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Integrated water assessment and modelling: A bibliometric analysis of trends in the water resource sector
- Zare, Fateme, Elsawah, Sondoss, Iwanaga, Takuya, Jakeman, Anthony J., Pierce, Suzanne A.
- Journal of hydrology 2017 v.552 pp. 765-778
- bibliometric analysis, climate change, decision making, decision support systems, ecology, economics, groundwater, issues and policy, landscapes, models, social sciences, stakeholders, uncertainty
- There are substantial challenges facing humanity in the water and related sectors and purposeful integration of the disciplines, connected sectors and interest groups is now perceived as essential to address them. This article describes and uses bibliometric analysis techniques to provide quantitative insights into the general landscape of Integrated Water Resource Assessment and Modelling (IWAM) research over the last 45years. Keywords, terms in titles, abstracts and the full texts are used to distinguish the 13,239 IWAM articles in journals and other non-grey literature. We identify the major journals publishing IWAM research, influential authors through citation counts, as well as the distribution and strength of source countries. Fruitfully, we find that the growth in numbers of such publications has continued to accelerate, and attention to both the biophysical and socioeconomic aspects has also been growing. On the other hand, our analysis strongly indicates that the former continue to dominate, partly by embracing integration with other biophysical sectors related to water – environment, groundwater, ecology, climate change and agriculture. In the social sciences the integration is occurring predominantly through economics, with the others, including law, policy and stakeholder participation, much diminished in comparison. We find there has been increasing attention to management and decision support systems, but a much weaker focus on uncertainty, a pervasive concern whose criticalities must be identified and managed for improving decision making. It would seem that interdisciplinary science still has a long way to go before crucial integration with the non-economic social sciences and uncertainty considerations are achieved more routinely.