A Semi-analytical Model for Remote Sensing Retrieval of Suspended Sediment Concentration in the Gulf of Bohai, China

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Estimating the concentration of physico chemical parameters in hydroelectric power plant reservoir

The United Nations Educational, Scientific and Cultural Organization (UNESCO) defines the amazon region and adjacent areas, such as the Pantanal, as world heritage territories, since they possess unique flora and fauna and great biodiversity. Unfortunately, these regions have increasingly been suffering from anthropogenic impacts. One of the main anthropogenic impacts in the last decades has been the construction of hydroelectric power plants. As a result, dramatic altering of these ecosystems has been observed, including changes in water levels, decreased oxygenation and loss of downstream organic matter, with consequent intense land use and population influxes after the filling and operation of these reservoirs. This, in turn, leads to extreme loss of biodiversity in these areas, due to the large-scale deforestation. The fishing industry in place before construction of dams and reservoirs, for example, has become much more intense, attracting large populations in search of work, employment and income. Environmental monitoring is fundamental for reservoir management, and several studies around the world have been performed in order to evaluate the water quality of these ecosystems. The Brazilian Amazon, in particular, goes through well defined annual hydrological cycles, which are very importante since their study aids in monitoring anthropogenic environmental impacts and can lead to policy and decision making with regard to environmental management of this area. The water quality of amazon reservoirs is greatly influenced by this defined hydrological cycle, which, in turn, causes variations of microbiological, physical and chemical characteristics. Eutrophication, one of the main processes leading to water deterioration in lentic environments, is mostly caused by anthropogenic activities, such as the releases of industrial and domestic effluents into water bodies. Physico-chemical water parameters typically related to eutrophication are, among others, chlorophyll-a levels, transparency and total suspended solids, which can, thus, be used to assess the eutrophic state of water bodies. Usually, these parameters must be investigated by going out to the field and manually measuring water transparency with the use of a Secchi disk, and taking water samples to the laboratory in order to obtain chlorophyll-a and total suspended solid concentrations. These processes are time- consuming and require trained personnel. However, we have proposed other techniques to environmental monitoring studies which do not require fieldwork, such as remote sensing and computational intelligence. Simulations in different reservoirs were performed to determine a relationship between these physico-chemical parameters and the spectral response. Based on the in situ measurements, empirical models were established to relate the reflectance of the reservoir measured by the satellites. The images were calibrated and corrected atmospherically. Statistical analysis using error estimation was used to evaluate the most accurate methodology. The Neural Networks were trained by hydrological cycle, and were useful to estimate the physicalchemical parameters of the water from the reflectance of visible bands and NIR of satellite images, with better results for the period with few clouds in the regions analyzed. The present study shows the application of wavelet neural network to estimate water quality parameters using concentration of the water samples collected in the Amazon reservoir and Cefni reservoir, UK. Sattelite imagens from Landsats and Sentinel-2 were used to train the ANN by hydrological cycle. The trained ANNs demonstrated good results between observed and estimated after Atmospheric corrections in satellites images. The ANNs showed in the results are useful to estimate these concentrations using remote sensing and wavelet transform for image processing. Therefore, the techniques proposed and applied in the present study are noteworthy since they can aid in evaluating important physico-chemical parameters, which, in turn, allows for identification of possible anthropogenic impacts, being relevant in environmental management and policy decision-making processes. The tests results showed that the predicted values have good accurate. Improving efficiency to monitor water quality parameters and confirm the reliability and accuracy of the approaches proposed for monitoring water reservoirs. This thesis contributes to the evaluation of the accuracy of different methods in the estimation of physical-chemical parameters, from satellite images and artificial neural networks. For future work, the accuracy of the results can be improved by adding more satellite images and testing new neural networks with applications in new water reservoirs

Uso de imágenes satelitales para determinar los parámetros de calidad del agua en los ríos amazónicos Neshuya y Aguaytía - Perú

