WSTA 15th Gulf Water Conference

WSTA 15th Gulf Water Conference

Using technology to bridge the data gap for efficient management of agricultural water

Bert Coerver, Abdullah Barhy, Mohamed Abdallah

http://doi.org/10.5004/700100

Using technology to bridge the data gap for efficient management of agricultural water

Bert Coervera, Abdullah Barhyb, Mohamed Abdallahc*

aInternational Expert on Remote Sensing, FAO WaPOR Project, Land and Water Division, FAO Headquarters, FAO Regional Office for Near East and North Africa (RNE)
bGeospatial Expert, Geospatial Unit, Land and Water Division, FAO Headquarters
cProgramme Implementation Support Expert, Water Scarcity Initiative, FAO Regional Office for the Near East and North Africa

https://doi.org/10.5004/700100

ABSTRACT

Water scarcity represents a significant challenge to agricultural productivity and food security, particularly in the Near East and North Africa (NENA) region. Exacerbated by its arid and semi-arid climates, coupled with population growth, and changing climatic conditions, the demand for water in agriculture continues to rise despite the growing demands of other sectors, while water resources are becoming increasingly limited. In this context, data technologies, including Remote Sensing, Geographic Information Systems, Cloud Computing, Artificial Intelligence, among others, offer promising avenues for addressing water scarcity and agriculturerelated issues. Innovative solutions leveraging these technologies have emerged as crucial tools that provide valuable data and insights that contribute to monitoring of water use, assessment of crop yield and productivity, water requirements, and optimizing irrigation practices, and providing early warning, thereby enhancing water use efficiency and productivity in agriculture while considering the need of water in other sectors.

Keywords: Water scarcity; Agricultural productivity; Sustainable water management; Water use efficiency; Crop mapping; Remote sensing; Geographic information systems (GIS); Cloud computing; Artificial intelligence (AI); Geospatial technology; Analysis-ready data; Google earth engine (GEE); FAO SEPAL; FAO WaPOR

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