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生态水文学模型在大规模环境影响评价中的应用。

Ecohydrological modeling for large-scale environmental impact assessment.

机构信息

Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI, USA.

Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI, USA.

出版信息

Sci Total Environ. 2016 Feb 1;543(Pt A):274-286. doi: 10.1016/j.scitotenv.2015.11.044. Epub 2015 Nov 18.

Abstract

Ecohydrological models are frequently used to assess the biological integrity of unsampled streams. These models vary in complexity and scale, and their utility depends on their final application. Tradeoffs are usually made in model scale, where large-scale models are useful for determining broad impacts of human activities on biological conditions, and regional-scale (e.g. watershed or ecoregion) models provide stakeholders greater detail at the individual stream reach level. Given these tradeoffs, the objective of this study was to develop large-scale stream health models with reach level accuracy similar to regional-scale models thereby allowing for impacts assessments and improved decision-making capabilities. To accomplish this, four measures of biological integrity (Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT), Family Index of Biotic Integrity (FIBI), Hilsenhoff Biotic Index (HBI), and fish Index of Biotic Integrity (IBI)) were modeled based on four thermal classes (cold, cold-transitional, cool, and warm) of streams that broadly dictate the distribution of aquatic biota in Michigan. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow and water quality in seven watersheds and the Hydrologic Index Tool was used to calculate 171 ecologically relevant flow regime variables. Unique variables were selected for each thermal class using a Bayesian variable selection method. The variables were then used in development of adaptive neuro-fuzzy inference systems (ANFIS) models of EPT, FIBI, HBI, and IBI. ANFIS model accuracy improved when accounting for stream thermal class rather than developing a global model.

摘要

生态水文学模型常用于评估未采样溪流的生物完整性。这些模型在复杂性和规模上有所不同,其适用性取决于最终的应用。在模型规模上通常需要进行权衡,大规模模型可用于确定人类活动对生物条件的广泛影响,而区域规模(例如流域或生态区)的模型则为个别溪流河段的利益相关者提供了更详细的信息。鉴于这些权衡,本研究的目的是开发具有与区域规模模型相似的河段精度的大规模溪流健康模型,从而能够进行影响评估和改进决策能力。为了实现这一目标,基于广泛决定水生生物分布的四种热类(冷、冷过渡、凉爽和温暖),对四种生物完整性指标(蜉蝣目、石蝇目和毛翅目分类群(EPT)、生物完整性综合指数(FIBI)、希尔斯霍夫生物完整性指数(HBI)和鱼类生物完整性指数(IBI))进行了建模。土壤和水评估工具(SWAT)用于模拟七个流域的流量和水质,水文指数工具用于计算 171 个生态相关的流量状况变量。使用贝叶斯变量选择方法为每个热类选择独特的变量。然后,使用这些变量开发 EPT、FIBI、HBI 和 IBI 的自适应神经模糊推理系统(ANFIS)模型。在考虑溪流热类别的情况下,ANFIS 模型的准确性有所提高,而不是开发全局模型。

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