Name: Junxiao Wang
Date: 07/31/2026
Time (EST/EDT): 10:30 am
Location: CBL Nice Hall
Remote Access: email: mees@umd.edu

Committee Chair: Hongsheng Bi
Committee Members: Jian Zhao; Vyacheslav Lyubchich

Title: Spatiotemporal Salinity Dynamics in the Patuxent River: Governing Factors and Reconstruction Using Boundary Conditions

Abstract: Estuarine salinity integrates freshwater forcing, marine boundary conditions, mixing, and channel geometry, but these controls are often expressed unevenly along the estuarine gradient. This thesis examines salinity variability and its governing factors in the Patuxent River estuary and tests whether a machine-learning extension can improve a reduced-complexity physical framework. Chapter 2 shows that Patuxent salinity is organized by station-specific seasonal climatology rather than a single estuary-wide signal. Reduced-complexity model quantifies the contribution of flow and boundary salinity, while counterfactual and cross-sectional diagnostics identify a transition area where freshwater influence is filtered by geometry change. Chapter 3 applies a multilayer perceptron (MLP) to raw station-day observations. The MLP improves aggregate prediction and adds the most value in the upper-transition reach, especially under high- and low-flow conditions and representative stress-test years. Overall, the thesis shows that physical interpretation and predictive skill both depend on resolving the spatiotemporal structure of the estuary’s salinity variability.