Estimating nitrogen and phosphorus concentrations in streams and rivers across the Contiguous United States, supplement to: Shen, Longzhu; Amatulli, Giuseppe; Sethi, Tushar; Raymond, Peter; Domisch, Sami (accepted): Estimating nitrogen and phosphorus concentrations in streams and rivers, within a machine learning framework. Scientific Data

DOI

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.

Updated version, 2020-03-04.

Identifier
DOI https://doi.org/10.1594/PANGAEA.899168
Related Identifier https://hs.pangaea.de/Maps/USA_streams_N-P/Amatulli_2019_V1.zip
Metadata Access https://ws.pangaea.de/oai/provider?verb=GetRecord&metadataPrefix=datacite4&identifier=oai:pangaea.de:doi:10.1594/PANGAEA.899168
Provenance
Creator Shen, Longzhu; Amatulli, Giuseppe; Sethi, Tushar; Raymond, Peter; Domisch, Sami
Publisher PANGAEA - Data Publisher for Earth & Environmental Science
Publication Year 2019
Rights Creative Commons Attribution 4.0 International; https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Representation
Language English
Resource Type Supplementary Dataset; Dataset
Format text/tab-separated-values
Size 100 data points
Discipline Earth System Research
Spatial Coverage (-123.800W, 27.700S, -80.800E, 48.200N); United States of America