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Streamflow Simulation: A Nonparametric Approach, Ashish Sharma, David G. Tarboton, Upmanu L. Lall
Streamflow Simulation: A Nonparametric Approach, Ashish Sharma, David G. Tarboton, Upmanu L. Lall
Civil and Environmental Engineering Faculty Publications
In this paper kernel estimates of the joint and conditional probability density functions are used to generate synthetic streamflow sequences. Streamflow is assumed to be a Markov process with time dependence characterized by a multivariate probability density function. Kernel methods are used to estimate this multivariate density function. Simulation proceeds by sequentially resampling from the conditional density function derived from the kernel estimate of the underlying multivariate probability density function. This is a nonparametric method for the synthesis of streamflow that is data-driven and avoids prior assumptions as to the form of dependence (e.g., linear or nonlinear) and the form …
Introduction To Simulation/Optimization Modeling For Groundwater Containment Remediation And (B) Ramifications Of Applying S/O Modeling To Groundwater Containment Remediation, With Case Study Examples, Richard C. Peralta
Civil and Environmental Engineering Faculty Publications
Normal use of a simulation model to develop a groundwater extraction/injection strategy employs the following process: (1) specify management goals, (2) assume a pumping strategy, (3) simulate system response to the pumping strategy, (4) evaluate acceptability of the system responses, (5) repeat steps (2-4) as required. This is a trial and error approach that is unlikely to actually yield the best pumping strategy for complicated problems