Hydrometeorology of Flash Flooding Processes and Frequencies in the Northeastern United States

摘要山洪灾害是造成经济损失和人员伤亡最严重的天气灾害之一。研究表明，在当前的气候变化趋势下，高强度降雨将更加频繁，这似乎意味着山洪暴发也将变得更加频繁。然而，由于洪水是气象和水文过程复杂相互作用的结果，因此山洪暴发的真正趋势并不明显。研究表明，山洪暴发是降雨时空分布与前期土壤湿度和流域尺度水文变量共同作用的结果。我们最近的工作表明，美国东北部的暴雨径流更多地是总降雨量积累（饱和过剩）的产物，而不是高瞬时降雨率（霍顿径流）的产物。在这个项目中，我们将通过探索将大气过程与美国东北部地表水文过程联系起来的基本过程，来评估对山洪暴发的径流是否真的如此。主要研究问题是：（Q1）东北部山洪暴发的风暴事件与中西部和东南部的风暴事件有本质上的不同吗？（Q2）东北部的山洪暴发更多的是饱和过量还是霍顿风暴径流过程的结果？我们确定了2003-2007年美国东北部发生的186次山洪暴发事件，并将其作为我们的样本集。与往年相比，这一时期雷达数据的空白较少，在本世纪预计的气候条件下，这一时期洪水事件的相对高频率可能是典型的。将通过描述与这些山洪事件相关的天气尺度（1000公里）和中尺度（10-100公里）风暴事件结构的观测特征，以及基于雷达（在条件允许的情况下使用标准或热带反射率-降雨关系）和地面站（点尺度）数据得出的流域尺度降雨量和强度，来解决第1问题。这些数据将与公布的中西部和东南部的暴洪风暴信息进行比较，这些信息比东北部的数据更丰富。由于像土壤湿度这样的分布式水文信息没有被广泛测量，为了解决第二问题，我们将使用四种流域模型的集合来估计这些信息，这些模型从完全分布/完全机械到半分布/经验，这些模型已经通过对流量和土壤湿度的区域水文观测进行了很好的审查。我们将使用经过偏差校正的NEXRAD降雨数据来运行我们的流域模型。一旦我们知道？我们的先决条件（来自我们的流域模型结果）和引起山洪的降雨量（来自Q1），我们可以使用二元概率分析来确定产生山洪所需的流域湿度和降雨量重合的概率。通过分析产生山洪的降雨强度产生霍顿径流的频率，即超过土壤入渗能力的频率（这是土壤湿度的函数），我们可以确定山洪发生霍顿径流的频率。我们将使用四个具有不同机制和经验基础的流域模型的集合，以支撑我们的结果；注意：之所以采用这种方法，是因为对于机械论和经验论哪一种方法提供了最好的方法，几乎没有达成共识。结果。这项工作将促进大气和水文科学家之间有意义的合作，以帮助将气候变化预测置于它们可能如何影响洪水频率的背景中。结果将与国家气象局预报办公室共享，理想的结果是更及时和空间精确的山洪预警。研究生将进行大部分的研究，有助于他们作为科学家的训练。我们正在设计一门新生写作课程，围绕全球气候变化背景下的社会-科学-政策相互作用，将山洪暴发的水文气象学作为一致的主题或案例研究，并将开发课程模块，将本研究的发现和工具纳入其他科学和工程课程。

Project AbstractFlash flooding is one of the costliest weather hazards, both in economic losses and in human casualties. Research showing that high intensity rainfall will be more frequent in our current trend of climate change seems to imply that flash flooding will also become more frequent. However, because flooding results from complex interactions of meteorological and hydrological processes, it is not obvious what will be the true trends in flash flooding. It is well established that flash flooding results from the combination of the spatio-temporal distribution of rainfall with antecedent soil moisture and basin-scale hydrological variables. Our recent work suggests that storm runoff in the northeastern US is more often a product of total rainfall accumulation (saturation excess) rather than a product of high instantaneous rainfall rates (Hortonian runoff). In this project we will evaluate whether this is true for runoff that contributes specifically to flash floods by exploring the fundamental processes that link the atmospheric processes with surface-hydrological processes for the northeast U.S. The primary research questions are:(Q1) Are northeastern flash-flood-producing storm events substantially different from those that have been characterized for the midwest and southeast? (Q2) Are northeastern flash floods more often the result of saturation excess or Hortonian storm runoff processes?We have identified 186 flash flood events from 2003-2007 throughout the northeastern U.S that we will use as our sample set. There are fewer gaps in the radar data during this period than in previous years and the relatively high frequency of flooding events during this period may be typical under climatic conditions expected during this century. Q1 will be addressed by characterizing observations of both synoptic-scale (1000s km) and mesoscale (10-100s km) structures of storm events associated with these flash flood events, as well as the resultant watershed-scale rainfall amounts and intensities based on radar (using standard or tropical reflectivity-rainfall relationships as conditions warrant) and ground station (point-scale) data. These data will be compared with published information about flash flood storms in the Midwest and Southeast, which is more plentiful than that for the Northeast. Because distributed hydrologic information like soil moisture is not widely measured, to address Q2, we will estimate this information with an ensemble of four watershed models ranging from fully distributed/fully mechanistic to semi-distributed/empirical that have been well vetted with regional hydrologic observations of both discharge and soil moisture. We will use bias-corrected NEXRAD rainfall data to run our watershed models. Once we ?know? our antecedent conditions (from our watershed model results) and the flash-flood-causing rainfall (from Q1), we can use bivariate probability analysis to determine the probability of the coincidence of watershed wetness and rainfall needed to produce a flash flood. By analyzing how often flash-flood-generating rain intensities produce Hortonian runoff, i.e., exceed soil infiltration capacity, which is a function of soil moisture, we can determine how frequently flash floods are ?Hortonian.? We will use an ensemble of four watershed models with different mechanistic and empirical underpinnings in order to bracket our results; note: this approach is taken because there is little consensus about which approach, mechanistic vs empirical, provides the ?best? result. This work will foster meaningful collaboration between atmospheric and hydrologic scientists to help put climate change predictions in context as to how they are likely to influence flood frequency. Results will be shared with National Weather Service Forecast Offices ideally resulting in more timely and spatially precise flash flood warnings. Graduate students will conduct much of the research, contributing to their training as scientists. We are designing a Freshman Writing course around society-science-policy interactions in the context of global climate change that uses the hydrometeorology of flash flooding as a consistent theme or case study, and will develop course modules to incorporate the findings and tools from this study into other science and engineering courses.