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

0450385古普塔我们建议进行一个试点项目，以发展和测试的物理基础的统计缩放理论的峰值流量的个人的径流事件在自然流域。该理论依赖于一个峰值流量标度假设，可以表述为：统计分布的峰值流量为完整的H-S流在整体径流事件表现出规模不变性作为一个基本的组织原则，这可以预测从知识的时空降雨;渗透和径流产生;网络拓扑结构;几何形状;水力几何形状;渠道损失由于蒸腾从河岸植被和/或渗透;以及由于再充电而产生的信道增益。标度不变性或标度是复杂非线性系统的一种涌现性质，它没有内置到表示产生峰值流的物理过程的方程中。我们的目标是结合理论分析和现场项目的试点项目将在150平方米的土地上进行。公里.核桃峡谷盆地，亚利桑那州，21平方米。公里古德温溪盆地，MS，和1100平方米。公里.白水盆地，堪萨斯州。白水是一个精心挑选的流域，用于调查主要由地表径流引起的暴雨引发的洪水。它是核桃河的一条支流，核桃河是1995-2004年大气边界层实验（ABLE）的一个地点。我们项目的大气辐射测量（ARM）/能源部气候研究设施（ACRF）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，调查峰流量统计定标的物理基础。（2）通过在白水流域安装11个新的流量计，测试平均峰流量定标的初步有效性和物理假设的变化，这些流量计可以根据我们开发的新技术精确测量流量过程线。（3）检验一个新的蒸腾损失的Hortonian提取假设，该假设指出树木从通道网络中提取水的森林河岸提取的统计分布可预测地随H-S阶变化，并产生提取面积和蒸腾量的Horton比。安装第12个流量计，以准确测量由于蒸腾作用造成的水道连接中的流量损失，⑷利用现有WSR-88 D NEXRAD雷达和14个新雨量计站点的测量结果估计高质量的时空降雨强度数据，（5）对在目标下获得的降雨量数据进行统计比例分析-4并从物理过程中对降雨缩放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。我们的跨学科和多学科合作项目包括来自科罗拉多大学博尔德分校、爱荷华州大学和新墨西哥州大学的高级教师、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：自然河流流域径流事件峰值流量统计标度理论的物理基础，为解决无资料流域（PUB）洪水预测的长期问题迈出了关键一步。它还提供了一个严格的科学框架，用于检测和预测地貌和气候变异性方面的人为变化如何改变产生洪水的生物物理过程，可用于预测洪水统计数据。更广泛的影响：我们的试点项目是一个重要的第一步，发展一个新的统一的网络为基础的理论，耦合水文，边界层和水文气象学，景观和河流生态学，地球化学，气候变异性和人为变化的河流流域。

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.