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Design and development of a Python-based interface for processing massive data with the LOAD ESTimator (LOADEST)
Environmental Modelling & Software ( IF 4.9 ) Pub Date : 2020-10-09 , DOI: 10.1016/j.envsoft.2020.104897
Jungang Gao , Michael J. White , Katrin Bieger , Jeffrey G. Arnold

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.



中文翻译:

设计和开发基于Python的界面,用于使用LOAD ESTimator(LOADEST)处理海量数据

LOADEST是一种由美国地质调查局(USGS)开发的用于估算河流和溪流中的组成负荷的程序,但是它没有可促进处理大量数据的图形用户界面(GUI)。因此,我们提出了LOAD ESTimation(LOADEST)并行数据处理接口(LPDPI)。LPDPI的独特之处在于它具有易于使用的工作流程,可用于众多站点和多个组成部分的数据下载和水质评估,并且可轻松应用于具有流量和水质数据的任何站点。LPDPI包含一个并行模块,可以更快地估算负载,并且可以通过调整校准和估算数据输入来识别和修复在运行LOADEST时发生的错误。LPDPI还包括提取和过滤LOADEST输出的扩展,以促进进一步的数据分析和使用数据校准水文模型。该工具是Windows的独立可执行文件,无需任何其他程序包或软件即可直接使用。

更新日期:2020-10-30
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