Date of Award
2017
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Civil Engineering
Committee Chair
James F. Cruise
Committee Member
John R. Mecikalski
Committee Member
Ashraf Z. Al-Hamdan
Committee Member
Robert E. Griffin
Committee Member
Jason T. Kirby
Subject(s)
Agricultural systems--Mathematical models., Crops and soils--Computer simulation., Soil moisture--Measurement., Crops and climate--Mathematical models.
Abstract
The main focus of this study is to utilize Microwave (MW) and Thermal Infrared (TIR) based satellite derived soil moisture (SM) estimates within a robust, state-of-the-art crop model for obtaining gridded, high spatio-temporal estimates of crop yield and water stress, particularly during drought conditions. The study is unique in many aspects: primarily, it integrates MW and TIR based techniques to provide SM estimation from the surface (0-5 cm) downward to the rooting depth (2 m); further, for the first time, the Principle of Maximum Entropy (POME)-derived SM profiles were developed to drive a gridded crop model. This study allowed us to assess the robustness of agricultural decision support system in remote areas where ground-based SM and weather observations are not typically available for the crop model to perform adequately. Our previous study shows that satellite derived TIR based SM estimates can be made to run the crop model with reasonable success in terms of crop yields as compared to reported yields; yet further research was needed in order to attain higher accuracy at regional spatial scales. We present here: a) detailed validation of the POME model; b) disaggregation of MW SM estimates; c) developing MW/TIR coupled SM profiles using the POME model; and d) application of the developed profile into a crop model via Ensemble Kalman filter. coupling of MW and TIR SM estimates, downscaling of surface SM and assimilation into crop model are the key components of this study. NASAs Land Information system (LIS) gridded SM estimates from the Noah Land Surface Model (LSM), as well as ground based SM observations from operational Natural Resource Conservation Services (NRCS) SCAN sites within the study region were used for profile validation. Yield comparisons were made against NASS reported yields at county level.
Recommended Citation
Mishra, Vikalp, "Assimilation of coupled microwave/thermal infrared soil moisture profiles into a crop modeling system" (2017). Dissertations. 124.
https://louis.uah.edu/uah-dissertations/124