Ecohydrology
Group

Agricultural and Biological Engineering

Effectiveness and optimization of BMP’s in improving water quality from an agriculturally dominated watershed

Li Chi Chiang

Statement of Problem

This project is performed in Lincoln Lake watershed located in the Ozark Highlands of Northwest Arkansas. Due to intensive farm practices, nonpoint source pollution has become one of the most challenging environmental problems in agricultural and mixed land use watersheds. The NPS pollution problem can be controlled by implementing various best management practices (BMPs) in the watershed. However, before these practices are adopted, their effectiveness at various spatial and temporal scales must be evaluated. Therefore, a preliminary optimum BMP combination for current land use and weather condition can be evaluated. The sensitiveness of BMPs combination to different weather conditions needs to be evaluated by generating various possible 25-year period weather data. Furthermore, concerning land use change, the evaluation of the effectiveness of the preliminary optimum BMPs and how they need to be adjusted as land use changes will be done.

Current Activities

A total of 171 different BMP combinations (scenarios) incorporating grazing and pasture management, riparian and buffer zones, poultry litter and commercial fertilizers application were generated. 250 possible 25-year- period weather data based on measured historical climate data were also generated. The Soil and Water Assessment Tool (SWAT) model is used to simulate the flow, sediment and nutrient losses of these 171 different scenarios with 250 weather data. Since it is a big challenge to compute such large data and demand large memory space, all the model simulations are run in Condor, a specialized workload management system for computer-intensive jobs. After all the simulations of these scenarios are done, the sensitiveness of BMP scenarios to different weather conditions will be evaluated. The completion of 171 scenarios with 250 weather data shows that Condor is an efficient high throughput computing management system in this research field. Evaluation of BMP combination with different weather data will show the influence of the stochasticity in weather. Estimation of the uncertainty of BMP combination with land use change and climate change will provide information

Recent presentations and publications

1. Chiang, L., M. Gitau, and I. Chaubey. 2008. Effectiveness of BMPs considering uncertainties in weather patterns in a pasture dominated watershed.  Paper No. 083549, Annual International Conference of the ASABE, Providence, RI. June 29-July 2. Pdf of the presentation
   
   
2. Gitau, M., L. Chiang, I. Chaubey, and M. Sayeed.  2008. Computational approaches to evaluating BMPs considering stochasticity of weather.  Paper No. 083577, Annual International Conference of the ASABE, Providence, RI. June 29-July 2.
   
   
3. Chaubey, I., M. Gitau, L. Chiang, J.H. Popp, E. Gbur, M.A. Nelson, J. Pennington, G. Rodriguez, and B. Kurz.  2008.  BMP effectiveness assessment for a pasture dominated watershed: results from two years of CEAP assessment. Annual Conference of the USDA-CSREES.  Sparks, NV.  February 4-7.
   
   
4. Gitau, M.W., L. Chiang, I. Chaubey, and M. Sayeed.  2008.  Evaluating BMP scenario under CEAP: approaches to handling a multitude of runs and large datasets. Annual Conference of the USDA-CSREES.  Sparks, NV.  February 4-7.
   
   
5. Gitau, M., L. Chiang, I. Chaubey, and S. Mohammed.  2007. Evaluating best management practice impacts on water quality considering stochasticity of weather.  Poster Presented at the CRI, High Performance Computing Seminar, Purdue University.  October 25.