Sediment management is costly and critical for managing ecosystems and flood risks, especially in the context of sea-level rise. The field of civil and environmental engineering has numerous models to describe sediment transport and morphology based on hydrodynamics and sediment characteristics. Despite this, multi-decadal predictions of sediment transport are difficult due to stochasticity of environmental systems and uncertainty in future anthropogenic influences such as land-use changes and dredging. Accurately predicting sediment transport is important for coastal and sediment management, especially within urban regions. This dissertation seeks to address sediment management challenges through cross disciplinary research by developing a set of models and tools in response to stakeholder needs in an urban region (Southern California) experiencing numerous sediment management challenges. The second chapter of this dissertation focuses on developing a stochastic hydro-financial model to evaluate the risk of an enviro-financial instrument known as an Environmental Impact Bond (EIB). The model and EIB are applied to address excessive sedimentation resulting in negative environmental and financial outcomes in a transnational setting, the US-Mexico Border. The risk is then tied to an ``environmental interest rate'' which can then be used to reward investors for taking on additional environmental risk, as they would with traditional financial instruments. Chapter 3 of this dissertation develops a stochastic model of estuarine basin deposition using a response surface surrogate model trained using output from a high-fidelity hydromorphodynamic model (Delft3D). The advantages of the surrogate model is a reduction in computational time by multiple orders of magnitude, facilitating stochastic simulation of basin response to multiple model forcing and management scenarios, thereby improving the information available to estuarine managers. Finally, the fourth chapter of the dissertation utilizes a synthetic future forcing taken from a stochastic model to simulate future marsh surfaces utilizing a one-way coupling between a hydromorphodynamic (Delft3D) and marsh accretion model (WARMER) to better describe step changes in marsh surface elevations in ephemeral estuarine systems. This method is quantitatively compared to existing methods and applied to an urban estuary (Upper Newport Bay in Southern California) to evaluate the impacts of SLR on surface elevations and potential habitat suitability through 2100.