Enabling collaborative decision-making in watershed management using cloud-computing services

Watershed management, in its very nature, represents a participatory process, requiring horizontal and vertical collaborations among multiple institutions and stakeholders. For watershed-scale management to be effective, a social-learning infrastructure needs to be in place to allow for the integration of diverse knowledge and interests related to watershed protection and restoration. Environmental decision support systems (EDSS) have long been used to support co-learning processes during watershed management. However, implementation and maintenance of EDSS in house often pose a significant burden to local watershed partnerships because of budgetary and technological constraints. Recent advances in service-oriented computing can help shift away the technical burden of EDSS implementation to service providers and enable watershed partnerships to focus primarily on decision-making activities. In this paper, I describe the migration of an EDSS module from the traditional client-server-based architecture to a client of cloud-computing services. Google Drive, which is behind the new version of the EDSS module, provides a number of basic visual analytics features that can be used to increase the collaborative decision-making experience while drastically reducing the cost of small-scale EDSS. More sophisticated EDSS may be implemented by leveraging the strengths of both client–server architectures and cloud-computing services.

Figure optionsDownload as PowerPoint slideHighlights
► Watershed management requires collaborative decision-making.
► Development of client–server based, collaborative decision support systems is costly.
► Cloud-computing services can fundamentally change the way many systems are designed.
► We demonstrate the use of cloud-computing for total maximum daily load management.