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A large-scale, high-resolution hydrological model parameter data set for climate change impact assessment for the conterminous US

机译:大规模,高分辨率的水文模型参数数据集,用于对美国本土进行气候变化影响评估

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摘要

To extend geographical coverage, refine spatial resolution, and improvemodeling efficiency, a computation- and data-intensive effort was conductedto organize a comprehensive hydrologic data set with post-calibrated modelparameters for hydro-climate impact assessment. Several key inputs forhydrologic simulation – including meteorologic forcings, soil, land class,vegetation, and elevation – were collected from multiple best-available datasources and organized for 2107 hydrologic subbasins (8-digit hydrologicunits, HUC8s) in the conterminous US at refined 1/24°(~4 km) spatial resolution. Using high-performance computingfor intensive model calibration, a high-resolution parameter data set wasprepared for the macro-scale variable infiltration capacity (VIC) hydrologicmodel. The VIC simulation was driven by Daymet daily meteorological forcingand was calibrated against US Geological Survey (USGS) WaterWatch monthly runoff observations foreach HUC8. The results showed that this new parameter data set may helpreasonably simulate runoff at most US HUC8 subbasins. Based on thisexhaustive calibration effort, it is now possible to accurately estimate theresources required for further model improvement across the entireconterminous US. We anticipate that through this hydrologicparameter data set, the repeated effort of fundamental data processing can belessened, so that research efforts can emphasize the more challenging taskof assessing climate change impacts. The pre-organized model parameterdata set will be provided to interested parties to support furtherhydro-climate impact assessment.
机译:为了扩大地理覆盖范围,改善空间分辨率并提高建模效率,进行了计算和数据密集型工作,以组织具有后校准模型参数的综合水文数据集,以进行水气候影响评估。从多个最佳可用数据源中收集了几个关键的水文模拟输入,包括气象强迫,土壤,土地类别,植被和海拔,并为美国本土2107个水文盆地(8位水文单位,HUC8)按提炼的1 / 24°(〜4 km)空间分辨率。利用用于密集模型校准的高性能计算,为宏观可变渗透能力(VIC)水文模型准备了高分辨率参数数据集。 VIC模拟由Daymet每日气象强迫驱动,并已针对每个HUC8的美国地质调查局(USGS)WaterWatch每月径流观测值进行了校准。结果表明,这个新的参数数据集可以帮助大多数美国HUC8子流域合理地模拟径流。基于这一详尽的校准工作,现在可以准确估计整个美国范围内进一步模型改进所需的资源。我们预计,通过该水文参数数据集,可以减少基础数据处理的重复工作,从而使研究工作可以强调评估气候变化影响的更具挑战性的任务。预组织的模型参数数据集将提供给有关方面,以支持进一步的水文气候影响评估。

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