SGER: Evaluation of the Rating Curve Hysteresis Due to Unsteady Channel Flows Using Non-Intrusive Measurements Acquired During the Iowa 2008 Flood

SGER：使用 2008 年爱荷华州洪水期间获得的非侵入式测量结果评估因不稳定河道流量造成的额定曲线滞后

• 批准号: 0843798
• 负责人: Marian Muste
• 金额: --
• 依托单位: University of Iowa
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2010-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0843798&HistoricalAwards=false
• 关键词: SGER; Evaluation; Rating; Curve; Hysteresis

0843798MusteThe PI proposes to better understand and refine river discharge estimates using improved measures of rating curves. Traditional river discharge estimates are conducted at times when flow is relatively normal and steady, allowing safe and convenient measurement. These measurements serve as the basis for calculating rating curves. The curves, in turn, are used to estimate flow and discharge during flood events ? possibly leading to significant uncertainty due to hysteresis. Understanding the discharge-flow hysteresis relationship requires measurements during high flow events. The 2008 Midwestern flood offers a unique opportunity to couple flow and discharge measurements in order to better understand and model rating curve hysteresis during extreme events. With the goal of coupling river stage and discharge, measurements will be made in a non-contact manner developed at IIHR-Hydroscience & Engineering which uses Large-Scale Particle Image Velocimetry (LSPIV). This technique was initiated on June 10, 2008. Funds are requested to 1) finalize the on-going measurements; 2) perform topographic and bathymetric surveys; 3) evaluate deployed instruments by conducting baseline flow measurements; 4) analyze data and report findings; and 5) produce conceptual process models and define future research needs. The unique aspect of the proposed research is the use of non-intrusive measurement techniques in a natural extreme event provided by the 2008 Midwestern flood. The series of measurements will allow the PI to assess the technique and its ability to provide improved rating curve estimates under rare unsteady flow situations in natural channels. The expectation is that LSPIV will provide a simple, compact, cost- and effort-effective package for providing these critical measurements. Unsteady flows will be investigated in detail and conceptual frameworks will be developed in order to determine what ancillary data are needed to answer discharge hypotheses. The transformative, exploratory nature of this project will provide field testing for technical aspects of the LSPIV technique to include specular reflection for free-surface tracing, optimal velocity distribution laws in the water column testing as a function of stream characteristics, flood wave raising and falling data capture, and uncertainty analysis. Rating curves are the basis of stream stage measurements, yet their uncertainty during high-flow events obviates the ability to fully understand unsteady fluvial processes. River processes hypotheses regarding extreme and unusual flow regimes can be tested and the results of this study will enable river stage and discharge estimation in regions without gauging stations. Integrated hydrologic-geomorphic-biological studies will be possible through a better understanding of key temporal and spatial processes in flood propagation. Uncertainty in rating curves calculated during stable river flow regimes will hinder flood stage forecasting whereas this project will provide data useable by national mission agencies for more accurate flood estimates. With billions of dollars lost each year, more accurate flood data are timely and of broad interest.***

0843798 MustThe PI建议使用改进的额定曲线测量方法更好地理解和改进河流流量估计。传统的河流流量估算是在流量相对正常和稳定的时候进行的，这样可以安全和方便地测量。这些测量值作为计算额定曲线的基础。曲线，反过来，用于估计流量和流量在洪水事件？可能导致由于滞后而引起的显著不确定性。了解排放-流量滞后关系需要在高流量事件期间进行测量。2008年中西部洪水提供了一个独特的机会，耦合流量和流量测量，以更好地了解和模拟额定曲线滞后在极端事件。为了将河流水位和流量结合起来，将采用IIHR-水文科学工程部开发的非接触式方式进行测量，该方法使用大规模粒子图像测速仪（LSPIV）。这项技术于2008年6月10日启动。申请资金用于：1）最后确定正在进行的测量; 2）进行地形和水深测量; 3）通过进行基线流量测量评估部署的仪器; 4）分析数据和报告调查结果; 5）制作概念过程模型并确定未来的研究需求。拟议研究的独特之处在于，在2008年中西部洪水提供的自然极端事件中使用非侵入性测量技术。这一系列测量将使PI能够评估该技术及其在天然渠道中罕见的不稳定流情况下提供改进的额定曲线估计的能力。期望LSPIV将提供一个简单，紧凑，成本和努力有效的包提供这些关键的测量。将详细研究非恒定流，并制定概念框架，以确定回答排放假设所需的辅助数据。该项目的变革性和探索性将为LSPIV技术的技术方面提供现场测试，包括自由表面跟踪的镜面反射，水柱测试中作为水流特征函数的最佳速度分布规律，洪水波上升和下降数据捕获以及不确定性分析。等级曲线是河流水位测量的基础，但在高流量事件期间，其不确定性排除了充分了解非定常河流过程的能力。关于极端和不寻常的流态的河流过程假设可以进行测试，这项研究的结果将使河流水位和流量估计在没有测量站的地区。通过更好地了解洪水传播的关键时间和空间过程，将有可能进行水文-地貌-生物综合研究。在稳定的河流流量状态下计算的额定曲线的不确定性将阻碍洪水水位预测，而本项目将提供国家使命机构更准确的洪水估计可用的数据。由于每年损失数十亿美元，更准确的洪水数据是及时的，具有广泛的意义。