Water quality models serve as an economically feasible alternative to quantify fluxes of nutrient pollution and to simulate effective mitigation strategies; however, their applicability is often questioned due to broad uncertainties in model structure and parameterization, leading to uncertain outputs. We argue that reduction of uncertainty is partially achieved by integrating stable isotope data streams within the water quality model architecture. This article outlines the use of stable isotopes as a response variable within water quality models to improve the model boundary conditions associated with nutrient source provenance, constrain model parameterization, and elucidate shortcomings in the model structure. To assist researchers in future modeling efforts, we provide an overview of stable isotope theory; review isotopic signatures and applications for relevant carbon, nitrogen, and phosphorus pools; identify biotic and abiotic processes that impact isotope transfer between pools; review existing models that have incorporated stable isotope signatures; and highlight recommendations based on synthesis of existing knowledge. Broadly, we find existing applications that use isotopes have high efficacy for reducing water quality model uncertainty. We make recommendations toward the future use of sediment stable isotope signatures, given their integrative capacity and practical analytical process. We also detail a method to incorporate stable isotopes into multi-objective modeling frameworks. Finally, we encourage watershed modelers to work closely with isotope geochemists to ensure proper integration of stable isotopes into in-stream nutrient fate and transport routines in water quality models.
|Number of pages||19|
|Journal||Transactions of the ASABE|
|State||Published - 2018|
Bibliographical noteFunding Information:
We thank the University of Kentucky Department of Biosystems and Agricultural Engineering for partial funding of the graduate student while at the University of Kentucky. We gratefully acknowledge financial support of this research under National Science Foundation Award No. 163288, which provided partial support for the graduate student and corresponding author. This is Publication No. 17-05-074 of the Kentucky Agricultural Experiment Station and is published with the approval of the Director. This work is supported by the USDA National Institute of Food and Agriculture. Finally, we thank the three anonymous reviewers whose input and suggestions greatly improved the quality of the manuscript.
© 2018 American Society of Agricultural and Biological Engineers.
- Uncertainty analysis
- Water quality modeling
ASJC Scopus subject areas
- Food Science
- Biomedical Engineering
- Agronomy and Crop Science
- Soil Science