RCIN and OZwRCIN projects

Object

Title: Determining water level fluctuations in small-area lakes using satellite radar data

Creator:

Piasecki, Adam : Autor Affiliation ORCID ; Witkowski, Wojciech T. : Autor Affiliation ORCID

Date issued/created:

2024

Resource type:

Text

Subtitle:

Geographia Polonica Vol. 97 No. 1 (2024)

Publisher:

IGiPZ PAN

Place of publishing:

Warszawa

Description:

24 cm

Abstract:

The research objective was to determine whether and to what extent SAR data can be used to determine changes in the water level in small glacial lakes (with an area of ~1 km2). The research object was Lake Biskupińskie – a small post-glacial lake in central Poland. As part of the research, a methodology for determining water level in small-area lakes based on radar data was developed, the potential for determining lake water levels using high- and medium-resolution SAR data was determined, and the results were verified against field measurements. The analyses employed data from two satellites, TerraSAR-X and Sentinel-1. The research confirmed the effectiveness of using SAR data to determine water-level fluctuations in small glacial lakes. The proposed methodology for working with data from the Sentinel-1 satellite allows for accurate estimation of WLF based on the results of interferometric analyses. Comparative analysis of the radar data results (lake surface) and field measurements (water level) were fully consistent with the data from TerraSAR-X and partially consistent with the data from Sentinel-1. The methodology of radar data analysis to determine WLF proposed in the paper has major research and applied potential, especially in the reconstruction of historical lake water levels.

References:

