Predictions of un-gauged sub-basins in Canadian prairies dominated by boreal forest

以北方森林为主的加拿大大草原未测量子流域的预测

• 批准号: 155440-2006
• 负责人: Gan, Thian
• 金额: $ 2.47万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=391782
• 关键词: Predictions; un; gauged; sub; basins

Hydrologic models built for predicting streamflow of river basins are mostly data driven.  This study will develop a suite of techniques/tools to predict for un-gauged basins (PUB), an initiative started by the International Association of Hydrologic Sciences (IAHS) in 2003.  Study sites to be chosen are such as the regional scale, Athabasca River Basin (ARB) in the Canadian Prairies dominated by the Boreal Forest (BF) that exerts strong influence on the heat and water fluxes between land surface and the atmosphere.  Through field data collections, modifying soil-vegetation-atmosphere transfer models (SVAT) such as the MISBA, we can gain scientific understanding of climate, landscape and controls on hydrologic processes of the semi-arid Canadian Prairies, especially the BF.  To constrain uncertainties in un-gauged basin predictions, we will attempt to minimize uncertainty in local-scale climate input obtained from downscaling GCM scale, re-analysis data of ERA-40 of the European Centre for Mid-range Weather Forecasts (ECMWF) and/or NCEP re-analysis data of NASA, and regional scale observed data of say, ARB by a 2-stage process, e.g., GCM-regional scale and regional-local scale.  Next, we will modify MISBA's model structure to the Prairies' hydrologic and climatic conditions, and adding winter features of BF from another SVAT called SWAP to MISBA with modifications.  Lastly, we will geographically transfer model parameters calibrated for some gauged local-scale sub-basins located within or near ARB to the un-gauged sub-basin that are hydrologically similar.  We expect to adjust the model parameters through some stochastic schemes before transferring them to the un-gauged basin whose performance will be assessed quantitatively.  This combination of techniques will improve our ability to predict for un-gauged basins, and better prepared to assess future developments of relatively unknown river basins.

流域水文模型的建立主要是基于数据的。本研究将开发一套用于无资料流域预测的技术/工具（PUB），这是国际水文科学协会（IAHS）于2003年发起的一项倡议。研究地点将选择区域尺度，阿萨巴斯卡河流域（ARB）位于加拿大大草原，以北方森林（BF）为主，对地表和大气之间的热量和水通量产生强烈影响。通过野外数据收集，修改土壤-植被-大气传输模型（SVAT），如MISBA，我们可以获得半干旱加拿大大草原，特别是BF的气候，景观和水文过程控制的科学认识。为了限制未测量流域预测的不确定性，我们将尝试通过一个两阶段的过程来最大限度地减少局地尺度气候输入的不确定性，这些输入是从降尺度的GCM尺度、欧洲中期天气预报中心（ECMWF）ERA-40的再分析数据和/或美国宇航局的NCEP再分析数据以及区域尺度的观测数据（比如ARB）中获得的，例如，接下来，我们将修改MISBA的模式结构，以适应大草原的水文和气候条件，并将另一种称为SWAP的SVAT中的BF冬季特征添加到MISBA中。我们将在地理上将一些位于ARB内或附近的有测量的局部尺度子流域校准的模型参数转移到无测量的子流域，水文相似的流域。我们希望通过一些随机方案调整模型参数，然后将其转移到无资料流域，其性能将被定量评估。这种技术组合将提高我们对无资料流域的预测能力，更好地准备评估相对未知的河流流域的未来发展。