Uncertainty quantification in terrestrial hydrologic systems

该项目旨在开发一个框架，通过近似贝叶斯计算来模拟、量化和分析径流和植被动力学中的不确定性。水是基础性资源，如何在变化的环境中做出预测是水资源管理中的一个难点。由于观测和模型误差，自然系统预测中的不确定性使这一点变得更加困难。预计该项目的结果将推进水文学中的不确定度分析，并有助于理解不同类型的数据和信息如何为模型特征提供信息。这将有助于提供有关不确定性的属性和程度的重要信息，为水资源分析、管理和决策提供信息。

This project aims to develop a framework to simulate, quantify and analyse the uncertainty in streamflow and vegetation dynamics via approximate Bayesian computation. Water is a fundamental resource, and a difficulty in water resource management is to make predictions in a changing environment. Uncertainties in predictions of natural systems due to observational and model error make this more difficult. It is anticipated that the results from this project will advance uncertainty analysis in hydrology and help understand how different types of data and information can inform model characterisation. This will be useful in providing vital information on the attributes and extent of uncertainty to inform water resources analysis, management and decision making.