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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(2): 3716-3733
DOI: https://doi.org/10.20546/ijcmas.2018.702.441


Application of Fuzzy Logic and Statistical Approaches for Estimation of Suspended Sediment Concentration
Shreya Nivesh1*, Pravendra Kumar1, Pragati Sawant2 and Ramesh Verma3
1Department of Soil and Water Conservation Engineering, College of Technology, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar-263145, Uttarakhand, India 2Department of Soil and Water Conservation Engineering, Dr. A. S. College of Agricultural Engineering and Technology, Mahatma Phule Krishi Vidyapeeth, Rahuri, Ahmednagar- 413722, Maharashtra, India 3Department of Soil and Water Conservation Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi-221005, Uttar Pradesh, India
*Corresponding author
Abstract:

The accelerated erosion and the sediment outflow from agricultural lands is a serious global problem. Mankind will be facing great challenges in the next few decades. The present study was undertaken to estimate the suspended sediment concentration using Fuzzy Logic (FL), Multiple Linear Regression (MLR) and Sediment Rating Curve (SRC) models for the Vamsadhara river catchment comprising of 7820 km2 Area, situated between Mahanadi and Godavari river basins in south India. The perfect input of FL, MLR and SRC models was found by the use of Gamma Test (GT). Three different types of performance indicators viz. root mean square error (RMSE), correlation coefficient (r) and coefficient of efficiency (CE) were used to evaluate the accuracy of various models. Based on the performance analysis SRC, MLR and FL models were used for comparison. Comparison of training period length was also made utilizing two different architectures. Daily simulations using inputs with architecture (3*1) three years of training and one year of testing (RMSE-104.85 kg/sec, r-0.963 and CE value 87.93%) performed better than the simulation with architecture (2*2) two years of training and two years of testing. The study demonstrates that fuzzy logic model utilizing Gamma Test for input choosing has superior performance for sediment yield estimation in comparison to the conventional models such as MLR and SRC. The results indicated that fuzzy logic can be applied successfully to provide high accuracy and reliability for sediment estimation.


Keywords: Fuzzy Logic; Multiple Linear Regression; Sediment Rating Curve; Calibration; Validation
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How to cite this article:

Shreya Nivesh, Pravendra Kumar, Pragati Sawant and Ramesh Verma. 2018. Application of Fuzzy Logic and Statistical Approaches for Estimation of Suspended Sediment Concentration.Int.J.Curr.Microbiol.App.Sci. 7(2): 3716-3733. doi: https://doi.org/10.20546/ijcmas.2018.702.441