Leveraging Crowdsourced Navigation Data In Roadway Pluvial Flash Flood Prediction

This dissertation develops and tests a new data-driven framework for short-term roadway pluvial flash flood (PFF) risk estimation at the scale of road segments using crowdsourced navigation data and a simplified physics-based PFF model. Pluvial flash flooding (PFF) is defined as localized floods caused by an overwhelmed natural or engineered drainage system. This study develops a data curation and computational framework for data collection, preprocessing, and modeling to estimate the risk of PFF at road-segment scales. A hybrid approach is also developed that couples a statistical model and a simplified physics-based simulation model in a machine learning (ML) model to rapidly predict the risk of roadway PFF using Waze alerts in real-time

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

Doctor of Philosophy

dissertationControlling combined sewer overflows (CSOs) is one of the greatest urban drainage challenges in more than 700 communities in the United States. Traditional drainage design typically leads to centralized, costly and energy-intensive infrastructure solutions. Recently, however, application of decentralized techniques to reduce the costs and environmental impacts is gaining popularity. Rainwater harvesting (RWH) is a decentralized technique being used more often today, but its sustainability evaluation has been limited to a building scale, without considering hydrologic implications at the watershed scale. Therefore, the goal of this research is to study watershed-scale life cycle effects of RWH on controlling CSOs. To achieve this goal, (i) the life cycle costs (LCC) and long-term hydrologic performance are combined to evaluate the cost-effectiveness of control plans, (ii) the life cycle assessment (LCA) and hydrologic analysis were integrated into a framework to evaluate environmental sustainability of control plans, and (iii) the major sources of uncertainty in the integrated framework with relative impacts were identified and quantified, respectively. A case study of the City of Toledo, Ohio serves as the platform to investigate these approaches and to compare RWH with centralized infrastructure strategies. LCC evaluation shows that incorporating RWH into centralized control plans could noticeably improve the cost-effectiveness over the life cycle of drainage infrastructure. According to the results of the integrated framework, incorporating RWH could reduce Eco-toxicity Water (ETW) impacts, but caused an increase in the Global Warming Potential (GWP). In fact, incorporating RWH contributes to avoidance of untreated discharges into water bodies (thus reducing ETW) and additional combined sewage delivered to treatment facilities (thus increasing GWP). The uncertainty analysis suggests that rainfall data (as a hydrologic parameter) could be a significant source of the uncertainty in outputs of the integrated framework. Conversely, parameters of LCIA (life cycle impact assessment) could have trivial impacts on the outputs. This supports the need for robust hydrologic data and associated analyses to increase the reliability of LCA-based urban drainage design. In addition, results suggest that such an uncertainty analysis is capable of rendering optimal RWH system capacity as a function of annual rainfall depth to lead to minimized life cycle impacts. Capacities smaller than the optimal size would likely result in loss of RWH potable water savings and CSO control benefits, while capacities larger than optimal would probably incur excessive wastewater treatment burden and construction phase impacts

Simulating and Optimizing Storm Water Management Strategies in an Urban Watershed

Land development transforms the natural landscape and impacts in stream ecosystems and downstream communities as it alters the natural flow regime. An increase in impervious areas results in higher volumes of storm water runoff, reduced time to peak, and more frequent flooding. Best Management Practices (BMP) and Low Impact development (LID) are a few of the set of measures which are used to mitigate the impact of urbanization. Peak flow, runoff volume are few of the conventional metrics which are used to evaluate the impact and performance of these storm water management strategies on the watershed. BMP are majorly used to control the flood runoff but results in the release of large volumes of runoff even after the flood wave passed the reach and LIDs are used to replicate the natural flow regime by controlling the runoff at the source. Therefore need to incorporate a metric which includes the timing and area being inundated needs to be considered to study the impact of these strategies on the downstream. My proposed research will focus on simulating the Low Impact Development (LID) techniques like permeable pavements and rainwater harvesting on an urbanized watershed using a curve number approach to quantify the hydrologic performance of these strategies on the watershed. LID, BMPs, and combined strategies are introduced for retrofitting existing conditions and their hydrologic performance is accessed based on the peak flow and a new metric Hydrologic Footprint Residence. A simulation optimization framework would be developed which identifies cost effective LID options that maximize the reduction of peak flow from the existing condition design storms while meeting budget restrictions. Further LID and BMP placement is included in the optimization model to study the impact of the combined scenario on the storm water management plans and their performance based on different storms and corresponding budget. Therefore a tradeoff can be illustrated between the implementation cost and the hydrological impact on the watershed based on the storm water management approach of using only LID and combination of LID and BMP corresponding to varied spectrum of design storm events

Coastal Stormwater Management Through Green Infrastructure: A Handbook for Municipalities

