Forecasting of water quality parameters of Sandia station on Narmada basin using AI techniques, Central India

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2024-02-19 DOI:10.2166/wcc.2024.520

Deepak Kumar Tiwari, K. R. Singh, Vijendra Kumar

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引用次数: 0

Abstract

In addition to the influence of climate change on water availability and hydrological risks, the effects on water quality are in the early stages of investigations. This study aims to consolidate the latest interdisciplinary research in the application of artificial intelligence (AI) in the field of assessment of water quality parameters and its prediction. This research paper specifically explores the intricate relationship between climate change and water quality parameters at Sandia station, situated within the Narmada basin in Central India. As global climatic patterns continue to shift, the repercussions on water resources have gained prominence. In this work, electrical conductivity is predicted using the KERAS data processing environment on TensorFlow. The root mean square error (RMSE), coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), etc. are calculated between observed and predicted values to assess the model performance. A total of 10 models are developed depending upon the input geometry from past monthly timelines. The results indicate that Model no. 8, with 10 inputs performs the best based on the R2 value of 0.889. These results indicate that AI can be very helpful in analyzing the possible threats in the future for drinking, water, livestock feeding, irrigation, and so on.

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利用人工智能技术预测印度中部纳尔马达流域桑迪亚站的水质参数

除了气候变化对水资源供应和水文风险的影响外，对水质的影响也处于早期调查阶段。本研究旨在整合人工智能（AI）在水质参数评估及其预测领域应用的最新跨学科研究成果。本研究论文特别探讨了位于印度中部纳尔马达流域的桑迪亚站气候变化与水质参数之间的复杂关系。随着全球气候模式的不断变化，对水资源的影响也日益突出。在这项工作中，使用 TensorFlow 上的 KERAS 数据处理环境对电导率进行了预测。通过计算观测值和预测值之间的均方根误差（RMSE）、判定系数（R2）、纳什-苏克里夫效率（NSE）等来评估模型性能。根据过去每月时间轴的输入几何数据，共建立了 10 个模型。结果表明，8 号模型在 10 个输入参数中表现最好。根据 0.889 的 R2 值，有 10 个输入值的 8 号模型表现最佳。这些结果表明，人工智能可以很好地帮助分析未来在饮用水、水源、牲畜饲养、灌溉等方面可能存在的威胁。

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来源期刊

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464

期刊介绍： ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.