Estimating nitrogen and phosphorus concentrations in streams and rivers across the Contiguous United States
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| Autori principali: | , , , , |
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| Natura: | Dataset Open Access |
| Lingua: | en |
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PANGAEA
2019
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| _version_ | 1867168197848858624 |
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| author | Shen, Longzhu Amatulli, Giuseppe Sethi, Tushar Raymond, Peter Domisch, Sami |
| author_facet | Shen, Longzhu Amatulli, Giuseppe Sethi, Tushar Raymond, Peter Domisch, Sami |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Nitrogen (N) and Phosphorus (P) are essential nutritional elements for life processes in water bodies. However, in excessive quantities, they may represent a significant source of aquatic pollution. Eutrophication has become a widespread issue rising from a chemical nutrient imbalance and is largely attributed to anthropogenic activities. In view of this phenomenon, we present a new geo-dataset to estimate and map the concentrations of N and P in their various chemical forms at a spatial resolution of 30 arc-second (~1 km) for the conterminous US. The models were built using Random Forest (RF), a machine learning algorithm that regressed the seasonally measured N and P concentrations collected at 62,495 stations across the US streams for the period of 1994-2018 onto a set of 47 in-house built environmental variables that are available at a near-global extent. The seasonal models were validated through internal and external validation procedures and the predictive powers measured by Pearson Coefficients reached approximately 0.66 on average. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_899168 |
| institution | PANGAEA |
| language | en |
| publishDate | 2019 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Estimating nitrogen and phosphorus concentrations in streams and rivers across the Contiguous United States Shen, Longzhu Amatulli, Giuseppe Sethi, Tushar Raymond, Peter Domisch, Sami File content; File format; File name; File size; freshwater nutrients; machine learning; nitrogen; Phosphorus; stream network; Uniform resource locator/link to file; United States of America; USA_cont; water quality Nitrogen (N) and Phosphorus (P) are essential nutritional elements for life processes in water bodies. However, in excessive quantities, they may represent a significant source of aquatic pollution. Eutrophication has become a widespread issue rising from a chemical nutrient imbalance and is largely attributed to anthropogenic activities. In view of this phenomenon, we present a new geo-dataset to estimate and map the concentrations of N and P in their various chemical forms at a spatial resolution of 30 arc-second (~1 km) for the conterminous US. The models were built using Random Forest (RF), a machine learning algorithm that regressed the seasonally measured N and P concentrations collected at 62,495 stations across the US streams for the period of 1994-2018 onto a set of 47 in-house built environmental variables that are available at a near-global extent. The seasonal models were validated through internal and external validation procedures and the predictive powers measured by Pearson Coefficients reached approximately 0.66 on average. |
| title | Estimating nitrogen and phosphorus concentrations in streams and rivers across the Contiguous United States |
| topic | File content; File format; File name; File size; freshwater nutrients; machine learning; nitrogen; Phosphorus; stream network; Uniform resource locator/link to file; United States of America; USA_cont; water quality |
| url | https://doi.org/10.1594/PANGAEA.899168 |