A novel approach for estimating the capacity of ungauged small reservoirs using remote sensing and DEM

The estimation of small reservoir capacity is of great significance for water resources management. However, many widely distributed small reservoirs lack the capacity information because of the high costs of field measurements. This study proposed a novel approach to estimate the small reservoir capacity in the hilly area by using remote sensing and Digital Elevation Model (DEM). The basic idea of this approach is to explore the relationship between influential factors (i.e., topographic and geomorphic parameters) and measured reservoirs' capacity to establish a machine learning model based on particle swarm optimization-extreme learning machine (PSO-ELM) to estimate the capacity.