About Me

I am the Senior Water Resources Engineer & Solution Lead at GoldSim Technology Group. With a background in Civil & Environmental Engineering (BS from Brigham Young University, MS from University of Utah), I spent the early part of my career in traditional infrastructure consulting at CH2M HILL.

For the last 15 years, I have focused on the cutting edge of the industry: advanced dynamic simulation and stochastic modeling. I specialize in helping engineers build robust decision support models for Integrated Water Management, with a specific focus on climate change forecasting and tool development.

Currently, I work on integrating system dynamics with modern data science tools (including Python) to solve complex problems under uncertainty. On this blog, I share technical insights to assist other water resources engineers in mastering these tools.

Find me on LinkedIn: Jason Lillywhite

Popular posts from this blog

Simulation of Reservoir System Operations

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Introduction Reservoir storage is necessary to regulate highly variable water flows for more constant uses such as municipal and industrial water supply, irrigation, hydroelectric power generation, and navigation. Typically, the water drawn from a reservoir is used at a much slower (and constant) rate than the rate and consistency of the water flowing into the reservoir (see Figure 1). Reservoir modeling has typically been employed to help size reservoir storage capacities, establishing operating policies, evaluating operating plans, administering water allocations, developing management strategies, and real-time operations. Figure 1 - Inflow and Outflow Hydrograph The basic requirement for adequate representation of a reservoir is employment of the continuity equation, or conservation of volume over a period of time. This is a function that interacts dynamically with the current state of the reservoir. The foundational equation for conservation of volume is: The term “Res...
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Data Management and Analysis

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An important element of IWRM modeling is management and processing of data. Data is the fundamental key to a successful representation of a system. Without proper data representation, the model is lost. I decided to do a quick search to see what people are using today. Doing simple Google searches on the various tools, I found HEC-DSSVue and Hydstra to be the most popular (assuming Internet search returns is a measure of popularity). Here are the search results: HEC-DSSVue => 320 unique results Hydstra => 390 unique results Aquarius => 100 unique results In looking at scholarly documents online, I was able to compare the 3 tools (shown above) by counting the different kinds of models these were used for. HEC-DSSVue seems to have been used most often for water resources and flood modeling, Aquarius for water resources and operations models, and Hydstra for water quality and runoff models. Table 1 summarizes the results from this comparison. As part of my research, I p...
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Modular Systems Modeling

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It is necessary to study not only parts and processes in isolation, but also to solve the decisive problems found in the organization and order unifying them, resulting from dynamic interaction of parts, and making the behavior of parts different when studied in isolation or within the whole. Systems Modular systems modeling is an approach to modeling that can be very useful for applications in integrated water resources management because of its inherent structure and organization. Every system is designed to achieve some objective. A system is made up of a network of interrelated components, which may consist of data, data processors, reporting elements, and subsystems. The term "Systems Modeling" was introduced in the early 1960's and became famous shortly after the birth of FORTRAN. Since that time, it grew steadily in popularity until finally plateauing in the year 2000. The term "Systems Approach" peaked in 1975 and has since been on a steady decline...
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