Design and development of a Python-based interface for processing massive data with the LOAD ESTimator (LOADEST)

Abstract LOADEST is a program for estimating constituent loads in rivers and streams developed by the U.S. Geological Survey (USGS), but it does not have Graphical User Interface (GUI) that facilitates processing of large amounts data. Therefore, we present LOAD ESTimation (LOADEST) Parallel Data Processing (LPDPI). LPDPI unique as features an easy-to-use workflow data download water quality estimations numerous stations multiple constituents readily applicable to any station with both flow available. incorporates parallel module faster load estimation can identify fix errors occur while running adjusting calibration inputs. also includes extension extract filter output facilitate further analysis use calibrate hydrologic models. The tool standalone executable Windows be used without additional packages or software installation.