Near-term, iterative ecological forecasts with quantified uncertainty have great potential for improving lake and reservoir management. For example, if managers received a forecast indicating a high likelihood of impending impairment, they could make decisions today to prevent or mitigate poor water quality in the future. Increasing the number of automated, realtime freshwater forecasts used for management requires integrating interdisciplinary expertise to develop a framework that seamlessly links data, models, and cyberinfrastructure, as well as collaborations with managers to ensure that forecasts are embedded into decision-making workflows. The goal of this study is to advance the implementation of near-term, iterative ecological forecasts for freshwater management. We first provide an overview of FLARE (Forecasting Lake And Reservoir Ecosystems), a forecasting framework we developed and applied to a drinking water reservoir to assist water quality management, as a potential opensource option for interested users. We used FLARE to develop scenario forecasts simulating different water quality interventions to inform manager decision-making. Second, we share lessons learned from our experience developing and running FLARE over 2 years to inform other forecasting projects. We specifically focus on how to develop, implement, and maintain a forecasting system used for active management. Our goal is to break down the barriers to forecasting for freshwater researchers, with the aim of improving lake and reservoir management globally.

Virtual machines provide flexible, powerful execution environments for Grid computing, offering

 We created a real-time iterative lake water temperature forecasting system that uses sensors, data assimilation, and hydrodynamic modeling  Our water temperature forecasting system quantifies uncertainty in each daily forecast and is open-source  16-day future forecasted temperatures were within 1.4℃ of observations over 16 months in a reservoir case study

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Abstract-Peer-to-peer (P2P) networks have mostly focused on task oriented networking, where networks are constructed for single applications, i.e. file-sharing, DNS caching, etc. In this work, we introduce IPOP, a system for creating virtual IP networks on top of a P2P overlay. IPOP enables seamless access to Grid resources spanning multiple domains by aggregating them into a virtual IP network that is completely isolated from the physical network. The virtual IP network provided by IPOP supports deployment of existing IP-based protocols over a robust, self-configuring P2P overlay. We present implementation details as well as experimental measurement results taken from LAN, WAN, and Planet-Lab tests.