Advertisement

Towards the Improvement of Water Resource Management by Combining Technologies for Spatial Data Collection, Storage, Analysis and Dissemination

  • Nafaâ Jabeur
  • James D. McCarthy

Abstract

Water resource managers regularly deal with situations where timely, relevant information can be of significant benefit. One only needs to look at the extensive flooding in Australia in 2010 and 2011, and the associated loss of property and life, to discover why the desire for hydrologic monitoring tools is so great. When water resource managers deal with floods, they want to be able to monitor and predict water levels and direct emergency response efforts. However, flooding is not the only situation where water resources need to be monitored and analyzed (Thakur et al., 2011). To ensure appropriate water quality and supply for a region, these parameters must be regularly monitored, and appropriate entities must be alerted when certain warning thresholds are approached or broken. To study and preserve biodiversity, resource managers need access to long-term data about the environmental conditions in their study area, including any hydrologic factors that may have an impact on it. Several established and emerging technologies are currently providing experts with great benefit in managing environmental resources. In the hydrological domain, the use of Sensor Webs (SWs) in data collection provides decision makers with ever-growing amounts of relevant data and allows them to always be aware of conditions in their study area (Guru et al., 2008). These data can be supplemented with data collected using emerging mobile GIS technology and applications. Currently, a multitude of mobile platforms integrating GPS technology can support data entry through generic or dedicated applications.

