In probability, time is usually handled as a nested sequence of $\sigma$-algebras (say $B_t$, with $B_t \subset B_s$ if $t\leq s$), and to find the reality (call the reality $f$, and it includes the state at all times past and future) at time $t$, one takes the conditional expectation $f_t := E[f | B_t ]$. The sequence $(f_t)$ is then a martingale (a uniformly integrable martingale, more precisely), and this construction is the essence of what the big deal is about martingales.
Brownian motion is a martingale that you've probably heard of, but this also handles simpler situations. For example, consider the experiment: toss a coin repeatedly, and keep track of how many heads you've thrown, minus how many tails. We can capture this experiment in the following way: For $0\leq x <1$, let $f_n(x)$ be the number of 1's minus the number of 0's among the first $n$ digits of the binary expansion of $x$, and let $B_n$ be the $\sigma$-algebra (in this case, a boolean algebra) generated by the intervals $[i/2^n,(i+1)/2^n)$. Then $f_n$ is $B_n$-measurable, and $E[f_t | B_s]=f_s$ for any natural numbers $s < t$, and the sequence $(f_n)_{n=1}^\infty$ is a martingale (albeit different from the type mentioned above). If you want to play any fair game on the "coin tosses" as they come up (allowing use of knowledge of all previous-in-time tosses), then your fortune at time $t$ is still a martingale.
In other words, the passage of time is captured as un-conditional-expectating a function.
For a practical introduction to martingales, I recommend Williams' "Probability with martingales." It is a marvel of writing, and in my humble opinion should be taken as a model for how to write a monograph.
One point of synthetic differential geometry is that, indeed, it is "synthetic" in the spirit of traditional synthetic geometry but refined now from incidence geometry to differential geometry. Hence the name is rather appropriate and in particular highlights that SDG is more than any one of its models, such as those based on formal duals of C-infinity rings ("smooth loci"). Indeed, traditional algebraic geometry with formal schemes is another model for SDG and this is where the origin of the theory lies: William Lawvere was watching Alexander Grothendieck's work and after abstracting the concept of elementary topos from what Grothendieck did with sheaves, he next abstracted the Kock-Lawvere axioms of SDG from what Grothendieck did with infinitesimal extensions, formal schemes and crystals/de Rham spaces. The idea of SDG is to abstract the essence of all these niceties, formulate them in terms of elementary topos theory, and hence lay mathematical foundations for differential geoemtry that are vastly more encompassing than either algebraic geometry or traditional differential geometry alone. For instance there are also models in supergeometry, in complex analytic geometry and in much more exotic versions of "differential calculus" (such as Goodwillie calculus, see below).
Regarding applications, a curious fact that remains little known is that Lawvere, while widely renowned for his work in the foundations of mathematics, has from the very beginning and throughout the decades been directly motivated by, actually, laying foundations for continuum physics. See here for commented list of pointers and citations on that aspects. In particular SDG was from the very beginning intended to formalize mechanics, that's why one of the earliest texts on the topic is titled "Toposes of laws of motion" (referring to SDG toposes).
A little later Lawvere tried another approach to such foundations, not via the KL-axioms this time, but via "axiomatic cohesion". One may recover SDG in axiomatic cohesion in a way that realizes it in close parallel to modern D-geometry with axiomatic de Rham stacks, jet-bundles, D-modules and all. I like to call this differential cohesion but of course it doesn't matter what one calls it.
Viewed from this perspective the scope of models for the SDG axiomatics becomes more powerful still. For instance Goodwille tangent calculus is now also part of the picture, in terms of synthetic tangent cohesion. Another model is in spectral derived geometry that knows about structures of relevance in arithmetic geometry, chromatic homotopy theory and class field theory, this is discussed at differential cohesion and idelic structure.
All this synthetic reasoning is maybe best viewed from the general perspective that it is useful in mathematics to stratify all theory as much as possible by the hierarchy of assumptions and axioms needed, try to prove as much as possible from as little assumptions as necessary and pass to fully concrete models only at the very end. If you are interested only in one specific model, such as derived geometry over $C^\infty$-rings, then such synthetic reasoning may offer some guidance but might otherwise seem superfluous. The power of the synthetic method is in how it allows to pass between models, see their similarities and differences, and prove model-independent theorems. As in "I don’t want you to think all this is theory for the sake of it, or rather for the sake of itself. It’s theory for the sake of other theory." (Lurie, ICM 2010) Synthetic geometry is "inter-geometric", to borrow a term-formation from Mochizuki. If you run into something like the function field analogy then it may be time to step back and ask if such analogy between different flavors of geometry maybe comes from the fact that they all are models for the same set of "synthetic" axioms.
Best Answer
It depends on what you want out of your science!
If you want your relativity theory to include dramatic singularity theorems — then probably you will want excluded middle to prove them.
If you want your economics to use fixed-point theorems with short and conceptual proofs — then probably you will want excluded middle in those proofs.
But if what you want is predictions and calculations within specified error limits, then you won’t need excluded middle to do them: the arithmetic of rationals is decidable.
Similarly in chess, most of the instances of excluded middle that would occur to you will be constructively valid from the finitary nature of the situation.
So you can use examples from mathematical physics or mathematical economics in discussing constructive math. However, the existing modeling practices are diverse enough that they don’t provide a clear and non-circular justification for adopting or abandoning the logical principles at issue.