scholarly journals Influência do Uso e Cobertura da Terra Aliado à Precipitação Pluviométrica na Qualidade da Água da Bacia Hidrográfica do Rio Ingaí – RS/Brasil

2016 ◽  
Vol 32 ◽  
pp. 143
Author(s):  
Makele Rosa De Paula ◽  
Ana Caroline Paim Benedetti ◽  
Waterloo Pereira Filho
Keyword(s):  
Chl A ◽  
Landsat 5 Tm

Os impactos resultantes da ação antrópica geram uma série de alterações na qualidade da água. Nesse sentido, o objetivo desta pesquisa consiste em analisar a influência do uso e cobertura da terra e da precipitação pluviométrica da bacia hidrográfica do rio Ingaí nos parâmetros de qualidade da água do mesmo. A partir das imagens do Landsat 5/TM foram realizados os mapas de uso e cobertura da terra para as datas 21/01/2009 (período vegetativo - agricultura) e 20/10/2009 (período de entressafra – solo exposto). Para isso, utilizou-se o software SPRING 4.3.3. As classes de uso e cobertura da terra definidas foram: floresta, agricultura, solo exposto, área urbana, água e campo. Conjuntamente aos dados de precipitação e uso e cobertura da terra observaram-se então as suas influências em alguns parâmetros limnológicos: total de sólidos em suspensão (TSS); transparência da água (DS), clorofila a (Chl a), temperatura da água (temp.), potencial hidrogeniônico (pH) e condutividade elétrica (CE). Concluiu-se que a alteração das propriedades da água do rio Ingaí possui forte relação com as alterações no uso e cobertura da terra da bacia, provenientes principalmente de fontes difusas, devido à extensa área destinada a agricultura, áreas de solo exposto, aliados a ocorrência de precipitação pluviométrica. 

scholarly journals Empirical Estimation of Nutrient, Organic Matter and Algal Chlorophyll in a Drinking Water Reservoir Using Landsat 5 TM Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2256
Author(s):  
Md Mamun ◽  
Jannatul Ferdous ◽  
Kwang-Guk An
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Organic Matter ◽  
Linear Regression Analysis ◽  
Satellite Image ◽  
Empirical Models ◽  
Anthropogenic Factors ◽  
Chl A ◽  
Landsat 5 Tm

The main objective of this study was to develop empirical models from Landsat 5 TM data to monitor nutrient (total phosphorus: TP), organic matter (biological oxygen demand: BOD), and algal chlorophyll (chlorophyll-a: CHL-a). Instead of traditional monitoring techniques, such models could be substituted for water quality assessment in aquatic systems. A set of models were generated relating surface reflectance values of four bands of Landsat 5 TM and in-situ data by multiple linear regression analysis. Radiometric and atmospheric corrections improved the satellite image quality. A total of 32 compositions of different bands of Landsat 5 TM images were considered to find the correlation coefficient (r) with in-situ measurement of TP, BOD, and CHL-a levels collected from five sampling sites in 2001, 2006, and 2010. The results showed that TP, BOD, and CHL-a correlate well with Landsat 5 TM band reflectance values. TP (r = −0.79) and CHL-a (r = −0.79) showed the strongest relations with B1 (Blue). In contrast, BOD showed the highest correlation with B1 (Blue) (r = −0.75) and B1*B3/B4 (Blue*Red/Near-infrared) (r = −0.76). Considering the r values, significant bands and their compositions were identified and used to generate linear equations. Such equations for Landsat 5 TM could detect TP, BOD, and CHL-a with accuracies of 67%, 65%, and 72%, respectively. The developed empirical models were then applied to all study sites on the Paldang Reservoir to monitor spatio-temporal distributions of TP, BOD, and CHL-a for the month of September using Landsat 5 TM images of the year 2001, 2006, and 2010. The results showed that TP, BOD, and CHL-a decreased from 2001 to 2006 and 2010. However, S3 and S4 still have water quality issues and are influenced by climatic and anthropogenic factors, which could significantly affect reservoir drinking water quality. Overall, the present study suggested that the Landsat 5 TM may be appropriate for estimating and monitoring water quality parameters in the reservoir.

