Collaborative Research: Testing a Dynamical-Hortonian Scaling Theory for for Flood Events on Whitewater Basin, Kansas

[0450385]我们建议开展一个试点项目，以开发和测试自然流域个别降雨径流事件峰值流量统计标度理论的物理基础。该理论建立在峰流量尺度假设的基础上，其可表述为：降雨-径流事件中完整H-S流的峰流量统计分布表现出尺度不变性，这是一个基本的组织原则，可以通过时空降雨的知识来预测；入渗与产流；网络拓扑结构;几何;水力几何;河岸植被蒸腾和/或渗透造成的河道损失；和通道增益由于充电。尺度不变性或标度是复杂非线性系统的一个紧急特性，它不包含在表示产生峰值流量的物理过程的方程中。我们的试点项目的目标是结合理论分析和实地计划，将在150平方英尺的土地上进行。核桃峡谷盆地，AZ， 21平方公里。MS的古德温河盆地，面积1100平方公里。堪萨斯州白水盆地。白水是一个精心挑选的盆地，用于调查主要由陆地流引起的暴雨引发的洪水。它是核桃河的一条支流，在1995-2004年期间是大气边界层实验（ABLE）的一个站点。大气辐射测量(ARM)/美国能源部气候研究设施（ACRF）对我们项目的支持提供了我们需要的ABLE仪器的使用，并帮助在白水现场部署和维护仪器。我们的具体目标是：(1)利用两个ARS流域的现有数据研究峰值流量统计标度的物理基础；(2)通过在白水流域安装11个新的流量计，测试平均峰值流量标度的初步有效性和物理假设的变化，这些测量仪基于我们开发的新技术，可以准确测量溪流的水流曲线；(3)测试蒸腾损失的新Hortonian fetch假设；它指出，树木从河道网络中提取水的森林河岸取水的统计分布可预测地随着H-S顺序和取水面积和蒸发量的产生霍顿比而变化。(4)利用现有的WSR-88D NEXRAD雷达和14个新的雨量计站点的测量数据估算出高质量的时空降雨强度数据；(5)对目标4下获得的降雨数据进行统计标度分析，并从物理过程中对降雨标度统计数据进行预测性理解。(6)部署和测试一个新的网络，用于从我们的传感器实时收集、传输和存储数据。我们合作的跨学科和多学科项目包括来自科罗拉多大学、博尔德大学、爱荷华大学和新墨西哥大学的高级教师、博士后和研究生，以及来自美国地质调查局的科学家。智力优势：自然流域降雨径流事件峰值流量统计标度理论的物理基础为解决长期存在的未测量流域洪水预测问题提供了关键的一步。它还为探测和预测景观和气候变率的人为变化如何改变产生洪水的生物物理过程提供了一个严格的科学框架，可用于预测洪水统计。更广泛的影响：我们的试点项目是朝着发展一种新的统一的基于网络的理论迈出的重要的第一步，该理论将水文学、边界层和水文气象学、景观和河流生态学、生物地球化学、气候变率和流域的人为变化结合起来。

0450385GuptaWe propose to conduct a pilot project to develop and test the physical basis of a statistical scaling theory for peak flows for individual rainfall-runoff events in natural river basin. The theory rests on a peak-flow-scaling hypothesis that can be stated as: Statistical distributions of peak-flows for complete H-S streams in rainfall-runoff events exhibit scale invariance as a fundamental organizing principle, which can be predicted from knowledge of space-time rainfall; infiltration and runoff generation; network topology; geometry; hydraulic geometry; channel losses due to transpiration from riparian vegetation and/or infiltration; and channel gains due to recharge. Scale invariance or scaling is an emergent property of a complex nonlinear system, which is not built into the equations representing physical processes that produce peak flows. Our objectives for a pilot project combining both theoretical analyses and a field program will be carried out on the 150 sq. km. Walnut Gulch basin, AZ, the 21 sq. km Goodwin Creek basin, MS, and the 1100 sq. km. Whitewater basin, KS. Whitewater is a carefully selected basin for investigating heavy-rainfall induced floods resulting dominantly from overland flow. It is a tributary of the Walnut River, which was a site for Atmospheric Boundary Layer Experiments (ABLE) during 1995-2004. Atmospheric Radiation Measurement (ARM)/DOE Climate Research facility (ACRF) support of our project provides use of ABLE instruments that we need, and help with field deployment and maintenance of instruments in Whitewater. Our specific objectives are: (1) Investigate physical basis of statistical scaling in peak-flow using existing data from the two ARS basins, (2) Test preliminary validity of mean peak flow scaling and physically postulated change in it by installing eleven new stream flow gauges in the Whitewater basin that can accurately measure stream flow hydrographs on the basis of a new technology developed by us, (3) Test a new Hortonian fetch hypothesis for transpiration losses, which states that the statistical distributions of forested riparian fetches over which trees extract water from a channel network vary predictably with the H-S order and yield Horton ratios for fetch area and transpired volume. Installation of a twelfth stream flow gauge to accurately measure flow losses in a channel link due to transpiration, (4) Estimate good quality space-time rainfall intensity data using measurements from existing WSR-88D NEXRAD radars and 14 new rain gage sites, (5) Conduct statistical scaling analyses on rainfall data obtained under objective-4 and develop a predictive understanding of rainfall scaling statistics from physical processes, (6) Deploy and test a new network for real-time data collection, transmission and storage from our sensors. Our cooperative interdisciplinary and multidisciplinary project includes senior faculty, post docs, and graduate students from the University of Colorado, Boulder, the University of Iowa, and the University of New Mexico, and scientists from the U.S. Geological Survey. Intellectual Merit:A physical basis of the statistical scaling theory for peak flows for rainfall-runoff events in natural river basins provides a key step towards solving the long-standing problem of flood prediction from ungauged basins (PUB). It also provides a rigorous scientific framework for detecting and predicting how anthropogenic changes in landscape and climate variability modify biophysical processes generating floods, which can be used for predicting flood statistics. Broader Impacts:Our pilot project is a major first step towards developing a new unified network-based theory that couples hydrology, boundarylayer- and hydro- meteorology, landscape and stream ecology, biogeochemistry, climate variability and anthropogenic change in river basins.