Hydrological modeling and water management intrinsically require better integration of data, information and models due to their complex and interdisciplinary nature. The challenge is to provide policy- and decision-makers with efficient and reliable information, based on integrated data and tools derived from both Earth observations and scientific models. The latest technological advances in Earth observation and Web technologies have allowed the development of Spatial Data Infrastructures (SDIs) that are accelerating the pace of data sharing at regional and national scales, with the ongoing construction of a global SDI. A series of recent European projects (e.g. ACQWA, enviroGRIDS, GEOWOW) are contributing to the promotion of innovative Earth observation solutions that favor the uptake of scientific outcomes in water management and policy. Currently, hydrological, agricultural, meteorological and climatological data remain difficult to find and integrate because of various accessibility and incompatibility issues. New data streams from remote sensing or crowd sourcing are also producing valuable information to improve our understanding of the water cycle, while field sensors are developing rapidly and becoming less costly. International initiatives such as OGC, GEOSS and INSPIRE catalyze data sharing by promoting interoperability standards to maximize the use of data and by supporting easy access to and utilization of geospatial data. Additional standards (e.g., WaterML, netCDF) are enhancing interoperability between hydrology and other scientific disciplines. The UncertWeb modeling framework is an attempt to quantify and efficiently communicate uncertainty of data and models, which is an essential pre-requisite for decision-making. Distributed computing infrastructures can handle complex and large hydrological data and models, while Web Processing Services bring the flexibility to develop and execute simple to complex workflows over the Internet. The brokering approach allows binding heterogeneous resources published by different data providers and adapting them to tools and interfaces commonly used by consumers of these resources. The System of Systems (SoS) approach appears to be a valuable and promising concept in order to lower the entry-level barrier to a real multi-disciplinary framework. Successful SDIs rely therefore on various aspects: a shared vision between all participants, necessity to solve a common problem, adequate data policies, incentives, and sufficient resources. The need for capacity building at human (education and training of individuals), infrastructure (installing/configuring/managing of the needed technology) and institutional (enhancing the understanding within organization and/or governments) levels is also a major driver for reinforcing the commitment to SDI concepts.
Reviewing innovative Earth observation solutions for filling science-policy gaps in hydrology
Nativi S;
2014
Abstract
Hydrological modeling and water management intrinsically require better integration of data, information and models due to their complex and interdisciplinary nature. The challenge is to provide policy- and decision-makers with efficient and reliable information, based on integrated data and tools derived from both Earth observations and scientific models. The latest technological advances in Earth observation and Web technologies have allowed the development of Spatial Data Infrastructures (SDIs) that are accelerating the pace of data sharing at regional and national scales, with the ongoing construction of a global SDI. A series of recent European projects (e.g. ACQWA, enviroGRIDS, GEOWOW) are contributing to the promotion of innovative Earth observation solutions that favor the uptake of scientific outcomes in water management and policy. Currently, hydrological, agricultural, meteorological and climatological data remain difficult to find and integrate because of various accessibility and incompatibility issues. New data streams from remote sensing or crowd sourcing are also producing valuable information to improve our understanding of the water cycle, while field sensors are developing rapidly and becoming less costly. International initiatives such as OGC, GEOSS and INSPIRE catalyze data sharing by promoting interoperability standards to maximize the use of data and by supporting easy access to and utilization of geospatial data. Additional standards (e.g., WaterML, netCDF) are enhancing interoperability between hydrology and other scientific disciplines. The UncertWeb modeling framework is an attempt to quantify and efficiently communicate uncertainty of data and models, which is an essential pre-requisite for decision-making. Distributed computing infrastructures can handle complex and large hydrological data and models, while Web Processing Services bring the flexibility to develop and execute simple to complex workflows over the Internet. The brokering approach allows binding heterogeneous resources published by different data providers and adapting them to tools and interfaces commonly used by consumers of these resources. The System of Systems (SoS) approach appears to be a valuable and promising concept in order to lower the entry-level barrier to a real multi-disciplinary framework. Successful SDIs rely therefore on various aspects: a shared vision between all participants, necessity to solve a common problem, adequate data policies, incentives, and sufficient resources. The need for capacity building at human (education and training of individuals), infrastructure (installing/configuring/managing of the needed technology) and institutional (enhancing the understanding within organization and/or governments) levels is also a major driver for reinforcing the commitment to SDI concepts.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