수륙양용드론을 활용한 수질측정 및 DO, 온도에 따른 Chl-a 예측식 개발

2019 ◽  
Vol 19 (2) ◽  
pp. 111-121
Author(s):  
Soo Hyeon Kim ◽  
◽  
Sungchul Hong ◽  
Pyongin Yi ◽  
Seongho Jang ◽  
...  
Keyword(s):  
Chl A

PEMANFAATAN DATA PENGINDERAAN JAUH DAN TEKNOLOGI SIG UNTUK MENGIDENTIFIKASI BUILT UP AREA DAN KAITANNYA DENGAN RTRW DI KABUPATEN KENDAL

2019 ◽  
Vol 3 ◽  
pp. 521
Author(s):  
Mailendra Mailendra
Keyword(s):  
Supervised Classification ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Landsat 5 Tm

Integrasi data penginderaan jauh dengan sistem informasi geografis telah banyak dikembangkan, dan salah satunya dalam melihat perkembangan lahan terbangun. Tujuan penelitian ini adalah untuk melihat perkembangan lahan terbangun dan kesesuaiannya dengan Rencana Pola Ruang Kabupaten Kendal. Kemudian metode yang digunakan yaitu metode supervised classification dengan memanfaatkan data citra landsat 5 TM dan landsat 8 OLI yang selanjutnya dihitung luas dari masing lahan terbangun berdasarkan data temporal tahun 1990, tahun 2015 dan tahun 2017. Setelah diketahui luas lahan terbangun selanjutnya dioverlay dengan peta rencana pola ruang Kabupaten Kendal untuk melihat sesuai atau tidaknya penempatan lahan terbangun tersebut. Adapun hasil penelitiannya yaitu setiap tahunnya lahan terbangun terus meningkat di Kabupaten Kendal, terjadi peningkatan yang cukup signifikan dalam dua tahun terakhir yaitu tahun 2015 hingga tahun 2017. Selanjutnya diperkirakan 88 % lahan terbangun tersebut telah sesuai dengan RTRW karena sudah berada pada kawasan budidaya.

A Poisson-Pareto model of Chl-a fluorescence signals in marine environments

2015 ◽  
Vol 55 ◽  
pp. 373
Author(s):  
Stephen Woodcock ◽  
Bojana Manojlovic ◽  
Mark Baird ◽  
Peter Ralph
Keyword(s):  
Marine Environments ◽  
Chl A ◽  
Chl A Fluorescence ◽  
Pareto Model

scholarly journals The Role of Environmental Factors on the Fishery Catch of the Squid Uroteuthis chinensis in the Pearl River Estuary, China

2021 ◽  
Vol 9 (2) ◽  
pp. 131
Author(s):  
Dongliang Wang ◽  
Lijun Yao ◽  
Jing Yu ◽  
Pimao Chen
Keyword(s):  
River Estuary ◽  
Pearl River Estuary ◽  
Sea Surface ◽  
Spatiotemporal Variability ◽  
Pearl River ◽  
Coastal Current ◽  
Catch Per Unit Effort ◽  
Chl A ◽  
The Pearl River Estuary ◽  
The Pearl River

The Pearl River Estuary (PRE) is one of the major fishing grounds for the squid Uroteuthis chinensis. Taking that into consideration, this study analyzes the environmental effects on the spatiotemporal variability of U. chinensis in the PRE, on the basis of the Generalized Additive Model (GAM) and Clustering Fishing Tactics (CFT), using satellite and in situ observations. Results show that 63.1% of the total variation in U. chinensis Catch Per Unit Effort (CPUE) in the PRE could be explained by looking into outside factors. The most important one was the interaction of sea surface temperature (SST) and month, with a contribution of 26.7%, followed by the interaction effect of depth and month, fishermen’s fishing tactics, sea surface salinity (SSS), chlorophyll a concentration (Chl a), and year, with contributions of 12.8%, 8.5%, 7.7%, 4.0%, and 3.1%, respectively. In summary, U. chinensis in the PRE was mainly distributed over areas with an SST of 22–29 °C, SSS of 32.5–34‰, Chl a of 0–0.3 mg × m−3, and water depth of 40–140 m. The distribution of U. chinensis in the PRE was affected by the western Guangdong coastal current, distribution of marine primary productivity, and variation of habitat conditions. Lower stock of U. chinensis in the PRE was connected with La Niña in 2008.

scholarly journals Satellite-Derived Protein Concentration of Phytoplankton in the Southwestern East/Japan Sea

2021 ◽  
Vol 9 (2) ◽  
pp. 189
Author(s):  
Hyeonji Bae ◽  
Dabin Lee ◽  
Jae Joong Kang ◽  
Jae Hyung Lee ◽  
Naeun Jo ◽  
...  
Keyword(s):  
Protein Concentration ◽  
Japan Sea ◽  
Biological Properties ◽  
Measured Data ◽  
Trophic Levels ◽  
Coefficient Of Determination ◽  
P Value ◽  
Chl A ◽  
Major Factors

