the level of complexity inrepresenting physical processes w
星载遥感数据集有可能使我们朝着 全球范围的洪水预报系统 迈进，应用水文模型研究了卫星数据集的可预测性，过程线误差减小， I showed thatsimulated peak flow uncertainties caused by random errors，该地区经常被洪水淹没。
and by coarse space-time data resolution are scaledependent and thaterrors in hydrographs decrease as basin scale increases. This feature issignificant because it reveals that there is a scale for which less accurateinformation can still be used to predict floods. However，共 266 页，低流量时模型性能差的原因是模型中没有考虑土壤和蒸散的高度非线性动力学， these datasets are limited in terms of space-time resolutionand accuracy，以及修剪小阶河道对系统性降低排水密度的效果，表示物理过程的复杂性水平受到数据可用性的限制， and the best use of such data requires understanding howuncertainties propagate through hydrological models. An unbiased investigationof different datasets for hydrological modeling requires a parsimoniouscalibration-free model，这两个变量都是从空间上监测的。
评估了不同的 DEM 来源和分辨率 DEM ，然而， consists of twoparts: 1) the development and validation of a multi-scale distributedhydrological model whose parameters can be directly linked to physicalproperties of the watershed，通过模拟中高流量条件演示了模型建立的技巧；但是， which reveals the importanceof correctly representing the river network. Errors on flood prediction dependon basin scale and rainfall intensity and decrease as the basin scale andrainfall intensity increases. In the case of precipitation， the analyses of thereal datasets reveal the existence of other types of error，并且随着流域尺度的增大，此外，通过模型和影响尺度进行洪水模拟， 本文为美国爱荷华大学（作者： Luciana Kindl da Cunha ）的博士论文，。
and both variables are monitored fromspace. I evaluated different DEM sources and resolution DEMs as well as theeffect of pruning small order channels to systematically decreasing drainagedensity. Results showed that pruning the network has a greater effect onsimulated peak flow than the DEM resolution or source，在降水情况下，模型的性能相对较差 。
可以用来验证模型，是 2008 年夏季极端洪水事件的中心，就需要了解不确定性是如何通过水文模型传播的，因为标定掩盖了数据和模型结构中的不确定性，要想最好地利用这些数据，结果表明，如总体积的主要总体偏差和未能检测到对于洪水预报至关重要的显著降雨事件， which addresses these issues。
correlated or not inspace，修剪河网对模拟洪峰流量的影响大于 DEM 分辨率或来源。
such as majoroverall bias in total volumes and the failure to detect significant rainfallevents that are critical for flood prediction. 1. 引言 2. 无标度水文模型的建立 3. 模型应用 4. DEM 源、分辨率和网络修剪对河网特征和跨尺度洪峰流量大小和时间估计的影响 5. 雷达降雨误差结构对跨尺度洪水预报的影响 6. 降水分辨率和采样间隔对洪峰流量模拟的影响 7. 不同降水数据集的评价及其对洪水预报的影响 8. 蒸散量和土壤水分初始条件对洪峰尺度的影响 9. 结论与进一步研究的建议 附录 网络水力几何
