My major research interests encompass the broad interdisciplinary spectrum of water resources, environmental, climatological, ecological, and socio-economical sciences and engineering. I have developed a highly interdisciplinary research and teaching platform, “Ecological-Water Resources Engineering Lab (EWREL)”, incorporating topics related to the coupled human-natural systems and sustainability sciences/engineering from at-site to regional to global scales. The research emphasizes the hydrological, biogeochemical, ecological and socio-economic aspects of water resources engineering. Specifically, current research activities include developing robust, user-friendly engineering models to predict and assess (I) wetland and forest greenhouse gas (GHG) fluxes and carbon sequestration; (II) stream/river water quality and ecosystem health; and (III) urban stormwater flooding and drainage sustainability under extreme climate events. The long term research goal is to formulate appropriate ecological engineering principles, guidelines and designs by incorporating biological, ecological and socio-economical sciences into the traditional physics/chemistry based water resources engineering for achieving sustainability at variable time and space scales under a changing climate, sea level, population, land use/cover, and socio-economic scenarios.
1. Project Title: CAREER: Robust Modeling and Predictions of Stream Water Quality and Ecosystem Health.
Funding Agency: National Science Foundation (NSF); Duration: 2015-20.
PI (single): Omar I. Abdul-Aziz.
Funding Amount: $500,000.
Summary: The goal of this research is to investigate and robustly predict the dynamics of stream water quality and ecosystem health in complex urban-natural basins (e.g., coastal urban centers). The central research hypothesis is that urban stream biogeochemical and ecological processes follow emergent similitude, scale-invariant patterns and organizing principles, which will lead to spatiotemporally robust predictions of water quality and ecosystem health. Specific research objectives are to (1) identify the dominant controls and quantify relative linkages of stream water quality and ecosystem health variables in relation to the hydro-climatic, watershed and land use, in-stream, and coastal drivers/stressors; (2) investigate the similitude (parametric reductions), scaling laws (emergent patterns), and organizing principles for stream water quality and health variables; and (3) formulate informatics based empirical (i.e., data-driven) and mechanistically based behavioral models as ecological engineering tools to obtain spatiotemporally robust predictions of urban stream water quality and ecosystem health. The integrated educational objective is to develop an inductive-learning based interdisciplinary Ecological Engineering Pedagogy (EEP); in order to (1) increase retention of undergraduates and graduation of minority students in relevant STEM majors, (2) increase graduate students specializing in the emerging paradigm of ecological engineering, and (3) increase the number of K-12 students actively pursuing STEM educations/careers. The research will be primarily conducted in South Florida, a living laboratory and hot-spot for climate change and sea level rise; considering the region a prototype, case study of complex urban-natural environments around the world. The research will also utilize nationally available data for other coastal urban centers (e.g., New York, Los Angeles, Houston), incorporating hydro-climatic, biogeochemical and ecological gradients across the U.S. coasts.
The research will employ a data-analytics and informatics framework to achieve mechanistic understanding on the dominant controls of urban stream water quality and ecosystem health processes. It seeks to unravel the biogeochemical-ecological similitude and scaling laws for urban streams by deriving and utilizing appropriate dimensionless functional groups, which will identify the different environmental regimes and organizing principles of water quality and ecosystem health. The scale-invariant patterns and emerging organizing principles will help to formulate parsimonious empirical and mechanistic behavioral models that, with nominal calibrations, can provide spatiotemporally robust predictions of stream water quality and health indicators. The effort will utilize inductive learning methods to develop EEP case studies, involve minority undergraduates in research, and formulate simple Excel tools for K-12 students. Research outcomes will be shared with relevant agencies (e.g., Cities, County, NGOs) to improve their stream water quality and health management strategies. The EEP case studies will be utilized to teach two new interdisciplinary courses (developed by the PI): Ecohydrological Engineering (undergraduate) and Ecological Engineering (graduate). Research and educational outcomes will be broadly disseminated through journal publications, conference presentations, graduate theses/dissertation, reports, YouTube, and a project website. Local and regional high school students and teachers will be involved with the research-education by leveraging current and developing new collaborations.
2. Project Title: Ecological Similitude and Scaling for Robust Modeling and Predictions of Ecosystem Carbon, Water and Energy Fluxes.
Funding Agency: National Science Foundation (NSF); Duration: 2017-20.
PI (single): Omar I. Abdul-Aziz.
Funding Amount: $299,999.
