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Modeling catchment sediment yield: a genetic programming approach

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Abstract

Hydrologic processes are complex, non-linear, and distributed within a watershed both spatially and temporally. One such complex pervasive process is soil erosion. This problem is usually approached directly by considering the sediment yield. Most of the hydrologic models developed and used earlier in sediment yield modeling were lumped and had no provision for including spatial and temporal variability of the terrain and climate attributes. This study investigates the suitability of a recent evolutionary technique, genetic programming (GP), in estimating sediment yield considering various meteorological and geographic features of a basin. The Arno River basin in Italy, which is prone to frequent floods, has been chosen as case study to demonstrate the GP approach. The results of the present study show that GP can efficiently capture the trend of sediment yield, even with a small set of data. The major advantage of the GP analysis is that it generates simple parsimonious expression offering some possible interpretations to the underlying process.

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Acknowledgments

This work used software developed under the Talent Project N° 9800463 entitled “Data to Knowledge—D2K” funded by the Danish Technical Research Council (STVF) and the Danish Hydraulic Institute (DHI). The author gratefully acknowledges the anonymous reviewers and editors for their valuable reviews and suggestions.

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  1. Water Resources Division, Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun, Uttarakhand, 248 001, India

    Vaibhav Garg

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  1. Vaibhav Garg
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Garg, V. Modeling catchment sediment yield: a genetic programming approach. Nat Hazards 70, 39–50 (2014). https://doi.org/10.1007/s11069-011-0014-3

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