Key words: Turbidity, Total Suspended Solids, Nephelometric Tubidity Unit, Backscattering coefficient, Inherent Optical Properties, Bio-optical Model

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Candice Perry
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1 Investigating relationship of nephelometric turbidity unit and total suspended solids with the inherent optical properties paramete derived from spectra reflectance Kai Li KWOH [1], Sai Meng NG [1], Hong Nan KUAN [1], Kean CHIA [1], Soo Chin LIEW [3], Chew Wai CHANG [2], Leong Keong KWOH [3] [1] - Hwa Chong Institution, 661 Bukit Timah Road, Singapore [2] Centre for Environmental Sensing and Modeling, Singapore-MIT Alliance for Research and Technology, S , 3 Science Drive 2, Singapore [3] - Centre of Remote Imaging, Sensing and Processing (CRISP), National Univeity of Singapore, Block SOC-1, Level 2, Lower Kent Ridge Road, Singapore cklk@nus.edu.sg Key words: Turbidity, Total Suspended Solids, Nephelometric Tubidity Unit, Backscattering coefficient, Inherent Optical Properties, Bio-optical Model ABSTRACT: In this project, the relationships between the turbidity of water measured by its total suspended solids (TSS), Nephelometric Turbidity Units (NTU) and the inherent optical properties computed from the spectral reflectance using the bio-optical model were investigated. It is hope that the results obtained could allow one to compute the water turbidity without needing to physically visit the site and take measurements. This could be extended to estimating the turbidity from remote sensing satellite imagery. Control experiments were initially carried out with a 1m deep by 0.5m x 0.5m tank. The tank was fit filled with clean water. Various types of common soil (e.g. burnt soil, riverbed and silt) were then added progressively and the TSS, NTU and reflectance measured. The different types of soils were used to study the variability of the relationships across different soil types. The experiment results were very encouraging. Linear relationships between NTU and TSS, backscattering coefficient and TSS, backscattering coefficient and NTU were obtain. More interesting, the relationship between backscattering coefficient and NTU is independent of soil type. Field verification measurements were also conducted to confirm the findings of the lab experiments. 1. INTRODUCTION Turbidity is an important measure to determine quality of water. The standard measure for turbidity commonly used by water enginee is the NTU (Nephelometric Turbidity Units). TSS (Total Suspended Solids) is another measure to define the actual amount (weight) of suspended material in a given volume of water. NTU and TSS both measure the amount of suspended solids. However, NTU is not an absolute unit but an index derived by measuring the amount of light scattered from a sample, while TSS is a physical measure. This difference between TSS and NTU becomes important when trying to calculate total quantities of material in a stream. Such calculations are possible with TSS values but not with NTU. Turbidity affects the color and brightness of water. Swimming pool water appea bluish because it has very low turbidity and river water appear brownish because it has high turbidity. These characteristics can also be seen in the water s spectral reflectance as shown in figures below.

: Figure 1 Bluish Swimming Pool (left) and Brownish Turbid River 0.18 Reflectance R 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.

Sathyendranath, 2000], we can model the spectral reflectance of any water with a few paramete such as particle backscattering (X and Y), absorption (G and S), chlorophyll etc. 2. AIMS AND OBJECTIVES In this project, we aim to study the relationship between the particle backscattering parameter (b bp or X) of the bio-optical model and the NTU and TSS.

This is followed by field verification with measurements of actual lake and river wate.

2 : Figure 1 Bluish Swimming Pool (left) and Brownish Turbid River 0.18 Reflectance R River Swimming Pool Wave le ng th (n m ) Figure 2 Reflectance Spectrum of Swimming Pool and River water Using the established bio-optical model [Lee, 2002; Salinas, 2007; Sathyendranath, 2000], we can model the spectral reflectance of any water with a few paramete such as particle backscattering (X and Y), absorption (G and S), chlorophyll etc. 2. AIMS AND OBJECTIVES In this project, we aim to study the relationship between the particle backscattering parameter (b bp or X) of the bio-optical model and the NTU and TSS. We will start with controlled experiments with artificially created turbidity of varying degrees using 3 types of soil particles. We will then analyze the particle backscattering vs. TSS and NTU. This is followed by field verification with measurements of actual lake and river wate. We hope to be able to use this relationship to compute turbidity of water bodies from reflectance measured by remote sensing equipment such as satellite imagery, without needing to physically visit the site to take measurements. 3. EQUIPMENT, MATERIALS AND METHODS In the controlled experiment, the setting of a turbid water body is simulated by using a huge metal tank measuring about 0.5m by 0.5m by 1m. It was painted black in the interior to absorb most of the incoming light which hit the sides of the tank, preventing them from being reflected back. Clean tap water is then filled to the brim of the tank, so as to eliminate shadows cast by the tank walls. A certain quantity of a selected type of soil is then added into the tank. Water is

