Journal article

Partitioning multi-source uncertainties in simulating nitrogen loading in stream water using a coherent, stochastic framework: Application to a rice agricultural watershed in subtropical China.

Qiumei Ma, Lihua Xiong, Yong Li, Siyue Li, Chong-Yu Xu

Sci Total Environ | Published : 2018

Abstract

Uncertainty is recognized as a critical consideration for accurately predicting stream water nitrogen (N) loading, but identifying the relative contribution of individual uncertainty sources within the total uncertainty remains unclear. In this study, a powerful method, referred to as the Bayesian inference combined with analysis of variance (BayeANOVA) was adopted to detect the timing and magnitude of multiple uncertainty sources and their relative contributions to total uncertainty in simulating daily loadings of three stream water N species (ammonium-N: NH4+-N, nitrate-N: NO3--N and total N: TN) in a rice agricultural watershed (the Tuojia watershed) as influenced by non-point source N po..

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Grants

Awarded by “Hundred-Talent Program” of the Chinese Academy of Sciences


Awarded by National Natural Science Foundation of China