Benjamin L. Ruddell - US grants

Considering the growing importance of water resources issues around the globe, this project addresses the need to train the current and future generations of teachers, students and general public to use cyberinfrastructure (CI) to address water related issues. The overall goal of this project is to develop a prototype CI for data access and sharing, simulation modeling and visualization to address water related issues, and then show that this CI can be used as a platform to train educators, students and the general public. Specifically, this proposal: (i)bis developing WaterHUB (by utilizing Purdue HUBZero platform) to include prototype tools for accessing, analyzing and visualizing water resources geospatial and temporal data; (ii) is developing a prototype framework for collaboration among educators to develop, publish, review and share training material for using cyberinfrastructure to address water issues; (iii) is evaluating and assessing the effectiveness of the proposed cyberinfrastructure and the collaborative framework through application at three universities (Purdue, Arizona State U, Jackson State U); and (iv) is building community through workshops and training sessions for teachers, students, policy makers and the general public. This demonstration project will show proof-of-concept for a scalable mechanism to create water resources awareness among a much broader community by incorporating the needs of a diverse population through collaboration with faculty and students at three geographically and culturally diverse research institutions in the United States. External evaluation and assessment of all aspects of this demonstration project including community input through workshops and training sessions will provide the basis for developing a plan for scaling up the project.

Intellectual Merit
This proposal involves a group of hydrologists, computer scientists, an educational expert and an environmental researcher at three geographically and culturally different institutions (Purdue, Arizona State and Jackson State) to develop a CI for data access, analysis and visualization to study water resources issues including collaboration for teaching and training. Specifically, this proposal will use a proven CI, initially developed for nanotechnology (nanoHUB.org that has more than 100,000 users annually), to develop a customized cyber environment for water resources called WaterHUB. The core nanohub CI, known as HUBZero, is inadequate to handle large spatial and temporal datasets that are typical in water related studies, and lacks the capability to link such data with data driven, computationally intensive hydrologic simulations. This work will add the much needed data and coupling of data and high performance computing to HUBzero to support water resources studies. WaterHUB will be the first of its kind in the water resources community that will provide a collaborative web-based platform for research and education at all levels including P-12. The prototype WaterHUB is being developed to address three basic questions related to water storage, human impacts and energy fluxes by using public domain data and simulation models to address water related problems. This project also involves a comprehensive evaluation and assessment plan that will quantify the effect of cyber-enabled pedagogy on students learning. This assessment is critical in terms of evaluating the attributes of existing and future CI to meet the needs of next generation cyber learners and researchers.

Broader Impacts
The proposed WaterHUB is providing the much needed cyber environment to train and educate the current and next generation of citizens on water related issues. The activities will specifically target: (i) P-12 teachers and students through collaboration with Purdue?s INSPIRE institute; (ii) undergraduate and graduate students at three research universities; (iii) state and federal decision makers in the state of Indiana. Through collaboration with Jackson State and Arizona State universities, under-represented students are being trained through workshops and summer internships to use the latest cyber technology for exploring water related issues. In addition, workshop gatherings will be used to develop a strategy for up-scaling this effort to include more computational tools, national and international datasets and high quality curriculum material. WaterHUB?s cyber environment to develop collaborative teaching material will enable training of teachers and students at places that have inadequate resources to develop new curriculum material for adopting cyber technology to tackle water related issues.

This project is creating a new instructional strategy and new learning materials using data- and modeling-based modules that are enabling undergraduate students to better understand cause-effect relationships, form and test hypotheses, and learn how to integrate the latest tools for better understanding of hydrologic theory and processes. Collaborators at two research universities, a liberal arts college, and Chandler/Gilbert Community College are developing and testing the educational modules, and an editorial board comprising geosciences and engineering faculty from around the USA is supervising module development and formative evaluation. The project is creating an organized community of practice to develop, share, and publish data- and modeling-driven hydrology educational modules made available through the Science Education Research Center (SERC) website.

This project is using a structured process of collaborative community curriculum development to bring together a core user community and design a system to meet the needs of a broad range of hydrology educators. It is rigorously assessing the effectiveness of the technology on students' learning outcomes by comparing traditional lecture-based instruction with data- and modeling-driven instruction designed to enhance hydrologic learning among students. This project is achieving a broad impact by piloting a model of community development, evaluation, and dissemination of hydrologic cyberlearning modules.

In the cities of the southwestern United States, regional warming combined with increasing urban populations and the resulting urban heat effect are straining limited supplies of electricity and water. Cities can be designed that are more resilient, minimizing human impacts and energy and water stresses, under scenarios of decadal warming trends. However, improved micro-scale climate models that resolve urban landscape hydrology, vegetation dynamics and patch-scale water and energy balances are needed to support the design of these resilient urban systems; funds are provided to create and validate a modeling system capable of resolving these dynamics. The tRIBS land surface hydrology model will be modified for urban environments and coupled with the vertically nested WRF 3.2 mesoscale and microclimate model. The combined model will be used to test the efficacy of different urban green-space and neighborhood designs under climate change scenarios with respect to the water and energy balance, demand for and optimal application of irrigation water, patch-scale air temperatures and humidities, and urban flooding responses. This newly coupled model will transform the design of urban neighborhoods to be quantifiably more adaptive and resilient to all types of decadal climate change.

