Graduate Studies


Date of this Version

Fall 11-30-2015


Kukal, M.S. (2015). Quantification of Spatio-Temporal Changes in Climate Variables, Evapotranspiration and Crop Water Productivity for Maize and Soybean in The Great Plains, USA. MS thesis. University of Nebraska-Lincoln, Department of Biological Systems Engineering.


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Agricultural and Biological Systems Engineering, Under the supervision of Professor Suat Irmak. Lincoln, Nebraska: November 2015

Copyright (c) 2015 Meetpal S Kukal


Spatial and temporal information in regard of climate and crop water use and efficiency is crucial in order to gain understanding of environmental factors, and crop response to these factors. The Great Plains of the USA serve as an ideal agricultural laboratory in terms of agricultural production and its vast areal extent, and high spatial and temporal variability in climate, soils, water availability, cropping systems etc. is expected to occur in the region. Studies addressing this variability and its implications are needed for better decision making by the concerned community. In this thesis, we present four chapters, each addressing the following objectives:

The first chapter aims to assess the spatial and temporal performance of a temperature based reference evapotranspiration equation (Hargreaves-Samani equation) for estimating daily ETo over the US Great Plains. Also, several approaches aimed at a calibration of the HS equation are discussed, which include proposition of calibration coefficients for the climatic divisions in the region.

The second chapter, in its first of the two parts involves quantifying and mapping regional scale air temperatures, diurnal temperature range, precipitation, grass reference evapotranspiration (ETo) and aridity for a 46-year period (1968-2013). The second part aims to investigate temporal trends using non-parametric statistical techniques.

The third chapter focusses on the development of crop specific relationships between crop coefficients and a spectral index (NDVI) in order to predict maize and soybean spatial crop coefficients from satellite imagery. Actual crop (maize and soybean) evapotranspiration was quantified and mapped by amalgamation of the crop coefficients data with reference evapotranspiration data for the years 1982-2013. Spatial and temporal trends in the county-based maize and soybean evapotranspiration were investigated

The purpose of the final chapter is to quantify long-term crop water productivities, precipitation-use-efficiencies and study spatial and temporal trends that occur. All the analyses are based primarily on county-scale datasets, although region wide and statewide magnitudes are also reported.

Advisor: Suat Irmak