Abstract
Uncertainty in ground water hydrology originates from different sources. Neglecting uncertainty in ground water problems can lead to incorrect results and misleading output. Several approaches have been developed to cope with uncertainty in ground water problems. The most widely used methods in uncertainty analysis are Monte Carlo simulation (MCS) and Latin hypercube sampling (LHS), developed from MCS. Despite the simplicity of MCS, many runs are required to achieve a reliable result. This paper presents orthogonal array (OA) sampling as a means to cope with uncertainty in ground water problems. The method was applied to an analytical stream depletion problem. To examine the convergence rate of the OA sampling, the results were compared to MCS and LHS. This study shows that OA can be applied to ground water problems. Results reveal that the convergence rate of the OA sampling is faster than MCS and LHS, with a smaller error of estimate when applied to a stream depletion problem.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
