An adaptive weighted-average Kriging method applied to monitoring of freshwater ecosystems

IF 1.8 4区环境科学与生态学 Q2 FISHERIES

Marine and Freshwater Research Pub Date : 2024-06-20 DOI:10.1071/mf24003

Qilu Liu, Jingfang Shen, Yaohui Li

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引用次数: 0

Abstract

Context

The prediction of freshwater quality is important for detecting pollution risks and assessing changes in freshwater ecosystems. As a high-precision interpolation method, Kriging was able to predict freshwater quality by using previously monitored data. However, how to select the key parameters, regression functions and correlation functions of Kriging method in the process of improving prediction accuracy is still a bottleneck.

Aims

This study aims to propose an adaptive weighted-average Kriging (AWAK) method to further enhance the accuracy of freshwater-quality predictions.

Methods

The AWAK method consists of four main steps. First, the key parameters influencing pollution indicators are selected by FPS method. Subsequently, six different Kriging candidate models are constructed by using regression and correlation functions with different characteristics. Then, an enhanced-likelihood function is used to determine the weights of the six Kriging candidate models. Finally, AWAK is built by weighted sum of these six Kriging models.

Key results

The AWAK outperformed traditional Kriging in predicting pH and dissolved oxygen, significantly reducing prediction errors.

Conclusions

By employing the AWAK method, this study successfully improved the accuracy of freshwater-quality predictions.

Implications

The introduction of the AWAK provides an effective approach in the field of freshwater ecology.

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应用于淡水生态系统监测的自适应加权平均克里金法

背景淡水水质预测对于检测污染风险和评估淡水生态系统的变化非常重要。作为一种高精度的插值方法，克里金法能够利用先前的监测数据预测淡水水质。然而，在提高预测精度的过程中，如何选择 Kriging 方法的关键参数、回归函数和相关函数仍是一个瓶颈。目的本研究旨在提出一种自适应加权平均克里金法（AWAK），以进一步提高淡水水质预测的准确性。方法 AWAK 方法包括四个主要步骤。首先，通过 FPS 方法选择影响污染指标的关键参数。然后，利用具有不同特征的回归函数和相关函数构建六个不同的克里金候选模型。然后，使用增强似然函数确定六个 Kriging 候选模型的权重。最后，通过这六个 Kriging 模型的加权和建立 AWAK。主要结果 AWAK 在预测 pH 值和溶解氧方面优于传统克里金法，大大减少了预测误差。结论通过采用 AWAK 方法，本研究成功提高了淡水水质预测的准确性。意义引入 AWAK 为淡水生态学领域提供了一种有效的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Marine and Freshwater Research 环境科学-海洋学

CiteScore

4.60

自引率

5.60%

发文量

审稿时长

3.8 months

期刊介绍： Marine and Freshwater Research is an international and interdisciplinary journal publishing contributions on all aquatic environments. The journal’s content addresses broad conceptual questions and investigations about the ecology and management of aquatic environments. Environments range from groundwaters, wetlands and streams to estuaries, rocky shores, reefs and the open ocean. Subject areas include, but are not limited to: aquatic ecosystem processes, such as nutrient cycling; biology; ecology; biogeochemistry; biogeography and phylogeography; hydrology; limnology; oceanography; toxicology; conservation and management; and ecosystem services. Contributions that are interdisciplinary and of wide interest and consider the social-ecological and institutional issues associated with managing marine and freshwater ecosystems are welcomed. Marine and Freshwater Research is a valuable resource for researchers in industry and academia, resource managers, environmental consultants, students and amateurs who are interested in any aspect of the aquatic sciences. Marine and Freshwater Research is published with the endorsement of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) and the Australian Academy of Science.