Simulated water fluxes during the growing season in semiarid grassland ecosystems under severe drought conditions

- Grassland landscape productivity model reproduces measured variables well.
- Spatiotemporal responses of water fluxes to environmental and biological factors.
- Transpiration and evapotranspiration affect water fluxes more than precipitation.
- Responses are different under drought conditions from under normal conditions.

SummaryTo help improve understanding of how changes in climate and land cover affect water fluxes, water budgets, and the structure and function of regional grassland ecosystems, the Grassland Landscape Productivity Model (GLPM) was used to simulate spatiotemporal variation in primary water fluxes. The study area was a semiarid region in Inner Mongolia, China, in 2002, when severe drought was experienced. For Stipa grandis steppe, Leymus chinensis steppe, shrubland, and croplands, the modeled total, daily and monthly averaged, and maximum evapotranspiration during the growing season and the modeled water deficits were similar to those measured in Inner Mongolia under similar precipitation conditions. The modeled temporal variations in daily evaporation rate, transpiration rate, and evapotranspiration rate for the typical steppes also agreed reasonably well with measured trends. The results demonstrate that water fluxes varied in response to spatiotemporal variations in environmental factors and associated changes in the phenological and physiological characteristics of plants. It was also found that transpiration and evapotranspiration (rather than precipitation) were the primary factors controlling differences in water deficit among land cover types. The results also demonstrate that specific phenomena occur under severe drought conditions; these phenomena are considerably different to those occurring under normal or well-watered conditions. The findings of the present study will be useful for evaluating day-scale water fluxes and their relationships with climate change, hydrology, land cover, and vegetation dynamics.