Survey of Methods for Data-Scarce Processing Based on Mechanism Model

Abstract

Due to the imbalance in global economic development, the lack of response data is a prominent shortcoming in information concerning many river basins. The uncertainties incurred by data scarcity reduce the reliability of the simulation results of river basins and pose difficulties in the simulation of non-point source pollution and maritime search and rescue, which in turn affects the environment of the basin. Based on a simulation conducted using the mechanism model in the context of a lack of response data from rivers, this paper analyses a variety of methods of data processing in case of missing data. In the era of big data, this paper provides a variety means of using data-scarce simulation methods as an effective reference for simulations of water quality.