Off-campus UNL users: To download campus access dissertations, please use the following link to log into our proxy server with your NU ID and password. When you are done browsing please remember to return to this page and log out.

Non-UNL users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

A field -scale furrow irrigation model

Christopher John Skonard, University of Nebraska - Lincoln

Abstract

Predicting furrow irrigation performance is challenging due to the use of empirical relationships describing the infiltration of water into the soil. The parameters traditionally used in the empirical relationship are not correlated to soil properties and must be determined through irrigation evaluations and once determined are of limited value due to temporal and spatial variability. This research focuses on developing a methodology to predict field-scale performance of a furrow irrigated field. ^ A primary component in predicting furrow irrigation performance is the ability to use a physically-based infiltration equation. A two-dimensional, physically-based furrow infiltration model has been developed and is based on the Green-Ampt infiltration model which only requires three, physically-based parameters. The two-dimensional model has been shown to accurately predict cumulative volume infiltrated compared to a finite element based model for variably saturated flow. The two-dimensional model accounts for changing wetted perimeter during the irrigation due to the depth fluctuation of water in the furrow during irrigation. ^ The two-dimensional furrow infiltration model was incorporated into an existing surface irrigation software package. The surface irrigation model when used with the two-dimensional infiltration model is able to predict furrow irrigation water advance, recession, average depth infiltrated and average runoff depth. The modified surface irrigation model is valid across a broad range of soils. ^ The modified surface irrigation model was implemented in a stochastic modeling framework to predict field-scale irrigation performance. The method of Latin Hypercube Sampling was used to propagate soil variability through the modified surface irrigation model. The stochastic framework was able to incorporate field variability in the predicted field-scale response. Incorporating field variability into the decision making process allows for better field water management. ^

Subject Area

Agriculture, Agronomy|Engineering, Agricultural

Recommended Citation

Skonard, Christopher John, "A field -scale furrow irrigation model" (2002). ETD collection for University of Nebraska - Lincoln. AAI3074102.
http://digitalcommons.unl.edu/dissertations/AAI3074102

Share

COinS