Raúl J. Osorio , Anna Linhoss , Justin Murdock , Mindy Yeager-Armstead , Meena Raju
{"title":"Sensitivity analysis of a hydrodynamic and harmful algal model in a riverine system","authors":"Raúl J. Osorio , Anna Linhoss , Justin Murdock , Mindy Yeager-Armstead , Meena Raju","doi":"10.1016/j.ecolmodel.2024.110846","DOIUrl":null,"url":null,"abstract":"<div><p>Simulating algae blooms using a hydrodynamic-water quality model is challenging because it requires a thorough understanding of physical and biological processes and involves numerous parameters. This study conducted a sensitivity analysis of the EFDC+ hydrodynamic and water quality model for simulating cyanobacteria growth, an important Harmful Algal Bloom (HAB) species in the Ohio River, USA. The sensitivity analysis assessed 23 model input parameters, divided into nine functional groups according to their characteristics. This assessment analyzes the impact of changing these input parameters on four water quality model outputs including algae (i.e., cyanobacteria), dissolved oxygen, total nitrogen, and total phosphorus. Light extinction parameters, maximum algal growth rate, and algal base metabolism were identified as the most sensitive parameters for simulating algal growth. Solar radiation required for algal growth was moderately sensitive. Currently, there are only a few studies that simulate HAB dynamics in riverine systems. This study deepens our understanding of HAB development in rivers with lock and dam structures that create a series of pools along the river. Future work will involve focusing on the sensitive parameters in model calibration.</p></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Modelling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304380024002345","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Simulating algae blooms using a hydrodynamic-water quality model is challenging because it requires a thorough understanding of physical and biological processes and involves numerous parameters. This study conducted a sensitivity analysis of the EFDC+ hydrodynamic and water quality model for simulating cyanobacteria growth, an important Harmful Algal Bloom (HAB) species in the Ohio River, USA. The sensitivity analysis assessed 23 model input parameters, divided into nine functional groups according to their characteristics. This assessment analyzes the impact of changing these input parameters on four water quality model outputs including algae (i.e., cyanobacteria), dissolved oxygen, total nitrogen, and total phosphorus. Light extinction parameters, maximum algal growth rate, and algal base metabolism were identified as the most sensitive parameters for simulating algal growth. Solar radiation required for algal growth was moderately sensitive. Currently, there are only a few studies that simulate HAB dynamics in riverine systems. This study deepens our understanding of HAB development in rivers with lock and dam structures that create a series of pools along the river. Future work will involve focusing on the sensitive parameters in model calibration.
期刊介绍:
The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).