In-stream surface water quality in China: A spatially-explicit modelling approach for nutrients

Xi Chen*, Maryna Strokal, Michelle T.H. van Vliet, Xing Fu, Mengru Wang, Lin Ma*, Carolien Kroeze

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Scopus)

Abstract

Nutrient pollution is a widespread problem in rivers in China. Managing nutrient pollution requires better knowledge of in-stream processes governing the surface water quality. As current nutrient models for China mainly focus on river export of nutrients to seas, in-stream surface water quality and their contributing sources and processes are, therefore not well understood. This requires accounting for combined effects of nutrient inputs to rivers from produced waste, biochemistry of different forms of nutrients and their transport by river network. Moreover, improvements can be made in evaluating the model performance of large-scale nutrient models based on water quality measurements in China (using the surface water quality classes from 1 to 6). The objective of this study is to quantify the spatial variation in in-stream water quality for nutrients, and associated sources, for water quality classes in China. Our new Model to Assess River Inputs of Nutrients to seAs (MARINA 3.0) for in-stream water quality distinguishes different nutrient forms including dissolved inorganic (DIN, DIP) and organic (DON, DOP) nitrogen and phosphorus and was applied for the year 2012. Our model simulations compare reasonably well with measurements across 155 river sections. Results show that between 12% and 66% of the streams are highly polluted (exceeding water quality class 3) and depending on nutrient form. Diffuse sources dominate in 76% of the streams for DIN. Point sources such as direct discharges of animal manure dominate in 46%–59% of the streams for DON, DIP and DOP. The dominant sources vary considerably between rivers and nutrient forms. This indicates the need account for nutrient forms in models and national monitoring programs. Our model results could support effective management to reduce nutrient pollution in China.

Original languageEnglish
Article number130208
JournalJournal of Cleaner Production
Volume334
DOIs
Publication statusPublished - 1 Feb 2022

Keywords

  • China
  • Modelling
  • Nutrients
  • Surface water quality

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