OVERVIEW:ENSURING SUSTAINABLE AGRICULTURAL PRODUCTION AND COMMUNITIES IS A GRAND CHALLENGE THAT REQUIRES ADVANCESIN PLANT AND CROP SCIENCE, WEATHER AND CLIMATE FORECAST MODELS, HYDROLOGIC MODELS AND WATERMANAGEMENT TOOLS, AND MOST IMPORTANTLY, THE INTEGRATED ECOSYSTEM OF CLIMATE-FOOD-WATER. EFFECTIVEDEVELOPMENT, MANAGEMENT, AND OPTIMIZATION OF CROPPING SYSTEMS AND NATURAL RESOURCES IS IMPACTED BYMULTIPLE ISSUES, INCLUDING THE NEED TO RAPIDLY DEVELOP VARIETIES OF CROPS WITH HIGHER YIELDS UNDER STRESSESTHAT ARE RESISTANT TO PEST PRESSURES AND CLIMATE-RELATED ABIOTIC STRESSES ON PLANT HEALTH AND PRODUCTIVITYACROSS A WIDE RANGE OF GEOGRAPHIC AREAS AND DISPARATE SPATIAL AND TEMPORAL SCALES OF DATA ACQUISITION ANDPREDICTIVE MODELS.UNFORTUNATELY, MOST OF THE RECENT ADVANCES IN DIGITAL AGRICULTURE AND AI HAVE OCCURRED IN ISOLATION ANDHAVE FAILED TO EXPLORE THE CHALLENGES, OPPORTUNITIES, AND PAYOFF OF DEVELOPING SOLUTIONS FOR THEINTERCONNECTED FOOD, WATERSHED, WEATHER ECOSYSTEM BECAUSE OF THREE PRIMARY PROBLEMS. FIRST, THERE AREDATA ISSUES THAT LIMIT DEVELOPMENT OF THE METHODS. THIS INCLUDES (I) SCALE MISMATCH, (II) SOURCEMISALIGNMENT, AND (III) VOLUME OVERLOAD. SECOND, THERE ARE MODELING ASSUMPTIONS THAT RESTRICT THEAPPLICABILITY OF CURRENT METHODS FOR COMPLEX, HIGH-DIMENSIONAL, INTERCONNECTED ECOSYSTEMS. IN PARTICULAR,IT IS DIFFICULT TO LEARN AND REASON WHILE INCORPORATING (I) SCIENCE-BASED CONSTRAINTS, (II) RESOURCE TRADEOFFS,AND (III) LONG-RANGE DEPENDENCIES. THIRD, THERE ARE USABILITY CONCERNS THAT LIMIT THE DEPLOYMENT OFRELIABLE, FIELDABLE SOLUTIONS FOR RESEARCHERS, PRODUCERS, AND FARM MANAGEMENT SYSTEMS. THIS INCLUDES (I)LACK OF INTERPRETABILITY FOR HUMAN USERS, WHICH REDUCES TRUST, (II) MISMATCHED OBJECTIVES, AND (III)FRAGILE/UNSTABLE METHODS THAT ARE DIFFICULT TO TEST, EVALUATE, AND CERTIFY. SOLVING THESE CHALLENGES WILLREQUIRE NEW APPROACHES FROM SCIENCE-DRIVEN, HUMAN-GUIDED AI AND ANALYTICS TO ACHIEVE EFFECTIVE,EFFICIENT DECISION MAKING FROM PLANT GENOMICS RESEARCH TO SEASONAL AND MULTI-SEASON FARM OPERATIONS.OUR PLANNING GRANT PROJECT WILL FOCUS ON FIVE FUNDAMENTAL AREAS OF AI RESEARCH: REPRESENTATION, SCIENCEGUIDEDLEARNING, REASONING/PLANNING, EXPLAINABILITY/TRUST, AND ROBUSTNESS. OUR INVESTIGATION WILL CONSIDERTHE INTERACTION AND INTEGRATION OF THESE RESEARCH THEMES AND SEEK TO DEFINE THE MOST VIABLE AI APPROACHESAND MOST PROMISING RESEARCH DIRECTIONS TO ADDRESS THE CHALLENGES OF A SUSTAINABLE INTEGRATED CFWECOSYSTEM. THROUGH A SERIES OF ACTIVITIES WITH DOMAIN SCIENCE RESEARCHERS, AI RESEARCHERS, SUSTAINABILITYORGANIZATIONS, GROWERS, AND PRODUCERS, WE WILL EXPAND AND REFINE OUR UNDERSTANDING OF THE SCIENCE-GAPS,CONDUCT A COMMUNITY-DRIVEN PROGRAM OF DATA GATHERING, FORMULATE PROBLEM DEFINITIONS, AND EXPLORETARGETED RESEARCH QUESTIONS CONSTRUCTED FROM STAKEHOLDER INPUT.INTELLECTUAL MERIT:OUR PLANNING PROJECT WILL ELICIT THE MOST CRITICAL GAPS, PRESSING NEEDS, IMPEDIMENTS TO, AND PRACTICALCONSTRAINTS FOR, ADOPTION THROUGH COLLABORATIVE INTERACTION WITH DOMAIN SCIENTISTS, GROWERS, AND INDUSTRYPARTNERS. WE WILL IDENTIFY THE MOST PROMISING AI-FOCUSED RESEARCH DIRECTIONS TO ULTIMATELY ENABLESUSTAINABLE INTEGRATED WATER, FOOD, CLIMATE ECOSYSTEMS AND AGRICULTURAL COMMUNITIES. WE WILL CREATE ARESEARCH, EDUCATION, COMMUNITY ENGAGEMENT, AND DEPLOYMENT ROADMAP TO GUIDE THE DEVELOPMENT OF AN AIPLANNING GRANT: A GAP-BASED APPROACH TO FRAME AND DEVELOP ROBUST AI FOR SUSTAINABLE AGRICULTURE. WEWILL ALSO EDUCATE DOMAIN SCIENTISTS, GROWERS, AND COMMERCIAL PARTNERS IN THE OPPORTUNITIES, ISSUES, ANDAPPROACHES TO EFFECTIVELY AND RELIABLY USE AI TECHNIQUES, WHILE SIMULTANEOUSLY INFORMING AI RESEARCHERSOF USE-CASE GENERATED COMPLEXITIES, CHALLENGES, AND CONSTRAINTS TO GUIDE FIELDABLE ADVANCES OF AI RESEARCHAND TECHNIQUES TO IMPACT SOCIETY.BROADER IMPACTS:THE BROADER IMPACTS OF OUR WORK WILL INCLUDE DEVELOPING TECHNIQUES FOR AI-BASED ROAD MAPPING ANDCOMMUNITY-BASED FIELDABLE CONSTRAINT GENERATION FOR USE IN MANY APPLICATION AREAS. WE WILL ALSO DEVELOPEDUCATIONAL MATERIAL TO INTRODUCE "AI-LITERACY" TO END-USERS, SCIENCE RESEARCHERS, AND CITIZENS TO ENSURECORRECT, ROBUST, AND TRUSTABLE DEVELOPMENT AND DEPLOYMENT OF AI-GUIDED SOFTWARE AND DECISION-MAKINGSYSTEMS. BY INCREASING THIS TRUST, WE WILL ACCELERATE THE ADOPTION OF DATA-DRIVEN, AI-GUIDED TECHNIQUES TOIMPROVE THE EFFECTIVENESS AND EFFICIENCY OF SCIENTIFIC DISCOVERY, ENGINEERED SOLUTIONS, AND SUSTAINABLE,RESILIENT COMMUNITIES.