Deriving stage–discharge–sediment concentration relationships using fuzzy logic

@article{Lohani2007DerivingSC,
  title={Deriving stage–discharge–sediment concentration relationships using fuzzy logic},
  author={A. K. Lohani and N. K. Goel and K. Bhatia},
  journal={Hydrological Sciences Journal},
  year={2007},
  volume={52},
  pages={793 - 807}
}
  • A. K. Lohani, N. K. Goel, K. Bhatia
  • Published 2007
  • Environmental Science, Geology
  • Hydrological Sciences Journal
    • Abstract Many practical problems in water resources require knowledge of the sediment load carried by the rivers, or of the load the rivers can carry without danger of aggragadation or degradation. Hence, the measurement of sediments being transported by a river is of vital interest for planning and designing of various water resources projects. The conventional methods available for sediment load estimation are largely empirical, with sediment rating curves being the most widely used. The… CONTINUE READING
    View on Taylor & Francis
    84 Citations
    Highly Influential Citations
    1
    Background Citations
    7
    Methods Citations
    18
    Results Citations
    1
    84 Citations
    Citation Type

    Citation Type

    Sediment load estimation by MLR, ANN, NF and Sediment Rating Curve (SRC) in Rio Chama River
    • 4
    • PDF
    Prediction of Suspended Sediment Load Using Data-Driven Models
    • 15
    • PDF
    The role of sediment rating curve development methodology on river load modeling
    • N. Efthimiou
    • Environmental Science, Medicine
    • Environmental Monitoring and Assessment
    • 2019
    • 3
    Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data
    • 145
    Prediction of suspended sediment in river using fuzzy logic and multilinear regression approaches
    • 35
    Modeling of Suspended Sediment Concentration at Kasol in India Using ANN, Fuzzy Logic, and Decision Tree Algorithms
    • 55
    Prediction of riverine suspended sediment discharge using fuzzy logic algorithms, and some implications for estuarine settings
    • 5
    Modeling of Suspended Sediment Concentration Carried in Natural Streams Using Fuzzy Genetic Approach
    • 3
    Application of soft-computing techniques in forecasting sediment load and concentration
    Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers
    • 30

    References

    SHOWING 1-10 OF 57 REFERENCES
    River suspended sediment modelling using a fuzzy logic approach
    • 80
    Daily suspended sediment modelling using a fuzzy differential evolution approach / Modélisation journalière des matières en suspension par une approche d’évolution différentielle floue
    • 44
    Prediction of Sediment Load Concentration in Rivers using Artificial Neural Network Model
    • 311
    Development of Integrated Sediment Rating Curves Using ANNs
    • 223
    • Highly Influential
    Fitting and interpretation of sediment rating curves
    • 515
    • Highly Influential
    ESTIMATION AND FORECASTING OF DAILY SUSPENDED SEDIMENT DATA BY MULTI-LAYER PERCEPTRONS
    • 228
    • Highly Influential
    Generalized regression neural network in modelling river sediment yield
    • 260
    Suspended sediment estimation using neuro-fuzzy and neural network approaches/Estimation des matières en suspension par des approches neurofloues et à base de réseau de neurones
    • 308
    Takagi–Sugeno fuzzy inference system for modeling stage–discharge relationship
    • 106
    Fuzzy Rule-based Methodology for Estimating Monthly Groundwater Recharge in a Temperate Watershed
    • 21