Mainstreaming Sociohydrology: Towards Designing and Implementing Management Interventions
Mainstreaming Sociohydrology: Towards Designing and Implementing Management Interventions
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About this Research Topic
This Research Topic is closed for submissions.
Background
This Research Topic is part of a series of article collections published within Frontiers in Water for the the 2nd International Sociohydrology Conference.
Significant progress has been made in computational social sciences, the use of new, unconventional data, data sharing, and integrating quantitative and qualitative data to better understand and model human-water systems. However, less progress has been made in using sociohydrological models to develop future projections, and to successfully design, implement and evaluate interventions. The growing academic understanding of real-world human-water systems needs to be used better to design effective interventions for sustainable development. To provide solutions to diverse water challenges, while acknowledging that fixes often backfire because critical human-water feedbacks are not recognized or is ignored, this theme focuses on:
i) studies that use novel (unconventional) data and data science, integrate quantitative and qualitative data, identify means to fill data gaps, or build community open access datasets to better understand human-water system dynamics. ii) studies that improve predictions of coupled trajectories and develop future projections of human-water systems. iii) modeling effects of interventions in emergent phenomena and predictions of possibility (solution) spaces based on co-identified scenarios. iv) intervention design and implementation studies that enhance the adoption of the interventions based on empirically grounded behavioral and social methods. v) educational models to train the next generation of young minds on transdisciplinary methods and coupled human-water systems competencies.
Keywords: Interventions, human-water systems, real-world, sustainable development, diverse water challenges
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