Estimation of chlorophyll a content in inland turbidity waters using WorldView-2 imagery: a case study of the Guanting Reservoir, Beijing, China

Wang, Xing; Gong, Zhaoning; Pu, Ruiliang

doi:10.1007/s10661-018-6978-7

Cited by 30 publications

(22 citation statements)

References 26 publications

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“…In 1997, the reservoir was forced to withdraw from the urban drinking water system. After effective protection and restoration, the water quality of the reservoir improved, and it reopened in 2007 [35]. Due to a long-term interaction of the unique geographical environment, water quality and climatic conditions, Guanting Reservoir serves as a biodiversity hotspot for an abundancy of wet plants, especially in the upstream reservoir area where the water area is wide and the water depth gradient is obvious.…”

Section: A Study Areamentioning

confidence: 99%

Remote Sensing Monitoring of the Bottom Topography in a Shallow Reservoir and the Spatiotemporal Changes of Submerged Aquatic Vegetation Under Water Depth Fluctuations

Gong

Liang

Wang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Monitoring the growth and distribution of submerged aquatic vegetation (SAV) is crucial to the protection and restoration of the ecosystem of inland reservoirs. Considering the high sensitivity of SAV to water depth fluctuations in Guanting Reservoir, China, in this study, we realized the reconstruction of bottom topography by combining changing water level with a long time series remote sensing technology and explored the spatiotemporal succession law of SAV by analyzing the effect of water depth on the spatiotemporal distribution of SAV. Results of water depth spatial distribution in Guanting Reservoir were obtained by using water and land boundary lines to construct underwater terrain contours. The accuracy of estimated water depth data from remote sensing images was verified with measured water depth data, and the average relative error of water depth estimation results was about 0.25 m. The experimental results show that (1) the SWIR bands of Landsat images could avoid the interference of aquatic vegetation and realize the separation of land and water; and (2) after separating water area from land, an SWIR1_NIR index was used to effectively map SAV distribution in the reservoir. The results also indicate that the distribution of SAV in the reservoir is suitable for the water depth range of 0 − 2 m. Water depth fluctuations cause changes in the spatial distribution of suitable water depth. It is the main reason for the change of SAV distribution area in the reservoir during the past 20 years.

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Section: A Study Areamentioning

confidence: 99%

Remote Sensing Monitoring of the Bottom Topography in a Shallow Reservoir and the Spatiotemporal Changes of Submerged Aquatic Vegetation Under Water Depth Fluctuations

Gong

Liang

Wang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…A concentração de clorofila-A nos reservatórios indica a existência de organismos fotossintetizantes (Esteves, 2011;Wang et al, 2018), pois altos teores de clorofila-A são estimulados por fatores internos como fósforo total, transparência das águas; e por fatores externos como a temperatura (Batista et al, 2013).…”

Section: Análise Dos Atributos Limnológicos De Qualidade Da áGua Dos Reservatóriosunclassified

Análise de atributos limnológicos em reservatórios do semiárido nordestino

Sousa

Espíndola

Silva

2021

Rev. Bras. Geog. Fis.

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Este trabalho objetiva investigar os parâmetros limnológicos: condutividade, sólidos totais, turbidez, pH, e clorofila-A, de quatro reservatórios multiuso do semiárido nordestino, sendo estes: Barreiras, Bocaina, Estreito e Piaus. Durante os anos de 2018 a 2019, tais reservatório sofreram impactos decorrentes da seca resultando em volumes inferiores a 30% da capacidade total desses reservatórios. Ao longo do período estudado, foram comparados valores obtidos in situ aos valores estabelecidos na resolução CONAMA n° 357/2005 para águas doces de classe II. A correlação linear foi aplicada para verificar as relações entre os parâmetros estudados e fatores naturais como temperatura média e precipitação. A caracterização climática, volumétrica e a ocorrência de seca, foram fatores importantes na discussão dos atributos limnológicos. Os resultados demostram que a ocorrência da seca tem relação com a redução dos volumes dos reservatórios, impactando negativamente na qualidade da água. Os sólidos em suspensão na água foram apontados como determinantes na variação de outros parâmetros, principalmente, da turbidez, da condutividade e do pH. A clorofila-A, variável de grande importância para a qualidade da água, apresentou correlação significativa positiva com precipitação e temperatura. Quanto os valores determinados pelo CONAMA, observou-se que o pH, sólidos totais, e clorofila-A encontram-se com valores superiores ao que é recomendado. A turbidez foi o único parâmetro que se enquadrou dentro do limite de aceitabilidade desta resolução. Os reservatórios Barreiras e Estreito apresentaram os piores valores médios para os parâmetros analisados. Analysis of limnological attributes in northeastern semi-arid reservoirs A B S T R A C TThis work investigates the limnological parameters: conductivity, total solids, turbidity, pH, and chlorophyll-A, from four multipurpose reservoirs in the northeastern semi-arid region of Brazil, namely: Barreiras, Bocaina, Estreito, and Piaus. During the years 2018 to 2019, these reservoirs suffered impacts due to droughts, resulting in volumes below 30% of the reservoirs' full capacity. Over the study period, values obtained in situ were compared to the values established in CONAMA resolution n° 357/2005 for class II freshwater. A linear correlation was applied to verify the relationships between the studied parameters and natural factors such as average temperature and precipitation. Climatic and volumetric characterization and the occurrence of drought were essential factors in the discussion of limnological attributes. The results show that droughts' occurrence is related to the reduction of reservoir volumes, negatively impacting water quality. Suspended solids in water were identified as determining the variation of other parameters, mainly turbidity, conductivity, and pH. Chlorophyll-A, a variable of great importance for water quality, showed a significant positive correlation with precipitation and temperature. Regarding the values determined by CONAMA, it was observed that the pH, total solids, and chlorophyll-A are higher than what is recommended. Turbidity was the only parameter that fell within the acceptability limit of this resolution. The Barreiras and Estreito reservoirs had the worst average values for the analyzed parameters.Keywords: water quality, CONAMA resolution n° 357/2005, drought, semi-arid.

