Phase II – A Software Platform for Generation of Mutually Correlated Multi-Dimensional Stochastic Time Series Vectors

The project is aimed to establish and algorithm and computer software for generation of multiple time series of data which represent processes that are closely correlated and auto-correlated (i.e. data in time step i are correlated to the data in time steps i-1, i-2,i-3, etc.). This project is of significant importance to the company.  It represents significant improvement of our earlier developments in this field.  While this kind of algorithm has possible applications in many industries, our immediate interest is are application in the water resources sector, where this algorithm and the accompanying software would be able to generate stochastic hydrologic time series of hypothetical natural river flows for thousands of years  There is neither a universally recognized algorithm for generation of stochastic hydrologic time series that can meet all the needs in the water resources sector at present, nor is there a software package that could be used to achieve this. Use of stochastic hydrology is an important link in the process of studying river basin development and management, where stochastic hydrologic series are used as inputs into basin allocation studies that rely in the use of optimization algorithms, and the results of optimization studies are then reused is inputs into operational management tools.

Ognjen Sobajic
Faculty Supervisor: 
Dr. Mahmood Moussavi