Phosphorus is a water pollutant of concern around the world as it limits the productivity of most freshwater systems which can undergo eutrophication under high phosphorus inputs. The importance of treating stormwater as part of an integrated phosphorus pollution management plan is now recognized. Bioretention systems are urban stormwater best management practices (BMPs) that rely on terrestrial ecosystem functions to retain storm flows and reduce pollutant loads. Bioretention has shown great potential for stormwater quantity and quality control. However, phosphorus removal has been inconsistent in bioretention systems, with phosphorus leaching observed in some systems. Numerical models can be used to predict the performance of bioretention systems under various conditions and loadings. The aim of this paper is to identify and characterize bioretention phosphorus cycling processes, with a particular focus on process modelling. Both soluble and particulate phosphorus forms are expected in significant proportions in bioretention system inflows. Sorption mechanisms are expected to dominate soluble phosphorus cycling, while particulate phosphorus transport occurs mainly through sedimentation. Vegetative uptake, mineralization, and immobilization are also known to play a role in the cycling of phosphorus; however, data is lacking to assess their importance. There is a need for simple mathematical equations to represent dissolution and precipitation reactions in bioretention systems. More research is also needed to characterize the rates of colloidal capture and mobilization within soils. Finally, approaches used to model phosphorus transport in systems similar to bioretention are not applicable to bioretention system modelling. This reinforces the need for the development of a bioretention phosphorus transport model.
(NSF and IES 2018) describe reproducibility as a continuum (Fig. 1). The goal is to push work up the continuum to make data, models, code, directions, and other digital artifacts used in the research available for others to reuse (availability). Then, use shared artifacts to exactly reproduce published results (reproducibility, sometimes called bit or computational reproducibility). Finally, use artifacts with existing and new data sets to replicate findings across sites or domains (replicability). For example, the Journal of Water Resources Planning and Management policy to specify the availability of data, models, and code (Rosenberg and Watkins 2018) primarily targets availability in the reproducibility continuum. This Fig. 1. Reproducibility is a continuum.
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