2628007

CENTER: CREST PHASE II: CENTER FOR RESEARCH, EDUCATION, APPLICATION, AND TECHNOLOGY TRANSFER EXCELLENCE FOR AI-DRIVEN AGRICULTURAL WATER SUSTAINABILITY (CREATE-AI WATER) -THE NSF CENTERS FOR RESEARCH EXCELLENCE IN SCIENCE AND TECHNOLOGY (CREST) PROGRAM SUPPORTS EMERGING RESEARCH INSTITUTIONS (ERIS) IN OPERATING CENTERS THAT INTEGRATE RESEARCH AND EDUCATION TO ELEVATE INSTITUTIONS? NATIONAL RESEARCH COMPETITIVENESS, ADVANCE STEM KNOWLEDGE, AND DEVELOP THE STEM WORKFORCE. ONE SUCH CENTER, THE CENTER FOR RESEARCH, EDUCATION, APPLICATION AND TECHNOLOGY TRANSFER EXCELLENCE FOR AI-DRIVEN AGRICULTURAL WATER SUSTAINABILITY (CREATE-AI WATER) HOUSED AT TEXAS A&M UNIVERSITY, WILL FOCUS ON DEVELOPING WATER MANAGEMENT SOLUTIONS TO COMPETING DEMANDS FOR FRESHWATER FUELED BY TODAY?S EVER-INCREASING POPULATION, URBAN GROWTH, AND INCREASING IRRIGATION-DEPENDENT AGRICULTURAL PRODUCTION. THE CENTER WILL BECOME A NATIONAL LEADER IN WATER MANAGEMENT RESEARCH AND SERVE AS A HUB TO ASSIST WATER USE DECISION MAKING IN SOUTH TEXAS, WORKING AT THE INTERFACE OF TECHNOLOGY, AGRICULTURE, AND WATER RESOURCES, WHILE PREPARING THE NEXT GENERATION OF STEM PROFESSIONALS IN ENGINEERING AND AGRICULTURAL SCIENCES. THE CREATE-AI WATER WILL LEVERAGE EXISTING RESEARCH EXPERTISE AND EXTENSIVE STAKEHOLDER NETWORKS TO DELIVER AN INTEGRATED PROGRAM OF RESEARCH, EDUCATION, AND OUTREACH ACTIVITIES FOCUSED ON INTERCONNECTED WATER SUSTAINABILITY ISSUES AND BECOME A NATIONALLY RECOGNIZED SOURCE OF EXPERTISE, TRAINING, AND POLICY ENGAGEMENT RELATED TO WATER MANAGEMENT FOR SUSTAINABLE AGRICULTURE. OUTCOMES OF ACTIVITIES OF THE CREATE-AI WATER CENTER WILL ENHANCE AGRICULTURAL PRODUCTIVITY THROUGH SUSTAINABLE WATER MANAGEMENT STRATEGIES AND SOIL AMENDMENTS, PROMOTE RESILIENCE TO EXTREME WEATHER EVENTS, AND CONTRIBUTE TO FOOD SECURITY AND ENVIRONMENTAL SUSTAINABILITY, WHILE CREATING OPPORTUNITIES FOR JOB GROWTH AND INDUSTRY EXPANSION. THE GOALS AND OBJECTIVES OF CREATE-AI WATER ARE TO: 1) ADDRESS WATER QUALITY AND SUSTAINABILITY FOR AGRICULTURAL USE AMID THE CHALLENGES POSED BY FACTORS SUCH AS EXTREME WEATHER: DYNAMIC INTERACTIONS OF SOIL MOISTURE AVAILABILITY AND CONSERVATION PRACTICES; AND ISSUES RELATED TO CONTAMINANTS; 2) DEVELOP STAKEHOLDER-BASED DECISION SUPPORT SYSTEMS USING AI-ENABLED TECHNOLOGIES, 3) ENGAGE, TRAIN, AND DEVELOP NEXT-GENERATION, WORKFORCE-READY, AI-COMPETENT SCIENTISTS AND ENGINEERS, 4) ELEVATE THE CENTER?S NATIONAL RESEARCH COMPETITIVENESS AND SUSTAINABILITY; AND 5) PROVIDE EXPERIMENTAL AND EXPERIENTIAL LEARNING OPPORTUNITIES FOR STUDENTS, INCLUDING K-12. THE CREST CREATE-AI WATER CENTER WILL HAVE THREE SYNERGISTIC SUBPROJECTS THAT SUPPORT ITS CENTRAL RESEARCH AGENDA. THE FIRST FOCUSES ON FRESHWATER SUSTAINABILITY AND INTEGRATED WATER MANAGEMENT UNDER VARYING WEATHER CONDITIONS, WHICH AIMS TO IMPROVE OUR UNDERSTANDING OF THE INTERACTIONS BETWEEN LAND SURFACE STATES (E.G., SOIL MOISTURE), THEIR DATA ASSIMILATION, AND WEATHER FORECASTS. THE SECOND FOCUSES ON EMERGING WATER QUALITY CHALLENGES IN SUSTAINABLE AGRICULTURE WHICH AIMS TO GAIN AN IMPROVED UNDERSTANDING OF THE OCCURRENCE, FATE, AND TRANSPORT OF EMERGING CONTAMINANTS ASSOCIATED WITH AGRICULTURAL PRACTICES. THE THIRD SUBPROJECT FOCUSES ON ENHANCING STAKEHOLDER?S ADAPTIVE CAPACITY TO SUPPORT WHOLE SYSTEM RESILIENCY, WHICH AIMS TO UNDERSTAND AND CHARACTERIZE THE COMPLEX INTERACTION BETWEEN PEOPLE, NATURAL RESOURCES, AND ECONOMIC SECTORS IN HIGHLY INTERCONNECTED MULTI-AGENT SYSTEMS. CENTER RESEARCH IN ALL THREE SUBPROJECTS WILL CAPITALIZE ON THE USE OF TECHNOLOGIES INCLUDING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TOOLS TO ASSIST IN MANAGING BIG DATA SETS IN THE CREATION OF PREDICTIVE MODELS USEFUL IN DEVELOPING WATER MANAGEMENT STRATEGIES. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

Texas A&M University Kingsville

NOT APPLICABLE

47.076 - Education and Human Resources

Division of Undergraduate Education (DUE) [NSF]

Kingsville, Texas 78363-8202 United States

Single Zip Code

NOT APPLICABLE