PyMTRD:用于计算时间降雨分布指标的 Python 软件包

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2024-09-01 DOI:10.1016/j.envsoft.2024.106201
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引用次数: 0

摘要

时间降雨分布有助于了解不同时间尺度的降雨模式、极端事件以及相应的水资源影响。研究人员已经开发了各种时间降雨分布指标,但目前还没有易于使用的软件包来计算这些指标。为了弥补这一空白,我们开发了 PyMTRD 软件包,可方便地用于计算时间降雨分布指标和进行降雨模式分析。该软件包计算的指标包括降雨强度、降雨频率、连续干旱日、基尼系数、无等级基尼系数、湿日基尼系数、降水集中指数、无量纲季节性指数和季节性指数。本文记录了我们的 Python 软件开发过程,包括架构设计、应用编程接口设计、计算每个指标的算法,以及点和全球范围的应用。
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PyMTRD: A Python package for calculating the metrics of temporal rainfall distribution

Temporal rainfall distribution facilitates the understanding of rainfall patterns at various time scales, extreme events, and corresponding water resources implications. Researchers have developed various metrics of temporal rainfall distribution but there exist no easy-to-use software packages for calculating these metrics. To address this gap, we developed the PyMTRD package, which can be conveniently used to calculate the metrics of temporal rainfall distribution and conduct rainfall pattern analysis. The metrics calculated in the package included rainfall intensity, rainfall frequency, consecutive dry days, Gini index, unranked Gini index, wet-day Gini index, precipitation concentration index, dimensionless seasonality index, and seasonality index. This paper documented our Python software development, which included the architecture design, the Application Programming Interfaces design and algorithms for calculating each metric, and also the point and global scale applications.

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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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