Preprints
https://doi.org/10.5194/egusphere-2025-703
https://doi.org/10.5194/egusphere-2025-703
24 Feb 2025
 | 24 Feb 2025
Status: this preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).

CoSWAT-WQ v1.0: a high-resolution community global SWAT+ water quality model

Albert Nkwasa, Celray James Chawanda, Maria Theresa Nakkazi, and Ann van Griensven

Abstract. Quantifying the global extent of anthropogenic impacts on freshwater quality remains challenging due to limited monitoring data, especially in low and middle-income regions. To address this gap and improve our understanding of surface water quality, we introduce CoSWAT-WQ, a large-scale water quality model developed to simulate river water quality constituents of Total Nitrogen (TN) and Total Phosphorus (TP), across global and regional freshwater systems. CoSWAT-WQ, an adaptation of the Soil and Water Assessment Tool (SWAT), is run at a global scale, providing high-resolution simulations that capture spatial and daily temporal dynamics of riverine nutrient loads. Here, we describe the model's inputs, setup structure, processes, and evaluate its performance by comparing model outputs to in-situ water quality observations and other global nutrient models. CoSWAT-WQ achieves comparable ranges of river nutrient loads in comparison to other global nutrient models. Additionally, a normalized root mean square error (nRMSE) < 1 was achieved with in-situ observations at more than 80 % of the gauging stations for TN and TP concentrations. However, there was a general weak underestimation of observed concentrations and variability as seen with low Kling–Gupta efficiency (KGE) values for selected stations. Despite its limitations, the model enables the simulation of river TN and TP constituents at a global scale while keeping local relevance. CoSWAT-WQ’s modular setup allows coupling with sectoral models addressing lake systems, agricultural runoff, and aquatic biodiversity, thereby broadening its applicability for cross-sectoral assessments. The model outputs offer valuable data that can inform ecological risk assessments, human health evaluations, and policy decisions on global freshwater quality management.

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Albert Nkwasa, Celray James Chawanda, Maria Theresa Nakkazi, and Ann van Griensven

Status: open (until 28 Apr 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'How well can we predict water quality at the global scale?', Tobias Krueger, 05 Mar 2025 reply
Albert Nkwasa, Celray James Chawanda, Maria Theresa Nakkazi, and Ann van Griensven
Albert Nkwasa, Celray James Chawanda, Maria Theresa Nakkazi, and Ann van Griensven

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Short summary
Limited monitoring data make it difficult to assess human impacts on freshwater quality, especially in low-income regions. To address this, we developed a global water quality model that simulates river nutrient loads (Total Nitrogen and Total Phosphorus). The model provides high-resolution insights into freshwater pollution, supporting ecological risk assessments and policy decisions. While some uncertainties remain, this model offers a crucial tool for addressing global water quality.
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