The Experts below are selected from a list of 60366 Experts worldwide ranked by ideXlab platform
Luca Ridolfi - One of the best experts on this subject based on the ideXlab platform.
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Source identification in River Pollution problems: A geostatistical approach
Water Resources Research, 2005Co-Authors: Fulvio Boano, Roberto Revelli, Luca RidolfiAbstract:The geostatistical method, formulated in the groundwater field, has been applied to identify contaminant sources in River Pollution problems. The problem consists of recovering a contaminant source at a known location from a finite number of concentration measurements. It is an ill- posed problem, whose solution is nonunique and cannot be determined through standard techniques. The presence of dead zones has been considered because of their relevant influence on transport processes. The possibility of linear decay reactions in the main stream and in the dead zones has also been included. Applications to field data show that the method is efficient in recovering the release history of an arbitrarily distributed source as well as multiple independent point sources, given a finite number of observed concentrations at one or several downstream points. The influence of the degree of dispersion on the observations is stressed. Finally, the effects of measurement errors and of the number of measurement points have been investigated.
Fulvio Boano - One of the best experts on this subject based on the ideXlab platform.
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Source identification in River Pollution problems: A geostatistical approach
Water Resources Research, 2005Co-Authors: Fulvio Boano, Roberto Revelli, Luca RidolfiAbstract:The geostatistical method, formulated in the groundwater field, has been applied to identify contaminant sources in River Pollution problems. The problem consists of recovering a contaminant source at a known location from a finite number of concentration measurements. It is an ill- posed problem, whose solution is nonunique and cannot be determined through standard techniques. The presence of dead zones has been considered because of their relevant influence on transport processes. The possibility of linear decay reactions in the main stream and in the dead zones has also been included. Applications to field data show that the method is efficient in recovering the release history of an arbitrarily distributed source as well as multiple independent point sources, given a finite number of observed concentrations at one or several downstream points. The influence of the degree of dispersion on the observations is stressed. Finally, the effects of measurement errors and of the number of measurement points have been investigated.
Yezid Donoso - One of the best experts on this subject based on the ideXlab platform.
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delay disruption tolerant network based message forwarding for a River Pollution monitoring wireless sensor network application
Sensors, 2016Co-Authors: Carlos Velasquezvillada, Yezid DonosoAbstract:Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for River Pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream River’s course. Sensor clusters sent messages to a Gateway installed on the Riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas’ movement and network backhaul availability. Since the antennas were floating on the River, communications could be disrupted at any time. Also, 2G/3G availability near the River was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the River bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols.
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Delay/Disruption Tolerant Network-Based Message Forwarding for a River Pollution Monitoring Wireless Sensor Network Application.
Sensors, 2016Co-Authors: Carlos Velásquez-villada, Yezid DonosoAbstract:Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for River Pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream River’s course. Sensor clusters sent messages to a Gateway installed on the Riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas’ movement and network backhaul availability. Since the antennas were floating on the River, communications could be disrupted at any time. Also, 2G/3G availability near the River was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the River bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols.
Rao Y Surampalli - One of the best experts on this subject based on the ideXlab platform.
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development of a water quality modeling system for River Pollution index and suspended solid loading evaluation
Journal of Hydrology, 2013Co-Authors: Y T Tu, C P Yang, Rao Y SurampalliAbstract:Summary The Kaoping River Basin is the largest and most extensively used watershed in Taiwan. In the upper catchment, the non-point source (NPS) pollutants including suspended solid (SS) and ammonia nitrogen (NH 3 –N) are two major water pollutants causing the deterioration of Kaoping River water quality. Because SS is one of the four parameters involving in the River Pollution Index (RPI) calculation, it needs to be carefully evaluated to obtain the representative water quality index. The main objective of this study was to develop a water quality modeling system to obtain representative SS and RPI values for water quality evaluation. In this study, a direct linkage between the RPI calculation and a water quality model [Water Quality Analysis Simulation Program (WASP)] has been developed. Correlation equations between Kaoping River flow rates and SS concentrations were developed using the field data collected during the high and low flows of the Kaoping River. Investigation results show that the SS concentrations were highly correlated with the flow rates. The obtained SS equation and RPI calculation package were embedded into the WASP model to improve interactive transfers of required data for water quality modeling and RPI calculation. Results indicate that SS played an important role in RPI calculation and SS was a critical factor during the RPI calculation especially for the upper catchment in the wet seasons. This was due to the fact that the soil erosion caused the increase in the SS concentrations after storms. In the wet seasons, higher River flow rates caused the discharges of NPS pollutants (NH 3 –N and SS) into the upper sections of the River. Results demonstrate that the integral approach could develop a direct linkage among River flow rate, water quality, and Pollution index. The introduction of the integrated system showed a significant advance in water quality evaluation and River management strategy development.
Roberto Revelli - One of the best experts on this subject based on the ideXlab platform.
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Source identification in River Pollution problems: A geostatistical approach
Water Resources Research, 2005Co-Authors: Fulvio Boano, Roberto Revelli, Luca RidolfiAbstract:The geostatistical method, formulated in the groundwater field, has been applied to identify contaminant sources in River Pollution problems. The problem consists of recovering a contaminant source at a known location from a finite number of concentration measurements. It is an ill- posed problem, whose solution is nonunique and cannot be determined through standard techniques. The presence of dead zones has been considered because of their relevant influence on transport processes. The possibility of linear decay reactions in the main stream and in the dead zones has also been included. Applications to field data show that the method is efficient in recovering the release history of an arbitrarily distributed source as well as multiple independent point sources, given a finite number of observed concentrations at one or several downstream points. The influence of the degree of dispersion on the observations is stressed. Finally, the effects of measurement errors and of the number of measurement points have been investigated.
