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Terrestrial hydrological and nutrient cycles are subjected to major disturbances by agricultural operations and urbanization that profoundly influence freshwater resources. Non‐point source pollution is one of the primary causes for water quality deterioration, and thus an emerging imperative in limnology is establishing empirical models that connect watershed attributes and hydrological drivers with lake nutrient dynamics. Here, we compiled three nation‐wide nutrient, meteorological, and watershed‐landscape data sets, to develop Generalized Linear Models that predict lake phosphorus and nitrogen concentrations as a function of the surrounding watershed characteristics within various hydrological distances across 104 Chinese lakes and reservoirs. Our national‐scale investigation revealed that lake nutrient concentrations can be satisfactorily predicted by proxies of natural drivers and anthropogenic activities, reflecting the properties of the surrounding watershed. Counter to previous studies, we found that China's lake nutrient concentrations strongly depend on watershed characteristics within a hydrological distance of less than 45 km rather than the entire watershed. Furthermore, extensive human activities in watersheds not only compromise our predictive capacity, but also increase the hydrological distance that is relevant to predict lake nutrients. This national‐scale characterization can inform one of the most contentious issues in the context of China's lake management, that is, the determination of the extent of the nearshore area, where nutrient control should be prioritized. As far as we know, our study represents the first attempt to apply the concept of hydrological distance and establish statistical models that can delineate the critical spatial domain primarily responsible for the nutrient conditions along the watershed‐lake continuum. Plain Language Summary: Connecting watershed attributes with lake water quality at multiple scales is an emerging imperative in limnology. This study introduces the concept of hydrological distance and establish lake‐watershed relationships based on a comprehensive water quality data set from 2,424 sampling sites across China. Our key finding is that lake nutrient levels strongly depend on watershed features within a <45 km hydrological distance rather than the entire watershed. Activities related to agriculture and urbanization increase the relevant hydrological distance to modulate lake nutrient levels, and our national‐scale analysis provides evidence that areas with discernible impact can be located far from the vicinity of a given lake. Key Points: China's lake nutrient concentrations can be accurately predicted by watershed attributesChina's lake nutrient levels depended on watershed features within a <45 km hydrological distanceHuman footprint increases the relevant hydrological distance to predict water quality for China's lakes [ABSTRACT FROM AUTHOR]

The expanding cropland profoundly affects stream water quality. However, the relationships between landscape patterns and stream water quality in different cropland composition classes remain unclear. We observed total nitrogen (TN), total phosphorus (TP) concentrations, and landscape patterns changed in 78 sub-watersheds of the Taihu Lake Basin's Jiangsu segment from 2005 to 2020. The results showed that cropland area was positively correlated with TN and TP concentrations. The 21.10% reduction in cropland area, coupled with a 41.00% increase in building land, has led to an escalation in cropland fragmentation. Meanwhile, TN and TP concentrations declined by 26.67% and 28.57%, respectively. Partial least squares suggested that forest interspersion and juxtaposition metrics and forest area percentage were dominant factors influencing water quality in high- and medium-density cropland zones, respectively. The Cellular Automata–Markov Model shows reasonable distribution of forests. Scenarios with enhanced forest interspersion and juxtaposition metrics (75.28 to 91.12) showed reductions in TP (26.92% to 34.61%) and TN (18.45% to 25.89%) concentrations by 2025 compared to a natural economic development scenario. Landscape configuration optimization could assist managers in improving water quality. [ABSTRACT FROM AUTHOR]