The load quantification of solutes and suspended materials in rivers provides meaningful ecological information about watershed functionality. High-frequency measurements of flow are often available, whereas concentration data are commonly recorded at low frequencies. Different calculation methods have been developed by various authors to provide unbiased load estimation. We provide a new R package (RiverLoad) that implements several of the most widely used load estimation algorithms. The package provides an easy-to-use tool to rapidly calculate the load for various compounds and to compare different methods. The package also supplies additional functions to easily organize and analyze the data. A bootstrapping was performed on two example datasets to illustrate the reliability of the methods at different sampling frequencies. The RiverLoad package should make it easier to obtain load data and to compare different estimation algorithms. However, attention must be paid when selecting the method to avoid consistent error in the load estimation.
Nava, V., Patelli, M., Rotiroti, M., Leoni, B. (2019). An R package for estimating river compound load using different methods. ENVIRONMENTAL MODELLING & SOFTWARE, 117, 100-108 [10.1016/j.envsoft.2019.03.012].
An R package for estimating river compound load using different methods
Nava, V
Primo
;Patelli, MSecondo
;Rotiroti, M;Leoni, BUltimo
2019
Abstract
The load quantification of solutes and suspended materials in rivers provides meaningful ecological information about watershed functionality. High-frequency measurements of flow are often available, whereas concentration data are commonly recorded at low frequencies. Different calculation methods have been developed by various authors to provide unbiased load estimation. We provide a new R package (RiverLoad) that implements several of the most widely used load estimation algorithms. The package provides an easy-to-use tool to rapidly calculate the load for various compounds and to compare different methods. The package also supplies additional functions to easily organize and analyze the data. A bootstrapping was performed on two example datasets to illustrate the reliability of the methods at different sampling frequencies. The RiverLoad package should make it easier to obtain load data and to compare different estimation algorithms. However, attention must be paid when selecting the method to avoid consistent error in the load estimation.File | Dimensione | Formato | |
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Nava-2019-Environ Modell Software-AAM.pdf
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Descrizione: Research Article
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Author’s Accepted Manuscript, AAM (Post-print)
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