Topography fundamentally regulates how ecosystems access and redistribute water and energy, thereby shaping spatial patterns of vegetation productivity, soil carbon, and nutrient dynamics. Despite its recognized importance, the influence of topography on the spatial heterogeneity of coupled water and carbon processes remains poorly quantified. This is largely because real landscapes confound terrain effects with variability in climate, soil, and vegetation, and because many existing models treat ecohydrological and biogeochemical processes in a decoupled manner. Here, we isolate and quantify the role of terrain complexity by combining synthetic landscapes of varying geomorphic complexity – generated using a landscape evolution model – with meteorological forcings and land cover data from six FLUXNET sites spanning diverse biomes. Using the state-of-the-art, spatially distributed, ecohydrological model T&C-BG-2D, we simulate the distributions of evapotranspiration (ET), gross primary productivity (GPP), and soil organic carbon (SOC) across these landscapes. We find that, on average, ET and GPP decrease as terrain becomes more complex, reflecting enhanced hydrological redistribution and energy limitation. In contrast, SOC exhibits two contrasting response modes that depend on soil texture and hydroclimatic regime, highlighting the interactions between topography-driven processes and local biogeochemical controls. The spatial distributions of ET, GPP, and SOC are well described by lognormal and mixture-lognormal forms, whose shape parameters scale systematically with catchment-scale terrain complexity. An independent analysis of satellite-derived GPP and ET across three different biomes confirms that similar scaling relationships emerge in real landscapes, demonstrating that topography imposes a consistent and measurable constraint on ecohydrological variability. Together, these results provide a physically based framework linking terrain complexity to the spatial organization of coupled water and carbon processes, and offer quantitative guidance for the development of topography-aware parameterizations in large-scale land surface and Earth system models.