To illustrate the efficiency and effectiveness of the EC, we provide studies arising in a couple of complex molecular simulation systems. The first simulation system is the measurement of hydrophobicity on the surface of 2D self-assembled monolayers (SAMs), and the second system is the analysis of 3D solvation effects on acid-catalyzed reactions systems for biomass processing. Previous work suggests that the topology and geometry of water plays a critical role in understanding and predicting emergent physical and chemical properties for both of these systems. Thus, in both examples, we are focused on quantifying the topological structures and patterns emerging from solvent behavior at the surface of a SAM and around biomass-relevant reactants to quantify hydrophobicity and reactivity, respectively. We also show that the EC can be used to quantify different forms of data representations typically used in these types of MD simulations (hydrogen bond networks and density fields). Specifically, we show that the EC is a descriptor that correlates strongly with emergent properties and this enables the construction of lowdimensional and effective predictive models that are significantly more computationally tractable than recently-developed ML models such as CNNs. We show that simple regression models that take the EC as input are able to accurately predict the hydration free energy of simulated 2D SAMs and the change in reactivity due to solvation effects in acid-catalyzed reaction systems. These studies also illustrate the stability of the EC in quantifying noisy MD data and the physical intuition that can be gained through topological analysis. Moreover, we show that the EC can be used to monitor the dynamic evolution of topology in these MD systems which can be used, for instance, to determine when a system has achieved a topological steady-state. We also note that solvent-rich processes (like those studied here) are common in a diverse range of systems analyzed through MD, further supporting the general relevance of these methods. All code and data needed for reproducing our results are provided.