Acta Geographica Sinica ›› 2008, Vol. 63 ›› Issue (9): 958-968.doi: 10.11821/xb200809006

Previous Articles     Next Articles

Impacts of Engineering Measures for Water Conservancy on Annual Runoff in the Chaohe River Basin Based on an Empirical Statistical Model

LI Zijun1, LI Xiubin2   

  1. 1. College of Population, Resources and Environment, Shandong Normal University, Jinan 250014, China;
    2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2007-11-19 Revised:2008-06-15 Online:2008-09-25 Published:2008-09-25
  • Supported by:

    Knowledge Innovation Project of CAS, No.KZCX2-YW-401-2; Knowledge Innovation Project of CAS, No.CXIOG-A04-07; National Natural Science Foundation of China, No.40271010

Abstract:

Time series contrasting method is used to analyze the variation of precipitation, runoff, water consumption, water conservancy projects and soil and water conservation measures of the Chaohe River Basin from 1961 to 2005. The results show: (1) The annual precipitation in the drainage basin tends to decrease while the runoff has declined markedly since the 1960s, the mean annual runoff during 1991-2000 is only 90.9% in proportion to that of the period from 1961 to 1970. (2) The annual runoff variation in the drainage basin is significantly related to human activities such as soil and water conservation and hydraulic projects. The influence degree of engineering measures for water conservancy on runoff reduction is calculated by using the rainfall-runoff statistical model. The results show that during 1981-1990, 1991-2000, 2001-2005 and 1981-2005, the average annual runoff reduction amounts are 1.15 ×108, 0.28 ×108, 1.10 ×108 and 0.79 ×108 m3 respectively and the average annual runoff-reducing effects are 31.99% , 7.13% , 40.71% and 23.79% accordingly. Runoff-reducing effects by engineering measures for water conservancy are more prominent in the low water period.

Key words: engineering measures for water conservancy, annual runoff, rainfall-runoff statistical model, the Chaohe River Basin