Dynamic integration of water quality simulation into Pywr

The dynamic relationship between water quantity and quality has been neglected in water resources models. This study dynamically integrated simple water quality processes into Pywr to allow water quality to inform water allocation. To demonstrate, Pywr-WQ is applied to the highly human-modified Grootdraai Dam catchment in southern Africa. Pywr-WQ simulations of Total Dissolved Solids (TDS) and various nutrients were generally representative of variations in observed water quality in the Grootdraai Dam. Water quality thresholds for water abstraction were applied to the Grootdraai Dam, with the results showing that Pywr-WQ dynamically ‘switched off’ the abstraction when these thresholds were exceeded. This study confirms the viability of dynamically adding water quality simulation to Pywr. This can aid in more realistic estimations of water yield considering water quality constraints. Given the flexibility of Pywr, more complex rules between water quantity and quality can be implemented. • Simple water quality processes were dynamically integrated into Pywr (Pywr-WQ) • Pywr-WQ was applied to the highly modified Grootdraai Catchment • Water quality simulations were representative of monitoring data • Water abstractions were dynamically turned off by setting water quality thresholds • Opportunities for representing more complex water quantity-quality dynamics

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Publication Details

Journal
Environmental Modelling & Software
Published
2026-03-24
DOI
https://doi.org/10.1016/j.envsoft.2026.106965
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
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article

Dynamic integration of water quality simulation into Pywr

Environmental Modelling & Software
Hydrology and Watershed Management Studies
article

Dynamic integration of water quality simulation into Pywr

article en

Abstract

The dynamic relationship between water quantity and quality has been neglected in water resources models. This study dynamically integrated simple water quality processes into Pywr to allow water quality to inform water allocation. To demonstrate, Pywr-WQ is applied to the highly human-modified Grootdraai Dam catchment in southern Africa. Pywr-WQ simulations of Total Dissolved Solids (TDS) and various nutrients were generally representative of variations in observed water quality in the Grootdraai Dam. Water quality thresholds for water abstraction were applied to the Grootdraai Dam, with the results showing that Pywr-WQ dynamically ‘switched off’ the abstraction when these thresholds were exceeded. This study confirms the viability of dynamically adding water quality simulation to Pywr. This can aid in more realistic estimations of water yield considering water quality constraints. Given the flexibility of Pywr, more complex rules between water quantity and quality can be implemented. • Simple water quality processes were dynamically integrated into Pywr (Pywr-WQ) • Pywr-WQ was applied to the highly modified Grootdraai Catchment • Water quality simulations were representative of monitoring data • Water abstractions were dynamically turned off by setting water quality thresholds • Opportunities for representing more complex water quantity-quality dynamics

Environmental Modelling & SoftwareVol. 201
Pearson (United States) (US), WRc (United Kingdom) (GB), Rhodes University (ZA), Higher National Veterinary School (DZ), Wiltshire and Swindon History Centre (GB)
Clean water and sanitation
Openalex Percentile: Top 11%
Hydrology and Watershed Management Studies
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