RESUMEN
This study proposes a new method to retrieve the bathymetry of turbid-water floodplains from the inundation frequency (IF) data derived from over 32 years of composite optical remote sensing data. The new method was tested and validated over the Curuai floodplain in the lower Amazon River, where the entire bathymetry was surveyed in 2004, and water level gauge data has been available since 1960. The depth was estimated based on the relationship derived from IF and surveyed depth data, and the results were compared to those retrieved from bare-Earth DEM. We further assessed the sensitivity of the approach by analyzing the deepest part of the lake (i.e., permanent water body ~ 8m) with high IF, as well as the effect of gradual sedimentation in the lake over time. The results showed that the model is highly accurate and sensitive to IF changes even in the permanent water body areas, suggesting that this model can be used in other seasonal lakes worldwide with turbid-waters, where large-scale bathymetry surveys are not feasible due to high operation costs.
Asunto(s)
Monitoreo del Ambiente , Lagos , Ríos , Monitoreo del Ambiente/métodosRESUMEN
In this present research, we assessed the performance of band algorithms in estimating chlorophyll-a (Chl-a) concentration based on bands of two new sensors: Operational Land Imager onboard Landsat-8 satellite (OLI/Landsat-8), and MultiSpectral Instrument onboard Sentinel-2A (MSI/Sentinel-2A). Band combinations designed for Thematic Mapper onboard Landsat-5 satellite (TM/Landsat-5) and MEdium Resolution Imaging Spectrometer onboard Envisat platform (MERIS/Envisat) were adapted for OLI/Landsat-8 and MSI/Sentinel-2A bands. Algorithms were calibrated using in situ measurements collected in three field campaigns carried out in different seasons. The study area was the Barra Bonita hydroelectric reservoir (BBHR), a highly productive aquatic system. With exception of the three-band algorithm, the algorithms were spectrally few affected by sensors changes. On the other hands, algorithm performance has been hampered by the bio-optical difference in the reservoir sections, drought in 2014 and pigment packaging.
RESUMEN
Wildfires are behaving differently now compared to other time in history in relation to frequency, intensity and affected ecosystems. In Brazil, unprecedented fires are being experienced in the last decade. Thus, to prevent and minimize similar disasters, we must better understand the natural and human drivers of such extreme events. The Brazilian Pantanal is the largest contiguous wetland in the world and a complex environmental system. In 2020, Pantanal experienced catastrophic wildfires due to the synergy between climate, inadequate fire management strategies and weak environmental regulations. In this study, we analyzed recent patterns and changes in fire behavior across the Pantanal based on land use and cover (LULC) classes. The inter-annual variability of the fire and land cover changes between 2000 and 2021 was assessed using BA from MCD64A1 V.6 product and LULC data from Landsat satellite. Our work reveals that fires in the Pantanal over the last two decades tended to occur more frequently in grassland than in others land cover types, but the 2020 fires have preferentially burned forest regions. Large fire patches are more frequent in forest and grasslands; in contrast, croplands exhibit small patches. The results highlight that a broad scale analysis does not reflect distinct localized patterns, thus stratified and refined studies are required. Our work contributes as a first step to disentangling the role of anthropogenic-related drivers, namely LULC changes, in shaping the fire regime in the Pantanal biome. This is crucial not only to predict future fire activity but also to guide appropriated fire management in the region.
Asunto(s)
Incendios , Incendios Forestales , Ecosistema , Bosques , Humanos , HumedalesRESUMEN
Climate projections models indicate that longer periods of droughts are expected within the next 100 years in various parts of South America. To understand the effects of longer periods of droughts on aquatic environments, we investigated the response of chlorophyll-a (Chl-a) concentration to recent severe drought events in the Barra Bonita Hydroelectric Reservoir (BBHR) in São Paulo State, Brazil. We used satellite imagery to estimate the Chl-a concentration from 2014 to 2020 using the Slope Index (NRMSE of 18.92% and bias of -0.20 mg m-3). Ancillary data such as precipitation, water level and air temperature from the same period were also used. Drought events were identified using the standardized precipitation index (SPI). In addition, we computed the probability of future drought events. Two periods showed extremely dry conditions: 1) January-February (2014) and 2) April-May (2020). Both periods were characterized by a recurrence probability of 1in every 50 years. The highest correlation was observed between Chl-a concentration and SPI (-0.97) in 2014, while Chl-a had had the highest correlation with water level (-0.59) in 2020. These results provide new insights into the influence of extreme drought events on the Chl-a concentration in the BBHR and their relationship with other climate variables and reservoir water levels. Drought events imply less rainfall, higher temperatures, and atmospheric dryness, and these factors affect evaporation and the water levels in the reservoir.
