Estimating the suspended sediment yield in a river network by means of geomorphic parameters and regression relationships
نویسنده
چکیده
An application of regression relationships depending on geomorphic parameters is proposed to predict the amount of the average annual suspended sediment yield at different sections of the drainage network. Simple and multiple regression relationships, utilising the drainage density and the hierarchical anomaly index as independent variables, based on data from 20 river basins of different size located in Italy, are here tested. An application is also shown for a small river basin located in central Italy where it is possible to compare the obtained suspended sediment yield estimates with reservoirs siltation data. The results confirm the potential applicability of regression equations for estimating the suspended sediment yield depending on the topological behaviours of the river network. A discussion of the reliability of the method for ungauged basins is also provided, which puts in light the necessity of additional tests to support the application of the approach to small size watersheds.
منابع مشابه
Estimating 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 کاملModeling 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 کاملA spatially distributed analysis of erosion susceptibility and sediment yield in a river basin by means of geomorphic parameters and regression relationships
Papers published in Hydrology and Earth System Sciences Discussions are under open-access review for the journal Hydrology and Earth System Sciences Abstract In the present work, an application of statistical regression relationships utilising ge-omorphic parameters is attempted in a spatially distributed mode, in order to predict the amount of river sediment supply at varying sections of the d...
متن کاملThe Relationship between Geomorphic Characteristics and Watershed Sediment Yield: A Case of Selected Subwatersheds of Khorasan Razavi
Extended abstract 1- Introduction Soil erosion by water is a dominant geomorphic process which threatens food security in most parts of the world .The geomorphic characteristics of a watershed play an important role in watershed hydrology, soil erosion processes and sediment yield. Geomorphic characteristics can be an indicator of soil erosion and sedimentation of a watershed. Geomorphic char...
متن کاملOptimization of sediment rating curve coefficients using evolutionary algorithms and unsupervised artificial neural network
Sediment rating curve (SRC) is a conventional and a common regression model in estimating suspended sediment load (SSL) of flow discharge. However, in most cases the data log-transformation in SRC models causing a bias which underestimates SSL prediction. In this study, using the daily stream flow and suspended sediment load data from Shalman hydrometric station on Shalmanroud River, Guilan Pro...
متن کامل