AMPSOM: A measureable pool soil organic carbon and nitrogen model for arable cropping systems

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2025-02-01 DOI:10.1016/j.envsoft.2024.106291
Inès Astrid Tougma , Marijn Van de Broek , Johan Six , Thomas Gaiser , Maire Holz , Isabel Zentgraf , Heidi Webber
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Abstract

Most cropping system models simulate conceptual soil organic matter (SOM) pools, such as active, passive and slow pools that cannot be measured, complicating model calibration. In reality, SOM can be described in terms of quantifiable pools of particulate organic matter (POM) and mineral-associated organic matter (MAOM) which respond differently to management and climate. We present the AMPSOM model, integrated in a cropping system modelling framework (SIMPLACE). AMPSOM simulates carbon and nitrogen dynamics in MAOM and POM in response to crop growth and management, as well as soil texture, water and nitrogen content and temperature. It also simulates the radiocarbon isotope (14C) of soil organic carbon (SOC) to constrain the turnover time of slowly cycling SOC pools. Model calibration and evaluation were performed for thirty six sandy and loamy arable soils in Brandenburg, Germany. Results show that AMPSOM can reproduce observed patterns of SOC and nitrogen stocks in POM and MAOM along depth profiles across different soil types.
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一个可测量的耕地种植系统土壤有机碳和氮模型
大多数种植系统模型模拟的是概念土壤有机质(SOM)库,如无法测量的主动、被动和缓慢库,使模型校准复杂化。在现实中,SOM可以用可量化的颗粒有机质(POM)和矿物相关有机质(MAOM)池来描述,它们对管理和气候的响应不同。我们提出了集成在种植系统建模框架(SIMPLACE)中的AMPSOM模型。AMPSOM模拟MAOM和POM中碳氮动态,以响应作物生长和管理,以及土壤质地,水氮含量和温度。模拟土壤有机碳(SOC)的放射性碳同位素(14C),以约束缓慢循环的有机碳库的周转时间。对德国勃兰登堡地区36种沙质和壤土进行了模型标定和评价。结果表明,AMPSOM能沿不同土壤类型重现POM和MAOM土壤有机碳和氮储量的分布规律。
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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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