Preprints
https://doi.org/10.5194/hess-2021-5
https://doi.org/10.5194/hess-2021-5

  20 Jan 2021

20 Jan 2021

Review status: this discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.

Drought-induced non-stationarity in the rainfall-runoff relationship invalidates the role of control catchment at the Red Hill paired-catchment experimental site

Yunfan Zhang1,2,3, Lei Cheng1,2,3, Lu Zhang4, Shujing Qin1,2,3, Liu Liu5, Pan Liu1,2,3, Yanghe Liu1,2,3, and Jun Xia1,2,3 Yunfan Zhang et al.
  • 1State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
  • 2Hubei Provincial Collaborative Innovation Center for Water Resources Security, Wuhan 430072, China
  • 3Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, Hubei, China
  • 4CSIRO Land and Water, Black Mountain, Canberra, ACT 2601, Australia
  • 5College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China

Abstract. The most widely used approaches for estimating impacts of vegetation changes on runoff are the paired-catchment method, the time-trend analysis method, and the sensitivity-based method. These three methods have yielded consistent results in many paired-catchment studies, except at the Red Hill experimental site in Australia. However, reasons for the inconsistency have not yet been identified. The objective of this study was to identify the reasons for the inconsistency amongst results using observations of two paired catchments from 1990 to 2015. Results from these three methods showed that afforestation accounted for 32.8 %, 93.5 %, and 76.1 % of total runoff changes, respectively. The inconsistency in results were still apparent even the longest available observation record was used. The rainfall-runoff relationship of the control catchment has been used only in the paired-catchment method. This relationship was confirmed to become non-stationary during the pre- and post-calibration periods due to a 10-year prolonged drought, leading to the inconsistency amongst results. By eliminating drought's effects on the rainfall-runoff relationship of the control catchment, afforestation’s contribution to runoff reduction was 73.4 % using the paired-catchment method, agreeing well the other two methods. This study not only revealed the reason for the inconsistent results that had long been observed at the famous experimental site, but also proved, using experimental observations, that prolonged drought can induce non-stationary rainfall-runoff relationship in catchment. It also demonstrated that the stationarity test is vital for correct use of historical time series and effective research on ecological hydrology in the case of frequent extreme climate.

Yunfan Zhang et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-5', Anonymous Referee #1, 03 Feb 2021
    • AC1: 'Reply on RC1', Lei Cheng, 27 Apr 2021
  • RC2: 'Comment on hess-2021-5', Anonymous Referee #2, 31 Mar 2021
    • AC2: 'Reply on RC2', Lei Cheng, 27 Apr 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-5', Anonymous Referee #1, 03 Feb 2021
    • AC1: 'Reply on RC1', Lei Cheng, 27 Apr 2021
  • RC2: 'Comment on hess-2021-5', Anonymous Referee #2, 31 Mar 2021
    • AC2: 'Reply on RC2', Lei Cheng, 27 Apr 2021

Yunfan Zhang et al.

Yunfan Zhang et al.

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Short summary
We use statistical methods and data assimilation method with physical model to verify that prolonged drought can induce non-stationarity in the control catchment rainfall-runoff relationship, which causes three inconsistent results at the Red Hill paired-catchment site. The findings are fundamental to correctly use long-term historical data and effectively assess ecohydrological impacts of vegetation change given that extreme climate events are projected to occur more frequently in the future.