Blessy VA1*, Mukesh Kumar2, CK Saxena2 and Ajita Gupta2
1Division of Agricultural Engineering, ICAR-Indian Institute of Sugarcane Research, Lucknow, India
2Irrigation and Drainage Engineering Division, ICAR-Central Institute of Agricultural Engineering, Bhopal, India
*Corresponding Author: Blessy VA, Division of Agricultural Engineering, ICAR-Indian Institute of Sugarcane Research, Lucknow, Uttar Pradesh, India.
Received: August 01, 2023; Published: November 27, 2023
Physical, chemical, and biological factors are used in water quality assessments to assess the water's appropriateness for a certain purpose. The total suspended solids and turbidity, out of all of these variables, are the most crucial for determining the general quality of the water from the perspective of agricultural applications. TSS measurements have a variety of applications, such as observing erosive processes in a landscape or irrigation systems. On the other hand, it is challenging to quickly monitor the TSS content in the water and to address urgent problems. Turbidity may be measured swiftly with the help of a turbidity meter. Given the correlation between turbidity and TSS, one may estimate the water's TSS using the turbidity value. Turbidity is affected by various types of soil solids that are present in the soil. The aim of this study was to determine the correlation between TSS and turbidity, based on this develop regression models, compare the performance of the regression models for vertisols that was segregated into sand, silt, clay, mixed soil and natural soil solids. The data on TSS and turbidity were preprepared for 5 different soil fractions in the laborartary conditions through the sedimentation process. Using the known methods, TSS through the gravimetric method and turbidity through the turbidity meter at different concentration levels from 1 to 1500 mg/L, it is the possible minimum to maximum turbidity values for agricultural applications. These values were used to develop the linear regression model for the study. The results showed a strong positive relationship between turbidity and the TSS for all types of soil fractions. The correlation coefficient was found to be over 0.9 for these soils, which have demonstrated a high correlation. While monitoring, sand-sized percentage of soil fractions were immediately dropped below the turbidity-meter-monitored zone, which had an impact on the TSS value. However, it was discovered that the percentage of sand in black cotton soil were quite low; therefore, the established relationship can be helpful for TSS assessment. It is concluded that the generated models presented with good adjustments can be able to be used for predicting the concentration of TSS as a function of turbidity.
Keywords: TSS; Turbidity; Water Quality; Black Cotton Soils; Vertisol
Citation: Blessy VA., et al. “Predicting Total Suspended Solids from Turbidity for different types of Soil Particles". Acta Scientific Agriculture 7.12 (2023): 30-39.
Copyright: © 2023 Blessy VA., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.