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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #334981
Research Project: Design and Implementation of Monitoring and Modeling Methods to Evaluate Microbial Quality of Surface Water Sources Used for Irrigation

Location: Environmental Microbial & Food Safety Laboratory

Title: Simulating seasonal variability of phytoplankton in stream water using the modified SWAT model

Author
item PYO, JONGCHEOL - University Of Ulsan College Of Medicine
item Pachepsky, Yakov
item KIM, MINJEONG - University Of Ulsan College Of Medicine
item BAEK, SANG-SOO - University Of Ulsan College Of Medicine
item LEE, HYUK - University Of Ulsan College Of Medicine
item CHA, YOONKYUNG - Seoul National University
item PARK, YONGEUN - University Of Ulsan College Of Medicine
item CHO, KYUNGHWA - University Of Ulsan College Of Medicine

Submitted to: Environmental Modelling & Software
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/8/2017
Publication Date: 11/8/2017
Citation: Pyo, J., Pachepsky, Y.A., Kim, M., Baek, S., Lee, H., Cha, Y., Park, Y., Cho, K. 2017. Simulating seasonal variability of phytoplankton in stream water using the modified SWAT model. Environmental Modelling & Software. 122:104073. https://doi.org/10.1016/j.envsoft.2017.11.005.
DOI: https://doi.org/10.1016/j.envsoft.2017.11.005

Interpretive Summary: Algae blooms affect biological and microbiological water quality in freshwater sources. The widely used watershed war quality model SWAT has a module to simulate algal; growth, but it apparently has never been tested. We tested this module with monitoring data for cyanobacteria, green algae, and diatoms, and found that it gives erroneous results. The objective of this work was to improve the algal module. We found that drastic improvement of algae biomass dynamics modeling in SWAT can be achieved by introducing proper algae-specific temperature correction to rates of biological processes, and accounting for dead algae biomass as the nutrients source. Results of this work are expected to be useful for professional in water quality assessment and management in that they allow seamlessly integrate the biological water quality assessment in the set of water quality assessments performed with the SWAT model.

Technical Abstract: The ability to simulate algal systems is critical for watershed-scale models. The objective of this study was to develop and evaluate a new algal module that simulates the dynamics of three major algal groups, i.e., cyanobacteria, green algae, and diatoms, using variables available in the soil and water assessment tool (SWAT). The module has two new features: 1) modeling dynamics of the three algal groups accounting for nutrients from algal die-off and 2) the temperature multiplier functions to consider the effect of temperature changes in kinetic rates. Data to test the module were collected at a forest-dominated watershed for 6 years. The new module was efficient in the prediction of seasonal variations in the algal group biomass and described the impact of nutrients on algal growth. This module will be useful in predicting the dynamics of the three algal groups and evaluating best management practices for algal blooms in watersheds.