3 stirred gently to mimic the river s moving wate, which suspends small particles, but allows heavier particles to sink to the bottom. The TSS, NTU and reflectance spectrum for each turbidity level is then measured. To measure the TSS, suspended solids were extracted from water samples by filtering the water sample through a filter paper with 0.5 microns pores in a Buchner funnel, then dried and weighed. NTU is measured with the Eurotech TN100 NTU meter. To measure the water s reflectance, a spectroradiometer (GER 1000) was aimed at a white card. With the known reflectance from the white card, the solar irradiance (E d ) can be calculated from the measured radiance of the white card. Then the radiance of the water (L t ) and the radiance of the sky (L sky ) were taken. The surface reflection of the sky is removed from the total measured radiance to give the water radiance and the reflectance, R (λ) computed as follows: R = L rl t E d sky where r is the Fresnel reflection coefficient, which is very close to From each reflectance spectrum, R (λ), the Excel Solver is used to estimate the various paramete of X, Y, G, S and g 0 using the bio-optical model. We are particularly interested in X (particle backscattering parameter at reference wavelength of 555 nm). We will compare X with the NTU and TSS obtained earlier. The process is repeated for about 10 different turbidity levels for each soil type and the whole experiment repeated for three types of soil. 4. THEORY OF BIO-OPTICAL MODEL The bio-optical model [Lee, 2002; Salinas, 2007; Sathyendranath, 2000] worked around the absorption coefficient, a(λ), and backscattering coefficient, b b (λ). The absorption coefficient a(λ) is dependent on absorption of pure water a w (λ), absorption of colored matter a dg (λ) and absorption of chlorophyll a φ (λ). Thus: a = a + a a w dg + The backscattering coefficient b b (λ) is dependent on backscattering of pure water b bw (λ) and backscattering of suspended particles b bp (λ). Thus: b = b + b b bw While a w (λ) and b bw (λ) are experimentally measured quantities, the rest of the component absorption and backscattering coefficients are modeled as follows: bp φ

4 a b dg bp S ( λ λ0 ) = Ge a = P a + P a φ 0 0 λ0 = X λ Y 1 1 From a(λ), and b b (λ), the underwater remote sensing reflectance r (λ) is obtained as follows: g 0 is an empirical scaling factor. r = g o bb a( λ) + bb However, what we measure is the above water remote sensing reflectance R (λ). The reflectance above water R (λ) is computed from the underwater reflectance r (λ) as follows: R 0.52r = 1 1.7r The numbe 0.52 and 1.7 are physically derived from the refractive index of water, The modeled R (λ) is then compared to the measured R (λ). By varying the various paramete (g0, G, S, X and Y), a solution is found when the modeled R (λ) and the measured R (λ) fits within acceptable tolerance. The Microsoft Excel spreadsheet, with its free add-in module Solver, is used to find the solution. 5. RESULTS AND ANALYSIS 5.1 TSS vs. NTU / Particle Backscattering Figure 3 (left) TSS vs NTU. Figure 4 (right) TSS vs Particle Backscattering

5 Figure 3 shows the results when TSS is plotted against NTU. From this graph, TSS and NTU are observed to have a linear relationship. This is consistent with scientific literature reports, since increasing the amount of suspended particles in the water will correspond to a higher turbidity level (i.e. the cloudier it is). It has been suggested that 1 mg/l TSS = 1 ~ 1.5 NTU. However our experiment shows that the range is wider than the above suggestion (1 mg/l TSS = 0.75~1.7 NTU). Figure 4 shows the results when TSS (mg/l) is plotted against the particle backscattering coefficient (m -1 ). From the results above, particle backscattering coefficient and TSS have a linear relationship. However the relationship is different for different types of soil. 5.2 NTU vs. Particle Backscattering Figure 5 NTU vs Backscattering for each soil type Figure 6 Combine relationship for all soil type From Figure 5, NTU has a linear relationship with the particle backscattering coefficient of light (m -1 ). This is within expectations since NTU is directly proportionate to TSS. It is observed that different types of soil give almost the same relationship between NTU and particle backscattering coefficient (i.e. they are independent of soil type). In Figure 6, a single straight line through all the points can be plotted and this graph shows excellent correlation (R 2 = 0.94). We can thus propose a relationship that NTU 45 X, independent of soil type. This result may be due to the fact that both NTU and particle backscattering coefficient are based on optical properties of light. 6. FIELD VERIFICATION After the ratio NTU 45X was obtained, some measurements of river and lake water samples were taken to verify the results obtained from the controlled experiments.

6 Water Source Measured NTU NTU comp from X %error Little Guilin* S. Ulu Pandan A Jurong River Kent Ridge Pond* Jurong Canal S. Ulu Pandan B S. Ulu Pandan B Avg % error 12.0 Note -- * indicate water with high amount of Chlorophyll (water appea green) Table 1 comparison of measured NTU and computed NTU Figure 7 Computed vs Measured NTU The table 1 and figure 7 above shows good agreement between the NTU measured with NTU meter and computed NTU with the measured reflectance spectra, using the relationship we established, from field verification exercise. The average error was 12.0% and the maximum error is 19.4%. The relationship is also valid for the two samples which has high amount of chlorophyll (Little Guilin and Kent Ridge Pond). 7. CONCLUSION The NTU and backscattering coefficient have correlated extremely well, thus providing a possible method of converting between the 2 values. This vital information has allowed the possibility for analysis of satellite imaging to estimate the NTU of the water. On the other hand, TSS values have instead turned out to be affected by the soil type. The controlled experiments, used to obtain the NTU vs. particle backscattering relationship, were done with chlorophyll-free water. However the field verification results showed that the relationship is also valid for water with chlorophyll. REFERENCES Lee, Z.P., Carder, K.L., and Arnone, R., Deriving inherent optical properties from water color: A multi-band quasi-analytical algorithm for optically deep wate. Applied Optics. Vol 41, No 27, pp Salinas S.V, Chang C.W, Liew S.C (2007). Multiparameter Retrieval Of Water Optical Properties From Above-Water Remote-Sensing Reflectance Using The Simulated Annealing Algorithm, Applied Optics 46(14), Sathyendranath, S, Remote Sensing of Ocean Colour in Coastal, and Other Optically- Complex, Wate. Int. Ocean Colour Coordinating Group Report Number 3.

Estimation of chlorophyll-a concentration in estuarine waters:

Estimation of chlorophyll-a concentration in estuarine waters: case study of the Pearl River estuary Yuanzhi Zhang *, Chuqun Chen #, Hongsheng Zhang *, Xiaofei*, Chen Guiying Chen# *Institute of Space