A case study of field-scale maize irrigation patterns in western Nebraska: implications for water managers and recommendations for hyper-resolution land surface modeling

Authors

Justin P. Gibson, University of Nebraska-LincolnFollow
Trenton E. Franz, University of Nebraska-LincolnFollow
Tiejun Wang, University of Nebraska - LincolnFollow
John Gates, The Climate Corporation
Patricio Grassini, University of Nebraska - LincolnFollow
Haishun Yang, University of Nebraska - LincolnFollow
Dean E. Eisenhauer, University of Nebraska - LincolnFollow

Date of this Version

2017

Citation

Hydrol. Earth Syst. Sci., 21, 1051–1062, 2017

Comments

© Author(s) 2017.

doi:10.5194/hess-21-1051-2017

Abstract

In many agricultural regions, the human use of water for irrigation is often ignored or poorly represented in land surface models (LSMs) and operational forecasts. Because irrigation increases soil moisture, feedback on the surface energy balance, rainfall recycling, and atmospheric dynamics is not represented and may lead to reduced model skill. In this work, we describe four plausible and relatively simple irrigation routines that can be coupled to the next generation of hyper-resolution LSMs operating at scales of 1 km or less. The irrigation output from the four routines (crop model, precipitation delayed, evapotranspiration replacement, and vadose zone model) is compared against a historical field-scale irrigation database (2008–2014) from a 35 km² study area under maize production and center pivot irrigation in western Nebraska (USA). We find that the most yield-conservative irrigation routine (crop model) produces seasonal totals of irrigation that compare well against the observed irrigation amounts across a range of wet and dry years but with a low bias of 80mmyr^-1. The most aggressive irrigation saving routine (vadose zone model) indicates a potential irrigation savings of 120mmyr^-1 and yield losses of less than 3% against the crop model benchmark and historical averages. The results of the various irrigation routines and associated yield penalties will be valuable for future consideration by local water managers to be informed about the potential value of irrigation saving technologies and irrigation practices. Moreover, the routines offer the hyper-resolution LSM community a range of irrigation routines to better constrain irrigation decision-making at critical temporal (daily) and spatial scales (<1 >km).