Shen, Longzhu; Amatulli, Giuseppe; Sethi, Tushar; Raymond, Peter; Domisch, Sami (2019): Estimating nitrogen and phosphorus concentrations in streams and rivers across the Contiguous United States. PANGAEA, https://doi.org/10.1594/PANGAEA.899168, Supplement to: Shen, L et al. (accepted): Estimating nitrogen and phosphorus concentrations in streams and rivers, within a machine learning framework. Scientific Data
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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.
Median Latitude: 37.950000 * Median Longitude: -102.300000 * South-bound Latitude: 27.700000 * West-bound Longitude: -123.800000 * North-bound Latitude: 48.200000 * East-bound Longitude: -80.800000
Updated version, 2020-03-04.
100 data points