Achite, M., Ouillon, S.: Suspended sediment transport in a semiarid watershed. J. Hydrol. 343(3–4), 187–202 (2007)
CrossRef
Google Scholar
Adib, A., Mahmoodi, A.: Prediction of suspended sediment load using ANN GA conjunction model with Markov chain approach at flood conditions. KSCE J. Civ. Eng. 21(1), 447457 (2016)
Google Scholar
Asselman, N.E.M.: Fitting and interpretation of sediment rating curves. J. Hydrol. 234(3–4), 228–248 (2000)
CrossRef
Google Scholar
Aytek, A., Kisi, O.: A genetic programming approach to suspended sediment modelling. J. Hydrol. 351(3–4), 288–298 (2008)
CrossRef
Google Scholar
Bouzeria, A.H., Ghenim, A.N., Khanchoul, K.: Using artificial neural network (ANN) for prediction of sediment loads, application to the Mellah catchment, northeast. J. Water Land Dev. 33(IVVI), 47–55 (2017)
Google Scholar
Cobaner, M., Unal, B., Kisi, O.: Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data. J. Hydrol. 367(1–2), 52–61 (2009)
CrossRef
Google Scholar
Crowder, D.W., Demissie, M., Markus, M.: The accuracy of suspended sediments when log transformation produces nonlinear suspended sedimentdischarge relationships. J. Hydrol. 336(3–4), 250–268 (2007)
CrossRef
Google Scholar
Ganju, N.K., Knowles, N., Schoellhamer, D.H.: Temporal downscaling of decadal suspended sediment estimates to a daily interval for use in hind cast simulations. J. Hydrol. 349(3–4), 512–523 (2008)
CrossRef
Google Scholar
Gao, P.: Understanding watershed suspended sediment transport. Prog. Phys. Geogr. 32(3), 243–263 (2008)
CrossRef
Google Scholar
Heng, C.S., Suetsugi, T.: Using artificial neural network to estimate sediment load in ungauged catchments of the Tonle Sap River Basin. J. Water Resour. Prot. 5, 111–123 (2013)
CrossRef
Google Scholar
Jain, S.K.: Development of integrated sediment rating curves using ANNs. J. Hydraul. Eng. ASCE 1, 30–37 (2001)
CrossRef
Google Scholar
Lenzi, M.A., Mao, L., Comiti, F.: Effective discharge for sediment transport in a mountain river, computational approaches and geomorphic effectiveness. J. Hydrol. 326(1–4), 257–276 (2006)
CrossRef
Google Scholar
Partal, T., Cigizoglu, H.K.: Estimation and forecasting of daily suspended sediment data using waveletneural networks. J. Hydrol. 358(3–4), 317–331 (2008)
CrossRef
Google Scholar
Rai, R.K., Patel, R.A.S., Rastogi, R.A., Jain, M.K.: Response functions of suspended sediment flow for a Himalayan watershed. Int. Agric. Eng. J. 13(1–2), 37–46 (2004)
Google Scholar
Sadeghi, S.H.R., Mizuyama, T., Miyata, S., Gomi, T., Kosugi, K., Fukushima, T., Mizugaki, S., Onda, Y.: Determinant factors of sediment graphs and rating loops in a reforested watershed. J. Hydrol. 3056(3–4), 271–282 (2008)
CrossRef
Google Scholar
Wang, P., Linker, L.C.: Improvement of regression simulation in fluvial suspended sediments. J. Hydraul. Eng. ASCE 134(10), 1527–1531 (2008)
CrossRef
Google Scholar
Yitian, L., Gu, R.R.: Modelling flow and sediment transport in a river system using an artificial neural network. Environ. Manage. 31(1), 122–134 (2003)
CrossRef
Google Scholar