AquaNutriOpt II: A multi-period bi-objective nutrient optimization python tool for controlling harmful algal blooms — A case study of Lake Okeechobee

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software Pub Date : 2025-03-16 DOI:10.1016/j.envsoft.2025.106428

Ashim Khanal , Osama M. Tarabih , Mauricio E. Arias , Qiong Zhang , Hadi Charkhgard

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Abstract

We introduce a significantly enhanced version of AquaNutriOpt, now equipped with advanced mathematical optimization capabilities absent in its initial release (Khanal et al., 2024). AquaNutriOpt II is a user-friendly, free, open-source Python tool designed to address the complex challenge of optimizing nutrient management for controlling harmful algal blooms. In this latest version, users gain the flexibility to incorporate multiple time periods into their analyses. Moreover, they can now optimize the management of two nutrients concurrently (primarily phosphorus and nitrogen) through an innovative multi-objective optimization framework. Building upon its predecessor, AquaNutriOpt II continues to streamline the identification of optimal Best Management Practices (BMPs) and Treatment Technologies (TTs), including determining the most suitable locations for implementation while considering budgetary constraints. To showcase the efficacy and advantages of AquaNutriOpt II, we apply it to a real-world case study centered on Lake Okeechobee in Florida, USA.

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AquaNutriOpt II：用于控制有害藻华的多时期双目标营养优化python工具-以奥基乔比湖为例

我们推出了一个显着增强的AquaNutriOpt版本，现在配备了最初版本中缺乏的高级数学优化功能（Khanal等人，2024）。AquaNutriOpt II是一个用户友好的、免费的、开源的Python工具，旨在解决优化营养管理以控制有害藻华的复杂挑战。在这个最新版本中，用户可以灵活地将多个时间段合并到他们的分析中。此外，他们现在可以通过创新的多目标优化框架同时优化两种营养素的管理（主要是磷和氮）。在其前身的基础上，AquaNutriOpt II继续简化最佳管理实践（BMPs）和处理技术（tt）的识别，包括在考虑预算限制的情况下确定最合适的实施地点。为了展示AquaNutriOpt II的功效和优势，我们将其应用于以美国佛罗里达州Okeechobee湖为中心的现实案例研究。

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来源期刊

Environmental Modelling & Software 工程技术-工程：环境

CiteScore

9.30

自引率

8.20%

发文量

241

审稿时长

60 days

期刊介绍： Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.