Asunto(s)
Clorofila , Sequías , Brasil , Clorofila A , Estaciones del Año , AguaRESUMEN
As of October 8th, 2020, the number of confirmed cases and deaths in Brazil due to COVID-19 hit 5,002,357 and 148,304, respectively, making the country one of the most affected by the pandemic. The State of São Paulo (SSP) hosts the largest number of confirmed cases in Brazil, with over 1,016,755 cases to date. This study was carried out to investigate how the social distancing measures could have influenced the Ibitinga reservoir's water transparency in São Paulo State, Brazil. We hypothesize that although the city's drainage is the major reservoir's input, as opposed to what has been reported elsewhere, the effect of extensive lockdown in the city of São Paulo due to COVID-19 is marginal on the water transparency. A time series of OLI/Landsat-8 images since 2014 were used to estimate the Secchi Disk Depth (ZSD). The COVID-19 cases and deaths (per 100,000 inhabitants), and social isolation index were used to find links between the ZSD and COVID-19. The results showed that the highest ZDS (higher than 1.6 m) occurred during the dry season (Austral autumn and beginning of Austral winter) and the lowest (0.4-0.8 m) during March 2020 (end of Austral summer). Paired sample t-Tests between images of 2020 and all the others showed that April 20th values were not different from that of June 14th, April 17th and March 18th. ZSD values from May 20th were not statistically different from May 14th and April 15th; June 20th values were not different from June 14th; and March 20th values were statistically different from all. We therefore conclude that, based on satellite data, the lockdown in SSP unlikely have influenced the water transparency in the Ibitinga reservoir.
RESUMEN
One of the worst socio-environmental disasters to mark the history of Brazil and the world occurred in November 2015 and involved the mining sector. The collapse of the Fundao dam released approximately 43 million m³ of iron ore tailings, which moved downstream to reach the Doce River. This resulted in the contamination of water, soil, and sediments along the entire course of the river, which also affected its mouth in the Atlantic Ocean. Four years after the disaster, several socio-environmental problems continue to persist in the affected areas. In this context, the reservoirs built along the Doce River deserve special attention as they are artificial environments that are highly vulnerable to changes in water parameters. This study aims to determine water quality indicators of these reservoirs using remote sensing data and image processing methods, including semi-analytical algorithms, to comprehend the progress of eutrophication processes. Operational land imager/Landsat-8 data (from 2013 to 2019) were used to map the suspended particulate matter (SPM), euphotic zone (Zeu) and chlorophyll-a (Chl-a) before and after the collapse. The results showed significant changes in SPM and Zeu in the reservoirs after the collapse. Non-conformity of these parameters is observed even now, and they tend to intensify during rainy periods when resuspension processes of sediments occur. Moreover, there has been an increase in the eutrophication of reservoirs as noticed by the significant increase in Chl-a after the disaster, especially in January, July, and August.
