HSPEXP+: An Enhanced Expert System for HSPF Model Calibration—A Case Study of the Snake River Watershed in Minnesota

Abstract

The U.S. Geological Survey developed the Expert System (HSPExp) in 1994 to assist modelers in the calibration of Hydrologic Simulation Program-FORTRAN (HSPF) models by calculating statistics, displaying graphs, and recommending parameter adjustments, based on model-data comparisons and several sets of rules. HSPExp has been used extensively since its release; however, HSPExp support was recently discontinued, and the software does not operate reliably on most modern computers. Many organizations have developed software to calculate calibration statistics, but these programs are neither freely available nor open source, which limits their usability by a wide user community. Using the existing open source codebase of Better Assessment Science Integrating Point and Nonpoint Sources (BASINS), RESPEC developed HSPEXP+and released it in February 2015. HSPEXP+replicates most of the functionality of HSPExp, and provides several additional reports and an advanced graphing functionality to assist a modeler in obtaining meaningful insights about the model on an overall basis, as well as on an operation-by-operation basis. This paper presents a case study of the calibration of the Snake River watershed situated in the eastern part of Minnesota. Snake River is a tributary to the St. Croix River at the border of Minnesota and Wisconsin, and drains a watershed of > 2 500 km(2), with multiple lakes. HSPEXP+was used to assist in hydrologic and water quality calibration in the watershed. The hydrologic model resulted in a model fit efficiency of > 0.9 for monthly flow and > 0.8 for daily flow with a mean error < 10% in total volume. The water quality calibration included simulated loading rate comparisons with the target loading rates, and a graphical comparisons of instream observed and simulated data. The Snake River watershed model was satisfactory based on quantitative and graphical comparisons, and the model can be used for TMDL development.