QUANTIFICATION OF NET IRRIGATION REQUIREMENT AND APPLICATION OF GIS AND GEOGRAPHICALLY WEIGHTED REGRESSION TO EVALUATE THE SPATIAL NON-STATIONARITY BETWEEN PRECIPITATIONS VS IRRIGATED AND RAINFED MAIZE AND SOYBEAN YIELDS ACROSS NEBRASKA

Authors

Vivek Sharma, University of Nebraska - LincolnFollow

Date of this Version

5-2011

Document Type

Article

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Masters of Science, Major: Agricultural and Biological Systems Engineering, Under the supervision of Professor Suat Irmak. Lincoln, Nebraska: May 2011

Copyright (c) 2011 Vivek Sharma

Contact: vivekpathankot@gmail.com

Abstract

Efficient use of fresh water in agriculture is a critical issue in the United States and around the world because of the rapid depletion of fresh water resource due to increasing trend of industrial and environmental development and drought conditions. Understanding the relationships between spatial distribution of environmental variable and yield on large scales can help managers to better evaluate the long-term trends in agricultural productivity to make better assessments in food security, policy decisions, resource assessments, land and water resources enhancement, and management decisions. The Geographic Information System (GIS), along with two different statistical techniques [Geographically Weighted Regression (GWR) and conventional Ordinary Least Square regression (OLS)], was utilized to analyze such relationships between various precipitation categories and irrigated and rainfed maize and soybean in Nebraska (NE). The precipitation was spatially interpolated in ArcGIS using a spline interpolation technique with zonal statistics.

In this study: (i) we interpolate and map spatial distribution of long-term irrigated and rainfed maize and soybean yields for all 93 counties in NE using GWR, OLS, and GIS techniques and to assess the variability of irrigated and rainfed yields with respect to precipitation, (ii) develop relationships between monthly (May to September), seasonal (May 1- September 30), and annual (January 1-December 31) precipitation and crop yields to determine both irrigated and rainfed crop yield response to the magnitude of three precipitation categories, (iii) to investigates the potential advantages of GWR technique over OLS in predicting crop yields, (iv) Calculate reference evapotranspiration (ET_ref )for each of the 93 Nebraska counties, (v) Quantify the actual evapotranspiration (ET_a ) for maize and soybean, (vi) Quantify growing season (May 1 – September 30) net irrigation requirements for maize and soybean and (vii) Evaluate the trends of growing season net irrigation requirements of each county from 1986 to 2009.