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United States Department of Agriculture

Agricultural Research Service

Research Project: Effects of Agricultural Water Management and Land Use Practices on Regional Water Quality
2013 Annual Report


1a.Objectives (from AD-416):
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.


1b.Approach (from AD-416):
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. Replacing 5310-61000-014-00D 02/2012.


3.Progress Report:
Objective 1 of the project involves making improvements to existing modeling technologies and developing new software tools that will enable using the models to assess irrigation and salinity management problems at larger scales than before. In FY2013, progress was made towards developing systems needed for specifying required model parameters across large areas. Two approaches were evaluated: (i.) a static geodatabase approach wherein soil survey data for a region is analyzed at one time to generate a large, fixed map of model parameters; and (ii.) a dynamic approach wherein parameters are generated as needed for a particular geocoordinate based on internet access to raw soils data. The latter approach was determined to possess a number of advantages and was adopted. Software has been developed for retrieving via webservices raw USDA-NRCS soil survey data for a given geocoordinate, aggregating or processing the retrieved data, and generating the required model parameter estimates. The system is able to consider model parameter distributions (rather than just single parameter values), which makes it possible to evaluate parameter-related uncertainties in model predictions. An example of such an uncertainty analysis was developed in FY2013, with salinity leaching predications and uncertainties being generated using Monte Carlo techniques.

A critical SY vacancy has delayed progress on Objective 2.1. The vacant position has been filled recently, with a new scientist joining the research team in August of 2013.

Objective 2.2 of the project focuses on the development of new technologies for improved modeling of coupled overland and subsurface flow and transport. In FY2013 numerical and analytical models have been developed to simulate transport in runoff water, streams, and rivers. In particular, we have incorporated 1D and 2D formulations for overland flow and transport into a partial differential equation solver. Preliminary results have demonstrated the ability to accurately couple overland flow and transport with the subsurface. This model will be further refined and tested, before conducting detailed numerical experiments and examining upscaling issues. Existing analytical models have also been adapted to simulate transport in rivers. These models were based on 1D, 2D, and 3D solutions of the advective-dispersion equation (ADE), or the ADE with terms for transient storage and inactivation.


4.Accomplishments
1. Quantifying uncertainties in salinity leaching and management. Maintaining irrigated agricultural productivity in the face of diminishing water and land availability will require more effective management of irrigation and soil salinity.One roadblock to using advanced computer simulation tools to better manage irrigation is that the models usually do not provide an estimate of the uncertainty in model predictions, which can be substantial. In FY2013, researches at ARS-Riverside demonstrated that some model uncertainties could be estimated using a statistical method known as Monte Carlo simulation. Sensitivity analyses were also used to identify model parameters having the greatest impact on prediction and uncertainty. Simulation results were compared with data measured in large lysimeters packed with clayey soil materials. The work will help researchers develop improved tools and guidelines for irrigation and salinity management.


Review Publications
Perez Guerrero, J.S., Pimentel, L.C., Skaggs, T.H. 2012. Analytical solution for the advection-dispersion transport equation in layered media. International Journal of Heat and Mass Transfer. 56:274-282.

Siyal, A.A., Van Genuchten, M.T., Skaggs, T.H. 2013. Solute transport in a loamy soil under subsurface porous clay pipe irrigation. Agricultural Water Management. 121(2013):73-80.

Skaggs, T.H., Suarez, D.L., Goldberg, S.R. 2013. Effects of soil hydraulic and transport parameter uncertainty on predictions of solute transport in large lysimeters. Vadose Zone Journal. doi:10.2136/vzj2012.0143.

Perez-Guerrero, J.S., Pontedeiro, E.M., Van Genuchten, M.T., Skaggs, T.H. 2013. Analytical solutions of the one-dimensional advection-dispersion solute transport equation subject to time-dependent boundary conditions. Chemical Engineering Journal. 221:487-491.

Kasel, D., Bradford, S.A., Simunek, J., Putz, T., Vereecken, H., Klumpp, E. 2013. Limited transport of functionalized multi-walled carbon nanotubes in two natural soils. Environmental Pollution. 180:152-158.

Leij, F.J., Bradford, S.A. 2013. Colloid transport in dual-permeability media. Journal of Contaminant Hydrology. 150:65-76.

Simunek, J., Jacques, D., Langergraber, G., Bradford, S.A., Sejna, M., Van Genuchten, M.T. 2013. Numerical modeling of contaminant transport using HYDRUS and its specialized modules. Journal of Indian Institute of Sciences. 93(2):265-284.

Van Genuchten, M.T., Leij, F.J., Skaggs, T.H., Toride, N., Bradford, S.A., Pontedeiro, E.M. 2013. Exact analytical solutions for contaminant transport in rivers 1. The equilibrium advection-dispersion equation. Journal of Hydrology and Hydromechanics. 61(2):146-160.

Kasel, D., Bradford, S.A., Simunek, J., Heggen, M., Vereecken, H., Klumpp, E. 2013. Transport and retention of multi-walled carbon nanotubes in saturated porous media: Effects of input concentration and grain size. Water Research. 47(2):933-944.

Liang, Y., Bradford, S.A., Simunek, J., Vereecken, H., Klumpp, E. 2013. Sensitivity of the transport and retention of stabilized silver nanoparticles to physicochemical factors. Water Research. 47(7):2572-2582.

Last Modified: 12/18/2014
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