Lake chlorophyll-a linked to upstream nutrients across the CONUS

Abstract Chlorophyll-a (Chl-a) is a commonly used proxy for algal biomass within surface waters, which can be indicative of harmful algal blooms. Excess nutrients, such as nitrogen or phosphorus, promote Chl-a production, often leading to eutrophication. However, little research exists on river nutrients-to-downstream lake Chl-a linkages at large watershed scales and across disparate climatic and physiographic regions. We found a significant positive relationship between measured total nitrogen (TN) and total phosphorous (TP) concentrations in upstream rivers and Chl-a concentrations in downstream lakes at the watershed scale (average area = 99.8 km²[35.8-628.6 km²], n = 254) throughout the conterminous United States (CONUS). Additionally, through random forest machine learning models, we demonstrate that a small number of explanatory variables (2-3 per model) can accurately predict (71%-83% accuracy) classifications of high or low riverine TN, TP, or lake Chl-a concentrations throughout the CONUS at the watershed scale. The most important model variables were vegetation type, runoff, tile drainage, temperature, and nitrogen inputs. This work supports the hypothesis that rivers supply nutrients that enhance Chl-a concentrations in downstream lakes and demonstrates the power of parsimonious models to elucidate primary landscape factors related to nutrient concentrations and algal blooms across the CONUS. Synopsis River nutrient concentrations are positively correlated with downstream lake chlorophyll-a and each can be effectively predicted by parsimonious models.