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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 in "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 4590 E.A. Hernandez, V. Uddameri upper and lower bounds that help identify the uncertainties in the decision making process.

Worldwide, access to clean drinking water is not available for more than 800 million people. The biosand filter (BSF), an intermittently operated slow sand filter, was developed to address this problem. The BSF is used in homes to improve water quality. Three main objectives were examined in this research: (1) investigate initial startup and recovery performance after cleaning BSF, (2) examine the number of people the BSF may effectively serve, and (3) determine effects of an extended pause period on BSF performance. Laboratory experiments examined the BSF's ability to reduce fecal coliforms (FC) and turbidity for the various objectives. Results indicate that during the startup period, 27 days were needed to achieve 1 log reduction, while only 17 days were needed after cleaning the BSF to achieve 1 log reduction. A maximum of six people can be effectively served by a single BSF based upon the results of the experiment. A 7-day extended pause period determined that the bacterial layer will begin to go dormant or die off when the filter is not used for an extended period.