Implementing and evaluating a higher resolution weather dataset on a coupled hydrological-crop model
Date of Award
2023
Document Type
Thesis
Degree Name
Master of Science in Engineering (MSE)
Department
Civil and Environmental Engineering
Committee Chair
Ashraf Al-Hamdan
Committee Member
Robert Griffin
Committee Member
Michael Anderson
Subject(s)
Crop yields--Models, Hydrologic models, Meteorology--Remote sensing
Abstract
Climate change and climate variability stand as threats to agriculture, especially in low-income countries. Crop models, which simulate crop growth and development, can be used to support decision making in water and agriculture in the context of an uncertain and variable climate. RHEAS is a modeling framework that integrates a hydrologic model, a crop model, and satellite-based observations. It uses gridded input data as forcing variables for the estimation of land surface fluxes and regional crop yield. One of the input datasets is the meteorology dataset, which contains temperature and wind speed data. RHEAS includes the NCEP reanalysis dataset as the standard meteorology dataset. In this work, a higher resolution meteorology dataset, the ERA5 reanalysis, was implemented and its effect on RHEAS evaluated for a domain in Eastern and Southern Africa. The new dataset did not have any effect on the hydrologic component of the framework, however, it affected the yield estimates for the maize crop in the study region. This resulted in an increase to the overall correlation coefficient, a decrease in the absolute bias, and an increase in variance of the time to harvest.
Recommended Citation
Quintero Puentes, Diego Andres, "Implementing and evaluating a higher resolution weather dataset on a coupled hydrological-crop model" (2023). Theses. 503.
https://louis.uah.edu/uah-theses/503