ELM, An Estuarine Nitrogen Loading Model: Formulation and Verification of Predicted Concentrations of Dissolved Inorganic Nitrogen

• Published in: Water, air, and soil pollution Vol. 157; no. 1-4; pp. 365 - 391
• Main Authors: Valiela, Ivan, Mazzilli, Stefano, Bowen, Jennifer L., Kroeger, Kevin D., Cole, Marci L., Tomasky, Gabrielle, Isaji, Tatsu
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer 01.09.2004; Springer Nature B.V
• Subjects: Applied sciences; Brackish; Earth sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Environmental monitoring; Estuaries; Exact sciences and technology; Geochemistry; Groundwater; Groundwater flow; Mineralogy; Natural water pollution; Nitrogen; Nutrient dynamics; Pollution; Pollution, environment geology; Seawaters, estuaries; Sediments; Silicates; Streams; Water column; Water geochemistry; Water treatment and pollution; United States; North America; Massachusetts; America; ANW, USA, Massachusetts, Cape Cod; ANW, USA, Massachusetts; USA, Massachusetts, Cape Cod; Uncertainty; wastewater; Fertilization; nitrogen; Water resource management; Estuaries; nutrient loading; Concentration; Forecast model; Modeling; fertilizer; Eutrophication; Annual average; atmospheric deposition; Inorganic nitrogen; watersheds; Water quality; Nutrient; Agriculture; Water pollution; Waste water discharge
• ISSN: 0049-6979; 1573-2932
• DOI: 10.1023/B:WATE.0000038881.65397.06

ELM is an Estuarine Loading Model that calculates mean annual concentration of dissolved inorganic nitrogen (DIN) available to producers in shallow estuaries by considering how different processes modify pools of nitrogen provided by inputs (streams, groundwater flow, atmospheric deposition, N sub(2) fixation, and regeneration), and losses (burial and denitrification), within components of the estuarine system (bare sediments, seagrass meadows, salt marshes, water column). ELM also considers the effect of flushing rate within an estuary. Its formulation was constrained to minimize demands of data needed to run the model. In spite of simplifications such as the use of loss coefficients instead of functional formulations of processes, and uncertainties in all the terms included in ELM, predictions of mean annual DIN in water were not significantly different than field measurements done in estuaries in Cape Cod, Massachusetts, subject to different rates of nitrogen (N) loading. This verification suggests that, in spite of its simple formulation, ELM captures the functioning of nutrient dynamics within estuaries. ELM may therefore be a reasonable tool for use in basic studies in nutrient dynamics and land/estuary coupling. Because of its simplicity and comprehensiveness in inclusion of components and processes, ELM may also be useful in efforts to manage N loads to estuaries and related management issues.