Journal
WATER RESOURCES MANAGEMENT
Volume 24, Issue 15, Pages 4589-4612Publisher
SPRINGER
DOI: 10.1007/s11269-010-9681-1
Keywords
Fuzzy sets; Imprecision; Multi-criteria decision making; Vagueness; BMPs
Categories
Funding
- Center for Research Excellence in Science & Technology Research on Environmental Sustainability of Semi And Coastal Areas (CREST RESSACA) at Texas A&M University-Kingsville with the National Science Foundation (NSF) [0206259]
- Division Of Human Resource Development
- Direct For Education and Human Resources [0206259] Funding Source: National Science Foundation
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Improper agricultural practices can affect ground water through leaching, surface water through runoff, algae infestations, deforestation, and air quality through burning operations and ammonia emissions These effects may be mitigated through the institution of best management practices The utility of best management practices (BMPs) is recognized and being actively promoted by agricultural agencies, however, identifying a set of mandatory BMPs is inappropriate given variations between climactic, demographic and geographic regions as well as differences in farming practices In this study, a multi-criteria decision making model based on Attanassov's Intuitionistic Fuzzy Set (A-IFS) theory is introduced and its utility to rank agricultural best management practices is illustrated using a case-study from South Texas Implementation of the A-IFS MCDM method to the South Texas region resulted m irrigation scheduling being ranked as the most preferred alternative, while brush control/management' was the least preferred The A-IFS MCDM approach was particularly suitable for prioritizing and ranking agricultural best management practices because decision makers often tend to have both likes and dislikes with regards to specific BMPs and for a given evaluation attribute Not only does the A-IFS MCDM method provide a single composite score to rank the BMP alternatives, but the output of the A-IFS MCDM method also includes
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