Keywords

Sensor Network Wireless Sensor Network Water Resource Management Multiagent System Spatial Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Barbini, R., Colao, F., Fantoni, R., Palucci, A. and Ribezzo, S. (1995). Remote sea- water quality monitoring by means of a lidar fluorosensor. Global Process Monitoring and Remote Sensing of the Ocean and Sea Ice. Volume 2586. pp 4655.Google Scholar
  2. Colllins, J. (2004). NASA creates thinking RF sensors. RFID Journal, Retrieved January 20, 2011 from http://www.rfidjournal.com/article/articleview/1146/1/47/
  3. Delin, K. and Small, E. (2009). The Sensor Web: Advanced Technology for Situational Awareness. Wiley Handbook of Science and Technology for Homeland Security. John Wiley and Sons.Google Scholar
  4. Delin, K.A. and Jackson, S.P. (2003). The Sensor Web: A New Instrument Concept. SPIE Symposium on Integrated Optics, San Jose, CA.Google Scholar
  5. Graniero, P.A., Weiler, M., Nickerson, B.G., Arp, P.A. and Jabeur, N. (2007). An integrated sensor web design and deployment infrastructure for watershed monitoring. Retrieved February 5, 2011 from http://matrix.memf.uwindsor.ca/publications/posters/SWAN-GranieroEtAl-SWANOverview-GEOIDE2007.pdf
  6. Guru, S.M., Taylor, P., Neuhaus, H., Shu, Y., Smith, D. and Terhorst, A. (2008). Hydrological Sensor Web for the South Esk Catchment in the Tasmanian state of Australia. In: IEEE 4th International Conference on eScience, 7(12), 432-433.Google Scholar
  7. Heavner, M.J., Fatland, D.R., Hood, E. and Connor, C. (2007). SEAMONSTER: A Sensor Web Technology Implementation and Testbed in Southeast Alaska. Paper presented at NASA Science and Technology Conference, College Park, MD.Google Scholar
  8. Hempstead, M., Tripathi, N., Mauro, P., Wei, G-Y. and Brooks, D. (2005). An ultra low power system architecture for sensor network applications. Proceedings of SIGARCH Computational Architecture, 33, 208-219.CrossRefGoogle Scholar
  9. Herring, J.R. (2010). OpenGIS Implementation Standard for Geographic information - Simple feature access - Part 1: Common architecture. Open Geospatial Consortium. 93 pp. Retreived February 15, 2011 from http:// www.opengeospatial.org/standards/sfa
  10. Howe, B.M., Parrish, N., Tracy, L., Gray, A., Chao, Y., McGinnis, T., Arabshahi, P. and Roy, S. (2008). A Smart Sensor Web for Ocean Observation: Integrated Acoustics, Satellite Networking, and Predictive Modeling. In: Proceedings of NASA Science Technology Conference (NSTC2008), University of Maryland.Google Scholar
  11. Intanagonwiwat, C., Govindan, R. and Estrin, D. (2000). Directed diffusion: a scalable and robust communication paradigm for sensor networks. In: Proceedings of International conference on Mobile Computing and Networking.Google Scholar
  12. Irish, J.L. and White, T.E. (1998). Coastal engineering applications of high-resolution lidar bathymetry. Proceedings of Coastal Engineering, 35(1), 47-71.CrossRefGoogle Scholar
  13. Jabeur N. and Haddad, H. (2009). Using Causality Relationships for a Progressive Management of Hazardous Phenomena with Sensor Networks. In: Proceedings of the International Conference on Computational Science and Applications (ICCSA'09), Yongin, Korea, pp. 1-16Google Scholar
  14. Jabeur, N. and Graniero, P. (2007). A Hybrid Location-Semantic Approach to Routing Assisted by Agents in a Virtual Network. In: Frontiers of High Performance Computing and Networking. ISPA 2007 Workshops, pp. 523-533.Google Scholar
  15. Jabeur, N., Graniero, P., McCarthy, J. and Xing, X. (2009). A Knowledge-Oriented Meta-Framework for Integrating Sensor Network Infrastructures. International Journal of Computers and Geosciences, 35, 1-14.CrossRefGoogle Scholar
  16. Jabeur, N., McCarthy, J.D. and Graniero, P. (2008). Improving Wireless Sensor Network Efficiency and Adaptability through an SOS Server Agent. In: Proceeding of the 1st IEEE International Workshop on the Applications of Digital Information and Web Technologies (ICADIWT 2008), Ostrava, Czech Republic, pp. 409-414.Google Scholar
  17. Jacques, P., Seshagiri, R., Prabhakar, T.V., Jean-Pierre, H. and Jamadagni, H.S. (2007). COMMONSense Net: A Wireless Sensor Network for Resource-Poor Agriculture in the Semiarid Areas of Developing Countries. Journal of Information Technologies and International Development, 4(1), 51-67.CrossRefGoogle Scholar
  18. Levis, Ph., Gay, D., Handziski, V., Hauer, J.H., Greenstein, B., Turon, M., Huio, J., Klues, K., Sharp, C., Szewczyk, R., Polastre, J., Buonadonnao, Ph., Nachman, L., Tolleo, G., Cullero, D. and Wolisz, A. (2005). T2: A Second Generation OS for Embedded Sensor Networks. Technical Reports Series, (Ed.) Dr.-Ing. Adam Wolisz.Google Scholar
  19. Markovic, N., Stanimirovic, A. and Stoimenov, L. (2009). Sensor Web for River Water Pollution Monitoring and Alert System. In: Proceedings of 12th AGILE International Conference on Geographic Information Science Advances in GIScience, Germany. ISSN 2073-8013.Google Scholar
  20. McCarthy, J.D., Graniero, P.A. and Rozic, S.M. (2008). An Integrated GIS-expert system framework for live hazard monitoring and detection. Sensors International Journal, 8, 830-846.CrossRefGoogle Scholar
  21. McGarry, F. (2008). Collaborative Geomatics for Social Innovation in Environmental Practice. Presented at the First Nations GIS Workshop. Retrieved February 10, 2011 from http://www.comap.ca/index.php?MenuItemID=7
  22. Nakamura, K., Wakabayashi, H., Naoki, K., Nishio, F., Moriyama, T. and Uratsuka, S. (2005). Observation of sea-ice thickness in the sea of Okhotsk by using dual- frequency and fully polarimetric airborne SAR (pi-SAR) data. IEEE Transactions in Geoscience and Remote Sensing, 43 (11), 2460-2469.CrossRefGoogle Scholar
  23. Nickerson, B.G., Sun, Z. and Arp, J. (2005). A sensor web language for mesh architectures. Proceedings of the 3 rd Annual Communication Networks and Services Research Conference (CNSR'05), Halifax, NS, Canada. IEEE Computer Society, pp. 269-274.Google Scholar
  24. Rozic, S.M. and Graniero, P.A. (2005). Representing domain and spatial knowledge with ontologies in a spatial decision support framework. In: Proceedings of GeoComputation 2005, Ann Arbor, MI. 15 (CD-ROM).Google Scholar
  25. Sahli, N., Jabeur, N. and Badra, M. 2011. Agent-Based Approach to Plan Sensors Relocation in a Virtual Geographic Environment. In: Proceeding of International Conference on New Technologies, Mobility and Security (NTMS'2011).Google Scholar
  26. Stockdon, H.F., Sallenger, Jr., A.H., List, J.H. and Holman, R.A. (2002). Estimation of Shoreline Position and Change using Airborne Topographic Lidar Data. Journal of Coastal Research, 18(3), 502-513.Google Scholar
  27. Thakur, J.K., Thakur, R.K., Ramanathan, A., Kumar, M. and Singh, S.K. (2011). Arsenic Contamination of Groundwater in Nepal - An Overview. Water, 3(1), 120.Google Scholar
  28. Xing, X. (2008). An architectural framework for developing advanced integrated environmental monitoring systems. Unpublished MSc thesis, Department of Earth and Environmental Sciences, University of Windsor.Google Scholar
  29. Zennaro, M., Pehrson, B. and Bagula, A. (2008). Wireless Sensor Networks: a great opportunity for researchers in Developing Countries. In: Proceedings of 2nd IFIP International Symposium on Wireless Communications and Information Technology in Developing Countries (South Africa).Google Scholar

Copyright information

© Capital Publishing Company 2011

Authors and Affiliations

  • Nafaâ Jabeur
    • 1
  • James D. McCarthy
    • 2
  1. 1.Computer Science DepartmentDhofar UniversityOman
  2. 2.Mapping, Analysis and Design, Faculty of Environment University of WaterlooCanada

Personalised recommendations