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A Satellite Supported Inverse Biophysical Modeling Approach for the Detection of Irrigated Agricultural Land and the Determination of the Amount of Irrigation in Arid and Semi Arid Regions
Project Start Date
09/01/2011
Project End Date
08/31/2014
Solicitation
default

Team Members:

Person Name Person role on project Affiliation
Lahouari Bounoua Principal Investigator NASA GSFC, Greenbelt, United States
Marc Imhoff Co-Investigator NASA's Goddard Space Flight Center, Greenbelt, United States
Ping Zhang Co-Investigator NASA, Greenbelt, United States
Arnon Karnieli Co-Investigator Ben Gurion University of the Negev, Negev, Israel
Mohamed Messouli Co-Investigator University Cadi Ayyard of Marrakech, Morocco, Marrakech, Morocco
Abstract

One of the world's most vital needs is a stable supply of food and water. Population is increasing and so is the demand for agricultural products. Agriculture expansion significantly affects land cover and land-use and because it is the largest water-use sector, it has strong influence on water resources through diversion and extraction of fresh water, especially in arid and semi-arid regions. The scarcity of food and fresh water availability is already the subject of conflicts around the world where political boundaries dissect natural watersheds, aquifers and river flow. For these regions in particular where population, agricultural and water demand are increasing for the same or decreasing precipitation, and where the food and water supply and demand are out of balance, changes in agricultural drivers such as regional climate, population growth, agricultural practices and technology can have potentially predictable environmental and socio-economic consequences. Understanding the relationships between agricultural production (land-use and water demand), local climate and socio-economic trends can significantly improve agricultural efficiency and optimize its production. This will likely slow its impact on land cover and water resources and provide essential information to farmers, food producers, land-use and water managers, and policy makers. We propose to combine Landsat and MODIS observations along with an inverse biophysical modeling technique to detect irrigated agricultural lands in the arid and semi-arid regions of North Africa, the Middle Easte and South Central Asia and quantify the amount of irrigation water needed for agricultural production as influenced by climate, crop type, soil characteristics and other socio-economic drivers. We also propose to develop realistic change scenarios that link the ever-rising demand for agricultural products to changes in local climate, demographic and technological advances and examine the impact of these changes on agricultural lands and their adaptability to a changing climate.

Project Research Area