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Global sensitivity analysis of a three-dimensional nutrients-algae dynamic model for a large shallow lake

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  • Yi, Xuan
  • Zou, Rui
  • Guo, Huaicheng

Abstract

Sensitivity analysis is a primary approach used in mathematical modeling to identify important factors that control the response dynamics in a model. In this paper, we applied the Morris sensitivity analysis method to identify the important factors governing the dynamics in a complex 3-dimensional water quality model. The water quality model was developed using the Environmental fluid dynamics code (EFDC) to simulate the fate and transport of nutrients and algal dynamics in Lake Dianchi, one of the most polluted large lakes in China. The analysis focused on the response of four water quality constituents, including chlorophyll-a, dissolved oxygen, total nitrogen, and total phosphorus, to 47 parameters and 7 external driving forces. We used Morris sensitivity analysis with different sample sizes and factor perturbation ranges to study the sensitivity with regard to different output metrics of the water quality model, and we analyzed the consistency between different sensitivity scenarios. In addition to the analysis with aggregate outputs, a spatiotemporal variability analysis was performed to understand the spatial heterogeneity and temporal distribution of sensitivities. Our results indicated that it is important to consider multiple characteristics in a sensitivity analysis, and we have identified a robust set of sensitive factors in the water quality model that will be useful for systematic model parameter identification and uncertainty analysis.

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  • Yi, Xuan & Zou, Rui & Guo, Huaicheng, 2016. "Global sensitivity analysis of a three-dimensional nutrients-algae dynamic model for a large shallow lake," Ecological Modelling, Elsevier, vol. 327(C), pages 74-84.
    • Handle: RePEc:eee:ecomod:v:327:y:2016:i:c:p:74-84
    DOI: 10.1016/j.ecolmodel.2016.01.005
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    4. Zou, Rui & Wu, Zhen & Zhao, Lei & Elser, James J. & Yu, Yanhong & Chen, Yihui & Liu, Yong, 2020. "Seasonal algal blooms support sediment release of phosphorus via positive feedback in a eutrophic lake: Insights from a nutrient flux tracking modeling," Ecological Modelling, Elsevier, vol. 416(C).
    5. Ruichen Xu & Yong Pang & Zhibing Hu & Xiaoyan Hu, 2022. "The Spatiotemporal Characteristics of Water Quality and Main Controlling Factors of Algal Blooms in Tai Lake, China," Sustainability, MDPI, vol. 14(9), pages 1-17, May.
    6. Bae, Soonyim & Seo, Dongil, 2018. "Analysis and modeling of algal blooms in the Nakdong River, Korea," Ecological Modelling, Elsevier, vol. 372(C), pages 53-63.
    7. Xu, Zhihao & Yin, Xinan & Yang, Zhifeng & Cai, Yanpeng & Sun, Tao, 2016. "New model to assessing nutrient assimilative capacity in plant-dominated lakes: Considering ecological effects of hydrological changes," Ecological Modelling, Elsevier, vol. 332(C), pages 94-102.
    8. Bae, Sunim & Seo, Dongil, 2021. "Changes in algal bloom dynamics in a regulated large river in response to eutrophic status," Ecological Modelling, Elsevier, vol. 454(C).
    9. Soares, L.M.V. & Calijuri, M.C., 2021. "Sensitivity and identifiability analyses of parameters for water quality modeling of subtropical reservoirs," Ecological Modelling, Elsevier, vol. 458(C).

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