Statistical Analysis and Modeling of Suspended Sediment Yield Dependence on Environmental Conditions

Abstract

This paper describes the modelling of suspended sediment yield in a plains region in the European part of Russia (EPR) and its prediction for ungauged catchments. The studied plains area, excluding the Caucasus and Ural Mountains, covers 3.5 × 106 km2 of the total area of about 3.8 × 106 km2. Multiple regression methods, such as a generalized linear model (GLM) and a generalized additive model (GAM), are used to construct the models. The research methodology is based on a catchment approach. There are 49,516 river basins with an average area of about 75 km2 in the plain regions. The suspended sediment yield geodatabase contains data from 385 gauging stations. The linear GLM model of suspended sediment yield explains about 50% and the GAM model about 65% of the data variability (R-squared adjusted). The models include mean slope steepness, percentage of arable land, runoff per unit area, catchment area, soil rank and catchment soil erodibility as significant predictors. They also include a zonal-sectoral gradient (the sum of active temperatures and the standard deviation of air temperature, or directly by geographic coordinates). A GAM model is trained to predict suspended sediment yields for unexplored areas of the area. The paper presents the results of extrapolating suspended sediment yield values to ungauged river basins in a plains region of the EPR. For the first time for such a large area, the models built and the use of the basin approach made it possible to predict runoff values for hydrologically unexplored river basins.