4.6 Review

Review of Nonpoint Source Pollution Models: Current Status and Future Direction

期刊

WATER
卷 14, 期 20, 页码 -

出版社

MDPI
DOI: 10.3390/w14203217

关键词

nonpoint source pollution; model construction; model application; uncertainty; decision-making; best management practice

资金

  1. National Key R&D Program of China [2021YFD1700600]
  2. National Natural Science Foundation of China [42277044]
  3. Fund for Innovative Research Group of the National Natural Science Foundation of China [52221003]

向作者/读者索取更多资源

This paper reviews the progress in the development of non-point source (NPS) models and proposes a systematic description of model framework, identifies common challenges, and summarizes future directions. The challenges include limitations in understanding specific NPS pollution processes, model expansion to different scales, data scarcity, prediction uncertainty, and insufficient accuracy for decision-making. The future directions for NPS model development include establishing a source-flow-sink framework, standardizing model input and parameter, and providing reliable decision support.
Modelling tools are commonly used for predicting non-point source (NPS) pollutants and it is timely to review progress that has been made in terms of the development of NPS models. This paper: (1) proposes a systematic description of model framework and generalizes some commonly used models; (2) identifies the common challenges in model structure and applications; (3) summarizes the future directions of NPS models. Challenges in model construction and application are based on the following: (1) limitations in understanding specific NPS pollution processes; (2) model expansion to different scales; (3) data scarcity and its impacts on model performance; (4) prediction uncertainty due to model input, parameter and model structure; (5) insufficient accuracy for decision-making. Finally, this paper proposes future directions for model development, including: (1) a source-flow-sink framework for model development; (2) standardization for model input and parameter; (3) reliable decision support for environmental management. The findings of this review provide helps in the accurate prediction and management of NPS pollution around the world.

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