Each year an oxygen-depleted (hypoxia) zone forms in the Northern Gulf of Mexico, negatively impacting coast and marine fisheries and local economies. The spatial extent of this zone is about three times the target goal of the national Hypoxia Action Plan. The scientific assessment of causes and consequences of these hypoxic conditions indicates that both nitrogen and phosphorous loadings from the Upper Mississippi River Basin and Ohio River Basin stream systems are significant contributors to the size and duration of the zone. Land use, primarily from agriculture, is a key driver of these nutrient loadings and is the result of decisions made by more than 500,000 individual producers in those river basins. However, understanding the biogeochemical processes alone is insufficient to understanding the dynamics of this complex system. This project takes a fresh look at the natural and human dynamics of this enormous system by developing integrated and data-rich models that capture the spatial and temporal non-linearity associated with scaling up the impacts from individuals to the watershed under different scenarios. The research will produce the first complete modeling system that traces agricultural land-use decisions, made at the field scale in the Upper Mississippi, Ohio, and Tennessee Basins through both environmental and hydrologic components, to downstream water quality effects, including the size of the hypoxic zone in the Gulf of Mexico. Uniquely, the modeling effort will incorporate feedbacks via the market, and feedbacks via public policy in the form of adaptive management. This project will demonstrate how to integrate human and natural process models using the powerful tools of evolutionary algorithms.
Hypoxia is a growing environmental problem for coastal habitats elsewhere in the United States and many other countries. The development of a general modeling framework from this research will provide an effective tool for the design and implementation of policy to address both Gulf hypoxia and water quality concerns, and identify cost-effective placement of conservation practices within the landscape. This project will strengthen an interdisciplinary collaboration among scientists at five different institutions, and will support the training of graduate and undergraduate students.
In this study, a team of economists, agricultural engineers, ocean scientists, and computational experts developed a fully integrated watershed based model of the Mississippi River Basin linked with a statistical model of the size of the Gulf of Mexico hypoxic zone. The model has been termed "LUMINATE" which is an acronym for Land Use Model Integrating Agricultural and The Environment. LUMINATE provides the capacity to evaluate a wide range of land use scenarios to link how changes in agricultural practices alter the average size of the hypoxic zone. The SWAT model was used to simulate the effects of cropland conservation investments on nutrient delivery to the Gulf. The results from the model was fed to an optimization model to evaluate the various options and ways to reduce the Nitrogen loading into Gulf of Mexico. The agricultural nutrients load is considered to the largest source of nutrient pollution in the Gulf of Mexico causing hypoxia and thus reduces the production/harvest of fish from marine water. Reductions in these nutrients will be needed to meet the 5,000 km2 policy goal set by the national Gulf of Mexico Task Force's Action Planings. The current model assumes the current agricultural practice in estimating the nutrient loads to Gulf of Mexico. However, these loads can vary based on climate variability and land use/crop distribution and management change such as adapting conservation practices to reduce the nutrient loads to Gulf of Mexico.