The cellular macromolecular contents and energy value of phytoplankton as primary food source determine the growth of higher trophic levels, affecting the balance and sustainability of oceanic food webs. Especially, proteins are more directly linked with basic functions of phytoplankton biosynthesis and cell division and transferred through the food chains. In recent years, the East/Japan Sea (EJS) has been changed dramatically in environmental conditions, such as physical and chemical characteristics, as well as biological properties. Therefore, developing an algorithm to estimate the protein concentration of phytoplankton and monitor their spatiotemporal variations on a broad scale would be invaluable. To derive the protein concentration of phytoplankton in EJS, the new regional algorithm was developed by using multiple linear regression analyses based on field-measured data which were obtained from 2012 to 2018 in the southwestern EJS. The major factors for the protein concentration were identified as chlorophyll-a (Chl-a) and sea surface nitrate (SSN) in the southwestern EJS. The coefficient of determination (r2) between field-measured and algorithm-derived protein concentrations was 0.55, which is rather low but reliable. The satellite-derived estimation generally follows the 1:1 line with the field-measured data, with Pearson’s correlation coefficient, which was 0.40 (p-value < 0.01, n = 135). No remarkable trend in the long-term annual protein concentration of phytoplankton was found in the study area during our observation period. However, some seasonal difference was observed in winter protein concentration between the 2003–2005 and 2017–2019 periods. The algorithm is developed for the regional East/Japan Sea (EJS) and could contribute to long-term monitoring for climate-associated ecosystem changes. For a better understanding of spatiotemporal variation in the protein concentration of phytoplankton in the EJS, this algorithm should be further improved with continuous field surveys.

scholarly journals Nutrient Loading, Temperature and Heat Wave Effects on Nutrients, Oxygen and Metabolism in Shallow Lake Mesocosms Pre-Adapted for 11 Years

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 127
Author(s):  
Erik Jeppesen ◽  
Joachim Audet ◽  
Thomas A. Davidson ◽  
Érika M. Neif ◽  
Yu Cao ◽  
...  
Keyword(s):  
Heat Wave ◽  
Shallow Lake ◽  
Nutrient Loading ◽  
Global Changes ◽  
Significant Positive Effect ◽  
Mixed Effect ◽  
Chl A ◽  
Nutrient Loadings ◽  
Positive Effect ◽  
Oxygen Concentrations

Global changes (e.g., warming and population growth) affect nutrient loadings and temperatures, but global warming also results in more frequent extreme events, such as heat waves. Using data from the world’s longest-running shallow lake experimental mesocosm facility, we studied the effects of different levels of nutrient loadings combined with varying temperatures, which also included a simulated 1-month summer heat wave (HW), on nutrient and oxygen concentrations, gross ecosystem primary production (GPP), ecosystem respiration (ER), net ecosystem production (NEP) and bacterioplankton production (BACPR). The mesocosms had two nutrient levels (high (HN) and low (LN)) combined with three different temperatures according to the IPCC 2007 warming scenarios (unheated, A2 and A2 + 50%) that were applied for 11 years prior to the present experiment. The simulated HW consisted of 5 °C extra temperature increases only in the A2 and A2 + 50% treatments applied from 1 July to 1 August 2014. Linear mixed effect modeling revealed a strong effect of nutrient treatment on the concentration of chlorophyll a (Chl-a), on various forms of phosphorus and nitrogen as well as on oxygen concentration and oxygen percentage (24 h means). Applying the full dataset, we also found a significant positive effect of nutrient loading on GPP, ER, NEP and BACPR, and of temperature on ER and BACPR. The HW had a significant positive effect on GPP and ER. When dividing the data into LN and HN, temperature also had a significant positive effect on Chl-a in LN and on orthophosphate in HN. Linear mixed models revealed differential effects of nutrients, Chl-a and macrophyte abundance (PVI) on the metabolism variables, with PVI being particularly important in the LN mesocosms. All metabolism variables also responded strongly to a cooling-low irradiance event in the middle of the HW, resulting in a severe drop in oxygen concentrations, not least in the HN heated mesocosms. Our results demonstrate strong effects of nutrients as well as an overall rapid response in oxygen metabolism and BACPR to changes in temperature, including HWs, making them sensitive ecosystem indicators of climate warming.

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