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A model of phosphorus cycling to explore the role of biomass turnover in submerged aquatic vegetation wetlands for Everglades restoration
KTH, School of Architecture and the Built Environment (ABE), Land and Water Resources Engineering. (Ekosystemteknik)
2013 (English)In: Ecological Modelling, ISSN 0304-3800, E-ISSN 1872-7026, Vol. 251, 135-149 p.Article in journal (Refereed) Published
Abstract [en]

Engineered wetlands using submerged aquatic vegetation (SAV) are a cornerstone to the Stormwater Treatment Area (STA) project for stripping phosphorus from agricultural stormwater and lake water before entering protected Everglades marshes in south Florida, USA. However, recent efforts have suggested that the apparent lowest achievable outflow P (C*) in SAV systems (similar to 16 mu g/l) may not be low enough for proposed regulatory criteria. Thus, deepened predictive understanding on the functionality of these systems is of critical importance. Here, we develop a steady-state mass balance model of intermediate complexity to investigate C* in SAV systems. The model focuses on the role of SAV biomass turnover and P release to the water column, drawing upon established principles from shallow lake studies. This study introduces several large and unique datasets collected from a single study site (STA-2 Cell 3) over a 10-year period and demonstrates coherence in these data through the modeling approach. The datasets included inflow outflow values, P storage in accrued sediment at two intervals, annual surveys of SAV species composition, gradients of SAV tissue-P, and gradients of internal water column P concentration (previously published). The model was implemented and calibrated in an uncertainty framework with Monte Carlo methods, threshold screening, and multi-criteria limits of acceptability. Model calibration and validation appeared successful, resulting distributions of model parameters and accepted model simulations were relatively narrow, and results deepened perspectives on the previously identified C*. Rooted SAV species may be mining substantial P from underlying soils via root uptake and thus contributing internal loads. Steady turnover and decomposition of SAV biomass may be accounting for up to about a third of the background C*. These perspectives are relevant to STA optimization; our unique data, usage, and calibration strategy should be of interest to the aquatic ecosystem modeling community in general.

Place, publisher, year, edition, pages
2013. Vol. 251, 135-149 p.
Keyword [en]
Everglades, Phosphorus, Stormwater Treatment Areas, Submerged aquatic vegetation, SAV, Mass balance, Model, Uncertainty, GLUE, Limits of acceptability
National Category
Environmental Engineering
Identifiers
URN: urn:nbn:se:kth:diva-104340DOI: 10.1016/j.ecolmodel.2012.12.001ISI: 000317258100014Scopus ID: 2-s2.0-84873256210OAI: oai:DiVA.org:kth-104340DiVA: diva2:564022
Note

QC 20130520. Updated from manuscript to article in journal.

Available from: 2012-11-01 Created: 2012-11-01 Last updated: 2017-12-07Bibliographically approved
In thesis
1. Environmental Modelling: Learning from Uncertainty
Open this publication in new window or tab >>Environmental Modelling: Learning from Uncertainty
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Environmental models are important tools; however uncertainty is pervasive in the modeling process.   Current research has shown that under­standing and representing these uncertainties is critical when decisions are expected to be made from the modeling results.  One critical question has become: how focused should uncertainty intervals be with consideration of characteristics of uncertain input data, model equation representations, and output observations?   This thesis delves into this issue with applied research in four independent studies.  These studies developed a diverse array of simply-structured process models (catchment hydrology, soil carbon dynamics, wetland P cycling, stream rating); employed field data observations with wide ranging characteristics (e.g., spatial variability, suspected systematic error); and explored several variations of probabilistic and non-probabilistic uncertainty schemes for model calibrations.  A key focus has been on how the design of various schemes impacted the resulting uncertainty intervals, and more importantly the ability to justify conclusions.  In general, some uncertainty in uncertainty (u2) resulted in all studies, in various degrees.  Subjectivity was intrinsic in the non-probabilistic results.  One study illustrated that such subjectivity could be partly mitigated using a “limits of acceptability” scheme with posterior validation of errors.  u2 was also a factor from probabilistic calibration algorithms, as residual errors were not wholly stochastic.  Overall however, u2 was not a deterrent to drawing conclusions from each study. One insight on the value of data for modeling was that there can be substantial redundant information in some hydrological time series.  Several process insights resulted: there can be substantial fractions of relatively inert soil carbon in agricultural systems; the lowest achievable outflow phosphorus concentration in an engineered wetland seemed partly controlled by rapid turnover and decomposition of the specific vegetation in that system.  Additionally, consideration of uncertainties in a stage-discharge rating model enabled more confident detection of change in long-term river flow patterns.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xii, 36 p.
Series
Trita-LWR. PHD, ISSN 1650-8602 ; 1068
Keyword
Models, data, error, uncertainty, hydrology, soil carbon, wetlands, phosphorus
National Category
Environmental Engineering
Identifiers
urn:nbn:se:kth:diva-104336 (URN)978-91-7501-538-5 (ISBN)
Public defence
2012-11-23, V2, Teknikringen 76 2tr, KTH, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

QC 20121105

Available from: 2012-11-05 Created: 2012-11-01 Last updated: 2012-11-05Bibliographically approved

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