EXPLORE THE DATA ECOSYSTEM

Increasing water scarcity and environmental concerns have urged the search for solutions for better water management in irrigated agriculture. Precision irrigation is one of these solutions.
Technologies have developed potential systems, although effective partnerships have to be fostered between private industry and scientific community to shape up some common and complementary solutions.
The project proposes the development of an expert system, based on the exploitation of results from three previous projects in order to acquire data from sensors, match it against a data base, produce decisions on water and energy savings

The innovative solution of the proposal resides (1) on his historical database built upon real case studies, (2) is shared on the web which guarantees cheaper access to this technology and (3) helps changing the current culture and behavior and into getting agricultural exploitation into the use of ICTs.
A) Direct benefits are:
1)Saving water, especially where annual traditional amount of irrigation water is beyond average crop water requirements.
2)Saving energy and manpower required to pump and distribute excess water.

B) Indirect benefits are:
1)Reducing leaching of fertilizers out of the plant root zone
2)Improving water and fertilizers availability for the plant
3)Reducing deep water percolation and contamination to underground aquifer by agricultural chemicals.
4)Providing information about the local soil hydrodynamic characteristics, the advance of wetting front during irrigation events and the depth and daily pattern of root water uptake.
5)Providing information on the hydraulic performance of the irrigation system in use.
6)Providing information on the current crop development and growing stages.
7)Creating a closer relationship between the farmer and his production system. It offers him a better real understanding of water and nutrient balance within water-soil-plant system.
8)Creating consistency in yields between years.

Acronym
OpIRIS
Website
Address
ES
Scientific discipline(s)
Geographic coverage
Type
Data science categories
Data science categories