scholarly journals Estimation of Suspended Sediment Concentration from Remote Sensing and In Situ Measurement over Lake Tana, Ethiopia

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Zelalem R. Womber ◽  
Fasikaw A. Zimale ◽  
Mebrahtom G. Kebedew ◽  
Bekalu W. Asers ◽  
Nikole M. DeLuca ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Temporal Distribution ◽  
Sediment Concentration ◽  
In Situ Measurement ◽  
Spatial And Temporal Distribution ◽  
Lake Tana

Discharge from basins joining a lake is the main factor determining the lake volume and sediment inflow to the lake. Suspended sediment is an important parameter for describing the water quality of aquatic ecosystems. Lake Tana is an important and the largest lake in Ethiopia for the local ecological system. However, environmental change and anthropogenic activities in the area threaten its water quality. The conventional methods of suspended sediment concentration (SSC) observation are unable to determine and compare spatial and temporal SSC patterns for the lake over a period of years. Remote sensing methods have made it possible to map SSC. The objective of this study is to characterize the spatial and temporal distribution of suspended sediment of Lake Tana using in situ measurement and remote sensing applications and specifically to develop a relationship between in situ and remote sensing observation to retrieve suspended sediment concentration and map the spatal distribution of SSC. This study used MODIS-Terra and in situ data to characterize the spatial and temporal distribution of SSC in the rainy season. Four sampling campaigns (20 samples per campaign) were carried out on Lake Tana, and the first three sampled campaigns on May 11–13, 2018, June 08–10, 2018, and July 15–17, 2018, were used for calibration of regression models. MODIS-Terra reflectance in NIR was found best related to in situ water quality data and varies linearly with SSC (r2 = 0.81) and turbidity (r2 = 0.85). Secchi disc depth (SDD) found the best fit for a power relation with NIR band reflectance (r2 = 0.74). The MODIS-Terra reflectance in red was found to be poorly related to in situ measurements. The relation in NIR reflectance was validated using the LOOCV (leave-one-out-cross-validation) technique and the fourth sampled data set collected on August 12–14, 2018. Developed models are validated with RMSE of 42.96 mg/l, 14.6 NTU, and 0.17 m, ARE of 23.3%, 27.6%, and 12.4%, and RRMSE of 25.1%, 44.5%, and 29.6% for SSC, turbidity, and SDD, respectively, using LOOCV. The equation was also validated using August 2018 collected data sets with RMSE of 87.6 mg/l, 11.7 NTU, 0.08 m, ARE of 20.8%, 25.9%, and 28.8%, and RRMSE of 17.8%, 20.5%, and 27.9% for SSC, turbidity, and SDD, respectively. Applying the developed regression model, a 10-year time series of SSC from 2008–2017 for May-August was estimated and the trend was tested using the Mann–Kendall trend test. It was found that an increasing trend was observed from the period 2008 to 2017. The result shows that satellite data like the MODIS-Terra imagery could be used to monitor and obtain past records of SSC with the developed equation. The increasing SSC can be reduced by implementing selected management practices in the surrounding watersheds of the lake to reduce nutrient and sediment inflow.

scholarly journals Automatic calibration of a large-scale sediment model using suspended sediment concentration, water quality, and remote sensing data

RBRH ◽  
2019 ◽  
Vol 24 ◽  
Author(s):  
Hugo de Oliveira Fagundes ◽  
Fernando Mainardi Fan ◽  
Rodrigo Cauduro Dias de Paiva
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Suspended Sediment ◽  
Large Scale ◽  
Suspended Sediment Concentration ◽  
Remote Sensing Data ◽  
Sediment Concentration ◽  
Spatial Discretization ◽  
Calibration And Validation ◽  
Sediment Model

ABSTRACT Calibration and validation are two important steps in the application of sediment models requiring observed data. This study aims to investigate the potential use of suspended sediment concentration (SSC), water quality and remote sensing data to calibrate and validate a large-scale sediment model. Observed data from across 108 stations located in the Doce River basin was used for the period between 1997-2010. Ten calibration and validation experiments using the MOCOM-UA optimization algorithm coupled with the MGB-SED model were carried out, which, over the same period of time, resulted in 37 calibration and 111 validation tests. The experiments were performed by modifying metrics, spatial discretization, observed data and parameters of the MOCOM-UA algorithm. Results generally demonstrated that the values of correlation presented slight variations and were superior in the calibration step. Additionally, increasing spatial discretization or establishing a background concentration for the model allowed for improved results. In a station with high quantity of SSC data, calibration improved the ENS coefficient from -0.44 to 0.44. The experiments showed that the spectral surface reflectance, total suspended solids and turbidity data have the potential to enhance the performance of sediment models.

