English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.

water

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)