Ensemble and parameter uncertainty
Models are run across parameter sets and forcing ensembles; the spread is reported as the range, not collapsed to a mean.
GCRI · Water Nexus
面向水模型的不确定性量化
Uncertainty quantification is what makes the evidence honest: every modelled value on this platform carries a range, a label and the assumptions behind it, so a decision-maker can see how much weight it bears.
02申请
What uncertainty quantification and model validation does here.
Uncertainty quantification and model validation characterise how uncertainty in inputs, parameters and model structure affects predictions. They establish how much confidence a model’s outputs deserve. In water, climate and hazards and 关键基础设施, uncertainty quantification shows where risk estimates are robust and where they are fragile. It guides where better data or models would change decisions. The canonical description is on STEM Commons.
Propagation through the cascade
Uncertainty in inflow is carried into storage, generation, treatment and health effects, so the final range reflects every step.
Evidence labelling
Each value is labelled observed, published statistics, modelled, estimated, forecast or unknown, and the label travels with the value into every figure and table.
03部门特征
The sector signature of uncertainty quantification for water models.
The sectors uncertainty quantification for water models touches and how strongly they depend on each other: what a study has to observe and model together.
选择角点 · 悬停连线6 / 15 项关系
签名
水及其合作伙伴
水为粮食提供灌溉（0.8），为能源提供冷却水和水电（0.6），为生物多样性提供环境流量（0.6）。
W · E · I · F · H · B
- 部门
- 4 共 6
- 关系
- 6 共 15
- 耦合
- 0.43 占总量份额
当前最强的关系
- 粮食 → 生物多样性 · 土地转换0.6
- 水 → 能源 · 冷却水与水电0.6
- 水 → 粮食 · 灌溉0.8
- 水 → 生物多样性 · 生态流量0.6
04数据
该方法使用的输入。
Datasets and records used by uncertainty quantification and model validation on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| Model ensembles | Spread and sensitivity | 模型生成 |
| Observation error estimates | Input uncertainty | 估算 |
| 专家意见征询 | Where no data exist | 估算 |
05方法与证据
How uncertainty quantification for water models is modelled, measured and tested.
模型、其假设、数据和不确定性，以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意，不是研究发现。
不确定性区间
How far the outlook for uncertainty quantification for water models could spread, shown as ranges rather than a single line.
- 中心估计值
- 集合的中位数
- 范围
- IPCC 校准用语中的“可能”和“很可能”
- 集合
- 明示成员、情景和初始条件
- 配合阅读
- 结果对每项输入的敏感性
FAIR 指导原则 · GO FAIR 和 FORCE11W3C PROV · 万维网联盟关于一致处理不确定性的指南 · IPCCCEOS 分析就绪数据 · 地球观测卫星委员会
06验证
结果如何核查。
Predictive distributions are tested for calibration and sharpness against held-out observations. Verification confirms that code solves the intended equations.
| 核查 | 如何开展 |
|---|---|
| 敏感性分析 | The inputs that drive most of the output range are identified and reported |
| Calibration of probabilities | Stated probabilities are checked against outcomes where a record exists |
| Label audit | A sample of published values is traced back to the evidence behind its label |
Structural uncertainty and unknown unknowns are difficult to represent. Computational cost limits exploration of high-dimensional models.
07流程
流程如何运行。
Process explorer · Process
Uncertainty quantification for water models: Hazard, exposure, vulnerability
10 steps·4 个阶段
流程
Uncertainty quantification for water models: Hazard, exposure, vulnerability
In IPCC AR6 Working Group II, climate risk results from interactions between hazards and a system’s exposure and vulnerability, and responses can add risk.
01 驱动因素
02 评估
- 05应对措施带来的风险Component · Basin authority当气候应对措施未能实现目标，或因权衡取舍或负面副作用，就会产生来自应对措施的风险。
- 06脆弱性Component · Basin authority易受不利影响的倾向或习性。它包括对伤害的敏感性以及应对与适应能力的缺乏。
- 07风险Model · Water NexusRisk results from dynamic interactions between hazards and the system’s exposure and vulnerability. Each may be uncertain and change.
03 响应
- 08风险管理与响应Step · Basin authority风险管理是指降低不利后果发生的可能性或规模的计划、行动、战略或政策。
- 09剩余风险Record · Basin authority在适应与减缓努力之后仍然存在的气候影响风险。适应可能在地区与群体之间重新分配风险。
04 决定
- 10由责任方作出决定Decision · Basin authority该框架不指定单一决策者。关于应对措施的决定由责任方依据其自身规则作出。
依据公开来源对某一外部标准或方法的概述。它描述的是该框架的内容，而非任何运行记录。它并不表明 Nexus 或任何合作伙伴执行、认证或批准某一步骤。关口是该方法的一个步骤，绝不是 Nexus 的批准。
09管理责任
由谁维护该方法。
系统科学与建模 stewards uncertainty quantification and model validation for the Consortium and reviews how it is applied across platforms.
10已关联
本页在整个联合体中通向何处。
11问题
问题与解答。
What are the limits of uncertainty quantification and model validation in this field?
Structural uncertainty and unknown unknowns are difficult to represent. Computational cost limits exploration of high-dimensional models.
结果如何核查？
Predictive distributions are tested for calibration and sharpness against held-out observations. Verification confirms that code solves the intended equations.
本页面上的数值是真实的吗？
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
该方法还应用于何处？
维持社会运转的 规范方法页面 列出应用该方法的每个平台。
报告贡献
从本页贡献证据。
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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