Citation: Qi, J.; Kang, X.; Li, S.; Meng, F. Evaluating Impacts of Detailed Land Use and Management Inputs on the Accuracy and Resolution of SWAT Predictions in an Experimental Watershed. Water 2022, 14, 2352. https://doi.org/10.3390/w14152352 Academic Editor: David Post Received: 6 June 2022 Accepted: 26 July 2022 Published: 29 July 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). water Article Evaluating Impacts of Detailed Land Use and Management Inputs on the Accuracy and Resolution of SWAT Predictions in an Experimental Watershed Junyu Qi 1, *, Xiaoyu Kang 2 , Sheng Li 3 and Fanrui Meng 2 1 Earth System Science Interdisciplinary Center, University of Maryland, 5825 University Research Ct, College Park, MD 20740, USA 2 Faculty of Forestry and Environmental Management, University of New Brunswick, P.O. Box 4400, 28 Dineen Drive, Fredericton, NB E3B 5A3, Canada; xiaoyu.kang@unb.ca (X.K.); fmeng@unb.ca (F.M.) 3 Fredericton Research and Development Centre, Agriculture and Agri-Food Canada, P.O. Box 20280, 95 Innovation Road, Fredericton, NB E3B 4Z7, Canada; sheng.li@agr.gc.ca * Correspondence: junyuqi@umd.edu Abstract: Land use and management practice inputs to the Soil and Water Assessment Tool (SWAT) are critical for evaluating the impact of land use change and best management practices on soil erosion and water quality in watersheds. We developed an algorithm in this study to maximize the usage of land use and management records during the setup of SWAT for a small experimental watershed in New Brunswick, Canada. In the algorithm, hydrologic response units (HRUs) were delineated based on field boundaries and associated with long-term field records. The SWAT model was further calibrated and validated with respect to water flow and sediment and nutrient (nitrate and soluble phosphorus) loadings at the watershed outlet. As a comparison, a baseline version of SWAT was also set up using the conventional way of HRU delineation with limited information on land use and management practices. These two versions of SWAT were compared with respect to input and output resolution and prediction accuracy of monthly and annual water flow and sediment and nutrient loadings. Results show that the SWAT set up with the new method had much higher accuracies in generating annual areas of crops, fertilizer application, tillage operation, flow diversion terraces (FDT), and grassed waterways in the watershed. Compared with the SWAT set up with the conventional method, the SWAT set up with the new method improved the accuracy of predicting monthly sediment loading due to a better representation of FDT in the watershed, and it also successfully estimated the spatial impact of FDT on soil erosion across the watershed. However, there was no definite increase in simulation accuracy in monthly water flow and nutrient loadings with high spatial and temporal management inputs, though monthly nutrient loading simulations were sensitive to management configuration. The annual examination also showed comparable simulation accuracy on water flow and nutrient loadings between the two models. These results indicate that SWAT, although set up with limited land use and management information, is able to provide comparable simulations of water quantity and quality at the watershed outlet, as long as the estimated land use and management practice data can reasonably represent the average land use and management condition of the watershed over the target simulation period. Keywords: distributed hydrological model; best management practices; hydrologic response units; water quality; soil erosion 1. Introduction Aside from field experiments, distributed hydrological models are important tools for assessing the impact of climate change and human interventions on hydrological processes, water resources, and non-point-source pollution [1,2]. These types of models have been used to assess the impact of land use change and best management practices Water 2022, 14, 2352. https://doi.org/10.3390/w14152352 https://www.mdpi.com/journal/water