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

2015 ◽  
Vol 7 (5) ◽  
pp. 5373-5397 ◽  
Author(s):  
Jin-Ling Kong ◽  
Xiao-Ming Sun ◽  
David Wong ◽  
Yan Chen ◽  
Jing Yang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Suspended Sediment ◽  
Analytical Model ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration

scholarly journals ESTIMATION Of SUSPENDED SEDIMENT CONCENTRATION USING VNREDSAT – 1A MULTISPECTRAL DATA, A CASE STUDY IN RED RIVER, HANOI, VIETNAM

2018 ◽  
Vol 11 (3) ◽  
pp. 49-60 ◽  
Author(s):  
Le Hung Trinh ◽  
V. R. Zablotskii ◽  
Thi Giang Le ◽  
Thi Thu Hien Dinh ◽  
Thi Trinh Le ◽  
...  
Keyword(s):  
Water Quality ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Surface Water Quality ◽  
Ground Truth ◽  
Monitoring And Evaluation ◽  
Sediment Concentration ◽  
Red River ◽  
Multispectral Data ◽  
Synoptic View

The traditional methods for measuring water quality variables are timeconsuming and do not give a synoptic view of a water body or, more significantly, a synoptic view of different water bodies across the landscape. However, remote sensing technology with advantages such as wide area coverage and short revisit interval have been effectively used for environmental pollution applications, such as for monitoring water quality parameters. Many studies around the world show that optical satellite imagery can be used effectively in evaluating suspended sediment concentration. This article presents results of monitoring suspended sediment concentration in Red River, Hanoi, Vietnam through ground truth measurements and VNREDSat-1A multispectral data. The results obtained in the study can be used to serve the management, monitoring and evaluation of surface water quality.

scholarly journals Developing of Total Suspended Sediment Model Using Landsat-8 Satellite Image and In-Situ Data at The Surabaya Coast, East Java, Indonesia

2017 ◽  
Vol 49 (1) ◽  
pp. 73 ◽  
Author(s):  
Teguh Hariyanto ◽  
Trismono C. Krisna ◽  
Khomsin Khomsin ◽  
Cherie Bhekti Pribadi ◽  
Nadjadji Anwar
Keyword(s):  
Water Quality ◽  
Suspended Sediment ◽  
Coastal Water ◽  
Satellite Image ◽  
Coastal Region ◽  
Sediment Concentration ◽  
Landsat 8 ◽  
Total Suspended Sediment ◽  
Coastal Water Quality

The decrease of coastal-water quality in the Surabaya coastal region can be recognized from the conceentration of Total Suspended Sediment(TSS ) . As a result we need a system for monitoring sediment concentration in the coastal region of Surabaya which regularly measures TSS. The principle to model and monitor TSSconcentration using remote sensing methods is by the integration of Landsat-8OLI satellites image processing using some ofTSS-models then those are analyzed for looking its suitability with TSS value direcly measured in the field ( in-situ measurement). The TSS value modeled from all algorithms validated usingcorrelation analysis and linear regression . The result shows that TSS model with the highest correlation value is TSS algorithm by Budiman (2004)with r value 0.991. Hence this algorithm can be used to investigate TSS-distribution which represent the coastal water quality of Surabaya with TSS value between 75 mg/L to 125 mg/L.

scholarly journals Quantifying Suspended Sediment using Acoustic Doppler Current Profiler in Tidung Island Seawaters

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Henry Munandar Manik ◽  
Randi Firdaus
Keyword(s):  
Water Column ◽  
Suspended Sediment ◽  
Suspended Solids ◽  
Acoustic Doppler Current Profiler ◽  
Sediment Concentration ◽  
In Situ Measurement ◽  
Ocean Current ◽  
Echo Intensity ◽  
Current Profiler

Tidung Island, located near Jakarta Bay, is a tourism and conservation area. It is necessary to keep these seawaters unpolluted. To calculate the level of pollution, it is necessary to know the sediment concentration. Quantifying concentration suspended sediment is important for knowledge of sediment transport. Researchers usually use water sample analysis and optical method for quantifying suspended sediment in seawater. Less accuracies of these methods are due to under sample of seawater and the existence of biological fouling. One promising method to measure concentration of suspended sediment is using Acoustic Doppler Current Profiler (ADCP). ADCP is usually used by oceanographer and hydrographer to measure ocean current. In this research, ADCP with 300 kHz operating frequency was used effectively to measure suspended sediment concentration (SSC) and ocean current simultaneously. The echo intensity received from suspended sediment was computed using sonar equations to quantify SSC. The empirical equation between echo intensity and SSC was found. The SSC value obtained by ADCP was also compared with in situ measurement. The result showed that quantified SSC value obtained by ADCP was nearly equal with SSC obtained from in situ measurement with coefficient correlation of 0.98. The high concentration ranged from 55 mg/L to 80 mg/L at the surface layer to a depth 12 m, moderate concentration ranged from 45 mg/L to 55 mg/L at a depth 12 m to 40 m, and low concentration less than 45 mg/L at a depth greater than 40 m. The distribution of SSC was correlated with ocean current condition. In small currents, suspended solids will settle faster so that the concentration in the water column will decrease. Conversely, if the velocity is high, suspended solids will continue to float carried by the current in the water column so that the concentration is high.

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