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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publication #377015

Research Project: Resilient Management Systems and Decision Support Tools to Optimize Agricultural Production and Watershed Responses from Field to National Scale

Location: Grassland Soil and Water Research Laboratory

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

Author
item GAO, JUNGANG - TEXAS AGRILIFE RESEARCH
item White, Michael
item BIEGER, KATRIN - TEXAS AGRILIFE RESEARCH
item Arnold, Jeffrey

Submitted to: Environmental Modelling & Software
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/6/2020
Publication Date: 1/1/2021
Citation: Gao, J., White, M.J., Bieger, K., Arnold, J.G. 2021. Design and development of a python-based interface for processing massive data with the LOAD ESTimator (LOADEST). Environmental Modelling & Software. 135. Article 104897. https://doi.org/10.1016/j.envsoft.2020.104897.
DOI: https://doi.org/10.1016/j.envsoft.2020.104897

Interpretive Summary: LOADEST is a program for estimating constituent loads in rivers and streams at a single site developed by the U.S. Geological Survey (USGS). In this work we describe the development and application of LOAD ESTimation (LOADEST) Parallel Data Processing Interface (LPDPI) an interface that allows the LOADEST to be applied at many sites with parallel processing. LPDPI has modules to facilitate additional data analysis and fix common errors. The tool is a standalone executable for Windows and can be readily used without any additional packages or software installation.

Technical 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 a Graphical User Interface (GUI) that facilitates processing of large amounts of data. Therefore, we present the LOAD ESTimation (LOADEST) Parallel Data Processing Interface (LPDPI). LPDPI is unique as it features an easy-to-use workflow for data download and water quality estimations for numerous stations and multiple constituents and is readily applicable to any station with both flow and water quality data available. LPDPI incorporates a parallel module for faster load estimation and can identify and fix errors that occur while running LOADEST by adjusting calibration and estimation data inputs. LPDPI also includes an extension to extract and filter LOADEST output to facilitate further data analysis and use of the data to calibrate hydrologic models. The tool is a standalone executable for Windows and can be readily used without any additional packages or software installation.