Asunto(s)
Contaminantes Químicos del Agua , Agua , Océano Atlántico , Brasil , Monitoreo del Ambiente , Eutrofización , Contaminantes Químicos del Agua/análisisRESUMEN
The Fundão dam, located in Mariana city, Minas Gerais State, southeastern Brazil, collapsed in November 2015, causing the discharge of over 50 million m3 of iron ore tailings in the Doce river basin. The mud generated by the disaster was composed of fine particulates (silt and clay), which are more sensitive to wind dispersion. Based on laboratory analyses and hydrodynamic modeling, early research postulates the hypothesis that the mud discharged in the ocean traveled 10,000 km up north and may have reached the Abrolhos coral reefs. This research aims to investigate further this hypothesis based on broad-scale remotely sensed data. Satellite images were used to estimate the suspended particulate matter (SPM) in the coastal zone before, during, and after the dam collapse. Results indicate that higher concentrations of SPM appeared during and post-collapse and were restricted to the coastal zone and its shallower regions, including beaches. However, we demonstrate that under exceptional circumstances the wind blew to the north, carrying fine particulate material and potentially-toxic metals derived from the iron ore tailings towards the northeastern Brazilian coastline and possibly the reefs of the Abrolhos Bank.
Asunto(s)
Desastres , Colapso de la Estructura , Brasil , Arrecifes de Coral , RíosRESUMEN
As of 16 May 2020, the number of confirmed cases and deaths in Brazil due to COVID-19 hit 233,142 and 15,633, respectively, making the country one of the most affected by the pandemic. The State of São Paulo (SSP) hosts the largest number of confirmed cases in Brazil, with over 60,000 cases to date. Here we investigate the spatial distribution and spreading patterns of COVID-19 in the SSP by mapping the spatial autocorrelation and the clustering patterns of the virus in relation to the population density and the number of hospital beds. Clustering analysis indicated that São Paulo City is a significant hotspot for both the confirmed cases and deaths, whereas other cities across the state were less affected. Bivariate Moran's I showed a low relationship between the number of deaths and population density, whereas the number of hospital beds was less related, implying that the fatality depends substantially on the actual patients' conditions. Multivariate Local Geary showed a positive relationship between the number of deaths and population density, with two cities near São Paulo City being negatively related; the relationship between the number of deaths and hospital beds availability in the São Paulo Metropolitan Area was basically positive. Social isolation measures throughout the State of São Paulo have been gradually increasing since early March, an action that helped to slow down the emergence of the new confirmed cases, highlighting the importance of the safe-distancing measures in mitigating the local transmission within and between cities in the state.
Asunto(s)
COVID-19/epidemiología , Análisis Espacio-Temporal , Brasil/epidemiología , COVID-19/mortalidad , Ciudades/epidemiología , Ambiente , Humanos , Pandemias , SARS-CoV-2 , Factores SocioeconómicosRESUMEN
Here we present a proof of concept evaluation of the impacts of riverbed-mining on river-wetland connectivity by analyzing the temporal trends of the flood frequencies in the Vietnamese Mekong Delta (VMD), while accounting for the effect of dyke constructions. We focus on the Long Xuyen Quadrangle (LXQ), which is significant in terms of biodiversity and economic contribution to the VMD as it is one of the most important food baskets of Southeast Asia that depends on seasonal flooding. Our results indicate that the flood frequency in LXQ has decreased significantly over the past 20 years (1995-2015). Time-series analyses of water level data at Chau Doc, Tan Chau, and Can Tho stations confirmed that the overall descending trend is statistically significant (p-value < 0.001 and tau ~ 0.1). However, the river discharge at Kratie showed no significant trend (p-value = 0.98) over the same period. This indicates that the flood frequency is associated with the lowering of the riverbed (incision) other than climatic factors. The connectivity analysis also revealed a remarkable drop in the inundation duration after early 2000, which corresponds to the previous observations of the shifting shoreline of the VMD from construction to shrinking. Finally, regression and principal component analyses underpinned the strong causality between the riverbed-mining and the decreased seasonal flooding patterns in LXQ, while accounting for the effect of the dyke system over the last decades (R2 = 0.75). This study offers compelling evidences on the relationship between sand-mining in the river and the disrupted flood regimes in VMD. The reduction in water and sediments that is necessary for sustaining current rates of agricultural production in the long term would endanger the livelihoods of millions of VMD inhabitants.
