Variability of Trophic State of Bottom Biotopes of the Gorky Reservoir by Sedimentary Pigments

2021 ◽  
Vol 48 (1) ◽  
pp. 82-91
Author(s):  
N. A. Timofeeva ◽  
L. E. Sigareva ◽  
V. V. Zakonnov
Keyword(s):  
Trophic State ◽  
Sedimentary Pigments

APLIKASI CITRA LANDSAT 8 OLI UNTUK IDENTIFIKASI STATUS TROFIK WADUK GAJAH MUNGKUR WONOGIRI, JAWA TENGAH

2017 ◽  
Vol 19 (2) ◽  
pp. 113
Author(s):  
Kusuma Wardani Laksitaningrum ◽  
Wirastuti Widyatmanti
Keyword(s):  
Chlorophyll A ◽  
Total Phosphorus ◽  
Trophic State ◽  
Water Clarity ◽  
Coefficient Of Determination ◽  
Physical Factors ◽  
Landsat 8 ◽  
Trophic State Index ◽  
Landsat 8 Oli ◽  
State Index

<p align="center"><strong>ABSTRAK</strong></p><p class="abstrak">Waduk Gajah Mungkur (WGM) adalah bendungan buatan yang memiliki luas genangan maksimum 8800 ha, terletak di Desa Pokoh Kidul, Kecamatan Wonogiri, Kabupaten Wonogiri. Kondisi perairan WGM dipengaruhi oleh faktor klimatologis, fisik, dan aktivitas manusia yang dapat menyumbang nutrisi sehingga mempengaruhi status trofiknya. Tujuan dari penelitian ini adalah mengkaji kemampuan citra Landsat 8 OLI untuk memperoleh parameter-parameter yang digunakan untuk menilai status trofik, menentukan dan memetakan status trofik yang diperoleh dari citra Landsat 8 OLI, dan mengevaluasi hasil pemetaan dan manfaat citra penginderaan jauh untuk identifikasi status trofik WGM. Identifikasi status trofik dilakukan berdasarkan metode <em>Trophic State Index</em> (TSI) Carlson (1997) menggunakan tiga parameter yaitu kejernihan air, total fosfor, dan klorofil-a. Model yang diperoleh berdasar pada rumus empiris dari hasil uji regresi antara pengukuran di lapangan dan nilai piksel di citra Landsat 8 OLI. Model dipilih berdasarkan nilai koefisien determinasi (R<sup>2</sup>) tertinggi. Hasil penelitian merepresentasikan bahwa nilai R<sup>2</sup> kejernihan air sebesar 0,813, total fosfor sebesar 0,268, dan klorofil-a sebesar 0,584. Apabila nilai R<sup>2 </sup>mendekati 1, maka semakin baik model regresi dapat menjelaskan suatu parameter status trofik. Berdasarkan hasil kalkulasi diperoleh distribusi yang terdiri dari kelas eutrofik ringan, eutrofik sedang, dan eutrofik berat yaitu pada rentang nilai indeks 50,051 – 80,180. Distribusi terbesar adalah eutrofik sedang. Hal tersebut menunjukkan tingkat kesuburan perairan yang tinggi dan dapat membahayakan makhluk hidup lain.</p><p><strong>Kata kunci: </strong>Waduk Gajah Mungkur, citra Landsat 8 OLI, regresi, TSI, status trofik</p><p class="judulABS"><strong>ABSTRACT</strong></p><p class="Abstrakeng">Gajah Mungkur Reservoir is an artificial dam that has a maximum inundated areas of 8800 ha, located in Pokoh Kidul Village, Wonogiri Regency. The reservoir’s water conditions are affected by climatological and physical factors, as well as human activities that can contribute to nutrients that affect its trophic state. This study aimed to assess the Landsat 8 OLI capabilities to obtain parameters that are used to determine its trophic state, identifying and mapping the trophic state based on parameters derived from Landsat 8 OLI, and evaluating the results of the mapping and the benefits of remote sensing imagery for identification of its trophic state. Identification of trophic state is based on Trophic State Index (TSI) Carlson (1997), which uses three parameters there are water clarity, total phosphorus, and chlorophyll-a. The model is based on an empirical formula of regression between measurements in the field and the pixel values in Landsat 8 OLI. Model is selected on the highest value towards coefficient of determination (R<sup>2</sup>). The results represented that R<sup>2</sup> of water clarity is 0.813, total phosphorus is 0.268, and chlorophyll-a is 0.584. If R<sup>2</sup> close to 1, regression model will describe the parameters of the trophic state better. Based on the calculation the distribution consists of mild eutrophic, moderate eutrophic, and heavy eutrophic that has index values from 50.051 to 80.18. The most distribution is moderate eutrophication, and it showed the high level of trophic state and may harm other living beings.</p><p><strong><em>Keywords: </em></strong><em>Gajah Mungkur Reservoir, </em><em>L</em><em>andsat 8 OLI satellite imagery, regression, TSI, trophic state</em></p>

scholarly journals Determining trophic state in experimental lakes

1999 ◽  
Vol 44 (4) ◽  
pp. 1176-1179 ◽  
Author(s):  
Gertrud K. Nürnberg
Keyword(s):  
Trophic State

scholarly journals Trophic State Evolution over 15 Years in a Tropical Reservoir with Low Nitrogen Concentrations and Cyanobacteria Predominance

