Any engineering books on control theory and signal processing is systems theory using mathematics such as linear algebra, differential equations, etc. The reason why books like Meadow’s are so light on the math is that there is already a large body of works that use the mathematics. Books light on the math are meant to accessibly extend the philosophy to those who may feel they do not have the proper math background.

“Modern Control Theory” by Katsuhiko Ogata applies the theory to thermal systems, fluid systems, mechanical, electrical, etc.

“Discrete-Time Signal Processing” by Alan V. Oppenheim is a great book on its subject.

Both are related to analytical approaches to systems thinking.

Mathematics is definitely a weakness I feel acutely as I press up against the boundary between knowing-about and knowing-how-to-do.

I'd say the next book to read in a formal direction is Hartmut Bossel's Systems and Models, which happily dives into the calculus. Then, as my sibling comment explains, control theory, signal processing and information theory are major influences on various branches of systems thought (systems dynamics, cybernetics and so on).

That said, as Sterman points out, many interesting problems can't be solved analytically and require simulation in order to come up with useful approximations. Furthermore a page of sigils is comprehensible to relatively few people: a systems model is useful only insofar as people will believe its descriptive, predictive and prescriptive qualities. If they don't understand it, they won't trust it and will ultimately ignore it.

Systems dynamics and other simulation approaches (particularly discrete event simulation and agent-based modelling) are much easier to explain and verify qualitatively with subject-matter experts and end users.

Definitely read Sterman first, nobody else has such a thorough treatment of the field.