Summary: The goal of this research is to discover the similitude patterns and scaling laws of ecosystem carbon, water and energy fluxes, and formulate robust models to predict the fluxes at variable time and space scales. The underlying hypothesis is that the ecosystem fluxes follow emergent ecological similitude and scaling laws, which will lead to robust estimation and predictive models. The specific research objectives are to (1) identify the dominant drivers and quantify the relative linkages of ecosystem carbon (CO2), latent heat (LE) and sensitive heat (H) fluxes with the relevant climatic, hydrologic and ecological variables at different time and space scales; (2) investigate similitude (parametric reductions), formulate meaningful dimensionless groups, and develop scaling laws (emergent patterns) for the ecosystem fluxes; and (3) formulate spatiotemporally robust empirical models for predicting the ecosystem fluxes from diverse ecosystems. The research will utilize the AmeriFlux data of fluxes, climate, environmental, and ecological variables for different time-scales (e.g., hourly, daily, weekly, monthly, yearly) and periods (e.g., 2000-2015) at numerous sites (above 100) across America, representing gradients of hydro-climatic, biogeochemical, and ecological processes. The research objectives will be achieved by conducting dimensional analysis and empirical modeling, which has successfully been applied in fluid mechanics, hydraulic engineering and stream ecology. The research builds on a previous NSF project of the PI on wetland biogeochemical similitude and scaling (CBET-1336911) to robustly predict wetland greenhouse gas fluxes by using chamber-based field data. The proposed project will use flux tower-based eddy-covariance data (AmeriFlux) to generalize the similitude, scaling and robust modeling hypothesis across diverse ecosystems (e.g., deciduous forests, evergreen needleleaf forests, rain forests, grasslands, croplands, wetlands) at variable time (hour to year) and space (site, region, continent) scales.
The ecosystem fluxes have traditionally been predicted using complex process-based models that are often highly parameterized (high uncertainty), requiring a site-specific calibration for reliable predictions. The proposed research will employ a data-analytics and informatics framework to achieve mechanistic insights into the dominant drivers of the carbon, water and energy fluxes from many diverse ecosystems at variable time and space scales. The mechanistic insights will be utilized to identify the ecological similitude and emergent scaling laws by deriving dimensionless functional groups or numbers. Critical thresholds of the dimensionless ecological numbers will unravel fundamental scientific information by identifying different environmental regimes of the ecosystem fluxes. The scale-invariant patterns will lead to parsimonious empirical models that can provide spatiotemporally robust predictions of the ecosystem fluxes. The scaling laws and empirical models can also be utilized as the generalized data-benchmarks and organizing (or guiding) principles to develop process-based models for reliable predictions of the ecosystem fluxes under a changing climate and environment. The research will significantly advance the scope of ecological engineering beyond the paradigm of streams, rivers and wetlands to expand on the engineering and management of terrestrial carbon, water and energy fluxes. The transformative research will promote environmental sustainability by contributing rare insights, profound understanding, and broad knowledge into the emergence (similarity and scaling) patterns of ecosystem carbon, water and energy fluxes. Robust, parsimonious models can be utilized as simple, scale-independent engineering tools to predict the ecosystem fluxes across a wide range of spatial and temporal scales. Research outcomes will be broadly disseminated through journal publications, conference presentations, graduate dissertations, reports, YouTube videos, and an open-access project website. The research findings will be utilized to teach two interdisciplinary courses, Ecohydrological Engineering (undergraduate) and Ecological Engineering (graduate), using inductive learning methods. High school students and teachers will also be involved with the research through outreach. The project will hire two Ph.D. students and engage many undergraduate students, giving priority to the minority and female students. The project activities at WVU (an EPSCoR institution) will further strong participations of the economically disadvantaged groups and minorities in U.S.A.
3. Project Title: Expanding Blue Carbon Implementation: Increasing GHG Model Application in Tidally Restricted and Restored New England Salt Marshes.
Funding Agency: National Oceanic and Atmospheric Administration (NOAA)’s National Estuarine Research Reserve System Science Collaborative Program; Duration: 2015-19.
Collaborative PIs: Omar I. Abdul-Aziz (WVU); Jianwu Tang (Marine Biological Laboratory, MA); Kevin Kroeger (USGS Woods Hole, MA); Serena Moseman-Valtierra, (University of Rhode Island); Stephen Emmett-Mattox (Restore America’s Estuary).
Funding Amount: $750,000.
