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

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.

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Quantitative Assessment on Multiple Timescale Features and Dynamics of Sea Surface Suspended Sediment Concentration Using Remote Sensing Data

Journal of Geophysical Research Oceans ◽

10.1002/2017jc013082 ◽

2017 ◽

Vol 122 (11) ◽

pp. 8739-8752 ◽

Cited By ~ 10

Author(s):

Zhou Zhou ◽

Changwei Bian ◽

Chenghao Wang ◽

Wensheng Jiang ◽

Rong Bi

Keyword(s):

Remote Sensing ◽

Suspended Sediment ◽

Quantitative Assessment ◽

Suspended Sediment Concentration ◽

Remote Sensing Data ◽

Sediment Concentration ◽

Sea Surface ◽

Sensing Data ◽

Multiple Timescale

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

Advances in Civil Engineering ◽

10.1155/2021/9948780 ◽

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.

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Estimation of Suspended Sediment Concentration in Downstream of the Ba River Basin using Remote Sensing Images

Inżynieria Mineralna ◽

10.29227/im-2021-02-27 ◽

2021 ◽

Vol 1 (2) ◽

Author(s):

Ba Dung NGUYEN ◽

Tuyet Minh DANG

Keyword(s):

Remote Sensing ◽

Suspended Sediment ◽

River Basin ◽

Large Scale ◽

Suspended Sediment Concentration ◽

Image Interpretation ◽

Sediment Concentration ◽

Initial Result ◽

Remote Sensing And Gis ◽

Landsat Satellite

Assessing the tendency of suspended sediment concentration (SSC) in the river watershedsenables a better understanding of the hydromorphological properties of its basins and the associatedprocesses. In addition, analyzing this trend is essential to address several important issues such as erosion,water pollution, human health risks, etc. Therefore, it is critical to determine a proper method to quantifyspatio-temporal variability in SSC. In recent years, remote sensing and GIS technologies are being widelyapplied to support scientists, researchers, and environmental resource investigators to quickly andsynchronously capture information on a large scale. The combination of remote sensing and GIS data willbecome the reliable and timely updated data source for the managers, researchers on many fields. Thereare several tools, software, algorithms being used in extracting information from satellites and support forthe analysis, image interpretation, data collection. The information from satellite images related to waterresources includes vegetational cover, flooding events on a large scale, rain forecast, populationdistribution, forest fire, landslide movements, sedimentation, etc., and especially information on waterquality, sediment concentration. This paper presents the initial result from LANDSAT satellite imageinterpretation to investigate the amount of sediment carried downstream of the Ba river basin.

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Research on the Coastal Suspended Sediment Movement of Matakong Island in Guinea, Africa Based on Remote Sensing Data

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.333-335.275 ◽

2013 ◽

Vol 333-335 ◽

pp. 275-279

Author(s):

Yin Cai ◽

Hong Bo Zhao ◽

Shu Hua Zuo

Keyword(s):

Remote Sensing ◽

Suspended Sediment ◽

Suspended Sediment Concentration ◽

Remote Sensing Data ◽

Sediment Concentration ◽

Concentration Data ◽

Sediment Distribution ◽

Sensing Data ◽

Sediment Movement ◽

Wide Range

A wide range of suspended sediment concentration can be obtained by satellite remote sensing. According to the multi-temporal remote sensing data and quasi-simultaneously surface sediment concentration data, research works on the surface suspended sediment distribution and movement trends of Matakong coastal area, Africa were carried out. The results showed that the suspended sediment concentration of the studied area is not large, and the sediment movement is not active. The sediment source comes from the nearshore shallow flats, where they could be entrained by the wind waves and then diffuses by the tidal currents.

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The Application of GOCI Data Based Remote Sensing Technology in the Field of Sediment Reserch

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.303-306.786 ◽

2013 ◽

Vol 303-306 ◽

pp. 786-789

Author(s):

Hua Feng Liu ◽

Rui Jie Li ◽

Xi Shan Pan ◽

Lie Mo

Keyword(s):

Remote Sensing ◽

Water Level ◽

Suspended Sediment ◽

Suspended Sediment Concentration ◽

Remote Sensing Data ◽

Sediment Concentration ◽

Acceptable Result ◽

Remote Sensing Technology ◽

Sensing Technology ◽

Sediment Transportation

The application of GOCI data in the research of sediment transportation is introduced in the paper..Compared with traditional ways to verify the simulated results, remote sensing data can contain a huge observation scope and a longer observing time.In. The computed results of water level and suspended sediment concentration were compared with processed GOCI data and had an acceptable result.

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