Journal of Geographical Sciences ›› 2021, Vol. 31 ›› Issue (12): 1873-1894.doi: 10.1007/s11442-021-1927-8

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An optimized baseflow separation method for assessment of seasonal and spatial variability of baseflow and the driving factors

SUN Jiaqi1,2(), WANG Xiaojun2,3, Shamsuddin SHAHID4, LI Hongyan5,6   

  1. 1. College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
    2. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China
    3. Research Center for Climate Change, Ministry of Water Resources, Nanjing 210029, China
    4. School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia
    5. College of New Energy and Environment, Jilin University, Changchun 130021, China
    6. Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China
  • Received:2020-08-19 Accepted:2021-03-09 Online:2021-12-25 Published:2022-02-25
  • About author:Sun Jiaqi (1992‒), PhD, specialized in hydrology and water resources. E-mail: jqsun@hhu.edu.cn
  • Supported by:
    National Key R&D Program of China(2017YFC0403506);Young Top-Notch Talent Support Program of National High-level Talents Special Support Plan and Strategic Consulting Projects of Chinese Academy of Engineering(2016-ZD-08-05-02)

Abstract:

Baseflow is an important component of river or streamflow. It plays a vital role in water utilization and management. An improved Eckhardt recursive digital filter (IERDF) is proposed in this study. The key filter parameter and maximum baseflow index (BFImax) were estimated using the minimum smoothing method to improve baseflow estimation accuracy. The generally considered BFImax of 0.80, 0.50 and 0.25 according to the drainage basin’s predominant geological characteristics often leads to significant errors in the regions that have complex subsurface and hydrologic conditions. The IERDF improved baseflow estimation accuracy by avoiding arbitrary parameter values. The proposed method was applied for baseflow separation in the upstream of Yitong River, a tributary of the Second Songhua River, and its performance was evaluated by comparing the results obtained using isotope-tracer data. The performance of IERDF was also compared with nine baseflow separation techniques belonging to filter, BFI and HYSEP methods. The IERDF was also applied for baseflow separation and calculation of rainfall infiltration recharge coefficient at different locations along the Second Songhua River’s mainstream for the period 2000-2016. The results showed that the minimum smoothing method significantly improved BFImax estimation accuracy. The baseflow process line obtained using IEDRF method was consistent with that obtained using isotope 18O. The IERDF estimated baseflow also showed stability and reliability when applied in the mainstream of the Second Songhua River. The BFI alone in the river showed an increase from the upstream to the downstream. The proportion of baseflow to total flow showed a decrease with time. The intra-annual variability of BFI was different at different locations of the river due to varying climatic conditions and subsurface characteristics. The highest BFI was observed at the middle reaches of the river in summer due to a water surplus from power generation. The research provided valuable information on baseflow characteristics and runoff mode determination, which can be used for water resources assessment and optimization of economic activity distribution in the region.

Key words: Improved Eckhardt recursive digital filtering, baseflow separation, rainfall infiltration coefficient, the Second Songhua River Basin