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Article

Hydrostats: A Python Package for Characterizing Errors between Observed and Predicted Time Series

Department of Civil and Environmental Engineering, Brigham Young University, Provo, UT 84602, USA
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Hydrology 2018, 5(4), 66; https://doi.org/10.3390/hydrology5040066
Received: 30 September 2018 / Revised: 26 November 2018 / Accepted: 29 November 2018 / Published: 2 December 2018
Hydrologists use a number of tools to compare model results to observed flows. These include tools to pre-process the data, data frames to store and access data, visualization and plotting routines, error metrics for single realizations, and ensemble metrics for stochastic realizations to calibrate and evaluate hydrologic models. We present an open-source Python package to help characterize predicted and observed hydrologic time series data called hydrostats which has three main capabilities: Data storage and retrieval based on the Python Data Analysis Library (pandas), visualization and plotting routines using Matplotlib, and a metrics library that currently contains routines to compute over 70 different error metrics and routines for ensemble forecast skill scores. Hydrostats data storage and retrieval functions allow hydrologists to easily compare all, or portions of, a time series. For example, it makes it easy to compare observed and modeled data only during April over a 30-year period. The package includes literature references, explanations, examples, and source code. In this note, we introduce the hydrostats package, provide short examples of the various capabilities, and provide some background on programming issues and practices. The hydrostats package provides a range of tools to make characterizing and analyzing model data easy and efficient. The electronic supplement provides working hydrostats examples. View Full-Text
Keywords: hydrology; water resource engineering; Python; error metrics; statistics; predicted and observed flows hydrology; water resource engineering; Python; error metrics; statistics; predicted and observed flows
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MDPI and ACS Style

Roberts, W.; Williams, G.P.; Jackson, E.; Nelson, E.J.; Ames, D.P. Hydrostats: A Python Package for Characterizing Errors between Observed and Predicted Time Series. Hydrology 2018, 5, 66. https://doi.org/10.3390/hydrology5040066

AMA Style

Roberts W, Williams GP, Jackson E, Nelson EJ, Ames DP. Hydrostats: A Python Package for Characterizing Errors between Observed and Predicted Time Series. Hydrology. 2018; 5(4):66. https://doi.org/10.3390/hydrology5040066

Chicago/Turabian Style

Roberts, Wade, Gustavious P. Williams, Elise Jackson, E. J. Nelson, and Daniel P. Ames 2018. "Hydrostats: A Python Package for Characterizing Errors between Observed and Predicted Time Series" Hydrology 5, no. 4: 66. https://doi.org/10.3390/hydrology5040066

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