Altunkaynak, A., Şen, Z. (2007). Fuzzy logic model of lake water level fluctuations in Lake Van, Turkey. Theoretical and Applied Climatology, 90(3), 227-233. https://doi.org/10.1007/s00704-006-0267-z DOI
Bourgeau-Chavez, L., Endres, S., Battaglia, M., Miller, M. E., Banda, E., Laubach, Z., … & Marcaccio, J. (2015). Development of a bi-national Great Lakes coastal wetland and land use map using threeseason PALSAR and Landsat imagery. Remote Sensing, 7(7), 8655-8682. https://doi.org/10.3390/rs70708655 DOI
Brisco, B., Murnaghan, K., Wdowinski, S., & Hong, S. H. (2015). Evaluation of RADARSAT-2 acquisition modes for wetland monitoring applications. Canadian Journal of Remote Sensing, 41(5), 431-439. https://doi.org/10.1080/07038992.2015.1104636 DOI
Cao, N., Lee, H., Jung, H. C., & Yu, H. (2018). Estimation of water level changes of large- scale Amazon wetlands using ALOS2 ScanSAR differential interferometry. Remote Sensing, 10(6), 966. https://doi.org/10.3390/rs10060966 DOI
Coops H, Beklioglu M, & Crisman, T. L. (2003). The role of water-level fluctuations in shallow lake ecosystems-workshop conclusions. Hydrobiologia, 506, 23-27. https://doi.org/10.1023/B:HYDR.0000008595.14393.77 DOI
Coulibaly, P. (2010). Reservoir computing approach to Great Lakes water level forecasting. Journal of Hydrology, 381(1-2), 76-88. https://doi.org/10.1016/j.jhydrol.2009.11.027 DOI
Demir, V., & Yaseen, Z. M. (2023). Neurocomputing intelligence models for lakes water level forecasting: A comprehensive review. Neural Computing and Applications, 35, 303-343. https://doi.org/10.1007/s00521-022-07699-z DOI
Gownaris, N. J., Rountos, K. J., Kaufman, L., Kolding, J., Lwiza, K. M. M., & Pikitch, E. K. (2018). Water level fluctuations and the ecosystem functioning of lakes. Journal of Great Lakes Research, 44(6), 1154-1163. https://doi.org/10.1016/j.jglr.2018.08.005 DOI
Håkanson, L. (1977). The influence of wind, fetch, and water depth on the distribution of sediments in Lake Vänern, Sweden. Canadian Journal of Earth Sciences, 14(3), 397-412. https://doi.org/10.1139/e77-040 DOI
Hegerl, G. C., Black, E., Allan, R. P., Ingram, W. J., Polson, D., & Trenberth, K. E. (2015). Challenges in quantifying changes in the global water cycle. Bulletin of the American Meteorological Society, 96(7), 1097-1115. https://doi.org/10.1175/BAMS-D-13-00212.1 DOI
Hooper, A., Bekaert, D., Spaans, K., & Arıkan, M. (2012). Recent advances in SAR interferometry time series analysis for measuring crustal deformation. Tectonophysics, 514-517, 1-13. https://doi.org/10.1016/j.tecto.2011.10.013 DOI
Keddy, P. A., & Reznicek, A. A. (1986). Great Lakes vegetation dynamics: The role of fluctuating water levels and buried seeds. Journal of Great Lakes Research, 12(1), 25-36. https://doi.org/10.1016/S0380-1330(86)71697-3 DOI
Nagabhatla, N., Cassidy-Neumiller, M., Francine, N. N., & Maatta, N. (2021). Water, conflicts and migration and the role of regional diplomacy: Lake Chad, Congo Basin, and the Mbororo pastoralist. Environmental Science & Policy, 122, 35-48. https://doi.org/10.1016/j.envsci.2021.03.019 DOI
Nowlin, W. H., Davies, J. M., Nordin, R. N., & Mazumder, A. (2004). Effects of water level fluctuation and short-term climate variation on thermal and stratification regimes of a British Columbia reservoir and lake. Lake and Reservoir Management, 20(2), 91-109. https://doi.org/10.1080/07438140409354354 DOI
Palomino-Ángel, S., Anaya-Acevedo, J. A., Simard, M., Liao, T.-H., & Jaramillo, F. (2019). Analysis of floodplain dynamics in the Atrato River Colombia using SAR interferometry. Water. 11(5), 875. https://doi.org/10.3390/w11050875 DOI
Palomino-Ángel, S., Vázquez, R. F., Hampel, H., Anaya, J. A., Mosquera, P. V., Lyon, S. W., & Jaramillo, F. (2022). Retrieval of simultaneous water-level changes in small lakes with InSAR. Geophysical Research Letters, 49(2), e2021GL095950. https://doi.org/10.1029/2021GL095950 DOI
Piasecki, A., & Marszelewski, W. (2014). Dynamics and consequences of water level fluctuations of selected lakes in the catchment of the Ostrowo-Gopło Channel. Limnological Review, 14(4), 187-194. https://doi.org/10.1515/limre-2015-0009 DOI
Piasecki, A., Jurasz, J., & Adamowski, J. F. (2018). Forecasting surface water-level fluctuations of a small glacial lake in Poland using a wavelet-based artificial intelligence method. Acta Geophysica, 66(5), 1093-1107. https://doi.org/10.1007/s11600-018-0183-5 DOI
Piasecki, A., & Witkowski, W. T. (2021). Application of the Triple Diagram Method in forecasting lake water level, on the example of Lake Charzykowskie. Journal of Water and Land Development, (51), 11-16. https://doi.org/10.24425/jwld.2021.139009 DOI
Wdowinski, S., Kim, S. W., Amelung, F., Dixon, T. H., Miralles-Wilhelm, F., & Sonenshein, R. (2008). Space-based detection of wetlands' surface water level changes from L-band SAR interferometry. Remote Sensing of Environment, 112(3), 681-696. https://doi.org/10.1016/j.rse.2007.06.008 DOI
Wilcox, D. A. (2007). Lake-level variability and water availability in the Great Lakes. U.S. Geological Survey. https://doi.org/10.3133/cir1311 DOI
Wilcox, K. L., Petrie, S. A., Maynard, L. A., & Meyer, S. W. (2003). Historical distribution and abundance of Phragmites australis at Long Point, Lake Erie, Ontario. Journal of Great Lakes Research, 29(4), 664-680. https://doi.org/10.1016/S0380-1330(03)70469-9 DOI
Woolway, R. I., Kraemer, B. M., Lenters, J. D., Merchant, C. J., O'Reilly, C. M., & Sharma, S. (2020). Global lake responses to climate change. Nature Reviews Earth & Environment, 1(8), 388-403. https://doi.org/10.1038/s43017-020-0067-5 DOI
Yuan, T., Lee, H., Jung, H. C., Aierken, A., Beighley, E., Alsdorf, D. E., Tshimanga, R. M., & Kim, D. (2017). Absolute water storages in the Congo River floodplains from integration of InSAR and satellite radar altimetry. Remote Sensing of Environment, 201, 57-72. https://doi.org/10.1016/j.rse.2017.09.003 DOI
Zhang, B., Wdowinski, S., Oliver-Cabrera, T., Koirala, R., Jo, M. J., & Osmanoglu, B. (2018). Mapping the extent and magnitude of severe flooding induced by hurricane Irma with multi-temporal Sentinel-1 SAR and InSAR observations. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 42, 2237-2244. https://doi.org/10.5194/isprs-archives-XLII-3-2237-2018 DOI
Zhang, M., Li, Z., Tian, B., Zhou, J., & Tang, P. (2016). The backscattering characteristics of wetland vegetation and water-level changes detection using multi-mode SAR: A case study. International Journal of Applied Earth Observation and Geoinformation, 45, 1-13. https://doi.org/10.1016/j.jag.2015.10.001 DOI

Relation:

Geographia Polonica

Volume:

97

Issue:

1

Start page:

91

End page:

106

Detailed Resource Type:

Article

Resource Identifier:

oai:rcin.org.pl:240974 ; 0016-7282 (print) ; 2300-7362 (online) ; 10.7163/GPol.0270

Source:

CBGiOS. IGiPZ PAN, call nos.: Cz.2085, Cz.2173, Cz.2406 ; click here to follow the link

Language:

eng

Language of abstract:

eng

Rights:

Creative Commons Attribution BY 4.0 license

Terms of use:

Copyright-protected material. [CC BY 4.0] May be used within the scope specified in Creative Commons Attribution BY 4.0 license, full text available at: ; -

Digitizing institution:

Institute of Geography and Spatial Organization of the Polish Academy of Sciences

Original in:

Central Library of Geography and Environmental Protection. Institute of Geography and Spatial Organization PAS

Projects co-financed by:

European Union. European Regional Development Fund ; Programme Innovative Economy, 2010-2014, Priority Axis 2. R&D infrastructure

Access:

Open

Object collections:

Last modified:

Apr 10, 2024

In our library since:

Apr 10, 2024

Number of object content downloads / hits:

130

All available object's versions:

https://www.rcin.org.pl/igipz/publication/277263

Show description in RDF format:

RDF

Show description in RDFa format:

RDFa

Show description in OAI-PMH format:

OAI-PMH

×

Citation

Citation style:

This page uses 'cookies'. More information