The existence of lowland ponds alter watershed nitrogen (N) cycles via combined changes in runoff and N processing potential, which can significantly buffer watershed N transport. Here, we adopt the conceptual framework of the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model to describe N transport and explore the buffering roles of lowland ponds in a small headwater watershed of Taihu Lake Basin, China. Our model, which included variables for nutrient sources, riverine length, precipitation and pond density, explained 95% of the spatio-temporal variability in total N loads. Results indicated that the northern parts of this watershed were hotspot regions, which contributed relatively large N yields. While their contributions have high temporal variations, they depend upon local precipitation rates. The model results also revealed important processes of landscape N retention. On average, approximately 87% of terrestrial N inputs were removed via denitrification, plant uptake, and other processes or retained in the subsurface during land-to-water delivery. This amount can be further differentiated into 12% retained by lowland ponds and the remaining 75% associated with other landscapes including nutrient storage in soils and groundwater, as a legacy of historical inputs. By contrast, in-stream retention processes only removed 3% of the total terrestrial N inputs. In the future, riverine N pollution will likely be exacerbated by releases from legacy storage and intensified human activities, especially as climate change is expected to enhance extreme rainfall conditions. An integrated N management strategy that appropriately considers the buffering roles of lowland ponds and other landscapes, is required to optimize N fertilizer inputs and protect precious headwater resources.
Keywords: Headwater; Lake Taihu; Lowland pond; Nitrogen retention; Water quality.
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