2016 ◽  
Vol 227 (3) ◽  
Author(s):  
Frederico Guilherme de Souza Beghelli ◽  
Daniele Frascareli ◽  
Marcelo Luiz Martins Pompêo ◽  
Viviane Moschini-Carlos
Keyword(s):  
Trophic State ◽  
Tropical Reservoir ◽  
State Evolution ◽  
Nitrogen Concentrations ◽  
Low Nitrogen

scholarly journals Assessment of Trophic Responses of a Reservoir to Seasonal and Annual Variations in Monsoon

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2117
Author(s):  
Su-mi Kim ◽  
Hyun-su Kim
Keyword(s):  
Water Quality ◽  
Trophic State ◽  
Monsoon Season ◽  
Phytoplankton Growth ◽  
Phosphorus Loading ◽  
Nutrient Concentrations ◽  
Trophic State Index ◽  
Post Monsoon ◽  
Post Monsoon Season ◽  
State Index

The variations in water quality parameters and trophic status of a multipurpose reservoir in response to changing intensity of monsoon rain was investigated by applying a trophic state index deviation (TSID) analysis and an empirical regression model to the data collected in two periods from 2014 to 2017. The reservoir in general maintained mesotrophic conditions, and Carlson’s trophic state index (TSIc) was affected most by TSITP. Nutrient concentrations, particularly phosphorus, did not show strong correlations with precipitation, particularly in the period with weak monsoon, and a significant increase in total phosphorus (TP) was observed in Spring 2015, indicating the possibility of internal phosphorus loading under decreased depth and stability of water body due to a lack of precipitation. TSIChl was higher than TSISD in most data in period 1 when a negligible increase in precipitation was observed in the monsoon season while a significant fraction in period 2 showed the opposite trend. Phytoplankton growth was not limited by nutrient limitation although nutrient ratios (N/P) of most samples were significantly higher than 20, indicating phosphorus-limited condition. TSID and regression analysis indicated that phytoplankton growth was limited by zooplankton grazing in the Spring, and that cell concentrations and community structure in the monsoon and post-monsoon season were controlled by the changing intensity of the monsoon, as evidenced by the positive and negative relationships between community size and cyanobacterial population with the amount of precipitation in the Summer, respectively. The possibility of contribution from internal loading and an increase in cyanobacterial population associated with weak monsoon, in addition to potential for nutrient enrichment in the post-monsoon season, implies a need for the application of more stringent water quality management in the reservoir that can handle all potential scenarios of eutrophication.

scholarly journals Remote Estimation of Trophic State Index for Inland Waters Using Landsat-8 OLI Imagery

2021 ◽  
Vol 13 (10) ◽  
pp. 1988
Author(s):  
Minqi Hu ◽  
Ronghua Ma ◽  
Zhigang Cao ◽  
Junfeng Xiong ◽  
Kun Xue
Keyword(s):  
Yangtze River ◽  
Trophic State ◽  
Inland Waters ◽  
Landsat 8 ◽  
Trophic State Index ◽  
Type I ◽  
Water Type ◽  
Type Ii ◽  
Turbid Water ◽  
State Index

Remote monitoring of trophic state for inland waters is a hotspot of water quality studies worldwide. However, the complex optical properties of inland waters limit the potential of algorithms. This research aims to develop an algorithm to estimate the trophic state in inland waters. First, the turbid water index was applied for the determination of optical water types on each pixel, and water bodies are divided into two categories: algae-dominated water (Type I) and turbid water (Type II). The algal biomass index (ABI) was then established based on water classification to derive the trophic state index (TSI) proposed by Carlson (1977). The results showed a considerable precision in Type I water (R2 = 0.62, N = 282) and Type II water (R2 = 0.57, N = 132). The ABI-derived TSI outperformed several band-ratio algorithms and a machine learning method (RMSE = 4.08, MRE = 5.46%, MAE = 3.14, NSE = 0.64). Such a model was employed to generate the trophic state index of 146 lakes (> 10 km2) in eastern China from 2013 to 2020 using Landsat-8 surface reflectance data. The number of hypertrophic and oligotrophic lakes decreased from 45.89% to 21.92% and 4.11% to 1.37%, respectively, while the number of mesotrophic and eutrophic lakes increased from 12.33% to 23.97% and 37.67% to 52.74%. The annual mean TSI for the lakes in the lower reaches of the Yangtze River basin was higher than that in the middle reaches of the Yangtze River and Huai River basin. The retrieval algorithm illustrated the applicability to other sensors with an overall accuracy of 83.27% for moderate-resolution imaging spectroradiometer (MODIS) and 82.92% for Sentinel-3 OLCI sensor, demonstrating the potential for high-frequency observation and large-scale simulation capability. Our study can provide an effective trophic state assessment and support inland water management.

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