Advancing Urban Flood Resilience With Smart Water Infrastructure

Advances in wireless communications and low-power electronics are enabling a new generation of smart water systems that will employ real-time sensing and control to solve our most pressing water challenges. In a future characterized by these systems, networks of sensors will detect and communicate flood events at the neighborhood scale to improve disaster response. Meanwhile, wirelessly-controlled valves and pumps will coordinate reservoir releases to halt combined sewer overflows and restore water quality in urban streams. While these technologies promise to transform the field of water resources engineering, considerable knowledge gaps remain with regards to how smart water systems should be designed and operated. This dissertation presents foundational work towards building the smart water systems of the future, with a particular focus on applications to urban flooding. First, I introduce a first-of-its-kind embedded platform for real-time sensing and control of stormwater systems that will enable emergency managers to detect and respond to urban flood events in real-time. Next, I introduce new methods for hydrologic data assimilation that will enable real-time geolocation of floods and water quality hazards. Finally, I present theoretical contributions to the problem of controller placement in hydraulic networks that will help guide the design of future decentralized flood control systems. Taken together, these contributions pave the way for adaptive stormwater infrastructure that will mitigate the impacts of urban flooding through real-time response.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163144/1/mdbartos_1.pd

Design and Implementation of Large-Scale Wireless Sensor Networks for Environmental Monitoring Applications

Environmental monitoring represents a major application domain for wireless sensor networks (WSN). However, despite significant advances in recent years, there are still many challenging issues to be addressed to exploit the full potential of the emerging WSN technology. In this dissertation, we introduce the design and implementation of low-power wireless sensor networks for long-term, autonomous, and near-real-time environmental monitoring applications. We have developed an out-of-box solution consisting of a suite of software, protocols and algorithms to provide reliable data collection with extremely low power consumption. Two wireless sensor networks based on the proposed solution have been deployed in remote field stations to monitor soil moisture along with other environmental parameters. As parts of the ever-growing environmental monitoring cyberinfrastructure, these networks have been integrated into the Texas Environmental Observatory system for long-term operation. Environmental measurement and network performance results are presented to demonstrate the capability, reliability and energy-efficiency of the network

An Environmental Monitoring System for Managing Spatiotemporal Sensor Data over Sensor Networks

In a wireless sensor network, sensors collect data about natural phenomena and transmit them to a server in real-time. Many studies have been conducted focusing on the processing of continuous queries in an approximate form. However, this approach is difficult to apply to environmental applications which require the correct data to be stored. In this paper, we propose a weather monitoring system for handling and storing the sensor data stream in real-time in order to support continuous spatial and/or temporal queries. In our system, we exploit two time-based insertion methods to store the sensor data stream and reduce the number of managed tuples, without losing any of the raw data which are useful for queries, by using the sensors' temporal attributes. In addition, we offer a method for reducing the cost of the join operations used in processing spatiotemporal queries by filtering out a list of irrelevant sensors from query range before making a join operation. In the results of the performance evaluation, the number of tuples obtained from the data stream is reduced by about 30% in comparison to a naïve approach, thereby decreasing the query execution time

Proceedings of 2018 Kentucky Water Resources Annual Symposium

This symposium was planned and conducted as a part of the state water resources research institute annual program that is supported by Grant/Cooperative Agreement Number G16AP00055 from the United States Geological Survey. The contents of this proceedings document and the views and conclusions presented at the symposium are solely the responsibility of the individual authors and presenters and do not necessarily represent the official views of the USGS or of the symposium organizers and sponsors. This publication is produced with the understanding that the United States Government is authorized to reproduce and distribute reprints for government purposes. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey

Evaluation of Wireless Sensor Networks Technologies

Wireless sensor networks represent a new technology that has emerged from developments in ultra low power microcontrollers and sophisticated low cost wireless data devices. Their small size and power consumption allow a number of independent ‘nodes’ (known as Motes) to be distributed in the field, all capable of ad-hoc networking and multihop message transmission. New routing algorithms allow remote data to be passed reliably through the network to a final control point. This occurs within the constraints of low power RF transmissions in a congested 2.4GHz radio spectrum. Wireless sensor network nodes are suitable for applications requiring long term autonomous operation, away from mains power supplies, such as environmental or health monitoring. To achieve this, sophisticated power management techniques must be used, with the units remaining ‘asleep’ in ultra low power mode for long periods of time. The main aim of this research described in this thesis is first to review the area and then to evaluate one of the current hardware platforms and the popular software used with it called TinyOS. Therefore this research uses a hardware platform designed from University of Berkeley, called the TmoteSky. Practical work has been carried out in different scenarios. Using Java tools running on a PC, and customized applications running on the Motes, data has been captured, together with information showing topology configuration and adaptive routing of the network and radio link quality information. Results show that the technology is promising for distributed data acquisition applications, although in time critical monitoring systems new power management schemes and networking protocols to improve latency in the system will be required

Biotic Indicators for Ecological State Change in Amazonian Floodplains

Riverine floodplains are biologically diverse and productive ecosystems. Although tropical floodplains remain relatively conserved and ecologically functional compared to those at higher latitudes, they face accelerated hydropower development, climate change, and deforestation. Alterations to the flood pulse could act synergistically with other drivers of change to promote profound ecological state change at a large spatial scale. State change occurs when an ecosystem reaches a critical threshold or tipping point, which leads to an alternative qualitative state for the ecosystem. Visualizing an alternative state for Amazonian floodplains is not straightforward. Yet, it is critical to recognize that changes to the flood pulse could push tropical floodplain ecosystems over a tipping point with cascading adverse effects on biodiversity and ecosystem services. We characterize the Amazonian flood pulse regime, summarize evidence of flood pulse change, assess potential ecological repercussions, and provide a monitoring framework for tracking flood pulse change and detecting biotic responses

Biotic indicators for ecological state change in Amazonian floodplains

Riverine floodplains are biologically diverse and productive ecosystems. Although tropical floodplains remain relatively conserved and ecologically functional compared to those at higher latitudes, they face accelerated hydropower development, climate change, and deforestation. Alterations to the flood pulse could act synergistically with other drivers of change to promote profound ecological state change at a large spatial scale. State change occurs when an ecosystem reaches a critical threshold or tipping point, which leads to an alternative qualitative state for the ecosystem. Visualizing an alternative state for Amazonian floodplains is not straightforward. Yet, it is critical to recognize that changes to the flood pulse could push tropical floodplain ecosystems over a tipping point with cascading adverse effects on biodiversity and ecosystem services. We characterize the Amazonian flood pulse regime, summarize evidence of flood pulse change, assess potential ecological repercussions, and provide a monitoring framework for tracking flood pulse change and detecting biotic responses