Laboratory experiment, field and remotely sensed data analysis for the assessment of suspended solids concentration and secchi depth of the reservoir surface water

Choubey, V. K.

doi:10.1080/014311698214037

Cited by 28 publications

(12 citation statements)

References 18 publications

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“…The data of in situ measurements shows positive correlations between DN and TSS with R and Root Mean Squared (RMS) values were 0.9256 and 3.6237 mg/I respectively. Such characteristics were also observed by other investigators using remote sensing data in the visible channel for suspended sediment studies (Choubey, 1998). Figure 5 depicted higher concentrations of Total Suspended Solids were distributed near the river mouths and the shallow at the southern region of the channel.…”

Section: Remote Sensing-gis In Monitoring Water Quality In Malaysiasupporting

confidence: 65%

Use of Remote Sensing and GIS in Monitoring Water Quality

Usali

Ismail

2010

JSD

119

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The use of remote sensing and GIS in water monitoring and management has been long recognized. This paper however discusses the application of remote sensing and GIS specifically in monitoring water quality parameter such as suspended matter, phytoplankton, turbidity, and dissolved organic matter. In fact the capability of this technology offers great tools of how the water quality monitoring and managing can be operationalised in this country. Potential application and management is identified in promoting concept of sustainable water resource management. In conclusion remote sensing and GIS technologies coupled with computer modelling are useful tools in providing a solution for future water resources planning and management to government especially in formulating policy related to water quality.

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Section: Remote Sensing-gis In Monitoring Water Quality In Malaysiasupporting

confidence: 65%

Use of Remote Sensing and GIS in Monitoring Water Quality

Usali

Ismail

2010

JSD

119

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“…The results were satisfactory (R 2 = 0.82) for turbidity, however, poor for TSS (R 2 = 0.45). There are several reasons for the poor estimated TSS relations, including the various types and grain sizes of sediment, [ 58 , 59 ]. Gin et al [ 58 ] studied the spectral reflectance of water containing concentrations of organic and inorganic sediments isolated under controlled experimental conditions and natural sunlight.…”

Section: Resultsmentioning

confidence: 99%

Hyperspectral Sensing for Turbid Water Quality Monitoring in Freshwater Rivers: Empirical Relationship between Reflectance and Turbidity and Total Solids

Huang

et al. 2014

Sensors

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Total suspended solid (TSS) is an important water quality parameter. This study was conducted to test the feasibility of the band combination of hyperspectral sensing for inland turbid water monitoring in Taiwan. The field spectral reflectance in the Wu river basin of Taiwan was measured with a spectroradiometer; the water samples were collected from the different sites of the Wu river basin and some water quality parameters were analyzed on the sites (in situ) as well as brought to the laboratory for further analysis. To obtain the data set for this study, 160 in situ sample observations were carried out during campaigns from August to December, 2005. The water quality results were correlated with the reflectivity to determine the spectral characteristics and their relationship with turbidity and TSS. Furthermore, multiple-regression (MR) and artificial neural network (ANN) were used to model the transformation function between TSS concentration and turbidity levels of stream water, and the radiance measured by the spectroradiometer. The value of the turbidity and TSS correlation coefficient was 0.766, which implies that turbidity is significantly related to TSS in the Wu river basin. The results indicated that TSS and turbidity are positively correlated in a significant way across the entire spectrum, when TSS concentration and turbidity levels were under 800 mg·L−1 and 600 NTU, respectively. Optimal wavelengths for the measurements of TSS and turbidity are found in the 700 and 900 nm range, respectively. Based on the results, better accuracy was obtained only when the ranges of turbidity and TSS concentration were less than 800 mg·L−1 and less than 600 NTU, respectively and used rather than using whole dataset (R2 = 0.93 versus 0.88 for turbidity and R2 = 0.83 versus 0.58 for TSS). On the other hand, the ANN approach can improve the TSS retrieval using MR. The accuracy of TSS estimation applying ANN (R2 = 0.66) was better than with the MR approach (R2 = 0.58), as expected due to the nonlinear nature of the transformation model.

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“…All of these approaches result in robust statistical relationships between satellite‐derived reflectance and ground‐based SSC or turbidity data, with coefficients of determination (r 2 ) ranging from 0.60 to 0.99. Principle sources of uncertainty in these relationships result from differences in sediment color, grain size, and mineralogy within a study region [ Choubey , 1998; Novo et al , 1989; Han and Rundquist , 1996], from bottom reflectance in shallow areas where suspended sediment concentrations are less than 100 mg/L [ Tolk et al , 2000], from contamination by chlorophyll, carotenoids, and other reflective suspended or dissolved material [ Tassan , 1994; Quibell , 1991; Han , 1997], and from differences in atmospheric correction techniques [ Stumpf and Pennock , 1989]. Additionally, in regions with SSC values greater than 250 mg/L some studies have found that reflectance begins to saturate and that the SSC‐reflectance relationship becomes logarithmic [ Ritchie and Cooper , 1988; Ritchie et al , 2003].…”

Section: Remote Sensing Of Suspended Sediment Concentration In Freshwmentioning

confidence: 99%

Remote sensing of suspended sediment concentration, flow velocity, and lake recharge in the Peace‐Athabasca Delta, Canada

Pavelsky

Smith

2009

Water Resources Research

126

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[1] The transport of fine sediment, carried in suspension by water, is central to the hydrology, geomorphology, and ecological functioning of river floodplains and deltas. An extensive new field data set for the Peace-Athabasca Delta (PAD), Canada quantifies robust positive relationships between in situ suspended sediment concentration (SSC) and remotely sensed visible/near-infrared reflectance. These relationships are exploited using SPOT and ASTER satellite images to map suspended sediment concentrations across the PAD for four days in 2006 and 2007, revealing strong variations in water sources and flow patterns, including flow reversals in major distributaries. Near-daily monitoring with 276 MODIS satellite images tracks hydrologic recharge of floodplain lakes, as revealed by episodic infusions of sediment-rich water from the Athabasca River. The timing and magnitude of lake recharge are linked to springtime water level on the Athabasca River, suggesting a system sensitive to changes in river flow regime. Moreover, recharge timing differentiates lakes that are frequently and extensively recharged from those recharged more rarely. Finally, we present a first estimation of river flow velocity based on remotely sensed SSC, though saturation may occur at velocities >0.6 m/s. Viewed collectively, the different remote sensing methodologies presented here suggest strong value for visible/near-infrared remote sensing of suspended sediment to assess hydrologic and sediment transport processes in complex flow environments. Field observations including nephelometric turbidity, specific conductivity, water temperature, Secchi disk depth, suspended sediment concentration, and water level are archived at the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics (available at

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Laboratory experiment, field and remotely sensed data analysis for the assessment of suspended solids concentration and secchi depth of the reservoir surface water

Abstract: To cite this article: V. K CHOUBEY (1998) Laboratory experiment, field and remotely sensed data analysis for the assessment of suspended solids concentration and secchi depth of the reservoir surface water, International

Cited by 28 publications

References 18 publications

Use of Remote Sensing and GIS in Monitoring Water Quality

Use of Remote Sensing and GIS in Monitoring Water Quality

Hyperspectral Sensing for Turbid Water Quality Monitoring in Freshwater Rivers: Empirical Relationship between Reflectance and Turbidity and Total Solids

Remote sensing of suspended sediment concentration, flow velocity, and lake recharge in the Peace‐Athabasca Delta, Canada

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