Variations in the lake area, water level, and water volume of Hongjiannao Lake during 1986–2018 based on Landsat and ASTER GDEM data

  • Hui Yue
  • Ying LiuEmail author


In this paper, 329 Landsat images combined with the Deeply Clear Water Extraction Index were applied to delineate boundaries of Hongjiannao Lake during 1986–2018. The net shoreline movement (NSM) and linear regression rate (LRR) achieved by Digital Shoreline Analysis System (DSAS) were employed to depict the distance and rate change of lake shorelines. Based on the waterline method and lake boundaries, the water levels were derived from ASTER GDEM V2. Water volume variations were evaluated using the combination of lake area and water level. The variations in Hongjiannao Lake can be grouped into three stages: (i) The lake area, water level, and volume variations slightly declined from 57.25 km2, 1211.15 m, and − 0.0220 km3 in 1986 to 56.36 km2, 1210.66 m, and − 0.036 km3 in 1997, respectively. The average degradation distance (NSM) and rate (LRR) of lake shorelines were 74.26 m and 3.48 m/a, respectively. Although these three aspects slightly decreased, they maintained a stable high level due to stability of natural factors. (ii) A rapid decrease in these three aspects during 1998–2015 was expressed by rates of − 1.15 km2/a (the total decrease was − 21.72 km2), − 0.18 m/a (the total decrease was − 3.45 m), and − 0.0068 km3/a (the total decrease was − 0.1419 km3), respectively. The average shrinkage distance (NSM) and rate (LRR) of lake boundaries were 1049.35 m and 55.00 m/a, respectively, and gradually intensifying human activities were the leading factor. (iii) These three aspects increased from 31.75 km2, 1207.03 m, and − 0.1852 km3 in 2016 to 36.19 km2, 1207.23 m, and − 0.1883 km3, respectively, in 2018. The average enlargement distance (NSM) and rate (LRR) of lake shorelines were 196.87 m and 67.85 m/a, respectively, mainly caused by closing of small mines, sluicing activities, and increase in annual precipitation.


Lake area Water level Lake volume variation NSM and LRR Landsat ASTER GDEM 



The authors appreciate Yao Li for using a ridge regression method to establish a regression model in the paper.

Funding information

This work was jointly supported by the National Natural Science Foundation of China (41401496), Xi’an University of Science and Technology (2019YQ3-04), and Key Laboratory of Mine Geological Hazards Mechanism and Control (6000180096,KF2018-04).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.College of GeomaticsXi’an University of Science and TechnologyXi’anChina
  2. 2.Key Laboratory of Mine Geological Hazards Mechanism and ControlXi’anChina

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