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: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=362354
• 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.

用于预测河鲈流量的水文模型主要是数据驱动的。 This study will develop a suite of techniques/tools to predict for un-gauged basses (PUB), an initiative started by the International Association of Hydrologic Sc​​iences (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 气氛。通过现场数据收集，修改土壤蔬菜 - 大气转移模型（SVAT），例如MISBA，我们可以对气候，景观和控制半干旱加拿大大草原的水文过程的科学理解，尤其是BF。为了限制盆地不安全的预测中的不确定性，我们将尝试最大程度地减少欧洲中期天气预测中心（ECMWF）和/或NCEP重新分析数据的欧洲中心（ECMWF）中心中心40的局部规模攀爬投入的不确定性，重新分析数据的重新分析数据，并在nasa和ncep scale a n assa scale a sabe a sabe cos a的过程中进行了启动。 GCM区域量表和区域本地量表。接下来，我们将将Misba的模型结构修改为草原的水文和气候条件，并通过修改将BF的冬季特征添加到另一个称为Swap到Misba的SVAT的冬季特征。最后，我们将对位于ARB内或附近的某些测量的局部规模的子碱进行校准的地理转移模型参数，直到液压上相似的未命名的子碱。我们期望通过一些随机方案调整模型参数，然后再将其转移到未命名的盆地，其性能将被定量评估。这种技术的组合将提高我们预测未命名低音的能力，并准备好评估相对未知的河贝司的未来发展。