NRT-HDR: Transdisciplinary Research and Education for Air and Water Resources Solutions in Coastal Communities

沿海社区面临前所未有的环境挑战，如频繁和加剧的洪水和干旱、水资源的不确定可获得性、有害的藻类大量繁殖以及水和空气质量的恶化。由于人口快速增长、工业发展、城市化和气候变化等复杂的社会和环境因素，很难找到与空气和水资源相关的管理挑战的解决方案。因此，为了有效应对这些挑战，未来的环境专业人员，包括工程师、科学家、政策制定者、社会科学家和教育工作者，必须深入了解自然、社会和工程系统之间的动态关系，并具有超越传统学科界限的能力。这项授予德克萨斯农工大学金斯维尔分校的国家科学基金会研究培训奖将开发一种新的研究生培养模式，以培养具有深入知识和技能的下一代环境专业人员，以解决沿海地区的环境可持续性问题。该项目将培训78名硕士和博士生，其中包括24名由NRT资助的学员，他们来自工程、计算机科学、地球科学、农业科学、环境科学、植物和土壤科学、教育和社会学。新的研究生教育模式采用跨学科的方法进行研究生培养和汇聚研究，为有效的空气和水资源管理提供信息。NRT将集中于三个研究主题：1)沿海水文与防洪；2)沿海水质可持续性；3)沿海空气质量管理。该计划开发的模式包括：1)通过新的数据科学课程、网络研讨会/研讨会系列和跨学科数据驱动研究来准备学术技能，以解决沿海地区与空气和水资源相关的问题；2)通过新的实验室课程提高专业技能发展，以增强学员在沟通、团队合作、道德和领导力方面的技能和能力；以及3)人道主义服务-学习体验，积极让学员参与真实世界的体验，并与社区利益相关者合作，以获得积极的解决方案。学员将发展和综合数据科学应用、跨学科研究、沟通、团队合作、研究道德和领导力方面的技能。该项目将利用新的课程材料和框架设计新的跨学科环境可持续性和恢复力硕士和博士课程，以便其他机构可以实施类似的研究生教育项目。NSF研究培训(NRT)项目旨在鼓励为STEM研究生教育培训开发和实施大胆的、具有潜在变革性的新模式。该计划致力于通过创新的、基于证据的、与不断变化的劳动力和研究需求保持一致的综合实习生模式，在高度优先的跨学科或趋同研究领域对STEM研究生进行有效培训。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Coastal communities face unprecedented environmental challenges such as frequent and intensified floods and droughts, uncertain availability of water resources, harmful algal blooms, and deteriorating water and air quality. Finding solutions to the management challenges associated with air and water resources is difficult due to complex social and environmental factors such as rapid population growth, industrial development, urbanization, and climate change. To effectively address these challenges, future environmental professionals, including engineers, scientists, policymakers, social scientists, and educators, must therefore have in-depth knowledge of the dynamic relationships between the natural, social, and engineering systems and an ability to transcend traditional disciplinary boundaries. This National Science Foundation Research Traineeship award to Texas A&M University-Kingsville will develop a new graduate training model to educate the next generation of environmental professionals with in-depth knowledge and skills to address coastal issues of environmental sustainability. The project will train seventy-eight (78) M.S. and Ph.D. students, including 24 NRT-funded trainees, from engineering, computer science, geosciences, agriculture science, environmental science, plant and soil science, education, and sociology.The new graduate education model adopts a transdisciplinary approach to graduate training and convergence research that will inform effective air and water resources management. The NRT will focus on three research themes including: 1) coastal hydrology and flood prevention, 2) coastal water quality sustainability, and 3) coastal air quality management. The model developed by this program includes: 1) academic skills preparation via a new data science course, a webinar/seminar series, and transdisciplinary data-driven research to solve problems associated with air and water resources in the coastal regions; 2) professional skills development via a new lab course to enhance trainees’ skills and competencies in communication, teamwork, ethics, and leadership; and 3) humanitarian service-learning experience to actively involve trainees in real-world experiences and collaborations with community stakeholders toward active solutions. Trainees will develop and synthesize skills in data science applications, transdisciplinary research, communication, teamwork, research ethics, and leadership. The project will design new interdisciplinary M.S. and Ph.D. tracks in Environmental Sustainability and Resilience with new curricular materials and frameworks so that other institutions can implement similar graduate education programs.The NSF Research Traineeship (NRT) program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.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.