Coastal Stormwater Management through Green Infrastructure: A Handbook for Municipalities (Handbook) is designed to assist coastal municipalities within the Massachusetts Bays Program (MassBays) area to incorporate green infrastructure into their stormwater management planning as they respond to MS4 stormwater permit requirements, review development proposals, and retrofit existing municipal facilities and sites. The MassBays Program can assist those municipalities in using this Handbook to facilitate the use of green infrastructure and address stormwater runoff

Morphologic characterization of urban watersheds and its use in quantifying hydrologic response

2009 Summer.Covers not scanned.Includes bibliographical references.Print version deaccessioned 2022.Current methods for hydrologic characterization of urban watersheds and analysis of the impacts of urbanization are primarily based on the description of imperviousness and how changes in this characteristic affect storage, infiltration, and runoff generation. The morphology of urban watersheds and the effects of urbanization on the structure of the drainage system have been much less studied. The overarching objectives of this study are to develop methodologies to characterize the morphology of urban drainage systems including the hillslopes, streets, pipes, and channels and to use this characterization to model the hydrologic response of the watershed. These objectives are accomplished through: (a) an exploration of potential applications of morphologic theories in the characterization of urban watersheds and the impacts of urbanization; (b) the development and testing of a methodology to generate urban terrains (i.e. a raster representation of the topography) in which the effects of conduits typically observed in urban areas are represented; and (c) the development and testing of a new rainfall-runoff model called the U-McIUH (Urban Morpho-climatic Instantaneous Unit Hydrograph). The model is based on the morpho-climatic instantaneous unit hydrograph theory, in which the hydrologic response is identified from the spatial structure of the watershed and the properties of the storm event. The morphologic approach adopted reveals significant impacts of urbanization on the internal structure of natural watersheds at a wide range of scales. This finding is relevant when building stormwater models intended to simulate and compare the pre- and post-development catchment response. The morphologic impacts should be incorporated into stormwater models through the redefinition of model parameters that characterize both the channelized and unchannelized portions of the catchment when the urbanized scenario is simulated. This research also shows the importance of incorporating artificial conduits into urban terrain for hydrologic modeling. A new method to incorporate the artificial conduits into the DEM based on the real elevation of these conduits proved to be superior to other previously available methods because it better represents the flow directions and flow paths. Finally, the new rainfall-runoff model developed in this study fills an existing gap in the field of distributed stormwater modeling. It provides a more thorough treatment of the flows in minor conduits and unchannelized portions of the watershed, which enhances the simulations of runoff accumulation that are traditionally used in conceptual models. The model is parsimonious and uses a simplification of kinematic wave routing that considers the dependence of the unit hydrograph on rainfall intensity and the effect of upstream contribution on the travel times without explicitly solving the flow equation at each cell for each time step. This simplification reduces the complexity of the model computations while still producing reasonable model performance

Adaptive measurements of urban runoff quality

An approach to adaptively measure runoff water quality dynamics is introduced, focusing specifically on characterizing the timing and magnitude of urban pollutographs. Rather than relying on a static schedule or flow‐weighted sampling, which can miss important water quality dynamics if parameterized inadequately, novel Internet‐enabled sensor nodes are used to autonomously adapt their measurement frequency to real‐time weather forecasts and hydrologic conditions. This dynamic approach has the potential to significantly improve the use of constrained experimental resources, such as automated grab samplers, which continue to provide a strong alternative to sampling water quality dynamics when in situ sensors are not available. Compared to conventional flow‐weighted or time‐weighted sampling schemes, which rely on preset thresholds, a major benefit of the approach is the ability to dynamically adapt to features of an underlying hydrologic signal. A 28 km2 urban watershed was studied to characterize concentrations of total suspended solids (TSS) and total phosphorus. Water quality samples were autonomously triggered in response to features in the underlying hydrograph and real‐time weather forecasts. The study watershed did not exhibit a strong first flush and intraevent concentration variability was driven by flow acceleration, wherein the largest loadings of TSS and total phosphorus corresponded with the steepest rising limbs of the storm hydrograph. The scalability of the proposed method is discussed in the context of larger sensor network deployments, as well the potential to improving control of urban water quality.Key PointsAn Internet‐enabled sensor node autonomously adapts to weather forecasts and hydrograph features to collect water quality samplesFirst flush was not observed and peak loadings were primarily driven by erosion and flashinessCompared to present methods, our framework significantly reduces manpower and resource requirements in the study of water quality dynamicsPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135503/1/wrcr22370.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135503/2/wrcr22370_am.pd

Study of spatiotemporal rainfall structure and optimized local radar rainfall application to urban watershed, Louisville, Kentucky, 2010-2014.

