• Zhi Li
  • Wenzhao Liu
  • Xunchang Zhang
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 294)


Soil water balance has response to climate change and evaluation of soil water change is one of the most important items of climate change impact assessment. GCM outputs under three scenarios were statistically downscaled during 2010~2039 to simulate the potential change of soil water balance in Wangdonggou watershed on the Loess Plateau with WEPP model. GCM predicted a 1.8 to 17.5% increase in annual precipitation, 0.5 to 0.9 °C rises in maximum temperature, 2.0 to 2.3 °C rise in minimum temperature for the region. Plant transpiration will mainly change from April to June and soil evaporation mainly changed during July to September. Percent increases under climate changes, as averaged for each emissions scenario and slope, ranged from -5 to19% for crop transpiration, -4 to 4% for soil moisture, -7 to 7% for soil evaporation, 6.5 to 44.1% for wheat grain yield, 26.3 to 41.7% for maize yield. Climate change will affect soil water balance significantly and some countermeasures are necessary.


Soil Water Loess Plateau Regional Climate Model Emission Scenario Monthly Precipitation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Chen, D., 2000. A monthly circulation climatology for Sweden and its application to a winter temperature case study. International Journal of Climatology, 20: 1067–1076.CrossRefGoogle Scholar
  2. Ding, Y. , 2007. China's National Assessment Report on Climate Change (I): Climate change in China and the Future Trend. Advances in Climate Change Research, 2(1): 3–8.Google Scholar
  3. Hansen, J.W., Indeje, M., 2004. Linking dynamic seasonal climate forecasts with crop simulation for maize yield prediction in semi-arid Kenya. Agric. For. Meteo, 125: 143–157.CrossRefGoogle Scholar
  4. Huszar, T., Mika, J., Loczy, D., Molnar, K. and Kertesz, A., 1999. Climate change and soil moisture: A case study. Phys. Chem. Earth, 24(10): 905–912.CrossRefGoogle Scholar
  5. Mehrotra, R., 1999. Sensitivity of runoff, soil moisture and reservoir design to climate change in central Indian River basins. Climatic Change, 42(4): 725–757.CrossRefGoogle Scholar
  6. Naden, P.S. and Watts, C.D., 2001. Estimating climate-induced change in soil moisture at the landscape scale: An application to five areas of ecological interest in the U.K. Climatic Change, 49(4): 411–440.CrossRefGoogle Scholar
  7. Pan, Z., Arrit, R.W., Gutowski W, Jr. and Takle, E.S., 2001. Soil moisture in a regional climate model: Simulation and projection. Geophys. Res. Lett., 28(15): 2947–2950.CrossRefGoogle Scholar
  8. Ramos, M.C. and Mulligan, M., 2005. Spatial modelling of the impact of climate variability on the annual soil moisture regime in a mechanized Mediterranean vineyard. J Hydrol, 306(1–4): 287–301.CrossRefGoogle Scholar
  9. Solman, S. and Nunez, M., 1999. Local estimates of global climate change: a statistical downscaling approach. Int. J. Climatol, 19: 835–861.CrossRefGoogle Scholar
  10. von Storch, H., 1995. Inconsistencies at the interface of climate impacts studies and global climate research. Meteorologie Zeitschrift, NF4: 72–80.Google Scholar
  11. Wilby, R.L. et al., 1998. Statistical downscaling of general circulation model output: A comparison of methods. Water Resources Research, 34: 2995–3008.Google Scholar
  12. Zhang, X.C., 2005. Spatial downscaling of global climate model output for site-specific assessment of crop production and soil erosion. Agr. Forest. Meteorol., 135(1–4): 215–229CrossRefGoogle Scholar
  13. Zhang, X.C. and Liu, W.Z., 2005. Simulating potential response of hydrology, soil erosion, and crop productivity to climate change in Changwu tableland region on the Loess Plateau of China. Agr. Forest. Meteorol., 131: 127–142.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Northwest Sci-Tech University of Agriculture and ForestryYangling ShaanxiChina
  2. 2.USDA-ARS Grazinglands Research LaboratoryEl RenoUSA

Personalised recommendations