Victor Bacu

Water resources of the Black Sea Basin at high spatial and temporal resolution

The pressure on water resources, deteriorating water quality, and uncertainties associated with the climate change create an environment of conflict in large and complex river system. The Black Sea Basin (BSB), in particular, suffers from ecological unsustainability and inadequate resource management leading to severe environmental, social, and economical problems. To better tackle the future challenges, we used the Soil and Water Assessment Tool (SWAT) to model the hydrology of the BSB coupling water quantity, water quality, and crop yield components. The hydrological model of the BSB was calibrated and validated considering sensitivity and uncertainty analysis. River discharges, nitrate loads, and crop yields were used to calibrate the model. Employing grid technology improved calibration computation time by more than an order of magnitude. We calculated components of water resources such as river discharge, infiltration, aquifer recharge, soil moisture, and actual and potential evapotranspiration. Furthermore, available water resources were calculated at subbasin spatial and monthly temporal levels. Within this framework, a comprehensive database of the BSB was created to fill the existing gaps in water resources data in the region. In this paper, we discuss the challenges of building a large-scale model in fine spatial and temporal detail. This study provides the basis for further research on the impacts of climate and land use change on water resources in the BSB.

Experiments on ESIP—Environment oriented satellite data processing platform

The paper describes the features and the architectures of the ESIP (Environment oriented Satellite Data Processing) and gProcess platforms, supporting the Grid based satellite imagery processing. Features such as Grid services, interactive components, workflow execution, process monitoring, and service composition provided by gProcess, and satellite image processing operators provided by ESIP are described. The paper exemplifies the workflow based description of the GEMI vegetation index in ESIP. The experiments highlight and evaluate as well the performance of the GEMI workflow execution over the SEE-GRID infrastructure.

Grid based satellite image processing platform for Earth observation application development

Satellite images supply important information on earth surface, weather, clime, geographic areas, vegetation, and natural phenomena. Processing of satellite data requires high computation resources and flexible tools in order to search, discover, and reveal the main information, to experiment new algorithms, and to include them into new Earth Observation applications. This paper describes the features and the architectures of the ESIP and gProcess platforms, supporting the Grid based satellite imagery processing. The development methodology of Earth Observation applications is highlighted as well in order to hide the Grid complexity to the user.

Grid Based Training Environment for Earth Observation

The content of the satellite images supplies information on the earth surface, weather, clime, geographic areas, pollution, and natural phenomena. Unfortunately, the real time supervision and the teaching related techniques require high computation and massive spatial data storage resources. This paper presents the Grid oriented GiSHEO eLearning Environment (eGLE) supporting the training and experimental practice in Earth Observation (EO). eGLE facilitates specific access for the academic and scientific community to on-demand services related to specific EO applications. The teachers have the ability to easily create lessons for different topics, supporting both the knowledge presentation and Grid based processing. The eGLE environment is based on the gProcess platform developed through the MedioGrid national project. The gProcess platform consists of a set of tools supporting the flexible description, instantiation, scheduling and execution of the workflow based Grid processing.

Diagrammatic Description of Satellite Image Processing Workflow

Multiple experiments on grid based satellite imagery classification require flexible descriptions of the processing workflow. The user develops the processing workflow pattern by visual tools in terms of satellite image multi-band spectral data. Each pattern may be stored into a repository and instantiated later for a particular area and time of the satellite image. The specific processing can be scheduled for the right time and data flow. By this flexible approach the user can optimize the processing algorithm for appropriate resource configuration, image type and on-line data feeding.

Grid based architectural components for SWAT model calibration

Different scenarios based on environmental changes and water quality models could be used to assess the sustainability and vulnerability of a particular geographical region. The gSWAT application allows the calibration of SWAT models and the execution of different scenarios based on calibrated SWAT model over the Grid infrastructure. Based on the requirements for the SWAT models, lots of input and output data, the high number of simulations that must be performed in the calibration process, the Grid could offer both the storing and execution solutions. This paper presents the gSWAT system highlighting the architectural components and presenting some test cases to assess the system performances.

Grid based environment application development methodology

The satellite image oriented processing in the Grid based environment applications needs flexible tools, process description and execution in order to reveal significant information The main processing consists of imagery classification which is actually a search of information through combinations of multispectral bands of satellite data The Grid based application development process should assist the developer to implement required functionality, but making transparent to the user the Grid complexity and the mapping of the conceptual application over the physical Grid resources The paper exemplifies the gProcess based Grid application development methodology throughout the development phases of the GreenView environment application, and analyzes the efficiency of such an approach The primary aim of the GreenView application is the refinement of surface and vegetation parameters in SEE and CE regions based on satellite images The GreenView application is based on ESIP platform, which lies on the gProcess toolset specific satellite image processing operators and services.

Comparative parallel execution of SWAT hydrological model on multicore and grid architectures

The paper presents a comparative analysis made on the calibration of a large-scale model, executed both on grid and multicore architectures. The goal is to highlight the advantages brought by the grid infrastructure over the multicore architecture, especially for large-scale applications, which require large amounts of data and a large number of executions. The large-scale application used as a case study for this research work is the calibration of a large-scale SWAT hydrological model, covering the Danube River Basin.

Earth Observation application development based on the Grid oriented ESIP satellite image processing platform

Satellite images supply important information on earth surface, weather, clime, geographic areas, vegetation, and natural phenomena. Processing of satellite data requires high computation resources and flexible tools in order to search, discover, and reveal the main information, to experiment new algorithms, and to include them into new Earth Observation applications. This paper describes the features and the architectures of the ESIP and gProcess platforms, supporting the Grid based satellite imagery processing. The development methodology of Earth Observation applications is highlighted as well in order to hide the Grid complexity to the user.

Software Platform Interoperability Throughout EnviroGRIDS Portal

The Black Sea Catchment area is well known for subjects such as ecologically unsustainable development or inadequate resource management. The EnviroGRIDS project addresses these issues by using emerging information technologies. The enviroGRIDS Web Portal allows the users to access the geospatial functionality given by Web infrastructure, and to high power computation resources given by Grid infrastructure. The Black Sea Catchment Observation System portal provides a single point of access to the enviroGRIDS applications and tools. Both the vertical and horizontal interoperability are available between the platforms and applications throughout the portal. The horizontal interoperability is accomplished through services, meaning the applications are working together by the exposed services. The vertical interoperability is supported by the communication between the layers of end user applications, Web infrastructure, and Grid infrastructure. The basic solution of interoperability is accomplished by services, messages, and data. The paper highlights the solutions developed by the Black Sea Catchment Observation System portal to support various types of interoperability between the modules of geospatial data management, hydrological model calibration and running, satellite image processing, spatial data visualization, and virtual training center.