Using Sobol’ sensitivity analysis to identify important model layers of a prediction model for simulating soil nitrogen transport in surface runoff and subsurface water

• Published in: Stochastic environmental research and risk assessment Vol. 39; no. 2; pp. 747 - 763
• Main Authors: Zhang, Shiwei, Tong, Juxiu, Ye, Ming
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2025; Springer Nature B.V
• Subjects: Agricultural land; Agricultural runoff; Ammonia; Aquatic Pollution; Chemistry and Earth Sciences; Computational Intelligence; Computer Science; Earth and Environmental Science; Earth Sciences; Environment; Math. Appl. in Environmental Science; Nitrates; Nitrogen; Nonpoint source pollution; Original Paper; Parameter identification; Parameter sensitivity; Parameter uncertainty; Physics; Pollution dispersion; Pollution sources; Ponding; Prediction models; Probability Theory and Stochastic Processes; Runoff; Sensitivity analysis; Soil analysis; Soil conditions; Soil improvement; Soil layers; Soil mixing; Soil pollution; Soil surfaces; Soils; Statistics for Engineering; Subsurface water; Surface runoff; Surface water; Uncertainty analysis; Urea; Waste Water Technology; Water Management; Water Pollution Control; Sobol GSA; HYDRUS-1D; Model parameter; The prediction model of soil nitrogen transport

Due to complex soil conditions of farmlands, a model simulating soil nitrogen transport in surface runoff and subsurface water is subject to uncertainty not only in model parameters but also in representation of soil layers in model layers. This study presents a model of nitrogen transport with the...