doi.org/10.3390/w12020526 - 13 Feb 2020
Cited by 32 | Viewed by 6211
Abstract
Oceanic-atmospheric phenomena of different time scales concurrently might affect the streamflow in several basins around the world. The Atrato River Basin (ARB) and Patía River Basin (PRB) of the Colombian Pacific region are examples of such basins. Nevertheless, the relations between the streamflows [...] Read more.
Oceanic-atmospheric phenomena of different time scales concurrently might affect the streamflow in several basins around the world. The Atrato River Basin (ARB) and Patía River Basin (PRB) of the Colombian Pacific region are examples of such basins. Nevertheless, the relations between the streamflows in the ARB and PRB and the oceanic-atmospheric factors have not been examined considering different temporal scales. Hence, this article studies the relations of the climate indices and the variability of the streamflows in the ARB and PRB at interannual and decadal timescales. To this, the streamflow variability modes were obtained from the principal component analysis (PCA); furthermore, their linear dependence with indices of the El Niño/Southern Oscillation (ENSO), precipitation (PRP), the Choco low-level jet (CJ), and other indices were quantified through (a) Pearson and Kendall’s tau correlations, and (b) wavelet transform. The PCA presented a single significant mode for each basin, with an explained variance of around 80%. The correlation analyses between the PC1s of the ARB and PRB, and the climate indices showed significant positive (negative) high correlations with PRP, CJ, and Southern Oscillation Index (SOI) (ENSO indices). The wavelet coherence analysis showed significant coherencies between ENSO and ARB: at interannual (2–7 years) and decadal scale (8–14), preferably with the sea surface temperature (SST) in the east and west Tropical Pacific Ocean (TPO). For PRB with the SST in the central and western regions of the TPO in the interannual (4–8 years) and decadal (8–14 years) scales, the decreases (increases) in streamflow precede the El Niño (La Niña) events. These results indicate multiscale relations between the basins’ streamflow and climate phenomena not documented in previous works, relevant to forecast the extreme flow events in the Colombian Pacific rivers and for planning and implementing strategies for the sustainable use of water resources in the basins studied. Full article
(This article belongs to the Special Issue Assessment of Spatial and Temporal Variability of Water Resources)
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23 pages, 14567 KB  
Article
Streamflow Intensification Driven by the Atlantic Multidecadal Oscillation (AMO) in the Atrato River Basin, Northwestern Colombia
by Wilmar Loaiza Cerón, Mary Toshie Kayano, Rita Valeria Andreoli, Alvaro Avila, Teresita Canchala, Félix Francés, Irma Ayes Rivera, Wilfredo Alfonso-Morales, Rodrigo Augusto Ferreira de Souza and Yesid Carvajal-Escobar
Water 2020, 12(1), 216; https://doi.org/10.3390/w12010216 - 13 Jan 2020
Cited by 16 | Viewed by 6149
Abstract
The impact of the Atlantic Multidecadal Oscillation (AMO) on the variations in the streamflow in the Atrato River Basin (ARB) during the 1965–2016 period was analyzed here by considering the cold (1965–1994) and warm (1995–2015) phases of this oscillation. The mean streamflow increased [...] Read more.
The impact of the Atlantic Multidecadal Oscillation (AMO) on the variations in the streamflow in the Atrato River Basin (ARB) during the 1965–2016 period was analyzed here by considering the cold (1965–1994) and warm (1995–2015) phases of this oscillation. The mean streamflow increased after 1994 (AMO phase change). This increase is related to the strengthening of the zonal gradients of the sea surface temperature (SST) and sea level pressure (SLP) between the tropical central Pacific and the tropical Atlantic after 1994 (warm AMO phase). These gradients contributed to strengthen the Walker cell related upward movement over northern and northwestern South America, in particular during November-December (ND). Consistently, the frequency (R20 mm) and intensity (SDII) of extreme daily rainfall events increased during the 1995–2015 period. Our results show a connection between the AMO and the increase in the streamflow in the ARB during the last five decades. These results contribute to the studies of resilience and climate adaptation in the region. Full article
(This article belongs to the Special Issue Effects of Oceanic-Atmospheric Oscillations on Rivers)
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16 pages, 5270 KB  
Article
Analysis of Floodplain Dynamics in the Atrato River Colombia Using SAR Interferometry
by Sebastián Palomino-Ángel, Jesús A. Anaya-Acevedo, Marc Simard, Tien-Hao Liao and Fernando Jaramillo
Water 2019, 11(5), 875; https://doi.org/10.3390/w11050875 - 26 Apr 2019
Cited by 30 | Viewed by 7222
Abstract
Floodplain water flows have large volumetric flowrates and high complexity in space and time that are difficult to understand using water level gauges. We here analyze the spatial and temporal fluctuations of surface water flows in the floodplain of the Atrato River, Colombia, [...] Read more.
Floodplain water flows have large volumetric flowrates and high complexity in space and time that are difficult to understand using water level gauges. We here analyze the spatial and temporal fluctuations of surface water flows in the floodplain of the Atrato River, Colombia, in order to evaluate their hydrological connectivity. The basin is one of the rainiest areas of the world with wetland ecosystems threatened by the expansion of agriculture and mining activities. We used 16 Differential Interferometric Synthetic Aperture Radars (DInSAR) phase observations from the ALOS-PALSAR L-band instrument acquired between 2008–2010 to characterize the flow of surface water. We were able to observe water level change in vegetated wetland areas and identify flooding patterns. In the lower basin, flow patterns are conditioned by fluctuations in the levels of the main river channel, whereas in the middle basin, topography and superficial channels strongly influence the flow and connectivity. We found that the variations in water level in a station on the main channel 87 km upstream explained more than 56% of the variations in water level in the floodplain. This result shows that, despite current expansion of agriculture and mining activities, there remain significant hydrological connectivity between wetlands and the Atrato River. This study demonstrates the use of DInSAR for a spatially comprehensive monitoring of the Atrato River basin hydrology. For the first time, we identified the spatiotemporal patterns of surface water flow of the region. We recommend these observations serve as a baseline to monitor the potential impact of ongoing human activities on surface water flows across the Atrato River basin. Full article
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14 pages, 244 KB  
Review
Rights of Nature: Rivers That Can Stand in Court
by Lidia Cano Pecharroman
Resources 2018, 7(1), 13; https://doi.org/10.3390/resources7010013 - 14 Feb 2018
Cited by 146 | Viewed by 40392
Abstract
An increasing number of court rulings and legislation worldwide are recognizing rights of nature to be protected and preserved. Recognizing these rights also entails the recognition that nature has the right to stand in court and to be represented for its defense. This [...] Read more.
An increasing number of court rulings and legislation worldwide are recognizing rights of nature to be protected and preserved. Recognizing these rights also entails the recognition that nature has the right to stand in court and to be represented for its defense. This is still an incipient field and every step taken in this direction constitutes a precedent from which to learn and on which to base new rulings and legislation initiatives. Within this doctrine, rivers seem to be on the spotlight and court rulings on the rights of rivers are the ones setting precedent. These cases have taken place in New Zealand, Ecuador, India, and Colombia. This review looks into what all these rulings and legislation worldwide say about the rights of nature and what legal and systemic considerations should be taken into account as the recognition of the rights of nature moves forward. Full article
(This article belongs to the Special Issue New Water Regimes)
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