A modified load apportionment model for identifying point and diffuse source nutrient inputs to rivers from stream monitoring data

Determining point (PS) and diffuse source (DS) nutrient inputs to rivers is essential for assessing and developing mitigation strategies to reduce excessive nutrient loads that induce eutrophication. However, application of watershed mechanistic models to assess nutrient inputs is limited by large data requirements and intensive model calibration efforts. Simple export coefficient models and statistical models also require extensive primary watershed attribute information and further they cannot address seasonal patterns of nutrient delivery. In practice, monitoring efforts to identify all PSs within a watershed are very difficult due to time and economic limitations. To overcome these issues, based on the fundamental hydrological differences between PS and DS pollution, a modified load apportionment model (LAM) was developed relating the river nutrient load to nutrient inputs from PS, DS and upstream inflow sources while adjusting for in-stream nutrient retention processes. Estimates of PS and DS inputs can be easily achieved through Bayesian calibration of the five model parameters from commonly available stream monitoring data. It considers in-stream nutrient retention processes, temporal changes of PS and DS inputs, and nutrient contributions from upstream inflow waters, as well as the uncertainty associated with load estimations. The efficacy of this modified LAM was demonstrated for total nitrogen (TN) source apportionment using a 6-year record of monthly water quality data for the ChangLe River in eastern China. Aimed at attaining the targeted river TN concentration (2mgL-1), required input load reductions for PS, DS and upstream inflow were estimated. This modified LAM is applicable for both district-based and catchment-based water quality management strategies with limited data requirements, providing a simple, effective and economical tool for apportioning PS and DS nutrient inputs to rivers. © 2013 Elsevier B.V