Simulation and Prediction of the Groundwater Level in the Surrounding Area of the Nebraska Management System Evaluation Area site in Central Nebraska.

Authors

Cesar Augusto Gomez Peña, University of Nebraska-LincolnFollow

First Advisor

Yusong Li

Date of this Version

8-2017

Citation

Gomez Peña, C. A., & Li, Y. (2017). Simulation and Prediction of the Groundwater Level in the Surrounding Area of the Nebraska Management System Evaluation Area site in Central Nebraska. ETD collection for University of Nebraska - Lincoln.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of the Requirements For the Degree of Master of Science, Major: Civil Engineering, Under the Supervision of Professor Yusong Li Lincoln, Nebraska August, 2017

Copyright (c) 2017 Cesar Augusto Gomez Pena

Abstract

An efficient water budget is necessary to develop sustainable practices in irrigated lands and determine future trends. Despite a lack of detailed knowledge, climate change is found to profoundly influence groundwater resources through changes in groundwater recharge, groundwater elevation, and groundwater flow processes. Prediction of the groundwater level (GWL) under a changing climate is essential to improve agricultural management.

The goal of this research is to predict the GWL from 2056 to 2060 in the surrounding area of the MSEA. In order to achieve the target, the first research task is to develop a groundwater flow model and then simulate the model to match the historical GWL from 1991 to 2014. The School of Natural Resources (SNR) and the Nebraska Department of Natural Resources (DRN) provided historical groundwater level, soil lithology, and irrigation well data of the site. Visual MODFLOW Flex (version 2015.1) was used to develop the groundwater flow model. Results show that groundwater modeling fairly matched the historical groundwater pattern. The calibrated groundwater model was then applied to predict GWL in the area from 2057 to 2060 using future climate data. In this study, future climate data were obtained from a downscaled climate change predictions from the Community Climate System Model (CCSM4) that represents the worst climate scenario with a high greenhouse gas emission pathway. Future predictions show an overall decreasing trend of GWL over the simulation period, with increases in non-irrigated seasons (winter season) and decreases in irrigated seasons. Nevertheless, the declining rate is higher than the recharge rate, which leads to an average decreased amount of 3.34 feet from the year 2056 to the year 2060.

Advisor: Yusong Li