Premium
Quantifying streamflow change caused by forest disturbance at a large spatial scale: A single watershed study
Author(s) -
Wei Xiaohua,
Zhang Mingfang
Publication year - 2010
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2010wr009250
Subject(s) - streamflow , environmental science , evapotranspiration , disturbance (geology) , precipitation , climate change , watershed , hydrology (agriculture) , flood forecasting , climatology , physical geography , ecology , geography , drainage basin , meteorology , geology , cartography , geotechnical engineering , machine learning , computer science , biology , paleontology
Climatic variability and forest disturbance are commonly recognized as two major drivers influencing streamflow change in large‐scale forested watersheds. The greatest challenge in evaluating quantitative hydrological effects of forest disturbance is the removal of climatic effect on hydrology. In this paper, a method was designed to quantify respective contributions of large‐scale forest disturbance and climatic variability on streamflow using the Willow River watershed (2860 km 2 ) located in the central part of British Columbia, Canada. Long‐term (>50 years) data on hydrology, climate, and timber harvesting history represented by equivalent clear‐cutting area (ECA) were available to discern climatic and forestry influences on streamflow by three steps. First, effective precipitation, an integrated climatic index, was generated by subtracting evapotranspiration from precipitation. Second, modified double mass curves were developed by plotting accumulated annual streamflow against annual effective precipitation, which presented a much clearer picture of the cumulative effects of forest disturbance on streamflow following removal of climatic influence. The average annual streamflow changes that were attributed to forest disturbances and climatic variability were then estimated to be +58.7 and −72.4 mm, respectively. The positive (increasing) and negative (decreasing) values in streamflow change indicated opposite change directions, which suggest an offsetting effect between forest disturbance and climatic variability in the study watershed. Finally, a multivariate Autoregressive Integrated Moving Average (ARIMA) model was generated to establish quantitative relationships between accumulated annual streamflow deviation attributed to forest disturbances and annual ECA. The model was then used to project streamflow change under various timber harvesting scenarios. The methodology can be effectively applied to any large‐scale single watershed where long‐term data (>50 years) are available.