To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter (DOM) in typical rivers, this study conducted a multi-spectral investigation on three representative river types within Shandong Province: The mountainous Dawen River, the plain Tuhai River, and the artificial East Grand Canal. The DOM composition was analyzed using Ultraviolet-Visible (UV-Vis) absorption spectroscopy, Excitation-Emission Matrix (EEM) fluorescence spectroscopy, and parallel factor analysis (PARAFAC), while Principal Component Analysis (PCA) was employed to quantify the synergistic effects of natural processes and anthropogenic activities. Results revealed significant spatial heterogeneity in DOM composition and sources. The plain river exhibited the highest aromaticity (humic-like components: 43.3%) due to long-term agricultural non-point source inputs and urban wastewater discharge. The mountain stream, shaped by complex terrain and relatively intact ecosystems, was dominated by autochthonous DOM derived from microbial metabolism, with higher Fluorescence Index (FI = 2.12) and biological index (BIX = 1.35) than other river types. The artificial canal retained protein-like components (64.2%), largely attributed to winter hydrological stagnation and disturbances from shipping activities. Further analysis demonstrated that geographical settings (e.g., mountain terrain) and anthropogenic activities (e.g., agriculture, shipping) jointly regulated DOM composition by altering the balance between input and transformation processes. Integrated fluorescence parameters and PCA results suggested differentiated management strategies: protecting ecological integrity in mountain streams to sustain self-purification, enhancing non-point source interception in plain rivers, and mitigating shipping pollution in canals. This study systematically reveals the natural-anthropogenic coupling mechanisms driving DOM dynamics in northern China rivers, providing critical insights for precision water environment management at the watershed scale.