Multivariate polynomial regression modeling of total dissolved-solids in rangeland stormwater runoff in the Colorado River Basin

Abstract

A multivariate polynomial regression modeling (MPR) framework is developed to estimate total dissolved solids (TDS) in stormwater runoffs from rangelands in the Colorado River Basin in the Southwestern United States. An accurate TDS estimation model is needed to simulate terrestrial and aquatic salt transport processes on rangelands, identify critical source areas, and manage these sources effectively. However, modeling stormwater TDS runoff on rangeland sodic soils is challenging due to its complex correlation with variables in many aspects, such as topography, climate, soil, and vegetation. We propose a two-stage MPR framework based on field data collected from multiple rainfall simulator experiments: (1) variable selection with factor analysis and (2) TDS modeling via MPR, considering the nonlinear relationships between variables. Tabu search (TS) is used to optimize the TDS model in MPR. The proposed framework achieved a high prediction accuracy of 74.7% in estimating the TDS runoff transport.