Chuck Kroll
Hydrology, Water Resources and Ecological Engineering,
Environmental Modeling, Ecosystem Processes and Restoration

Tentative Office Hours for Fall 2018 Semester (Baker 424)

Mondays 9:00 - 10:00

Tuesdays 10:00 - 11:00 and 2:00 - 4:00

or  contact me at






Current and Recent Teaching Duties

APM395/595:  Probability and Statistics for Engineers

Fall Semesters: Next Offered Fall 2018

This course provides a rigorous introduction to calculus-based probability and statistical theory, with applications primarily drawn from engineering and the environmental sciences. Topics include: descriptive statistics and data presentation, probability, the theory and use of discrete and continuous probability distributions, confidence intervals, classical and distributional hypothesis testing, and regression analyses. This course also provides an introduction to the computing package R. 

Prerequisite(s): one year of Calculus.

APM595: This course meets one extra hour a week to provide an introduction to advanced statistical theory and application.  Additional topics covered include: smoothing data, data transformations, random number generation, principal component analyses, first-order error analyses, L-moments, maximum likelihood estimation, parametric and non-parametric trend tests, and censored data analyses. Additional applications in R are explored. 

ERE496: Advanced Engineering Statistics.  Students in APM395 may sign up for an additional 1-credit course that covers the material presented in APM595.

Course Syllabus

ERE445/645:  Hydrologic Modeling

Spring Semesters: Next Offered Spring 2019

Students in this course will learn about a variety of deterministic and stochastic hydrologic models, model development, and the use of computer programming to construct, calibrate, manipulate, and interpret hydrologic models. Theoretical and empirical approaches to describing hydrologic processes will be presented, including precipitation, evapotranspiration, infiltration, surface runoff, percolation, and groundwater discharge. Stochastic techniques presented will include frequency, trend, and regression analyses.

Prerequisite(s): Introductory computer programming, Probability and Statistics, one year of Calculus.

Course Syllabus

ERE496:  Engineering Sustainable Food Systems

Fall Semesters: Next Offered Fall 2019

This course presents an introduction to a wide variety of food system components, and introduces tools to assess the footprint and sustainability of these systems.   The course examines inputs (i.e. agricutural systems), outputs (i.e. nutrition and public health), as well as the myriad of ways in which these systems are connected and interact.   Students are introduced to optimization techniques such as linear programming, data analysis tools such a the R computing package, and system analysis tools such as life cycle analysis.   The culture aspects of food systems are also explored as well as an introduction to the culinary arts.

Course Syllabus

ERE465/665:  Environmental Systems Engineering

Fall Semesters: Next Offered Fall 2018

In this couse, mathematical models of environmental systems are presented and combined with optimization procedures, decision theory, uncertainty analysis, and engineering economics to develop integrated approaches to the planning, design, and sustainable management of complex environmental systems.  Students will evaluate and present a variety of optimization algorithms for a wide range of environmental applications.  Optimization includes constrained and unconstrained linear and nonlinear algorithms, including linear programming, dynamic programming, lagrange multipliers, genetic algorithms, and simulated annealing.