LAUSR

Abstract Simple models can help reduce nitrogen (N) loss from land and protect water quality. However, the complexity of primary production systems may impair the accuracy of simple models. A tool was developed that assessed the risk of N loss as the product of N source inputs and relative transport by leaching and runoff. A dynamic process‐based model was used to estimate the long‐term monthly N loss risk by leaching and runoff in response to the interaction of static biophysical factors like soil type, slope, and long‐term climate. Source inputs included dung and urine (from livestock), fertilizer, crop residues, and soil erosion. Estimates of the rank of N loss risk were related (r 2 = 0.69, p < 0.001) to 96 observations of N loss (kg ha−1 year−1) across nine land uses; all but two of the observations fell within 95% prediction intervals. Across land uses, leaching accounted for 84% of N loss risk. Additional observations are needed to determine if N loss risk is representative of short‐rotation vegetables and to account for potential lag times between calculated and measured losses. The good performance of the tool suggests that when displayed spatially, the tool can be used to target high‐risk areas with actions to reduce the risk of N loss and the likelihood of water quality impairment.