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Research Project: Effects of Agricultural Water Management and Land Use Practices on Regional Water Quality


Project Number: 2036-61000-015-000-D
Project Type: In-House Appropriated

Start Date: Feb 6, 2012
End Date: Feb 5, 2017

Objective 1. Assessment and improvement of existing modeling technologies for simulating regional scale hydrogeology, including land surface processes associated with agricultural water management; modeling assessments of the impacts of existing and changing agricultural water and land management practices on water quality for regions of interest. Objective 2. Development of new technologies for simulating agricultural practices at the regional scale by measuring or modeling mechanistic processes controlling contaminant loading rates (salinity, nutrients, and other contaminants of concern) from fields under varying environmental conditions and agricultural management practices used in arid and semi-arid regions. Objective 2.1 Development of new technologies for improved soil parameter estimates for regional hydrogeologic simulations. Objective 2.2 Development of new technologies for improved modeling of coupled overland and subsurface flow and transport.

Water availability for irrigated agriculture is decreasing in arid and semi-arid regions, forcing a greater reliance on recycled or otherwise degraded waters. Sustainable use of low quality waters requires soil, water, and crop management practices that optimize crop production while minimizing the degradation of groundwater resources by agricultural contaminants such as salts and nutrients. Advanced computer simulation models and decision-support tools are needed to evaluate the long term impacts of irrigation and land management practices on regional groundwater quality. The project is organized around short term and long term objectives. Looking to the near term (Objective 1), we will evaluate and adapt existing modeling strategies for incorporating vadose zone processes into regional simulations, identify parsimonious modeling techniques, assess uncertainties associated with differing modeling approaches, and make calculations illustrating uncertainties associated with modeling various management scenarios. In the longer term, we anticipate that increased computing power and improved sensing technologies and land use data will eventually permit significantly higher resolution simulations than is currently possible. Toward that end (Objective 2), we will investigate the use of remote sensing and other data to estimate soil properties at a higher resolution, and will develop improved models for coupled overland and subsurface transport which will be able take advantage of high resolution topographic data. The project should lead to recommendations for developing modeling components of basin-scale salinity and nutrient management plans, and to improved capabilities for predicting the long-term effects of management decisions on soil and groundwater quality.