ORIGINAL PAPER Modeling catchment sediment yield: a genetic programming approach Vaibhav Garg Received: 20 January 2011 / Accepted: 20 October 2011 Ó Springer Science+Business Media B.V. 2011 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. Keywords Sediment yield  Modeling and simulation  Evolutionary technique  Genetic programming  Soft computing 1 Introduction The constant growth in population, urban and industrial sprawl and extensive and intensive agriculture induces an increase in pressure on both land and water resources. The intrusion of human beings in agricultural lands, forests, and waterfronts led to heavy degradation of these non-renewable natural resources. The adverse affect of these activities has reached to hazardous levels leading to accelerated soil erosion, reduction in soil productivity, sedi- mentation and pollution of watercourses, floods and droughts, etc. Therefore, an accurate, reliable, timely, and continuous assessment of these resources and their condition in a V. Garg (&) Water Resources Division, Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun, Uttarakhand 248 001, India e-mail: vaibhav@iirs.gov.in 123 Nat Hazards DOI 10.1007/s11069-011-0014-3