Effects of dynamic crop growth on the simulated precipitation response to irrigation

Keith J. Harding, Tracy E. Twine, Yaqiong Lu

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

The rapid expansion of irrigation since the 1950s has significantly depleted the Ogallala Aquifer. This study examines the warm-season climate impacts of irrigation over the Ogallala using high-resolution (6.33 km) simulations of a version of the Weather Research and Forecasting (WRF) Model that has been coupled to the Community Land Model with dynamic crop growth (WRF-CLM4crop). To examine how dynamic crops influence the simulated impact of irrigation, the authors compare simulations with dynamic crops to simulations with a fixed annual cycle of crop leaf area index (static crops). For each crop scheme, simulations were completed with and without irrigation for 9 years that represent the range of observed precipitation. Reduced temperature and precipitation biases occur with dynamic versus static crops. Fundamental differences in the precipitation response to irrigation occur with dynamic crops, as enhanced surface roughness weakens low-level winds, enabling more water from irrigation to remain over the region. Greater simulated rainfall increases (12.42 mm) occur with dynamic crops compared to static crops (9.08 mm), with the greatest differences during drought years (+20.1 vs +5.9 mm). Water use for irrigation significantly impacts precipitation with dynamic crops (R2 = 0.29), but no relationship exists with static crops. Dynamic crop growth has the largest effect on the simulated impact of irrigation on precipitation during drought years, with little impact during nondrought years, highlighting the need to simulate the dynamic response of crops to environmental variability within Earth system models to improve prediction of the agroecosystem response to variations in climate.

Original languageEnglish (US)
JournalEarth Interactions
Volume19
Issue number14
DOIs
StatePublished - 2015

Keywords

  • Agriculture
  • Applications
  • Coupled models
  • Land use
  • Models and modeling
  • Physical meteorology and climatology
  • Precipitation
  • Vegetation–atmosphere interactions
  • Water budget

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