WaterCube: Big Data Water Science for Sustainability and Equity
Water resources and aquatic ecosystems around the world face increasing challenges and risks from climate change, natural and anthropogenic disasters, harmful algal blooms, and changes in land use. Recent advances in sensors, robotics, genomics, and computational modeling generate an amount and variety of data related to water at all scales.
These data offer a tremendous opportunity for revolutionizing scientific understanding and management of water resources; however, the challenges associated with the volume, heterogeneity, and uncertainty of the data pose a significant barrier for translating science into action. The WaterCube program was designed to prepare a competent workforce for addressing future sustainability and socio-economic challenges in water. We believe that solving complex, real-world water problems takes synergistic advancement and integration of data science, water science, and social science.
WaterCube is a National Research Traineeship (NRT) program funded by the National Science Foundation. Our goals are to:
- Train Ph.D. students who are:
- competent in the knowledge, understanding, and practice of issues at the intersection of data science, water science, and social science;
- well-versed in cross-disciplinary research collaboration; and
- well prepared for diverse career options.
- Create a convergent research paradigm that enables breakthroughs in addressing challenging, pressing water problems by merging the expertise and talent from broad backgrounds, and conversely, propels advancement of disciplines in data science, water science, and social science.
- Establish and disseminate a novel, generalizable approach to graduate training in big data-enabled water sustainability and equity.
WaterCube Traineeships: How does the program work?
The WaterCube program will provide trainees with broad technological, scientific, and cultural perspectives for addressing current and future water challenges. The program consists of:
- Coursework to provide foundational training in all three aspects of the WaterCube: data science, water science, and social science. Courses also integrate experiential learning opportunities.
- Convergent research addressing critical water issues
- Training in cross-disciplinary communication and collaboration
- Professional development experiences
- Regular seminars, symposia, and events with the WaterCube community
- Internships and international exchange opportunities
- Public outreach and communication experiences
Prospective or first year Ph.D. students are eligible to apply to the program. Students enroll in a home department at MSU and work with a WaterCube faculty trainer (mentor). WaterCube trainees receive at least one full year of fellowship through the NRT, which includes stipend, tuition & fees, with additional years of study supported through other forms of assistantships. Trainees also receive funds for research supplies and are eligible to receive travel funding.
Monitoring, Understanding, and Mitigating Harmful Algal Blooms
The proliferation of harmful algal blooms (HABs) is one of the most pressing problems facing aquatic ecosystems worldwide. HABs deteriorate water bodies by producing potent toxins that can get into water supplies and present health hazards. Core research questions WaterCube researchers will address include: How can we monitor HABs with high spatiotemporal resolution? How can we better understand, predict, mitigate, or even prevent the onset of HABs?
WaterCube faculty working in this area: Elena Litchman, Phanikumar Mantha, Xiaobo Tan, Hayder Radha, Stephen Gasteyer, Ashton Shortridge, Bruno Basso
Bridging the Gaps between Data and Water Safety and Sanitation
The COVID-19 pandemic has highlighted now more than ever the essential water services that provide access to drinking water, hygiene and sanitation. In the U.S. alone, 2.1 million people lack access to water and sanitation and that does not include the millions who live in places where water is coming through pipes but is not potable, or where sanitation is insufficient. By integrating advanced water quality instrumentation, remote sensing, modeling, and machine learning methods, we can improve the ability to integrate data into informational and decision-making frameworks. A core research question WaterCube researchers will address is: How can we collect, analyze, and translate big data to advance water safety and public health?
WaterCube faculty working in this area: Joan Rose, Jiliang Tang, Stephen Gasteyer, Amber Pearson, Wei Zhang, Jade Mitchell
Addressing Multi-scale Water Quantity and Quality Issues
Climate change and the acceleration in land-water management activities are pushing freshwater systems to tipping points in many global regions. Emerging big data from expansive sensor networks, remote sensing, climate projections by Earth System Models, and data on socio-economic changes have been rarely combined to better understand the intricately intertwined interactions among natural and human systems and address water-related problems. Core research questions WaterCube researchers will address include: How are the complex interactions among climate, water, human systems altering water availability and demands? How might we utilize big data and integrate social sciences into water systems modeling to better understand and address emerging water problems?
WaterCube faculty working in this area: Yadu Pokhrel, Phanikumar Mantha, Pang-Ning Tan, Sandra Marquart-Pyatt, Ashton Shortridge, Lifeng Luo, Pouyan Nejadhashemi
Designing Selective Fish Passage That Accommodates Indigenous Perspectives
The fragmentation of the majority of the world’s watercourses by dams and road-crossings is considered one of the greatest threats to global aquatic biodiversity, particularly fishes. However, dams are also focal points of human activity, providing critical services, including fisheries, flood control, power generation, drinking water supply, and invasive species suppression. A conundrum exists—how to reconnect the world’s riverine ecosystems to lakes and oceans to restore fish populations while preventing deleterious impacts of the loss of dams? A core research question WaterCube researchers will address is: How do we design and construct smart selective fishways to achieve the passage and blockage needs of diverse communities of stakeholders?
WaterCube faculty working in this area: Michael Wagner, Phanikumar Mantha, Xiaobo Tan, Jiayu Zhou, Stephen Gasteyer, Parisa Kordjamshidi
Advancing Community-based Participatory Research to Support Equitable Outcomes in Public Health
Lack of investment in infrastructure can result in water crises and promote a culture of fear and distrust in institutions that are counted on to protect public health and wellbeing. Regulatory standards, however, are not driven by public health measures but often by economic feasibility and practicality for local implementation. These are fundamentally political processes that affect the everyday lives of the public but for vulnerable populations who have experienced other forms of systemic oppression, infrastructure failures can increase distrust not only in government but science as well.
Public trust and investment in science are increasingly precarious but public participation in scientific efforts can increase trust in science, democratic inclusiveness in regulatory processes, and sense of control over one’s personal, family, and community well-being. A core research question WaterCube researchers will address is: How does community-based participatory research advance water science and support equitable outcomes for minoritized youth and marginalized communities?
WaterCube faculty working in this area: Jennifer Carrera, Courtney Carignan, Joan Rose, Xiaobo Tan, Wei Zhang
For more information, please contact:
Dr. Erin Dreelin, Program Coordinator (dreelin@msu.edu)