Los ecosistemas acuáticos son ambientes naturales que están en constante cambio y esto es debido a las variaciones físico-químicas que pueda ocurrir en el agua, estas variaciones físico-químicas son conocidas como parámetros de calidad de agua. Existen métodos tradicionales para su medición, pero con el transcurrir del tiempo han surgido otros métodos como es el caso de las imágenes satelitales. Los parámetros de calidad de agua que han sido evaluados con imágenes satelitales son la profundidad del disco Secchi, las concentraciones de clorofila, la carga de pigmento, los sedimentos totales suspendidos, la temperatura, Demanda Bioquímica de Oxígeno (BOD), Demanda Química de Oxígeno (COD), Carbono Orgánico Total (TOC), Índice de Permanganato (CODmn) y Nitrógeno Amoniacal. Las imágenes satelitales pueden proporcionar información muy valiosa ya que puede obtener información de lugares remotos y datos en un tiempo pasado que no han sido colectados in situ. El propósito de la presente tesis fue demostrar que el uso de imágenes satelitales puede determinar los valores de calidad de agua de los ríos Neshuya y Aguaytía. Diferentes autores han propuesto métodos haciendo uso de imágenes satelitales, en esta investigación estamos usando el método de correlación y regresión múltiple. Los parámetros evaluados fueron Demanda Bioquímica de Oxígeno (BOD), Demanda Química de Oxígeno (COD), Carbono Orgánico Total (TOC), Índice de Permanganato (CODmn) y Nitrógeno Amoniacal. El análisis de los datos mostró que BOD, COD y TOC tiene un coeficiente de correlación igual a uno es decir tienen una correlación perfecta con la reflectancia de la imagen. Esto quiere decir que se puede determinar los parámetros de calidad de agua haciendo uso de las imágenes satelitales. Finalmente, aunque los datos satelitales pueden usarse para reflejar los parámetros de calidad del agua, esta técnica es valioso e importante para áreas remotas donde el acceso directo no es fácil y donde el costo de la muestra y el análisis de laboratorio es alto, se debe enfatizar que esta técnica no puede sustituir los métodos tradicionales porque algunos parámetros de la calidad del agua, como metales pesados, nitrato, el fosfato y los contaminantes orgánicos no se pueden determinar por teledetección.Aquatic ecosystems are natural environments that are constantly changing and this is due to the physicochemical variations that may occur in the water, these physicochemical variations are known as water quality parameters. There are traditional methods for its measurement, but with the passage of time other methods have emerged such as satellite images. Water quality parameters that have been evaluated with satellite images are Secchi disk depth, chlorophyll concentrations, pigment loading, total suspended sediments, temperature, Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Organic Carbon (TOC), Permanganate Index (CODmn) and Ammoniacal Nitrogen. Satellite images can provide very valuable information since you can obtain information from remote locations and data in a past time that have not been collected in situ. The purpose of this thesis was to demonstrate that the use of satellite images can determine the water quality values of the Neshuya and Aguaytía rivers. Different authors have proposed methods using satellite images, in this investigation we are using the method of correlation and multiple regression. The parameters evaluated were Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Organic Carbon (TOC), Permanganate Index (CODmn) and Ammoniacal Nitrogen. The analysis of the data showed that BOD, COD and TOC have a correlation coefficient equal to one, that is, they have a perfect correlation with the reflectance of the image. This means that the water quality parameters can be determined using satellite images. Finally, although satellite data can be used to reflect water quality parameters, this technique is valuable and important for remote areas where direct access is not easy and where the cost of the sample and laboratory analysis is high, it should be Emphasize that this technique cannot replace traditional methods because some water quality parameters, such as heavy metals, nitrate, phosphate and organic pollutants cannot be determined by remote sensing

Hidromorfologias e hidroformas costeiras locais

A indicação de "Volume" foi introduzida pelo catalogadorTese dedoutoramento. Ciências de Engenharia. Faculdade de Engenharia. Universidade do Porto. 200