Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria

Abstract

Performance measures (PMs) and corresponding performance evaluation criteria (PEC) are important aspects of calibrating and validating hydrologic and water quality models and should be updated with advances in modeling science. We synthesized PMs and PEC from a previous special collection, performed a meta-analysis of performance data reported in recent peer-reviewed literature for three widely published watershed-scale models (SWAT, HSPF, WARMF), and one field-scale model (ADAPT), and provided guidelines for model performance evaluation. Based on the synthesis, meta-analysis, and personal modeling experiences, we recommend coefficient of determination (R2; in conjunction with gradient and intercept of the corresponding regression line), Nash Sutcliffe efficiency (NSE), index of agreement (d), root mean square error (RMSE; alongside the ratio of RMSE and standard deviation of measured data, RSR), percent bias (PBIAS), and several graphical PMs to evaluate model performance. We recommend that model performance can be judged satisfactory for flow simulations if monthly R2 > 0.70 and d > 0.75 for field-scale models, and daily, monthly, or annual R2 > 0.60, NSE > 0.50, and PBIAS ? 15% for watershed-scale models. Model performance at the watershed scale can be evaluated as satisfactory if monthly R2 > 0.40 and NSE > 0.45 and daily, monthly, or annual PBIAS ? 20% for sediment; monthly R2 > 0.40 and NSE > 0.35 and daily, monthly, or annual PBIAS ? 30% for phosphorus (P); and monthly…