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Using a Mamdani Fuzzy Inference System Model (MFISM) for Ranking Groundwater Quality in an Agri-Environmental Context: Case of the Hammamet-Nabeul Shallow Aquifer (Tunisia)
Water ( IF 3.0 ) Pub Date : 2021-09-12 , DOI: 10.3390/w13182507
Soumaya Hajji , Naima Yahyaoui , Sonda Bousnina , Fatma Ben Brahim , Nabila Allouche , Houda Faiedh , Salem Bouri , Wafik Hachicha , Awad M. Aljuaid

Using an adaptive Mamdani fuzzy inference system model (MFSIM), the purpose of this paper is mainly to assess and rank the assessment and ranking of water quality for irrigation occurring in the Hammamet-Nabeul (Tunisia) shallow aquifer. This aquifer is under Mediterranean climate conditions and affected by intensive and irrational agricultural activities. In the current study, the Mamdani fuzzy logic-based decision-making approach was adapted to classify groundwater quality (GW) for irrigation. The operation of the fuzzy model is based on the input membership functions of electrical conductivity (EC) and sodium absorption ratio (SAR) and on the output membership function of the irrigation water quality index (IWQI). Validation of the applied MFISM showed a rate of about 80%. Therefore, MFISM was shown to be reliable and flexible in quality ranking for irrigation in an uncertain and complex hydrogeological system. The results demonstrated that water quality contamination in the aquifer is affected by the overlaying of three types of negative anthropogenic practices: the excess use of water for irrigation and chemical fertilizers, and the rejection of partially treated wastewater in some areas. The implemented approach led to identifying the spatial distribution of water quality for irrigation in the studied area. It is considered a helpful tool for water agri-environmental sustainability and management.

中文翻译:

使用 Mamdani 模糊推理系统模型 (MFISM) 对农业环境中的地下水质量进行排名:以 Hammamet-Nabeul 浅层含水层为例(突尼斯)

本文的目的是使用自适应 Mamdani 模糊推理系统模型 (MFSIM),对发生在 Hammamet-Nabeul(突尼斯)浅层含水层中的灌溉水质进行评估和排序。该含水层处于地中海气候条件下,受到集约化和非理性农业活动的影响。在当前的研究中,基于 Mamdani 模糊逻辑的决策方法适用于对灌溉地下水质量 (GW) 进行分类。模糊模型的运行基于电导率 (EC) 和钠吸收率 (SAR) 的输入隶属函数以及灌溉水质指数 (IWQI) 的输出隶属函数。所应用的 MFISM 的验证率约为 80%。所以,在不确定和复杂的水文地质系统中,MFISM 被证明在灌溉质量排名方面是可靠和灵活的。结果表明,含水层中的水质污染受到三种负面人为行为的叠加影响:过度使用灌溉和化肥用水,以及部分地区拒绝部分处理的废水。实施的方法导致确定研究区域灌溉水质的空间分布。它被认为是水农业环境可持续性和管理的有用工具。灌溉用水和化肥的过度使用,以及在某些地区拒绝部分处理的废水。实施的方法导致确定研究区域灌溉水质的空间分布。它被认为是水农业环境可持续性和管理的有用工具。灌溉用水和化肥的过度使用,以及在某些地区拒绝部分处理的废水。实施的方法导致确定研究区域灌溉水质的空间分布。它被认为是水农业环境可持续性和管理的有用工具。
更新日期:2021-09-12
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