PyCHAMP:用于地下水管理的作物-水文-代理建模平台

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

摘要

作物-水文-代理建模平台(PyCHAMP)是一个基于 Python 的开源软件包,设计用于农业-水文系统建模。它采用模块化设计,包含含水层、作物田、地下水井、金融和行为等组件,使用户能够模拟和分析人类与自然系统之间的相互作用,同时考虑环境和社会经济因素。本研究通过模拟堪萨斯州高原含水层的地下水保护计划 Sheridan 6 地方强化管理区的动态变化,展示了 PyCHAMP 的能力。我们重点介绍了 PyCHAMP 所支持的模型如何准确捕捉人类与水的动态关系,包括地下水位、取水量以及每种作物的耕地比例。我们还展示了农民行为及其代表如何比环境条件更有力地推动系统结果。研究结果表明,PyCHAMP 有潜力成为人水研究和可持续地下水管理的有用工具,并为未来与详细的子模型整合以及对模型结构的不确定性进行系统评估提供了前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PyCHAMP: A crop-hydrological-agent modeling platform for groundwater management

The Crop-Hydrological-Agent Modeling Platform (PyCHAMP) is a Python-based open-source package designed for modeling agro-hydrological systems. The modular design, incorporating aquifer, crop field, groundwater well, finance, and behavior components, enables users to simulate and analyze the interactions between human and natural systems, considering both environmental and socio-economic factors. This study demonstrates PyCHAMP's capabilities by simulating the dynamics in the Sheridan 6 Local Enhanced Management Area, a groundwater conservation program in the High Plains Aquifer in Kansas. We highlight how a model, empowered by PyCHAMP, accurately captures human-water dynamics, including groundwater level, water withdrawal, and the fraction of cropland dedicated to each crop. We also show how farmer behavior, and its representation, drives system outcomes more strongly than environmental conditions. The results indicate PyCHAMP's potential as a useful tool for human-water research and sustainable groundwater management, offering prospects for future integration with detailed sub-models and systematic evaluation of model structural uncertainty.

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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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