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Historical and projected response of Southeast Asian lakes surface water temperature to warming climate.
Virdis, Salvatore Gonario Pasquale; Kongwarakom, Siwat; Juneng, Liew; Padedda, Bachisio Mario; Shrestha, Sangam.
Afiliación
  • Virdis SGP; Department of Information and Communication Technologies, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4 Klong Luang, Pathum Thani, 12120, Thailand. Electronic address: virdis@ait.ac.th.
  • Kongwarakom S; Department of Information and Communication Technologies, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4 Klong Luang, Pathum Thani, 12120, Thailand. Electronic address: siwatkongwarakom@gmail.com.
  • Juneng L; Department of Earth Sciences and Environment, Universiti Kebangsaan Malaysia, Malaysia. Electronic address: juneng@ukm.edu.my.
  • Padedda BM; Department of Architecture, Design and Urban Planning (DADU), University of Sassari, Via Piandanna 4, 07100, Sassari, Italy. Electronic address: bmpadedda@uniss.it.
  • Shrestha S; Water Engineering and Management, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4 Klong Luang, Pathum Thani, 12120, Thailand. Electronic address: sangam@ait.asia.
Environ Res ; 247: 118412, 2024 Apr 15.
Article en En | MEDLINE | ID: mdl-38316380
ABSTRACT
The temperature of surface and epilimnetic waters, closely related to regional air temperatures, responds quickly and directly to climatic changes. As a result, lake surface temperature (LSWT) can be considered an effective indicator of climate change. In this study, we reconstructed and investigated historical and future LSWT across different scenarios for over 80 major lakes in mainland Southeast Asia (SEA), an ecologically diverse region vulnerable to climate impacts. Five different predicting models, incorporating statistical, machine and deep learning approaches, were trained and validated using ERA5 and CHIRPS climatic feature datasets as predictors and 8-day MODIS-derived LSWT from 2000 to 2020 as reference dataset. Best performing model was then applied to predict both historical (1986-2020) and future (2020-2100) LSWT for SEA lakes, utilizing downscaled climatic CORDEX-SEA feature data and multiple Representative Concentration Pathway (RCP). The analysis uncovered historical and future thermal dynamics and long-term trends for both daytime and nighttime LSWT. Among 5 models, XGboost results the most performant (NSE 0.85, RMSE 1.14 °C, MAE 0.69 °C, MBE -0.08 °C) and it has been used for historical reconstruction and future LSWT prediction. The historical analysis revealed a warming trend in SEA lakes, with daytime LSWT increasing at a rate of +0.18 °C/decade and nighttime LSWT at +0.13 °C/decade over the past three decades. These trends appeared of smaller magnitude compared to global estimates of LSWT change rates and less pronounced than concurrent air temperature and LSWT increases in neighbouring regions. Projections under various RCP scenarios indicated continued LSWT warming. Daytime LSWT is projected to increase at varying rates per decade +0.03 °C under RCP2.6, +0.14 °C under RCP4.5, and +0.29 °C under RCP8.5. Similarly, nighttime LSWT projections under these scenarios are +0.03 °C, +0.10 °C, and +0.16 °C per decade, respectively. The most optimistic scenario predicted marginal increases of +0.38 °C on average, while the most pessimistic scenario indicated an average LSWT increase of +2.29 °C by end of the century. This study highlights the relevance of LSWT as a climate change indicator in major SEA's freshwater ecosystems. The integration of satellite-derived LSWT, historical and projected climate data into data-driven modelling has enabled new and a more nuanced understanding of LSWT dynamics in relation to climate throughout the entire SEA region.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Lagos / Ecosistema Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Res Año: 2024 Tipo del documento: Article Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Lagos / Ecosistema Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Res Año: 2024 Tipo del documento: Article Pais de publicación: Países Bajos