Evaluation of rainfall and wetland water area variability at Thirlmere Lakes using Landsat time-series data

被引:0
|
作者
B. P. Banerjee
S. Raval
W. Timms
机构
[1] The University of New South Wales,Australian Centre for Sustainable Mining Practices, School of Mining Engineering
关键词
Wetland monitoring; Remote sensing; Long-term monitoring; Time-series analysis; Landsat;
D O I
暂无
中图分类号
学科分类号
摘要
Thirlmere Lakes is a group of five freshwater wetlands in the southwest fringe of Sydney, Australia, that is subject to cyclic wetting and drying. The lakes are surrounded by activities that have led to increasing pressure on the local surface and groundwater supply including farming and mining. The mine has been operating for more than 30 years, and in recent times, there has been speculation that the surface subsidence and underground pumping may have some impact on surface water and groundwater hydrology. A study was undertaken using satellite imagery to examine the relation between water area changes and rainfall variability. The study utilised Landsat time-series data during the period 1982–2014 to calculate changes in the lake water area (LA), through the normalised difference water index (NDWI) threshold. High classification accuracy was achieved using NDWI against high-resolution data that are available for the years 2008 (88.4 %), 2010 (92.8 %), and 2013 (96.9 %). The LA measurement was correlated against 11 historic observations that occurred in 2009, 2010, and 2011 during drier wetland conditions. Correlation analysis of the LA with the residual rainfall mass spread across the past 30 years has found that rainfall variability is a major dominant factor associated with the wetland changes. The underground mining operations, if verified by independent investigations, probably play a minor or negligible contributor to variations in total wetland area during the study period. This study has demonstrated that remote sensing is a technique that can be used to augment limited historic data.
引用
收藏
页码:1781 / 1792
页数:11
相关论文
共 50 条
  • [41] EVALUATION OF PRACTICALITY AND COMPLEXITY OF SOME RAINFALL AND RUNOFF TIME-SERIES MODELS
    DELLEUR, JW
    TAO, PC
    KAVVAS, ML
    [J]. WATER RESOURCES RESEARCH, 1976, 12 (05) : 953 - 970
  • [42] A support vector machine to identify irrigated crop types using time-series Landsat NDVI data
    Zheng, Baojuan
    Myint, Soe W.
    Thenkabail, Prasad S.
    Aggarwal, Rimjhim M.
    [J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2015, 34 : 103 - 112
  • [43] SHORT-TERM VARIABILITY IN TIME-SERIES OF CV DATA
    ATTINGER, EO
    GLASHEEN, W
    SULLIVAN, MR
    ATTINGER, FML
    [J]. FEDERATION PROCEEDINGS, 1986, 45 (04) : 877 - 877
  • [44] Time-Series Landsat Data for 3D Reconstruction of Urban History
    Yu, Wenjuan
    Jing, Chuanbao
    Zhou, Weiqi
    Wang, Weimin
    Zheng, Zhong
    [J]. REMOTE SENSING, 2021, 13 (21)
  • [45] Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data
    Komba, Atupelye W.
    Watanabe, Teiji
    Kaneko, Masami
    Chand, Mohan Bahadur
    [J]. REMOTE SENSING, 2021, 13 (09)
  • [46] Lake Area Analysis Using Exponential Smoothing Model and Long Time-Series Landsat Images in Wuhan, China
    Duan, Gonghao
    Niu, Ruiqing
    [J]. SUSTAINABILITY, 2018, 10 (01) : 149
  • [47] Tracking bamboo dynamics in Zhejiang, China, using time-series of Landsat data from 1990 to 2014
    Li, Mengna
    Li, Congcong
    Jiang, Hong
    Fang, Chengyuan
    Yang, Jun
    Zhu, Zhiliang
    Shi, Lei
    Liu, Shirong
    Gong, Peng
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2016, 37 (07) : 1714 - 1729
  • [48] The Spatiotemporal Evolution of the Mudflat Wetland in the Yellow Sea Using Landsat Time Series
    Huang, Zicheng
    Tang, Wei
    Zhao, Chengyi
    Jiao, Caixia
    Zhu, Jianting
    [J]. Remote Sensing, 2024, 16 (22)
  • [49] Evaluating Impact Using Time-Series Data
    Wauchope, Hannah S.
    Amano, Tatsuya
    Geldmann, Jonas
    Johnston, Alison
    Simmons, Benno, I
    Sutherland, William J.
    Jones, Julia P. G.
    [J]. TRENDS IN ECOLOGY & EVOLUTION, 2021, 36 (03) : 196 - 205
  • [50] Evaluating wetland flow regulating functions using discharge time-series
    Smakhtin, VU
    Batchelor, AL
    [J]. HYDROLOGICAL PROCESSES, 2005, 19 (06) : 1293 - 1305