RESUMEN
Natural and manmade disasters have occurred more frequently due mainly to climate change and human pressure for productivity. One of the world's vastest disasters in the mining industry occurred due to the collapse of the Fundao dam, Brazil, which discharged about 43 million m3 of iron tailings at the Doce River basin. Extreme natural events also affect this region and provoke substantial mass movement and substantial floods in the Doce River basin, and flow of anomalous volumes of sediments in its mouth. The extent of tailings and the sediment flow in these events were approached in previous research. However, their effects on the penetration of sunlight into the water column in the coastal region are unknown. Here, we evaluate the effects of an extreme natural event and a manmade disaster on the light regime of the water column at the Doce River mouth, using remote sensing data. In both events, the spatial and temporal distribution of suspended particulate matter (SPM), diffuse light attenuation coefficient (Kd490) and Euphotic Zone (Zeu) were analyzed. During the natural event, light penetration into the water column was strongly attenuated (Kd490: 0.35â¯m-1; SPM: 8.81â¯g/m3) but re-established after 1â¯month due to sediment deposition. In the case of the dam collapse, the attenuation of light penetration was also intense along the event (Kd490: 0.34â¯m-1; SPM: 13.87â¯g/m3); however, sediment deposition occurred sooner. Re-suspension of sediments due to wind action was recurrent after 8â¯months of the dam collapse, in contrast to the natural event, where re-suspension was not perceptible in satellite images. The results indicate that both events have considerable effects on the penetration of light in the water column, but with different intensity and length.
RESUMEN
We used a three-dimensional model to assess the dynamics of diffusive carbon dioxide flux (F(CO2)) from a hydroelectric reservoir located at Amazon rainforest. Our results showed that for the studied periods (2013 summer/wet and winter/dry seasons) the surface averaged F(CO2) presented similar behaviors, with regular emissions peaks. The mean daily surface averaged F(CO2) showed no significant difference between the seasons (p>0.01), with values around -1338mg Cm-2day-1 (summer/wet) and -1395mg Cm-2day-1 (winter/dry). At diel scale, the F(CO2) was large during the night and morning and low during the afternoon in both seasons. Regarding its spatial distribution, the F(CO2) showed to be more heterogeneous during the summer/wet than during the winter/dry season. The highest F(CO2) were observed at transition zone (-300mg Cm-2h-1) during summer and at littoral zone (-55mg Cm-2h-1) during the winter. The total CO2 emitted by the reservoir along 2013 year was estimated to be 1.1Tg C year-1. By extrapolating our results we found that the total carbon emitted by all Amazonian reservoirs can be around 7Tg C year-1, which is 22% lower than the previous published estimate. This significant difference should not be neglected in the carbon inventories since the carbon emission is a key factor when comparing the environmental impacts of different sources of electricity generation and can influences decision makers in the selection of the more appropriate source of electricity and, in case of hydroelectricity, the geographical position of the reservoirs.
RESUMEN
Reservoirs are artificial environments built by humans, and the impacts of these environments are not completely known. Retention time and high nutrient availability in the water increases the eutrophic level. Eutrophication is directly correlated to primary productivity by phytoplankton. These organisms have an important role in the environment. However, high concentrations of determined species can lead to public health problems. Species of cyanobacteria produce toxins that in determined concentrations can cause serious diseases in the liver and nervous system, which could lead to death. Phytoplankton has photoactive pigments that can be used to identify these toxins. Thus, remote sensing data is a viable alternative for mapping these pigments, and consequently, the trophic. Chlorophyll-a (Chl-a) is present in all phytoplankton species. Therefore, the aim of this work was to evaluate the performance of images of the sensor Operational Land Imager (OLI) onboard the Landsat-8 satellite in determining Chl-a concentrations and estimating the trophic level in a tropical reservoir. Empirical models were fitted using data from two field surveys conducted in May and October 2014 (Austral Autumn and Austral Spring, respectively). Models were applied in a temporal series of OLI images from May 2013 to October 2014. The estimated Chl-a concentration was used to classify the trophic level from a trophic state index that adopted the concentration of this pigment-like parameter. The models of Chl-a concentration showed reasonable results, but their performance was likely impaired by the atmospheric correction. Consequently, the trophic level classification also did not obtain better results.