This study will demonstrate the technical feasibility, empirical validity, and computational tractability of this approach using neighborhoods in Phoenix, AZ as case studies. The microclimate predictions of the model will be useful to predict neighborhood-level human health and social impacts, water and energy use, urban heat island effects, and urban flooding, in neighborhoods in cities around the world. The potential social benefits of this research include a research tool that can empirically validate, quantitative design of urban neighborhoods that are more resilient to climate change and other future challenges (i.e. water or energy shortages), allows the optimization of neighborhoods that minimize water and energy use, mitigate heat island impacts, and improve social and health outcomes. This modeling tool can change cities by making them adaptive by design.

It is increasingly likely that predictions of decadal climate change and land use change will yield the accurate information needed to anticipate ecosystem adaptation to human-induced change (e.g. climate variability, land use change). It is therefore essential that we develop new theories, modeling tools, and data products that are capable of predicting ecosystem adaptation to these changes, and that can anticipate how possible nonlinear thresholds will affect ecosystem structure, function, and services. A new theoretical concept is proposed to measure and predict
ecosystem sensitivity and likely adaptation. This award will provide funds to develop complex-systems theoretical approach based on information flow in observed ecological process networks, using data from NEON and existing observational networks, which will be applied to, (1) predict nonlinear transition thresholds in the multiscalar couplings between local and regional ecosystem processes by observing feedback couplings in observed ecosystem process networks, and (2) directly measure the current sensitivity of regional ecosystems in the USA to incremental changes in specific climate variables. Data from existing observational networks (e.g. FLUXNET, LTER, NEON), and the National Phenology Network (NPN) will be used to predict the sensitivity of local and regional ecosystems across the USA to specific types of forcings. This new theoretical approach is able to directly quantify ecosystem sensitivity to changes in forcings, and how nonlinear feedback patterns can help predict possible ecosystem transition thresholds.

Broader Impacts: The proposed work will create and widely disseminate a set of tools and data products that will allow ecologists across the USA to apply process network theory and information theoretic approaches to analyze ecosystem-scale environmental observatory data. This conceptual approach will be a valuable contribution to the "data analysis toolbox" being used by environmental observatories to explain ecological change and its impact on human societies for which these ecosystems represent vital life support. Graduate students and a postdoctoral scholar will be trained in the creation and application of these advanced quantitative methods in ecology and in the synthetic analysis of multi-scalar ecosystem data. The products of the theory-based models will form a critical analytical bridge between raw data collection and the environmental understanding necessary for informed resource management and policy-making in a future driven by historically unprecedented and nonlinear climate change impacts.

Western US regions are particularly vulnerable to future climate-induced environmental changes, given their scarce water resources and heavy reliance on thermoelectric power generation. As climate-related environmental events become more common, water and electricity managers will face challenges when handling vulnerabilities in the interdependent water-electricity systems. These vulnerabilities may arise because existing infrastructures were designed for a demand profile that was significantly different from what is expected in coming decades, and because the institutions that manage the systems do not yet have anticipatory governance structures that would enable them to proactively address the future. This project will develop a framework for assessing coupled water and electricity infrastructure-institution vulnerability to future climate events.

There is a need to better understand how the governing of water and electricity services from local to regional scales can be coordinated to proactively reduce future vulnerability. This project will develop (1) a cross-scale model of the water and electricity systems in the Southwest, (2) an institutional assessment of infrastructure managers, decision makers, and policies that control or impact each component of the water and electricity infrastructure, and (3) an extreme climate vulnerability assessment that joins physical infrastructure characteristics with the institutional processes that govern them. With this coupled infrastructure-institutional vulnerability assessment (4) a learning game will be developed for infrastructure managers to both teach them about the vulnerabilities and help them understand how their institutional structures can be proactively changed to improve system-wide resilience. Through a series of workshops with infrastructure managers (5) the game will be tested through visioning and scenario analysis exercises. New knowledge and methods will be created for assessing water and electricity systems that acknowledges that failure can propagate through complex systems and can start with vulnerabilities in both physical and institutional infrastructure. The project will explore how game-based learning approaches can provide researchers and managers with knowledge of the complex system and an understanding of the strategies for creating anticipatory governance for a climate-impacted future.

