Temperature Surface of Guaíba Lake, RS, from time series of MODIS images

Abstract

The Guaíba lake is located in an area of complex weather variation and is influenced by many atmospheric circulation systems, bringing about violent occluded fronts, and, sometimes, intense precipitation. In Rio Grande do Sul, during El Niño, air temperatures and the precipitation index are higher, contrary to La Niña. Moreover, the Guaíba Lake receives water from the Guaíba's Hydrographical Region, which corresponds to 1/3 of Rio Grande do Sul State, and is thus an important water body to the metropolitan region of Porto Alegre. Methods that seek to understand the behavior of Guaíba lake surface water temperature (LSWT) may lead to relevant information to identify periods of more or less water warming, as well as the relations between LSWT, water quality deterioration and risks to human health. This paper aims to comprehend the behavior of Guaíba LSWT during periods of climatic anomalies (El Niño/La Niña). Therefore, 418 sea surface temperature (SST) images from the MODIS sensor were processed with SeaDas 7.2 software. The quarterly averages of LSWT were obtained and compared to the climatological anomalies in Equatorial Pacific Ocean. LSWT behavior is more complex in El Niño/La Niña periods. The results show that during climatic abnormality periods there are no direct relationship between the warming/cooling of Guaíba LSWT and the warming/cooling of Equatorial Pacific Ocean's SST. The precipitation indices were more significant to the behavior of LSWT during El Niño periods, but for all periods (of climatic normality and abnormality), air temperature is what most influences LSWT. This relation occurs with climatic factors of water retention time, water entry and precipitation, and air temperature. There is a major correspondence during La Niña periods with the cooling of Guaíba LSWT only for some years. On the other hand, during El Niño periods there are no correspondences of this phenomenon with the warming of Guaíba LSWT. There are only more intense oscillations in surface temperatures than during regular and La Niña periods, but with a tendency to LSWT warming. Keywords: El Niño; La Niña; Remote sensing. RESUMOO Lago Guaíba localiza-se em uma área de complexa variação de tempo meteorológico, e sofre influência de vários sistemas atmosféricos ocasionando choques frontais e por vezes precipitações intensas. No Estado, durante o El Niño, as temperaturas do ar são mais elevadas e o índice pluviométrico é maior, de modo contrário à La Niña. Além disso recebe águas da Região Hidrográfica do Guaíba, o que corresponde a 1/3 do Estado do Rio Grande do Sul, constituindo-se em importante corpo d'água para a região metropolitana de Porto Alegre. Métodos que buscam a compreensão do comportamento da TSL (temperatura de superfície de lago) do Guaíba podem trazer informações relevantes para identificação de períodos de maior e menor aquecimento da água, assim como as relações entre TSL e deterioração da qualidade da água e riscos a saúde humana. Esse trabalho tem como objetivo compreender o comportamento da TSL do ...

Comparison of Methods to Estimate Lake-Surface-Water Temperature Using Landsat 7 ETM+ and MODIS Imagery: Case Study of a Large Shallow Subtropical Lake in Southern Brazil

“…Landsat 7 ETM+ was chosen over other Landsat sensors because it has a time series that covers the entire period of the measured data, providing more matching dates of observed temperatures and satellite images, whereas the Landsat 5 mission ended in 2011, and Landsat 8 OLI was launched in 2013, resulting in fewer suitable images from these two sensors. In the case of MODIS, both MOD11 and MOD28, which have been used in previous studies of LSWT (e.g., References [8,10,16,23,41,42]), are available for Lake Mangueira, and are described in the following sections.…”

“…Data from satellite sensors may provide better information on LSWT variability than conventional field monitoring, since most modern sensors have improved capabilities with respect to spectral (e.g., spectral range of the thermal infrared), radiometric, temporal, and spatial resolutions [5,7]. Although satellite-derived water temperature is a description of the LSWT only in the top layer (i.e., approximately the upper 100 µm, called "skin temperature"), it may provide important information about the patterns of water-temperature variations in lakes, and has been used in many studies, such as analysis of temperature patterns and heat budget [8,9], spatial distribution of water-quality variables [4], evaporation estimation [10], LSWT spatial gradients [6,[11][12][13], LSWT temporal-variation patterns [14,15], and the assessment of the impact of El Niño/La Niña events [16] and climate change [3,17,18] on lakes.…”

“…Most LSWT studies have evaluated the accuracy of individual sensors [27], such as MODIS (e.g., References [6,10,16,23]) and Landsat (e.g., References [12,24,28]), indicating the limitations of each sensor, namely, the spatial/temporal resolution trade-off, different Landsat methodologies, and sensor accuracy. Therefore, comparative analysis considering different sensors to estimate LSWT is still needed and may reveal important differences and limitations in the application of each sensor and direct studies [29].…”

The Estimation of Water Quality Parameters in Lentic Environments Through Remote Sensing Technologies: a Review of the Past Two Decades

“…Other non-optically active parameters can also be inferred indirectly through their relationship with the optically active ones: total phosphorous (TP) (XIONG et al, 2019), total nitrogen (TN) (LIU et al, 2015), pH, chemical oxygen demand (COD) and dissolved oxygen (DO) (WANG et al, 2012;WANG et al, 2014;PU et al, 2019). Time series of satellite images have also been used to monitor surface water temperature (ALCÂNTARA et al, 2011;CURTARELLI et al, 2014;LUZ;ROCHA, 2017), an important parameter not only for WQ but also as a means to monitor climatic changes (LI et al, 2017).…”