Efficient and Robust Prediction at Ungauged Catchments

水文模型是在集水区尺度上形成的几乎所有环境模型的组成部分。它们用于规划、设计和运营水利基础设施。尽管这些模型很重要，但有限的降雨量和径流测量迫使这些模型例行公事地应用于对预报能力了解较少且几乎总是不令人满意的未经测量的地点。该项目将通过提供(A)量化不确定性的可靠框架和(B)改进对未测量流域的预测而使模型用户直接受益。这将为设计工程师和政策制定者提供更现实的指导，并对澳大利亚的大范围用水用户有重大好处。

Hydrological models are an integral part of virtually all environmental models formulated at the catchment scale. They are used in the planning, design and operation of water infrastructure. Despite the importance of these models limited rainfall and streamflow gauging forces these models to be routinely applied at ungauged locations where predictive power is poorly understood and almost always unsatisfactory. This project will directly benefit model users by providing (a) robust framework for quantifying uncertainty and (b) improved predictions at ungauged basins. This will provide more realistic guidance for design engineers and policy makers and be of significant benefit to a large range of Australian water users.