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“…Various traditional empirical models based on statistical regression and reflectance features have been developed to monitor optically active water parameters, e.g., Chl-a and TSP. Single-band models based on the correlation between the reflectance at a given wavelength and the water quality parameters [3,4]; two-band models based on the ratio of the peak reflectance to the valley [5,6] and three-band or four-band models [7][8][9] can be considered as empirical models. However, the robustness of these traditional empirical models is usually challenged by the varying and complex conditions of water, even if they are specially developed for optically active water substances; thus, these empirical models need to be tuned on the basis of locally collected samples to achieve good performance.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Traditional Empirical Models and BPNN Models in Monitoring the Concentrations of Chlorophyll-A and Total Suspended Particulate of Eutrophic and Turbid Waters

Jiang

Liu

Xing

et al. 2021

Water

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In order to use in situ sensed reflectance to monitor the concentrations of chlorophyll-a (Chl-a) and total suspended particulate (TSP) of waters in the Pearl River Delta, which is featured by the highly developed network of rivers, channels and ponds, 135 sets of simultaneously collected water samples and reflectance were used to test the performance of the traditional empirical models (band ratio, three bands) and the machine learning models of a back-propagation neural network (BPNN). The results of the laboratory analysis with the water samples show that the Chl-a ranges from 3 to 256 µg·L−1 with an average of 39 µg·L−1 while the TSP ranges from 8 to 162 mg·L−1 and averages 42.5 mg·L−1. Ninety sets of 135 samples are used as training data to develop the retrieval models, and the remaining ones are used to validate the models. The results show that the proposed band ratio models, the three-band combination models, and the corresponding BPNN models are generally successful in estimating the Chl-a and the TSP, and the mean relative error (MRE) can be lower than 30% and 25%, respectively. However, the BPNN models have no better performance than the traditional empirical models, e.g., in the estimation of TSP on the basis of the reflectance at 555 and 750 nm (R555 and R750, respectively), the model of BPNN (R555, R750) has an MRE of 23.91%, larger than that of the R750/R555 model. These results suggest that these traditional empirical models are usable in monitoring the optically active water quality parameters of Chl-a and TSP for eutrophic and turbid waters, while the machine learning models have no significant advantages, especially when the cost of training samples is considered. To improve the performance of machine learning models in future applications on the basis of ground sensor networks, large datasets covering various water situations and optimization of input variables of band configuration should be strengthened.

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Estimation of chlorophyll a content in inland turbidity waters using WorldView-2 imagery: a case study of the Guanting Reservoir, Beijing, China

Cited by 30 publications

References 26 publications

Remote Sensing Monitoring of the Bottom Topography in a Shallow Reservoir and the Spatiotemporal Changes of Submerged Aquatic Vegetation Under Water Depth Fluctuations

Remote Sensing Monitoring of the Bottom Topography in a Shallow Reservoir and the Spatiotemporal Changes of Submerged Aquatic Vegetation Under Water Depth Fluctuations

Análise de atributos limnológicos em reservatórios do semiárido nordestino

Evaluating Traditional Empirical Models and BPNN Models in Monitoring the Concentrations of Chlorophyll-A and Total Suspended Particulate of Eutrophic and Turbid Waters

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