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Ensemble projections of hydro-biogeochemical fluxes under climate change

气候变化下水文生物地球化学通量的集合预测

基本信息

批准号：
65984298
负责人：
Professor Dr. Lutz Breuer
金额：
--
依托单位：
Institut für Geographie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2008
资助国家：
德国
起止时间：
2007-12-31 至 2017-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/65984298?language=en
关键词：
Ensemble projections hydro biogeochemical fluxes

项目摘要

Uncertainty estimation in hydro-biogeochemical modeling is an ongoing area of research that focuses primarily on the investigation of stochastic model uncertainty. The evaluation of structural model uncertainty remains unusual, however there are various techniques available to quantify structural uncertainty. Ensemble modeling is one such technique that is commonly used in climatology and meteorology; disciplines where the structural uncertainty of predictive models has long been established. Its application in hydrological modeling is, however, much less common. Here we propose to evaluate structural uncertainty through *P ensemble modeling, using a set of four models to predict hydrological and nitrogen fluxes: SWAT, LASCAM, HBV-N and CMF-N. The models were selected to represent the range of complexity found in catchment scale modeling, from conceptual models to physically-based approaches, and from lumped to fully distributed descriptions. The GLUE concept is applied to quantify parameter uncertainty. This approach leads to the formulation of single-model ensembles. These single-model ensembles are then combined to produce different sets of probabilistic and deterministic multi-model ensembles. These multi-model ensembles are used to quantify the contribution of structural errors to overall predictive uncertainty. The development of conditional multi-model ensembles represents a large component of the work plan. In this case, the selection of the multi-model ensemble members is based on the capability of different model structures and parameterizations to capture certain conditions of the investigated catchments such as high-low flow, freeze-thaw cycles, or rewetting after extended droughts. The ensemble model is applied to German, Swedish and Australian catchments, and covers a broad range of different climatic boundary conditions, land uses and levels of anthropogenic disturbances.

水文生物地球化学模拟中的不确定性估计是一个正在进行的研究领域，主要侧重于随机模型不确定性的研究。结构模型不确定性的评估仍然不常见，但是有各种技术可用于量化结构不确定性。集合建模就是一种这样的技术，通常用于气候学和气象学；预测模型的结构不确定性早已建立的学科。然而，它在水文建模中的应用要少得多。本文提出通过*P集合模型评估结构不确定性，使用SWAT、LASCAM、HBV-N和CMF-N四种模型来预测水文和氮通量。选择的模型代表了流域尺度建模的复杂性范围，从概念模型到基于物理的方法，从集中描述到完全分布式描述。采用GLUE概念对参数不确定度进行量化。这种方法导致了单模型系综的形成。然后将这些单模型集成组合成不同的概率和确定性多模型集成集。这些多模型集成用于量化结构误差对整体预测不确定性的贡献。条件多模型集成的发展是工作计划的一个重要组成部分。在这种情况下，多模型集合成员的选择是基于不同模型结构和参数化的能力来捕捉所调查流域的某些条件，如高低流量、冻融循环或长期干旱后的再湿润。该综合模型适用于德国、瑞典和澳大利亚的集水区，涵盖了广泛的不同气候边界条件、土地利用和人为干扰水平。