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State of the art challenges in sustainable management of water resources have created demand for integrated, flexible and easy to use hydrological models which are able to simulate the quantitative and qualitative aspects of the hydrological cycle with a sufficient degree of certainty. Existing models which have been developed to fit these needs are often(More)
The hype on the Cloud is based on promising cost savings if, considering the new service platform concepts (IaaS, PaaS, SaaS) the term comes with, IT resources will be used effectively. Therefore, the trend is moving away from physical systems to more instant and short-term environments and virtualization is increasingly taking on a key role in various(More)
The pressure on environmental systems is increasing worldwide due to population growth and the consequences of climate change. Adaptable tools and methods are needed to elaborate information, develop understanding and strategies for sustainable use and management of environmental systems. Such tools should assist scientists, natural resource managers and(More)
A prerequisite for integrated land and water resources management (ILWRM) is a holistic river basin assessment. The latter requires information and data from different scientific disciplines but also appropriate data management systems to store and manage historical and real time data, set up protocols that facilitate data and information access and sharing(More)
Progress in the understanding of physical, chemical, and biological processes influencing water quality, coupled with advances in the collection and analysis of hydrologic data, provide opportunities for significant innovations in the manner and level with which watershed-scale processes may be quantified and modeled. This paper first provides a brief(More)
In order to apply environmental models successfully, it is essential to determine model parameters very carefully. A direct determination of parameter values is often not feasible since they lack a clear physical meaning or field measurements are too expensive. Therefore, estimation of parameters is usually done by fitting model response and observation in(More)