. Granting agencies invest millions of dollars on the generation and analysis of data, making these products extremely valuable. However, without sufficient annotation of the methods used to collect and analyze the data, the ability to reproduce and reuse those products suffers. This lack of assurance of the quality and credibility of the data at the different stages in the research process essentially wastes much of the investment of time and funding and fails to drive research forward to the level of potential possible if everything was effectively annotated and disseminated to the wider research community. In order to address this issue for the Hawai'i Established Program to Stimulate Competitive Research (EPSCoR) project, a water science gateway was developed at the University of Hawai‘i (UH), called the ‘Ike Wai Gateway. In Hawaiian, ‘Ike means knowledge and Wai means water. The gateway supports research in hydrology and water management by providing tools to address questions of water sustainability in Hawai‘i. The gateway provides a framework for data acquisition, analysis, model integration, and display of data products. The gateway is intended to complement and integrate with the capabilities of the Consortium of Universities for the Advancement of Hydrologic Science's (CUAHSI) Hydroshare by providing sound data and metadata management capabilities for multi-domain field observations, analytical lab actions, and modeling outputs. Functionality provided by the gateway is supported by a subset of the CUAHSI’s Observations Data Model (ODM) delivered as centralized web based user interfaces and APIs supporting multi-domain data management, computation, analysis, and visualization tools to support reproducible science, modeling, data discovery, and decision support for the Hawai'i EPSCoR ‘Ike Wai research team and wider Hawai‘i hydrology community. By leveraging the Tapis platform, UH has constructed a gateway that ties data and advanced computing resources together to support diverse research domains including microbiology, geochemistry, geophysics, economics, and humanities, coupled with computational and modeling workflows delivered in a user friendly web interface with workflows for effectively annotating the project data and products. Disseminating results for the ‘Ike Wai project through the ‘Ike Wai data gateway and Hydroshare makes the research products accessible and reusable.
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Complementary Vantage Points: Integrating Hydrology and Economics for Sociohydrologic Knowledge Generation
Because human and environmental systems in the Anthropocene are increasingly coupled, hydrologists and economists often find themselves studying the same systems from different vantage points. Here we argue that synthesis across economics and hydrology can help address two pressing sociohydrologic challenges: actionable prediction and the generation of transferable knowledge from place‐based studies. Specifically, we review (1) empirical methods and (2) theoretical approaches from economics and connect the two through a proposed iterative framework. First, we find that empirical methods for statistical analysis of natural and quasi‐experiments in economics can be leveraged to distinguish causal relations from mere correlations in complex and data scarce systems, which can help address the challenge of sociohydrologic prediction. Second, we find that economic theories based on rational choice can be used to decipher known paradoxes in water resources, which can help address the challenge of sociohydrologic knowledge generation. In both empirical and theoretical domains, specialized knowledge in hydrology remains critical to properly applying techniques from economics to coupled human‐water systems. We propose that linkages between the two fields highlight a large potential for interaction.
more » « less- NSF-PAR ID:
- 10453371
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 55
- Issue:
- 4
- ISSN:
- 0043-1397
- Page Range / eLocation ID:
- p. 2549-2571
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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