Project Status Applicants
Project Description This project explores an inverse modeling methodology using a biophysical model forced by observed satellite and climate data to quantify the irrigation water demand in semi-arid areas. We constrain the carbon and water cycles modeled under both equilibrium, balance between vegetation density and prevailing local climate and non-equilibrium, water added to irrigation, conditions. We postulate that the degree to which irrigated dry lands vary from equilibrium climate conditions is related to the amount of irrigation water used. The amount of water required over and above precipitation, if any, is considered as the minimum physiological water requirement.

The method estimates both the minimum physiological amount of water required to sustain unstressed photosynthetic production for crops and the total used for irrigation including agricultural efficiencies and losses. To calibrate and validate the approach, we need physiological parameters to characterize the different (major) crops.


Grade Level High School
Project Type Individual
Team
Work Site On Site
Time Frame Summer
R&D Computer & Information Sciences - Information Systems-Data Analysis SW
Computer & Information Sciences - Computer Science-Vision
Skills
Performance Expectations The student will work with the mentor to do literature search and web search for such parameters and present them in a table from assimilable by the model. The student will also be involved in the comparison of the model results with observations. The position requires skill in web research (basically Google) and a lot of organization.

The student is expected to develop a multidimensional table containing information about geographic region, the crop type, the crop seeding and harvesting periods and other parameters characterizing the crop. The student will also develop and present a poster describing his/her work at the end of the internship program.
Optional Questions

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