High Performance Computing Application to Address Non-Point Source Pollution at a Watershed Level

Abstract

Best management practices (BMPs) have been proven to effectively reduce the Nonpoint source (NPS) pollution loads from agricultural areas. BMP selection and placement problem needs to be addressed for the placement of BMPs in a watershed at a field scale that would achieve maximum pollution reduction subjected to minimum cost increase for the placement of BMPs in the watershed through optimization techniques. The BMP selection problem is linked with a hydrologic and water quality simulation model to estimate the pollution loads at various locations in the watershed. However, the optimization techniques get very complicated as the size of the watershed gets larger as the design variables increase proportionately. Also, the BMP optimization is linked to the watershed level hydrologic and water quality simulation mode and this makes the problem require very high amount of computation time for the simulations to get to a near optimal set of BMP placement in the watershed. In this regard, the high performance computing (HPC) helps a great deal by providing a platform for running the simulations on a multitude of processors rather than a single processor. Unix serves as the de-facto operating system for most of the HPC applications as the architecture allows to run simulations that take a long time to run in much lesser time when compared to the Windows OS machines. In the present work we have used the Soil and Water Assessment Tool (SWAT) model in combination with a genetic algorithm (GA) optimization technique NSGA-II to optimally select and place BMPs at a watershed scale. We have tested the application of the optimization algorithm to reduce sediment, nitrogen, and phosphorus from the LAnguille River Watershed, Arkansas and pesticide from Wildcat Creek Watershed, Indiana. The SWAT model was compiled in Unix and the optimization routine for BMP selection and placement was coded as an objective function in NSGA-II program in C language. The optimization model was compiled in Unix to optimize the various BMPs that can be placed at a field scale, which is represented as a Hydrologic Response Unit ( HRU) in SWAT.