相关实验视频

Updated: Mar 7, 2026

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

使用CWQI,基于CRITIC的改进CWQI,灵敏度分析,多变量技术,机器学习算法和GIS方法进行综合性水质评估及其预测,以确定河流盆地 (奥迪沙州) 的污染强度

¹Department of Civil Engineering, C.V. Raman Global University (CGU), Bhubaneswar, Odisha, India. das.abhijeetlaltu1999@gmail.com.

Environmental science and pollution research international

|March 5, 2026

概括

由于人类活动和农业,奥迪沙邦的玛哈纳迪河水质不佳,TDS和大肠杆菌水平高. 像ANFIS这样的先进方法显示了准确的水质评估和管理的潜力.

科学领域:

水地地化学水地地化学
环境科学环境科学
水资源管理水资源管理

背景情况:

玛哈纳迪河对奥迪沙的供水至关重要,但由于人类活动和农业而面临污染.
细菌污染和水质恶化的严重问题,需要紧急关注.

研究的目的:

为了对玛哈纳迪河的地表水进行水地化学研究.
确定控制地表水化学的过程,并评估家庭和农业用水的水质.
评估各种水质评估方法,包括WQI,MST和ML技术.

主要方法:

在季风季节 (2017-2024) 期间,从11个地点收集和分析了13个水样.
物理化学和初级离子分析,包括WQI,CRITIC-(C) R,PCA,DA,GAPSO-WQI,GMDH-WQI,火算法和ANFIS模型.
关键水质参数的敏感性分析.

主要成果:

地表水是性的,度高,TDS和大肠杆菌水平超过世卫组织的指导方针.
63.64%的水质不适合家庭使用,72.73%的水质根据改善的CWQI被认为不适合使用.
PCA确定了表面下水,工业/城市废水和农业下水是主要的污染源.
在ANFIS模型中,水质参数的预测准确度很高 (MAPE=9.09%,RMSE=17.08%).

结论:

玛哈纳迪河的水质受到人类活动和农业实践的重大影响.
多种评估方法揭示了水质普遍恶化,特定地点受到严重污染.
该研究强调了先进的ML模型的有效性,如ANFIS用于准确的水质预测和可持续的水资源管理.

关键词:

安菲斯 (ANFIS) 是一个字母.批评性批评性批评性综合水质指数 - - 水质指数机器学习是机器学习.玛哈纳迪河 (Mahanadi River) 是一个大河.多变量是多变量的.水资源管理水资源的管理.

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Watershed Planning within a Quantitative Scenario Analysis Framework

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

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