An assessment of the Artificial Neural Networks technique to geomorphologic modeling sediment yield (Case study Samandegan river system)
نویسنده
چکیده
Extended Abstract 1Introduction Estimating correct volume of sediment in a fluvial system is one of the most important issues in water engineering, river engineering, water resources, facilities, structures, water and environmental projects and programs for the development of them. The bed load transfers by saltation and suspension forms according to the sediment particle size. The sediment load is one of the most important parameters of hydraulic projects, a useful indicator of soil erosion, and watershed's ecological environment. Several physical experimental methods for estimating the sediment in a watershed has been developed.
منابع مشابه
Modeling of streamflow- suspended sediment load relationship by adaptive neuro-fuzzy and artificial neural network approaches (Case study: Dalaki River, Iran)
Modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. Recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. Thisstudy made us of adaptive neuro-fuzzy ...
متن کاملFlood Forecasting Using Artificial Neural Networks: an Application of Multi-Model Data Fusion technique
Floods are among the natural disasters that cause human hardship and economic loss. Establishing a viable flood forecasting and warning system for communities at risk can mitigate these adverse effects. However, establishing an accurate flood forecasting system is still challenging due to the lack of knowledge about the effective variables in forecasting. The present study has indicated that th...
متن کاملApplication of Two Methods of Artificial Neural Network MLP, RBF for Estimation of Wind of Sediments (Case Study: Korsya of Darab Plain)
The lack of sediment gauging stations in the process of wind erosion, caused of estimate of sediment be process of necessary and important. Artificial neural networks can be used as an efficient and effective of tool to estimate and simulate sediments. In this paper two model multi-layer perceptron neural networks and radial neural network was used to estimate the amount of sediment in Korsya o...
متن کاملEstimating river suspended sediment yield using MLP neural network in arid and semi-arid basins Case study: Bar River, Neyshaboor, Iran
Abstract Erosion and sedimentation are the most complicated problems in hydrodynamic which are very important in water-related projects of arid and semi-arid basins. For this reason, the presence of suitable methods for good estimation of suspended sediment load of rivers is very valuable. Solving hydrodynamic equations related to these phenomenons and access to a mathematical-conceptual mode...
متن کاملInvestigation of Possibility of Suspended Sediment Prediction Using a Combination of Sediment Rating Curve and Artificial Neural Network Case Study: Ghatorchai River, Yazdakan Bridge
Estimation of sediment loads in rivers is one of the most important, difficult components of sediment transport studies and river engineering. Accessing new methods that can be effective in this background are more important. In this research, we have used the artificial neural network (ANN) to optimize the results of the sediment rating curve (SRC) to predict the suspended sediment loads. For ...
متن کامل