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

沿海社区面临着前所未有的环境挑战，如频繁和加剧的洪水和干旱、水资源的不确定性、有害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。 为了有效地应对这些挑战，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，并能够超越传统的学科界限。这个国家科学基金会研究培训奖给得克萨斯州A M大学金斯维尔将开发一个新的研究生培训模式，以教育下一代的环境专业人员，深入的知识和技能，以解决环境可持续性的沿海问题。该项目将培训78名硕士。和博士新的研究生教育模式采用跨学科的方法进行研究生培训和融合研究，为有效的空气和水资源管理提供信息。NRT将专注于三个研究主题，包括：1）沿海水文和防洪，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的数据驱动研究来解决沿海地区空气和水资源相关问题的学术技能准备; 2）通过新的实验室课程来提高学员在沟通，团队合作，道德和领导方面的技能和能力的专业技能发展;和3）人道主义服务学习经验，积极让学员参与现实世界的经验，并与社区利益相关者合作以寻求积极的解决方案。学员将开发和综合数据科学应用，跨学科研究，沟通，团队合作，研究道德和领导能力的技能。该项目将设计新的跨学科的MS。和博士在环境可持续性和恢复力的轨道与新的课程材料和框架，使其他机构可以实施类似的研究生教育计划。NSF研究培训（NRT）计划的目的是鼓励开发和实施大胆的，新的潜在变革模型STEM研究生教育培训。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相一致的综合培训模式，在高优先级的跨学科或融合研究领域对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价值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.