Suppr超能文献

预测新罕布什尔州哈伯德布鲁克实验森林的酸化恢复情况:四种模型的评估。

Predicting acidification recovery at the Hubbard Brook Experimental Forest, New Hampshire: evaluation of four models.

机构信息

Environmental and Life Sciences, Trent University, 1600 West Bank Drive, Peterborough, Ontario, K9J 7B8, Canada.

出版信息

Environ Sci Technol. 2010 Dec 1;44(23):9003-9. doi: 10.1021/es102243j. Epub 2010 Oct 28.

Abstract

The performance and prediction uncertainty (owing to parameter and structural uncertainties) of four dynamic watershed acidification models (MAGIC, PnET-BGC, SAFE, and VSD) were assessed by systematically applying them to data from the Hubbard Brook Experimental Forest (HBEF), New Hampshire, where long-term records of precipitation and stream chemistry were available. In order to facilitate systematic evaluation, Monte Carlo simulation was used to randomly generate common model input data sets (n = 10,000) from parameter distributions; input data were subsequently translated among models to retain consistency. The model simulations were objectively calibrated against observed data (streamwater: 1963-2004, soil: 1983). The ensemble of calibrated models was used to assess future response of soil and stream chemistry to reduced sulfur deposition at the HBEF. Although both hindcast (1850-1962) and forecast (2005-2100) predictions were qualitatively similar across the four models, the temporal pattern of key indicators of acidification recovery (stream acid neutralizing capacity and soil base saturation) differed substantially. The range in predictions resulted from differences in model structure and their associated posterior parameter distributions. These differences can be accommodated by employing multiple models (ensemble analysis) but have implications for individual model applications.

摘要

采用系统的方法将四种动态流域酸化模型(MAGIC、PnET-BGC、SAFE 和 VSD)应用于新罕布什尔州哈伯布鲁克实验森林(HBEF)的长期降水和溪流化学记录,评估了这四种模型的性能和预测不确定性(由于参数和结构不确定性所致)。为了便于系统评估,采用蒙特卡罗模拟法从参数分布中随机生成常见的模型输入数据集(n = 10,000);随后将输入数据在模型之间转换,以保持一致性。使用校准后的模型集合来评估 HBEF 减少硫沉积对土壤和溪流化学的未来响应。尽管四个模型的后报(1850-1962 年)和预测(2005-2100 年)预测在定性上相似,但酸化恢复的关键指标(溪流酸中和能力和土壤基础饱和度)的时间模式存在显著差异。预测范围是由模型结构及其相关的后验参数分布差异造成的。通过采用多个模型(集合分析)可以解决这些差异,但对单个模型的应用会产生影响。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验