1509077
Qiu, Yueming

Commercial buildings are responsible for 36% of electricity consumption in the United States. Interactions among engineering, organizational, and behavioral factors and incentives determine building energy use and related environmental sustainability, and potentially cause divergence between true energy performance and theoretically possible performance. There has been increasing investment in energy efficient commercial building designs and technologies. Among the studies that conduct statistical post-occupancy evaluations (POE), there has been debate about whether "green" commercial buildings (i.e. LEED buildings) actually save energy or not, and this casts doubt on their energy sustainability. Evaluating the true energy performance of green commercial buildings requires empirical analysis of long data histories and larger sample sizes. To understand a complete picture of energy sustainability, social factors such as organizational management and occupant behaviors, as well as environmental and economic impacts of energy use, must be studied. Additionally, evaluating the effects of these factors on the timing of building energy use (i.e. peak hours versus non-peak hours) is essential to understand environmental (i.e. carbon) costs of electricity consumption. This project will conduct such holistic energy sustainability analysis using a comprehensive building energy dataset in a city (Phoenix) that is typical of energy use patterns in many of the world's rapidly growing hot and dry urban areas.

Specifically, the project will: 1) provide reliable statistical evidence of the true energy performance of green commercial buildings based on large datasets; 2) quantify the impact of green commercial buildings on power grid load profiles and electricity generation fuel mix; 3) apply surveys to quantify engineering, organizational, and behavioral factors that determine observed building energy performance; and 4) evaluate the systemic environmental and economic impacts of green commercial buildings in the Phoenix metropolitan area. The project will advance engineering research into energy sustainability of green commercial buildings through a novel "big data" empirical approach. First, this project will analyze much larger and reliable datasets of commercial buildings than previously studied, including historical electricity consumption and other key building level attributes. The dataset contains more than 700 Energy Star and LEED commercial buildings, and more than 17,000 total commercial electric customers. Second, compared to existing POE studies, this project adopts more rigorous and advanced statistical analysis including matching, panel regression, and nonparametric modelling. Importantly, this project uses much more credible control groups. Third, this project will provide the first empirically reliable evidence of how green building technologies impact environmental footprints by time of day and season, which are critical for determining environmental costs associated with electricity consumption. Finally, this project will empirically explore the interrelated factors in the coupled human-environmental systems including engineering (e.g. technical reliability and compatibility), organizational (e.g. principal-agent problem), and behavioral (e.g. bounded rationality) factors that influence the observed energy performance of commercial buildings and the impact on environmental sustainability. The insights produced may be directly implemented by practitioners including state energy policy makers, city environment planners, energy service companies, building engineers, building owners, and utility companies.

Flooding is the most damaging natural hazard in the U.S. and around the world, and most flood damage occurs in cities. Yet the ability to know when flooding is happening and communicate that risk to the public and first responders is limited. At the same time there is a surge in digitally connected technologies, many at the fingertips of the general public (e.g., smartphones). The need is for new flood information that can be generated from primary observations that are collected in exactly the right places and times to be coupled with the ability to more effectively communicate this risk to communities. This project will develop the Integrated Flood Stage Observation Network (IFSON), a system that can take in crowd-sourced information on flooding (from cameras, a smartphone app, and social media), intelligently assess flood risk (using machine learning), and communicate those risks in real time. IFSON will be scalable to any community or city and will provide a backbone for new crowd-sourced technologies.

This project will i) integrate several new technologies (each that directly engages with different communities) to provide new insights into and communication capacity around urban flooding hazards, ii) connect a range of communities to each other in near-realtime (from the general public to first responders to infrastructure managers) and develop flood sensing and avoidance capacities that can be used anywhere in the U.S. or even internationally, iii) develop new insights into how urban morphology contributes to flood risk, and iv) leverage prior funding by connecting practitioners from existing sustainability research networks and sending data to CUAHSI and eRams. Additionally, this research will develop outreach activities that will educate the public and practitioners on how flooding hazards occur, their impacts, and how to mitigate risks. The research will directly empower and engage local citizens in flood event reporting and response, and explores a concrete model for what it would mean to have a "smart and connected community" for minimizing flood risk. Although driven by a number of novel technologies and techniques, the central focus of this work is on the interface of community with technology and, in particular, how modern network technologies can engage and bring together ordinary citizens, city planners, first responders, and other local stakeholders within a shared, collaboratively constructed information space; a broad range of educational and outreach opportunities are included to engage stakeholders and amplify project impact. In addition to training students through research positions, the project will create a summer Research Experience for Undergraduates (REU) program. It will also connect with national, state, and local societies across a number of disciplines. For example, the project will work with the City of Phoenix during their Monsoon Preparedness day to educate first responders on how to use project results. Interdisciplinary course modules that show how to engage various communities (including the public, first responders, and infrastructure managers) in mitigating flood risk will be developed and disseminated. Additionally, infrastructure managers will be recruited to participate in workshops on how project data will reveal new insights into the condition of infrastructure and what strategies can be employed to reduce hazards.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.