Spatiotemporal Analysis of Global In-stream Phosphorus Concentrations from 2012 to 2021
Phosphorus (P) is an essential nutrient in nature, playing a critical role in plant growth and food production. However, the interplay between environmental factors and human activities, particularly the excessive use of P-based fertilizers, can significantly impact P concentrations in surface water...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | Persian |
| Published: |
Iranian Water Resources Association
2025-05-01
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| Series: | تحقیقات منابع آب ایران |
| Subjects: | |
| Online Access: | https://www.iwrr.ir/article_215297_4551af34ac29b705f10977d6c310ce42.pdf |
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| Summary: | Phosphorus (P) is an essential nutrient in nature, playing a critical role in plant growth and food production. However, the interplay between environmental factors and human activities, particularly the excessive use of P-based fertilizers, can significantly impact P concentrations in surface waters. This leads to a decline in water quality and serious environmental consequences, such as eutrophication. This study investigates the spatiotemporal variations in monthly P concentrations in global surface waters from 2012 to 2021. To achieve this, data from various sources such as GEMStat, WATERBASE, WQP, and CESI were aggregated, integrated, and standardized using machine learning algorithms into a comprehensive database named GloPhos. Statistical analyses revealed that the global mean and median P concentrations were 0.13 and 0.06 mg/L, respectively. Furthermore, approximately 58% of the monitoring stations recorded P levels exceeding the permissible limit of 0.05 mg/L. The high-risk stations were predominantly located in France, India, and the United States. The findings of this study offer valuable insights for policymakers, aiding in the development of effective management strategies to reduce P pollution and mitigate eutrophication in aquatic ecosystems. The proposed GloPhos database is freely available to support researchers in developing numerical models and future projections, contributing to efficient water quality management and the optimization of fertilizer usage. |
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| ISSN: | 1735-2347 |