In urban areas, a prevalence of combined sewer systems (CSS) exist that carry both storm water runoff and sanitary sewer flows in a single pipe, these system are considered combined sewers. In the absence of rainfall-runoff most of these systems function adequately, however CSS capacity is typically inadequate to carry peak stormwater runoff volume. In order to minimize sewage flooding into streets and backups into homes and businesses, most CSSs (as well as separate sanitary sewer systems) are designed to overflow into surface waters such as streams and rivers, lakes and seas. This occurrence is considered a combined sewer overflow (CSO) event and has a critical impact on urban aquatic environment and degrades downstream water quality. This investigation provides a framework for the application of radar-rainfall data to estimate the characteristics of rainfall events that produce a CSO event. The process addresses an urban sewer-shed, denoted as CSO 130, located in Louisville, Kentucky (USA). The characteristics of each heavy rainfall event; total volume, intensity, duration, continuity, and storm types govern the overflow in the approximately 13-ha (30-ac) sewer-shed. In urban hydrology, accurate fine resolution temporal and spatial rainfall observations is a key factor for managing urban hydrologic systems and forecasting storm water runoff, particularly in the current era of higher variability in recent rainfall events. To study this issue, rain gauge data from a ground based rainfall measurement network operated by the local stormwater management agency, Metropolitan Sewer District (MSD), in Jefferson County Kentucky is studied. Rainfall spatial characteristics are evaluated through correlation spectrum by distance and this reveals a spatial rainfall variation concave relationship. Besides, the event based rainfall classification has been performed to provide a context for identification and description of rain events that may be useful as guidance for urban stormwater management. Based on this study, the limitation of the one dimensional rainfall monitoring system has been revealed by the severe variation of the rainfall characteristics. In order to overcome this issue, the reliable areal rainfall measurement with fine spatiotemporal resolutions is urgently required to investigate the urban hydrologic issues. The radar data utilized in this study are from the weather radar associated with the National Weather Service (NWS) Forecast Office Louisville, Kentucky (denoted by call letters KLVX) and rain gauge data are from a regional network. The study applies fine resolution radar rainfall in this urban hydrologic system to reveal insights for planning CSO control and prevention under a range of rainfall event regimes. Weather radar data from the local NWS site is optimized using support vector classification (SVC) and serves as rainfall input for the urban sewer-shed. The radar-rainfall data were optimized through a comparison with NWS radar rainfall and a gauge network, the local stormwater and sewer agency. The optimized radar rainfall estimation has the highest spatiotemporal correlation in quarter hourly temporal resolution. The rainfall and flow events are defined using the criteria proposed by United States Environmental Protection Agency (USEPA) to define the physical continuity of natural rainfall processes and the corresponding hydrologic response. The optimized rainfall product has applied to the small scale urban watershed, CSO130 to investigate the sewer water overflow. In this setting, the extremity of the rainfall governs the overflow mainly with volumetric rainfall in the event based rainfall and its corresponding overflow with other decisive factors; rainfall intensity, duration, rain type as well as rainfall continuity. Discriminant analysis is introduced to classify these precipitation factors. The objective of this study is that downscaled hydrologic application to the places where the sub-hourly rainfall data is required such as a complex urban watershed in order to investigate the fast inundated floods, overflows in the artificial watersheds or any hydrologic preparation

Evaluating the Impact of Land Use Changes, Drivers of TMDL Development, and Green Infrastructure on Stream Impairments

Despite the water quality improvements and regulatory advancements over the last 50 years since the enactment of the Clean Water Act, water bodies within the United States are still impaired for a broad range of contaminants from non-point source pollution. Improving watershed management approaches to meet this challenge will require a greater understanding of (1) how changes within a watershed, such as changing land use, impact stream water quality, (2) what influence socioeconomic, spatial and political factors may have on the progress towards meeting water quality goals, such as those set within Total Maximum Daily Loads (TMDLs), and (3) how specific best management practices can be designed to address water body impairments. First, land use within a watershed is known to have a direct impact on downstream water quality; however, temporal dynamics of these relationships are ill-defined. This is an important gap as management approaches are largely compartmentalized among land use types. Additionally, while management plans can span several decades, the impact of land use changes on water quality is often overlooked. Therefore, this dissertation evaluates land-use changes and their relationship to discharge and water quality trends at stream gages across the U.S. Second, the TMDL program is the primary regulatory lever in the U.S. for addressing non-point source pollution, but its implementation has been uneven across states. This could be due to the diverse socioeconomic, spatial, and political factors of each state. This dissertation therefore seeks to define the influence of these factors on indicators of TMDL progress. Finally, at the site level, management actions to meet regulatory permits include the use of green stormwater infrastructure to capture, treat, and infiltrate runoff at the source. One of the largest sources of impairments in the TMDL program is temperature; however, it is unclear the degree to which green stormwater infrastructure in series mitigates runoff temperatures during summer storms. To address this gap, this dissertation analyzes the temperature mitigation potential of interconnected green infrastructure practices through field observations. Altogether, the outcomes of this dissertation help to advance our understanding of how watershed planning, regulatory, and engineering actions affect downstream water quality