Estimation of riverbank soil erodibility parameters using genetic algorithm

Abstract

Determination of the erodibility parameters, such as critical shear stress and erodibility coefficient, are necessary before estimating the annual bank erosion (or bank retreat) at river reaches. However, in many cases, the river site is inaccessible making it difficult to assess the soil parameters either by in situ tests or by laboratory experiments. In this study, Genetic Algorithm (GA)-based optimisation technique was used to estimate the erodibility parameters of middle reaches of the Brahmaputra River in India. Two approaches were followed. At first, erodibility parameters were estimated using daily stage records at a selected site. Secondly, based on the annual observed bank erosions (bank retreat) from satellite images, erodibility parameters were estimated in three different river reaches. All these results were compared with that from a previous study using in situ jet tests. Annual bank erosions (bank retreat) were estimated using the median values of the erodibility parameters. The results agree well with the average observed annual bank erosion of these river reaches. In addition, the effects of measurement errors and optimisation algorithms on the parameter estimation were analysed. Sensitivity analysis of the parameters in GA was evaluated and it was found that GA can be utilised in the data-scarce regions to estimate the average erodibility parameters.

Distribution of Shrubland and Grassland Soil Erodibility on the Loess Plateau

“…Recently, the development of GIS has provided new methods for soil erosion research [ 28 , 29 ], such as geomatics approach [ 30 ] and geospatial approach [ 31 ], and electrical resistivity tomography [ 32 ] has also been used for in situ measurement. In the data-scarce regions, genetic algorithm can be utilized to estimate the average erodibility parameters [ 33 ]. These new methods make the mapping of soil erodibility faster and keep the land surface undisturbed, although their accuracy needs more verification, especially when predicting the soil erodibility in hilly areas.…”

Spatial Variability of Soil Erodibility at El Hammam Catchment, Northeast of Algeria

“…Recently, the development of GIS has provided new methods for soil erosion research, such as geomatics approach and geospatial approach [8][9][10][11]. In addition, genetic algorithm can be used in regions with scarce data to estimate the average erodibility parameters [12]. These new methods make the mapping of soil erodibility faster and more accurate.…”