Image Use in the Characterization of Field Parameters: Integration of Remote Sensing and Hydrologic Simulation ModelingEPA Grant Number: U915329
Title: Image Use in the Characterization of Field Parameters: Integration of Remote Sensing and Hydrologic Simulation Modeling
Investigators: Fox, Garey A.
Institution: Texas A & M University
EPA Project Officer: Lee, Sonja
Project Period: August 1, 1998 through August 1, 2001
Project Amount: $54,810
RFA: STAR Graduate Fellowships (1998) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Engineering and Environmental Chemistry , Fellowship - Agricultural Engineering
The overall objective of this research project involves developing a system that inputs influential soil and crop parameters obtained from remote sensing applications into hydrologic simulation models for the purpose of developing time-interval checks on model performance and accuracy.This system will improve model simulations by adding periodic evaluations from remotely sensed data, and will correct for discrepancies in values of certain crop and soil properties at numerous times during the growing season.
Aerial images of several fields will be used along with the Agricultural Policy/Environmental Extender (APEX) modeling system. The research will first involve using the APEX model to simulate crop growth and nutrient activities within the watershed to determine the accuracy and precision of the predictions. Influential soil and crop parameters will be identified from the model results, and an investigation into the acquisition of such parameters from remote sensing applications will be made. After identifying the parameters that can be ascertained from the aerial images, routines will be developed in the APEX modeling system that incorporate the detailed measurements into model components at selected times during the growing season. If the model incorrectly predicts activities within the watershed, adjustments will be made to the model at individual points within the growing season. Performance comparisons of the model before and after incorporation of remote sensing applications will be made on the basis of crop yield and nutrient transport within the watershed using ground-truth data.