Summary: Blue carbon storage –carbon sequestration in wetlands –can help coastal managers and policymakers to achieve broader wetlands management, restoration, and conservation goals by, among other ways, securing payment for carbon credits. The Waquoit Bay National Estuarine Research Reserve (WBNERR) has been at the forefront of blue carbon research and end user engagement. WBNERR has found that while end users are becoming more interested in blue carbon opportunities, they are limited by their concerns about the transaction costs of realizing those opportunities. Use of models and readily available data such as temperature, vegetation type, and salinity can greatly reduce the transaction costs to bring restoration projects into a marketplace. WBNERR proposes to work with end users to greatly enhance the applicability of an existing model to accurately predict the complex process of green house gas (GHG) exchange across wide range coastal wetlands using a small number of readily accessible environmental and ecological variables. Additionally, the team proposes to explore the blue carbon-related information needs of end users and deliver resources to address those needs, including providing a case example of a feasibility analysis to seek carbon credits from a restoration project and teacher and decision-maker tools. This project will help WBNERR to maintain its leadership in climate issues and continue to support collaborative science to address local and national end user priorities.
4. Project Title: Investigation of Wetland Biogeochemical Similitudes and Scaling for Robust Predictions of Greenhouse Gas Emissions and Carbon Sequestration.
Funding Agency: National Science Foundation (NSF); Duration: 2013-16.
PI (single): Omar I. Abdul-Aziz.
Funding Amount: $146,169.
Summary: The objectives of this research are to (i) investigate and unravel similitudes (parametric reductions), spatiotemporal scaling patterns, and different environmental regimes of wetland greenhouse gas (GHG) emissions and carbon sequestrations; and (ii) formulate spatiotemporally robust models for predicting wetland GHG emissions and carbon sequestration across different climatic, hydrologic, biological, ecological, and biogeochemical gradients. A fundamental hypothesis of wetland GHG emissions and carbon sequestration following distinct biogeochemical similitudes and robust scaling relationships will be tested by conducting dimensional analysis and empirical modeling, which has successfully been applied in fluid mechanics, hydraulic engineering, and stream biogeochemistry/ecology. Robustness of the scaling relationships will first be determined by deriving analytical, truly dynamic sensitivity coefficients and uncertainty measures and quantifying them with field data. Scaling robustness will also be evaluated by comparing scaling parameters (coefficients and exponents) estimated with data from different seasons and locations representing a gradient of hydro-climatic, biogeochemical, and ecological processes. This research primarily leverages the PI's field data collections for major wetland GHGs (CO2, CH4, and N2O) and environmental parameters, model developments, and knowledge formation underway in a collaborative project funded by the National Oceanic and Atmospheric Administration (NOAA). It also utilizes wetland biogeochemistry and GHG flux data collected by other collaborators through chamber-based field campaigns across the U.S. East Coast.
The research targets to generate a fundamental body of knowledge and insights into the wetland biogeochemical emergence (similarity) patterns, identifying different environmental regimes and associated transition thresholds of GHG emissions and carbon sequestrations. Modeling of wetland GHG emissions has been an extremely challenging undertaking. Available models are mostly mechanistic and site-specific in nature, often failing to provide predictions that are relatively robust in time and space. To address this challenge, wetland biogeochemical similitudes and scaling laws will be investigated by employing analytical and empirical methods successfully applied in other branches of earth sciences and engineering. Improved understanding of similitudes and scaling is expected to lead to robust, parsimonious modeling and predictions of GHG emissions and carbon sequestration from diverse wetland ecosystems under a changing climate, sea level, and land use. The research on biogeochemical similitudes and scaling is anticipated to provide new insights into overall ecosystem carbon dynamics. The idea is potentially applicable to identify, understand, and predict robust patterns of carbon sequestration and GHG emissions from the terrestrial and marine ecosystems. The research should aid carbon management in wetland ecosystems around the world by unraveling fundamental scientific information and providing scale-independent engineering tools. Research outcomes will be broadly disseminated through peer-reviewed publications, presentations, workshops, reports, public meetings, open media (e.g., YouTube); and transferred to the coastal decision makers by leveraging the PI's current NOAA collaborative project-team of wetland scientists, engineers, economists, reserve managers, stakeholders, and NGOs. The research findings will be incorporated into education by designing inductive learning-based graduate and undergraduate courses at FIU (a large minority institution with around 59% Hispanic/Latino and 13% African-American students) and involving high school teachers and students. The research provides complementary funding for a current doctoral student at FIU and a potential undergraduate summer intern from the minority students.
