Wireless Technologies and Embedded Networked Sensing: Application to Integrated Urban Water Quality Management

Hondzo 0607138由于城市化进程的加快，流经流域的河流水质已经退化。这种退化的一般症状包括更频繁的大流量事件，降低通道复杂性，减少保留天然有机物，和营养物浓度升高。新出现的城市水质威胁，包括杀虫剂、除草剂、药物和雌激素，已知或怀疑会损害人类和生态系统的健康。河流的恢复和管理传统上试图改善河流或河岸带的水文和水质条件。最近的研究表明，流域的不透水面覆盖的部分，并通过雨水排水连接到河流是河流生态和健康的主要退化过程。这些研究结果表明，河流水质的可持续恢复和管理需要量化的水文，化学，生物和地貌过程，这些过程必须在一系列尺度进行评估。此外，跨流域生态地球化学过程之间的相互作用要么是非线性过程，要么是依赖于非线性驱动因素的线性过程。监测这种系统必然要求改变传统的实地取样战略。我们建议通过集成多尺度，空间密集，高频，实时和事件驱动的观察，通过嵌入式网络传感的无线网络，转换传统的和非常有限的（在空间和时间分辨率方面）现场测量。智力优点：我们的研究目标是建立一个无线网络与嵌入式传感能够监测基本水质参数。这种网络是流域观测站网络的一个关键组成部分。这些基本的水质参数用于预测城市河流中出现的化学污染物的存在的能力也将被确定。据推测，新出现的污染物的浓度将与使用传感器网络测量的基本参数相关，并且与传统的离散抓取采样相比，传感器网络将提供对这些污染物的负荷的改进的预测。我们的总体假设是，在城市土地不透水区的河流排水水质是由有效的雨水停留时间的均值和方差控制。水停留时间的平均值和方差，城市径流之间的不透水的城市土地和接收水体的时间，将被量化的射频识别技术（RFID），示踪剂的研究，并在拟议的无线网络内的流体流速测量。一个小的城市流域将配备无线网络传感，以解决以下目标：（1）以空间密集和高频分辨率测量基本水质和水文参数，（2）一般参数与出现的污染物的存在和/或水平的相关性，（3）以有效雨水停留时间的均值和方差为主要指标，将实测资料与流域进行整合。溪流的水质将作为对土地利用梯度和水文瞬变的动态响应而不是通过平均特性描述的平衡来观察。这一方法将使人们能够对溪流中的水质进行基于过程的缩放和预测，从溪流中的过程到流域一级。嵌入网络传感的无线网络设计用于量化各种尺度上变量的空间和时间异质性，不仅非常适合河流水质管理，而且非常适合不同部分之间相互连接的所有环境过程决定了系统的整体状态。该项目将开发的网络将侧重于城市河流，但未来可以扩展到包括具有不同土地用途的其他流域。生成的数据和缩放关系将改变城市规划实践和城市土地排水河流的水质管理。与其仅仅关注对流内处理的操作，更可持续的方法将是关注雨水最佳管理做法的选择和地点（例如，湿地或湿地）。拟议的实地测量侧重于评价最佳管理做法，以便进行更适当和有效的水文管理。该项目将有两个教育部分。一个是通过修订的教育课程来解决学生和科学家的问题。另一个是与丹麦技术大学合作，通过开发一个关于“综合城市水质管理”的因特网课程。"

Hondzo0607138The water quality of streams draining watersheds has been degraded by increasing urbanization. The general symptoms of this degradation include more frequent large flow events, reduction in channel complexity, reduced retention of natural organic matter, and elevated concentrations of nutrients. Newly emerging urban water quality threats, including insecticides, herbicides, pharmaceuticals, and estrogens, are known or suspected to damage the health of humans and ecosystems. The restoration and management of streams have traditionally attempted to improve the hydrological and water quality conditions in-stream or in riparian zones. Recent studies have indicated the portion of a watershed covered by impervious surfaces and connected to thestream by stormwater drainage is the primary degrading process of stream ecology and health. These findings suggest that the sustainable restoration and management of stream water quality require quantification of hydrological, chemical, biological, and geomorphological processes, and that these processes must be assessed across a range of scales. Furthermore, interactions among biogeochemical processes across watersheds are either non-linear processes or linear processes dependent on non-linear drivers. The monitoring of such a system inherently requires a change in traditional field sampling strategies. We propose to transform traditional and very limited (in terms of spatial and temporal resolution) field measurements through the integration of multi-scale, spatially-dense, high frequency, real-time, and event-driven observations by a wireless network with embedded networked sensing. Intellectual merit: The objective of our research is to establish a wireless network with embedded sensing capable of monitoring fundamental water quality parameters. Such a network is a key component for watershed observatory networks. The ability of these fundamental water quality parameters to be used for predicting the presence of emerging chemical contaminants in urban streams will also be determined. It is hypothesized that the concentrations of emerging contaminants will correlate with the fundamental parameters measured using the sensor network and that the sensor network will give improved prediction of the loads of these contaminants compared to traditional, discrete grab sampling. Our overall hypothesis is that water quality in streams draining impervious areas of urban land is controlled by the mean and variance of effectivestormwater residence time. The mean and variance of water residence time, the time it takes urban runoff to travel between the impervious urban land and a receiving aquatic body, will be quantified by radio frequency identification technology (RFID), tracer studies, and fluid-flow velocity measurements within the proposed wireless network. A small urban watershed will be equipped with wireless networked sensing to address the following objectives: (1) measurement of fundamental water quality and hydrologic parameters with spatiallydense and high frequency resolution, (2) correlation of general parameters with the presence and/or levels of emerging contaminants, and (3) integration of field measurements to the watershed using primarily the meanand variance of effective stormwater residence time. Water quality in streams will be observable as a dynamic response to land use gradients and hydrological transients rather than as an equilibrium described byaverage properties. This approach will enable process-based scaling and forecasting of water quality in streams from the in-stream processes to the watershed level.Broader impact: Wireless networks with embedded networked sensing are designed to quantify spatial and temporal heterogeneities of variables across a variety of scales and are perfectly suited not only for water quality management in streams but also to all environmental processes where interconnectivity among different parts determines the overall state of the system. The network to be developed in this project will focus on an urban stream, but can be expanded to include other watersheds with different land uses in the future. Generated data and scaling relationships will transform urban planning practices and management of water quality in streams draining urban land. Rather than focusing on manipulating in-stream processing only,a more sustainable approach would be to focus on selection and location of stormwater best management practices (e.g., detention ponds or wetlands). The proposed field measurements are focused on evaluating best management practices for more appropriate and effective hydrologic management. The project will have two educational components. One addresses students and scientists through a revised educational curriculum. Theother is an international collaboration with the Technical University of Denmark through a developed Internetcourse on "Integrated Urban Water Quality Management."