Hydroinformatics education – the Water Informatics in Science and Engineering (WISE) Centre for Doctoral Training

Abstract

Abstract. The Water Informatics in Science and Engineering Centre for Doctoral Training (WISE CDT) offers a postgraduate programme that fosters enhanced levels of innovation and collaboration by training a cohort of engineers and scientists at the boundary of water informatics, science and engineering. The WISE CDT was established in 2014 with funding from the UK Engineering and Physical Sciences Research Council (EPSRC) amongst the universities of Bath, Bristol, Cardiff and Exeter. The WISE CDT will ultimately graduate over 80 PhD candidates trained in a non-traditional 4-year UK doctoral programme that integrates teaching and research elements in close collaboration with a range of industrial partners. WISE focuses on cohort-based education and equips the PhD candidates with a wide range of skills developed through workshops and other activities to maximise candidate abilities and experiences. We discuss the need for, the structure and results of the WISE CDT, which has been ongoing from 2013–2022 (final year of graduation). We conclude with lessons learned and an outlook for PhD training, based on our experience with this programme.

Advancing Hydroinformatics and Water Data Science Instruction: Community Perspectives and Online Learning Resources

“…Hydroinformatics was initially taught in the mid-1990s to enable engineers to apply information technology to complex water problems (Abbott et al, 1994). Specific programs have since developed including courses for professionals (Popescu et al, 2012) and graduate students (Burian et al, 2013) and complete doctoral programs (Wagener et al, 2021). However, hydroinformatics courses remain limited, and to gain informatics skills, students often rely on technology incorporated into traditional hydrology courses, pursue self-learning (e.g., online courses, tutorials, etc.…”

“…Training in data science is typically separate from domain sciences; however, data science curricula cannot adequately address domain knowledge, so students are expected to rely on their own "substantive expertise" (Grus, 2015). Voices in industry and academia are calling for well-rounded and technology-literate water scientists (Chen and Han, 2016;McGovern and Allen, 2021), which may be achieved by packaging informatics and/or data science topics with realworld water science applications (Gibert et al, 2018;Wagener et al, 2021). In this paper, we use information gathered from instructors to understand how courses are being taught, what techniques are successful, and what would be useful going forward.…”

“…Instructors also reported difficulties with determining the best formats and technologies for rapidly pivoting to online instruction and the time-consuming nature of creating high quality online content. Reduced interaction and the time required for instructors to develop content are established drawbacks to online learning (Habib et al, 2019;Wagener et al, 2021), especially with the rapid shift that occurred in 2020 (Godber and Atkins, 2021;Rapanta et al, 2021).…”

“…Without training, students are unprepared to work or conduct research centered around large and complex data, questions, and tools (Merwade and Ruddell, 2012). To meet this need, hydroinformatics and water data science have been growing as specific topics of instruction, both in university programs and in community education settings (e.g., Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Virtual University and University of Washington WaterHackWeek) (Popescu et al, 2012;Burian et al, 2013;Wagener et al, 2021). In parallel, incorporation of technical tools in traditional water science courses is growing, though uptake has been uneven and lags behind what many see as needed (Habib et al, 2019;.…”

An open web‐based module developed to advance data‐driven hydrologic process learning

“…As demands on hydrologists have grown, so have calls to enhance hydrology education at the upper division and graduate levels to adequately prepare students for both research and industry (Merwade & Ruddell, 2012;Ruddell & Wagener, 2015;Wagener et al, 2021).…”