Global potential to increase crop production through water management in rainfed agriculture

By S. Rost, Dieter Gerten, H. Hoff, Wolfgang Lucht, M. Falkenmark, J. Rockström. 2009

167 citations recorded by the source corpus.

This modeling study explores—spatially explicitly, for current and projected future climate, and for different management intensity levels—the potential for increasing global crop production through on-farm water management strategies: (a) reducing soil evaporation (‘vapor shift’) and (b) collecting runoff on cropland and using it during dry spells (‘runoff harvesting’). A moderate scenario, implying both a 25% reduction in evaporation and a 25% collection of runoff, suggests that global crop production can be increased by 19%, which is comparable with the effect of current irrigation (17%). Climate change alone (three climate models, SRES A2r emissions and population, constant land use) will reduce global crop production by 9% by 2050, which could be buffered by a vapor shift level of 50% or a water harvesting level of 25%. Even if realization of the beneficial effects of rising atmospheric CO2 concentration upon plants was ensured (by fertilizer use) in tandem with the above moderate water management scenario, the water available on current cropland will not meet the requirements of a world population of 9–10 billion.

Subfields: Ecology, Evolution, Behavior and Systematics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/5fddcd88eceb65de89e28d8c8ba843659290e199

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology, Evolution, Behavior and Systematics

  1. L. Rosa
  2. Christoph Müller
  3. Arjen Y. Hoekstra
  4. A. Power
  5. R. A. Fischer

In Global and Planetary Change

  1. Arjen Y. Hoekstra
  2. Christoph Müller
  3. L. Rosa
  4. Martina Flörke
  5. Yoshihide Wada
  6. Cynthia Rosenzweig
  7. Simon N. Gosling
  8. Yoshimitsu Masaki

Citations in the corpus