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Article

Utilizing Multi-Source Datasets for the Reconstruction and Prediction of Water Temperature in Lake Miedwie (Poland)

1
Department of Hydrology and Water Management, Adam Mickiewicz University, Krygowskiego 10, 61-680 Poznań, Poland
2
College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China
3
School of Energy and Environment, University of Phayao, Phayao 56000, Thailand
4
Atmospheric Pollution and Climate Research Unit, School of Energy and Environment, University of Phayao, Phayao 56000, Thailand
5
HUN-REN Balaton Limnological Research Institute, 8237 Tihany, Hungary
6
Department of Meteorology and Climatology, Adam Mickiewicz University, Krygowskiego 10, 61-680 Poznań, Poland
7
College of Fisheries, Huazhong Agricultural University, Wuhan 430070, China
8
Department of Land Improvement, Environmental Development and Spatial Management, Poznań University of Life Sciences, Piątkowska 94E, 60-649 Poznań, Poland
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(15), 2753; https://doi.org/10.3390/rs16152753 (registering DOI)
Submission received: 28 June 2024 / Revised: 22 July 2024 / Accepted: 23 July 2024 / Published: 27 July 2024
(This article belongs to the Special Issue Remote Sensing and GIS in Freshwater Environments)

Abstract

Water temperature is a fundamental parameter of aquatic ecosystems. It directly influences most processes occurring within them. Hence, knowledge of this parameter’s behavior, based on long-term (reliable) observations, is crucial. Gaps in these observations can be filled using contemporary methodological solutions. Difficulties in reconstructing water temperature arise from the selection of an appropriate methodology, and overcoming them involves the proper selection of input data and choosing the optimal modeling approach. This study employed the air2water model and Landsat satellite imagery to reconstruct the water temperature of Lake Miedwie (the fifth largest in Poland), for which field observations conducted by the Institute of Meteorology and Water Management—National Research Institute ended in the late 1980s. The approach based on satellite images in this case yielded less accurate results than model analyses. However, it is important to emphasize the advantage of satellite images over point measurements in the spatial interpretation of lake thermal conditions. In the studied case, due to the lake’s shape, the surface water layer showed no significant thermal contrasts. Based on the model data, long-term changes in water temperature were determined, which historically (1972–2023) amounted to 0.20 °C per decade. According to the adopted climate change scenarios by the end of the 21st century (SSP245 and SSP585), the average annual water temperature will be higher by 1.8 °C and 3.2 °C, respectively. It should be emphasized that the current and simulated changes are unfavorable, especially considering the impact of temperature on water quality. From an economic perspective, Lake Miedwie serves as a reservoir of drinking water, and changes in the thermal regime should be considered in the management of this ecosystem.
Keywords: lakes; remote sensing; water temperature; climate change; Landsat lakes; remote sensing; water temperature; climate change; Landsat

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MDPI and ACS Style

Ptak, M.; Zhu, S.; Amnuaylojaroen, T.; Li, H.; Szyga-Pluta, K.; Jiang, S.; Wang, L.; Sojka, M. Utilizing Multi-Source Datasets for the Reconstruction and Prediction of Water Temperature in Lake Miedwie (Poland). Remote Sens. 2024, 16, 2753. https://doi.org/10.3390/rs16152753

AMA Style

Ptak M, Zhu S, Amnuaylojaroen T, Li H, Szyga-Pluta K, Jiang S, Wang L, Sojka M. Utilizing Multi-Source Datasets for the Reconstruction and Prediction of Water Temperature in Lake Miedwie (Poland). Remote Sensing. 2024; 16(15):2753. https://doi.org/10.3390/rs16152753

Chicago/Turabian Style

Ptak, Mariusz, Senlin Zhu, Teerachai Amnuaylojaroen, Huan Li, Katarzyna Szyga-Pluta, Sun Jiang, Li Wang, and Mariusz Sojka. 2024. "Utilizing Multi-Source Datasets for the Reconstruction and Prediction of Water Temperature in Lake Miedwie (Poland)" Remote Sensing 16, no. 15: 2753. https://doi.org/10.3390/rs16152753

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