(SGER) COLLABORATIVE RESEARCH: Hydrometeorological Analysis of the Spring Creek Flood of 1997-Fort Collins
(SGER) COLLABORATIVE RESEARCH: Hydrometeorological Analysis of the Spring Creek Flood of 1997-Fort Collins
批准号:
9732403
负责人:
James Smith
金额:
$1.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-12-01 至 1998-11-30
中文摘要
9732403史密斯提出了一项小额勘探拨款,用于使用最先进的遥感和降雨/径流模拟方法来研究1997年7月28日发生在科罗拉多州柯林斯堡斯普林克里克排水系统的灾难性洪水的气象学、径流和河道水力学。这场洪水仅科罗拉多州立大学就造成了约5000万至1亿美元的损失。其他损害包括两个流动房屋球场的破坏,许多房屋被洪水淹没,多人受伤,五人不幸死亡。这项拟议的研究是康涅狄格大学、密苏里大学和普林斯顿大学的研究人员共同努力的成果。参与研究的研究人员在雷达降雨估计、水文定标和开发包含遥感数据的最新降雨/径流模型方面拥有丰富的经验。这项拟议研究的目标是(1)描述7月28日晚上存在的气象条件,导致流域在不到3小时的时间内降雨量超过11英寸;(2)利用地面记录的降雨累积,校准和验证美国国家科学基金会资助的CSU-CHILL S波段双极化研究雷达和位于科罗拉多州丹佛市和怀俄明州夏延市附近的两台WSR-88D NEXRAD雷达的雷达降雨量估计;(3)利用地理信息系统收集和整理流域特征和洪水数据;(4)应用降雨和流域特征数据,使用基于物理的二维水文模型再现径流事件;(5)将二维径流模拟结果与使用更传统的SWMM和HEC-2洪水预警和水文设计方法再现洪水的性能进行比较和对比。合作的提倡者处于进行这项研究的独特地位,因为他们立即寻找并获得了与洪水相关的数据。此外,合作研究小组对利用遥感输入的降雨/径流模型进行了大量的研究和开发。此外,两位提名人曾在柯林斯堡居住多年,在该地区有广泛的水文联系,并对受洪水影响的地区非常熟悉。预计洪水的初步分析、建模和重建可在不到3个月的时间内完成,从而形成一份摘要报告和一份关于这一事件之前和期间情况的论文。在资金支出之前,将继续对建模工作进行进一步的改进和修改。这一初步努力将引起全国对导致这场风暴的水文气象条件的关注,并建立基于物理的、使用遥感降雨输入的分布参数径流模型的能力,以预测城市地区的短期山洪。这种即将评估的新的山洪模型方法具有显著的潜力,可以降低生命和财产风险,并提高城市地区水文设计的准确性。
英文摘要
9732403 Smith A small exploratory grant is proposed to employ advanced state of the art remote sensing and rainfall/runoff modeling approaches to examine the meteorology, runoff and channel hydraulics of the catastrophic flood which occurred on the Spring Creek drainage on July 28, 1997 in Fort Collins, Colorado. This flood resulted in an estimated 50 to 100 million dollars of damage to Colorado State University alone. Additional damages include the devastation of two mobile homes courts, flooding of numerous homes, multiple injuries and the unfortunate deaths of five people. The proposed study is a collaborative effort between researchers at the University of Connecticut, University of Missouri, and Princeton University. The researchers involved have extensive experience in radar-rainfall estimation, hydrologic scaling, and the development of state of the art rainfall/runoff models which incorporate remotely-senses data. The objectives of this proposed study are to (1) characterize the meteorological conditions which existed on the evening of July 28 leading to over 11 inches of rainfall in less than three hours on the watershed; (2) calibrate and verify radar-rainfall estimates from the NSF-funded CSU-CHILL S-band dual-polarization research radar, and the two WSR-88D NEXRAD radars located near Denver, Colorado and Cheyenne, Wyoming, using surface recorded rainfall accumulations; (3) collect and organize watershed characteristic and flood data using GIS; (4) apply the rainfall and watershed characteristic data to recreate the runoff event using a two-dimensional, physically-based hydrologic model; and (5) compare and contrast the performance of two-dimensional runoff simulation results with a recreation of the flood using the more traditional SWMM and HEC-2 approaches for flood warning and hydrologic design. The collaborative proposers are uniquely positioned to perform this research because they immediately sought and obtained data relevant to the flood. Additionally, the c ollaborative research team has conducted a significant amount of research and development to rainfall/runoff modeling using remotely-sensed inputs. Furthermore, the two of the proposers lived in Fort Collins for many years, have extensive hydrologic contacts in the area, and are intimately familiar with the region affected by the flood. It is anticipated that the initial analysis, modeling and re-creation of the flood can be performed in less than 3 months leading to a summary report and paper on the conditions leading up to, and during the event. Additional refinement and modifications of modeling efforts will continue until funding is expended. This initial effort will garner and focus national attention on the hydrometeorological conditions which lead to this storm, and establish the capabilities of physically-based, distributed-parameter runoff models using remotely-sensed rainfall input for predicting short-duration flash floods in urban areas. This new flash-flood modeling approach to be evaluated has significant potential to reduce the risk of life and property, as well as improve the accuracy of hydrologic design in urban areas.
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