Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis
Addressing the issue of shrinking saline lakes around the globe has turned into one of the most pressing issues for sustainable water resource management. While it has been established that natural climate variability, human interference, climate change, or a combination of these factors can lead to...
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| Format: | Article |
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MDPI AG
2023-04-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/15/8/1508 |
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| author | Babak Zolghadr-Asli Mojtaba Naghdyzadegan Jahromi Xi Wan Maedeh Enayati Maryam Naghdizadegan Jahromi Mohsen Tahmasebi Nasab John P. Tiefenbacher Hamid Reza Pourghasemi |
| author_facet | Babak Zolghadr-Asli Mojtaba Naghdyzadegan Jahromi Xi Wan Maedeh Enayati Maryam Naghdizadegan Jahromi Mohsen Tahmasebi Nasab John P. Tiefenbacher Hamid Reza Pourghasemi |
| author_sort | Babak Zolghadr-Asli |
| collection | DOAJ |
| description | Addressing the issue of shrinking saline lakes around the globe has turned into one of the most pressing issues for sustainable water resource management. While it has been established that natural climate variability, human interference, climate change, or a combination of these factors can lead to the depletion of saline lakes, it is crucial to investigate each case and diagnose the potential causes of this devastating phenomenon. On that note, this study aims to promote a comprehensive analytical framework that can reveal any significant depletion patterns in lakes while analyzing the potential reasons behind these observed changes. The methodology used in this study is based on statistical analysis, data mining techniques, and remote sensing-based datasets. To achieve the objective of this study, Maharlou Lake has been selected to demonstrate the application of the proposed framework. The results revealed two types of depletion patterns in the lake’s surface area: a sharp breaking point in 2007/2008 and a gradual negative trend, which was more pronounced in dry seasons and less prominent in wet seasons. Furthermore, the analysis of hydro-climatic variables has indicated the presence of abrupt and gradual changes in these variables’ time series, which could be interpreted as a signal that climate change and anthropogenic drought are changing the basin’s status quo. Lastly, analyzing the statistically significant correlation between hydro-climatic variables and the lake’s surface area showed the potential connection between the observed changing patterns. The results obtained from data mining models suggest that Maharlou Lake has undergone a morphological transformation and is currently adopting these new conditions. If preventive measures are not taken to revive Maharlou Lake, the tipping point might have been reached, and reviving the lake could be improbable, if not impossible. |
| first_indexed | 2024-03-11T04:25:51Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-11T04:25:51Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-1dc9917ba66c4baabd04623c0bd14c3d2023-11-17T21:48:08ZengMDPI AGWater2073-44412023-04-01158150810.3390/w15081508Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical AnalysisBabak Zolghadr-Asli0Mojtaba Naghdyzadegan Jahromi1Xi Wan2Maedeh Enayati3Maryam Naghdizadegan Jahromi4Mohsen Tahmasebi Nasab5John P. Tiefenbacher6Hamid Reza Pourghasemi7Sustainable Minerals Institute, The University of Queensland, Brisbane 4072, AustraliaDepartment of Water Engineering, College of Agriculture, Shiraz University, Shiraz 7144165186, IranThe Centre for Water Systems, University of Exeter, Exeter EX4 4QD, UKDepartment of Irrigation & Reclamation Engineering, Faculty of Agricultural Engineering & Technology, College of Agriculture & Natural Resources, University of Tehran, Karaj 3158777871, IranDepartment of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran 1417853933, IranDepartment of Civil Engineering, University of St. Thomas, 2115 Summit Avenue, St. Paul, MN 55105, USADepartment of Geography, Texas State University, San Marcos, TX 78666, USADepartment of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz 1352467891, IranAddressing the issue of shrinking saline lakes around the globe has turned into one of the most pressing issues for sustainable water resource management. While it has been established that natural climate variability, human interference, climate change, or a combination of these factors can lead to the depletion of saline lakes, it is crucial to investigate each case and diagnose the potential causes of this devastating phenomenon. On that note, this study aims to promote a comprehensive analytical framework that can reveal any significant depletion patterns in lakes while analyzing the potential reasons behind these observed changes. The methodology used in this study is based on statistical analysis, data mining techniques, and remote sensing-based datasets. To achieve the objective of this study, Maharlou Lake has been selected to demonstrate the application of the proposed framework. The results revealed two types of depletion patterns in the lake’s surface area: a sharp breaking point in 2007/2008 and a gradual negative trend, which was more pronounced in dry seasons and less prominent in wet seasons. Furthermore, the analysis of hydro-climatic variables has indicated the presence of abrupt and gradual changes in these variables’ time series, which could be interpreted as a signal that climate change and anthropogenic drought are changing the basin’s status quo. Lastly, analyzing the statistically significant correlation between hydro-climatic variables and the lake’s surface area showed the potential connection between the observed changing patterns. The results obtained from data mining models suggest that Maharlou Lake has undergone a morphological transformation and is currently adopting these new conditions. If preventive measures are not taken to revive Maharlou Lake, the tipping point might have been reached, and reviving the lake could be improbable, if not impossible.https://www.mdpi.com/2073-4441/15/8/1508climate changeremote sensingtime series analysisdata miningartificial neural networkenvironmental monitoring |
| spellingShingle | Babak Zolghadr-Asli Mojtaba Naghdyzadegan Jahromi Xi Wan Maedeh Enayati Maryam Naghdizadegan Jahromi Mohsen Tahmasebi Nasab John P. Tiefenbacher Hamid Reza Pourghasemi Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis Water climate change remote sensing time series analysis data mining artificial neural network environmental monitoring |
| title | Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis |
| title_full | Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis |
| title_fullStr | Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis |
| title_full_unstemmed | Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis |
| title_short | Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis |
| title_sort | uncovering the depletion patterns of inland water bodies via remote sensing data mining and statistical analysis |
| topic | climate change remote sensing time series analysis data mining artificial neural network environmental monitoring |
| url | https://www.mdpi.com/2073-4441/15/8/1508 |
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