5. Project Title: Carbon Management in Coastal Wetlands: Quantifying Carbon Storage and Greenhouse Gas Emissions by Tidal Wetlands.
Funding Agency: National Oceanic and Atmospheric Administration (NOAA)-NERRS; Duration: 2011-15.
Collaborative PIs: Omar I. Abdul-Aziz (FIU); Jianwu Tang (Marine Biological Laboratory, MA); Kevin Kroeger (USGS Woods Hole, MA); Serena Moseman-Valtierra, (University of Rhode Island); Stephen Emmett-Mattox (Restore America’s Estuary).
Funding Amount: $1,300,000.
Summary: The scientific goals are to develop and apply new techniques to quantify greenhouse gas (GHG) emissions and carbon (C) sequestration in coastal marshes, and to understand processes to predict fluxes across a range of environmental settings and under conditions of future change. By developing a user-friendly ecosystem model of GHG emissions and C sequestration in tandem with field experiments, our research will quantify the impacts of wetland restoration efforts and provide tools to guide policy and economic decisions. Collaborative learning principles will be used to connect the science investigators and key end-users to ensure that the latter help guide the research by providing feedback over the life of the project. Products of this study will include: 1) a GHG offset protocol and guidance for coastal wetlands, 2) a model for project developers and municipal officials that can be used to estimate a project’s GHG potential, including the effect of nitrogen (N) on the outcome, and 3) an analysis of the GHG and economic impact (positive or negative) of several realistic restoration and development scenarios. The primary user community of this research (collaborators on the project) will be developers of coastal wetland protocols and economic assessments of wetland services. The secondary users will be the restoration community, coastal managers, water quality managers, land managers and stakeholders involved in climate change or N pollution management.
6. Project Title: Florida Public Hurricane Loss Model Maintenance to Estimate Losses from Freshwater Flooding.
Funding Agency: Florida State Office of Insurance Regulations and International Hurricane Research Center. Duration: 07/01/2017 – 06/30/2018 (To be renewed each year through 2020 and beyond).
PI: Omar I. Abdul-Aziz (WVU).
Funding Amounts: $80,307.
Summary: Freshwater (rainfall-fed) flood modeling in large-scale urban-natural basins during extreme rainfalls and sea levels. See below for details.
7. Project Title: Florida Public Hurricane Loss Model: Enhancements to Estimate Losses from Storm Surge and Flooding: Freshwater Flooding Component.
Funding Agency: State of Florida Office of Insurance Regulations; Duration: 2013-17.
PIs: Shahid Hamid (Lead, FIU School of Business); Omar I. Abdul-Aziz (WVU); Keqi Zhang (FIU Earth & Environment); Shu-Ching Chen (FIU School of Computing and Information Sciences); Steve Cocke (Florida State University Center for Ocean-Atmospheric Prediction Studies); Kurtis Gurley (University of Florida Civil & Coastal Engineering); Jean-Paul Pinelli (Florida Institute of Technology Civil Engineering); Andrew Kennedy (University of Notre Dame Civil & Environmental Engineering).
Funding Amount: $575,435 (Dr. Abdul-Aziz's portion).
Summary: The overall goal of this research is to develop an operational model to predict stormwater (i.e., rainfall-fed freshwater) flooding of inlands during extreme climate events (e.g., hurricanes, tropical storms). Specific objectives are to (1) analyze frequency, duration, and intensity of extreme rainfall events (design storms); and (2) develop a process-based freshwater flood model to predict stormwater inundation for the coastal basins during extreme climate events. The fine spatial scale information on flooding depth will then be used to estimate associated structural damage functions by other collaborators of the project. We are building the FEMA certified, urban hydrology model of SWMM (http://www.epa.gov/nrmrl/wswrd/wq/models/swmm/) for different Florida basins to predict spatially explicit representation of stormwater inundation (depth). SWMM models drainage networks as a series of nodes (typically representing large changes in hydraulic head) connected by links (e.g., open channels, pipes). We have successfully calibrated SWMM for the Miami River Basin of Florida using historical data and quantified sensitivities of stormwater runoff to climate, hydrologic, and land use parameters.
8. Project Title: Developing a hydrologic model to predict fate and transport of reactive contaminants in the Savannah River Basin, Georgia, U.S.A.
Funding Agency: US Department of Energy (DOE) through the FIU Applied Research Center; Duration: 2014-15.
Subproject PI: Omar I. Abdul-Aziz; Lead PI: Leonel Lagos (FIU ARC)
Funding Amount: $33,675.