Developing an intelligent Decision Support System for environmentally optimized irrigation management using Sensors, Remote Sensing and Meteorological Forecast

Authors

  • Panagiota Syropoulou DRAXIS Environmental S.A
  • Machi Symeonidou DRAXIS Environmental S.A
  • Stavros Tekes DRAXIS Environmental S.A
  • Rafal Wawer The Institute of Soil Science and Plant Cultivation - State Research Institute http://orcid.org/0000-0001-9266-9577
  • Andreas Kazantzidis University of Patras
  • Vladimir Crnojevic Univerzitet U Novom Sadu Fakultet Tehnickih Nauka
  • Adriana Bruggeman The Cyprus Research and Educational Foundation

DOI:

https://doi.org/10.17700/jai.2017.8.2.375

Abstract

Globally, agriculture makes use of 70% of all water withdrawn from aquifers, streams and lakes. Agriculture accounts for 22% of freshwater abstraction in Europe, outnumbered only by freshwater abstraction for cooling in energy production (45%). In the light of the real need to practically improve the environmental performance of irrigation systems and prevent the misuse of water, the overall aim of ENORASIS is to develop an intelligent, integrated Decision Support System (ENORASIS Service Platform and Components) for environmentally optimized and thus, sustainable irrigation management to be used by farmers and water management organizations. ENORASIS system targets to motivate irrigation farmers to optimize the use of water, whereas it also provides (irrigation) water management organizations with intelligent tools and services to effectively forecast and manage irrigation water resources, cover irrigation demand and charge customers (farmers) on the basis of an intelligent system of motives and incentives that exploits irrigation demand side fluctuations. To achieve so, the ENORASIS project will develop and integrate a bouquet of advanced technologies, methodologies and models in the fields of: (i) weather prediction systems that exploit satellite observations; (ii) irrigation optimization techniques and (iii) smart irrigation systems; and (iv) wireless sensor networks (functioning with solar energy) as key enabling technology for field measurements and monitoring conditions.

Author Biography

Rafal Wawer, The Institute of Soil Science and Plant Cultivation - State Research Institute

Project manager and senior researcher in the Institute of Soil Science and Plant Cultuvation - State Research Institute

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Published

2017-08-03

How to Cite

Syropoulou, P., Symeonidou, M., Tekes, S., Wawer, R., Kazantzidis, A., Crnojevic, V., & Bruggeman, A. (2017). Developing an intelligent Decision Support System for environmentally optimized irrigation management using Sensors, Remote Sensing and Meteorological Forecast. Journal of Agricultural Informatics, 8(2). https://doi.org/10.17700/jai.2017.8.2.375

Issue

Section

Journal of Agricultural Informatics