A CURRENT CHALLENGE FOR THE GLOBAL COMMUNITY IS TO SECURE FOOD PROVISION FOR THE DECADES TO COME. THE GOAL OF THIS PROPOSAL IS TO DEVELOP A CONCEPTUAL MODEL TO PREDICT HYBRID PERFORMANCE IN RESPONSE TO HYDROCLIMATIC CHANGES. HISTORICALLY, GENETIC PROGRESSES IN MAIZE PRODUCTION HAVE RESPONDED TO BREEDING ACTIVITIES. TO PURSUE FUTURE SUCCESSFUL AND SUSTAINABLE CROP PRODUCTION WE PROPOSE TO DEVELOP A GENOMICS-BY-ENVIRONMENT MODEL. TO IMPLEMENT SUCH HYBRID STATISTICAL MODELING APPROACH, POSSIBLE SOURCES OF PREDICTABILITY OF CORN HYBRID PERFORMANCE THOROUGH CHANGING CLIMATE FORCINGS WILL BE INVESTIGATED AND IMPLEMENTED IN A CONCEPTUAL FRAMEWORK AS FOLLOWS: (1) DEVELOP A DATA MANAGEMENT TEST BED TO COLLECT, STANDARDIZE AND INTEGRATE DATA; (2) CHARACTERIZE SPATIOTEMPORAL HYDROCLIMATIC CONTROLS AND THE ASSOCIATED UNCERTAINTIES ACROSS SCALES; (3) DEVELOP A CONCEPTUAL GENETIC-, MULTI-TRAIT-, AND HYDROCLIMATIC-SENSITIVE MODEL; (4) PERFORM HYDROCLIMATIC-DRIVEN HYBRID PERFORMANCE FORECASTS BASED ON (A) THE SPATIAL REGIONALIZATION OF PHENOTYPIC AND ENVIRONMENTAL DATA AND (B) THE TEMPORAL INFLUENCE OF EHCES ON PHENOTYPIC EXPRESSIONS UNDER STANDARDIZED INDICES AND ABSOLUTE VALUES OF ENVIRONMENTAL VARIABLES; AND (5) DEVELOP A CONCEPTUAL FRAMEWORK FOR OPERATIONAL RAPID-RESPONSE HYBRID PERFORMANCE FORECASTS. ULTIMATELY, SIMULATED SUCCESSFUL HYBRIDS IN RESPONSE TO DROUGHTS MAY BE OBTAINED BY INTEGRATING THE GEOSPATIAL EXPANSION OF GENES AT FIELD-SCALE AND THE SYNTHESES OF GLOBAL-SCALE HYDROCLIMATIC PROCESSES.