Delineating the relative contribution of climate related variables to chlorophyll-a and phytoplankton biomass in lakes using the ERA5-Land climate reanalysis data

Stefanidis, Konstantinos; Varlas, George; Vourka, Aikaterini; Dimitriou, Elias

doi:10.1016/j.watres.2021.117053

Cited by 32 publications

(15 citation statements)

References 56 publications

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“…The data were provided in a regular latitude-longitude grid with a spacing of 0.1 • , covering an area including the 18 lakes studied. The extraction of time series for each lake was performed considering the nearest ERA5-Land grid cell to each lake location, adopting the same methodology applied by Stefanidis et al [22].…”

Section: Climate Datamentioning

confidence: 99%

“…Perhaps examining wind speeds at a finer temporal scale (e.g., on daily basis) may reveal significant changes in wind dynamics, for instance an increase or decrease of the frequency of extreme winds, that could influence lake mixing and phytoplankton productivity. Undoubtedly, delineating the effect of wind speed on limnological processes may prove a complex task [22] even for cases where a declining trend has been documented.…”

Section: Significant Changes Of Climatic Variablesmentioning

confidence: 99%

“…Mediterranean climate is the dominant climatic type which shows a strong seasonal variability of rainfall. Furthermore, the unique topography of Greece is responsible for a clear discrimination of the climate with colder and wetter winters at northern-western mountainous areas in relation to southeastern lowlands [17,22]. This spatial variability influences the hydrology of the Greek lakes and other significant lake processes such as the thermal stratification and the mixing regime.…”

Section: Introductionmentioning

confidence: 99%

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Four Decades of Surface Temperature, Precipitation, and Wind Speed Trends over Lakes of Greece

et al. 2021

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Climate change is known to affect world’s lakes in many ways. Lake warming is perhaps the most prominent impact of climate change but there is evidence that changes of precipitation and wind speed over the surface of the lakes may also have a significant effect on key limnological processes. With this study we explored the interannual trends of surface temperature, precipitation, and wind speed over 18 lakes of Greece using ERA5-Land data spanning over a period of almost four decades. We used generalized additive models (GAMs) to conduct time-series analysis in order to identify significant trends of change. Our results showed that surface temperature has significantly increased in all lakes with an average rate of change for annual temperature of 0.43 °C decade−1. With regard to precipitation, we identified significant trends for most lakes and particularly we found that precipitation decreased during the first two decades (1981–2000), but since 2000 it increased notably. Finally, wind speed did not show any significant change over the examined period with the exception for one lake. In summary, our work highlights the major climatic changes that have occurred in several freshwater bodies of Greece. Thus, it improves our understanding on how climate change may have impacted the ecology of these important ecosystems and may aid us to identify systems that are more vulnerable to future changes.

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Section: Climate Datamentioning

confidence: 99%

Section: Significant Changes Of Climatic Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Four Decades of Surface Temperature, Precipitation, and Wind Speed Trends over Lakes of Greece

et al. 2021

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“…Shallow reservoirs, on the other hand, present a signi cant correlation with nutrient resuspension(Araújo et al 2019;Mesquita et al 2020). Past research has indicated that although wind speed affects the dynamics of algal growth and eutrophication, there is a loss of information on wind dynamics on a monthly scale(Stefanidis et al 2021). Mix-layer depth has an inverse relationship with Chla, which is consistent with previous ndings(Stockwell et al 2020;Stefanidis et al 2021).…”

mentioning

confidence: 99%

“…Past research has indicated that although wind speed affects the dynamics of algal growth and eutrophication, there is a loss of information on wind dynamics on a monthly scale(Stefanidis et al 2021). Mix-layer depth has an inverse relationship with Chla, which is consistent with previous ndings(Stockwell et al 2020;Stefanidis et al 2021). There are several factors to consider when interpreting this relationship, such as water temperature, reservoir morphology, and the ratio between the mix-layer depth and thermocline depth.…”

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confidence: 99%

Uncovering the Influence of Hydrological and Climate Variables in Chlorophyll-A Concentration in Tropical Reservoirs with Machine Learning

Carvalho

Neto

Filho

2022

Preprint

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Climate variability and change, associated with increasing water demands, can have significant implications for water availability. In the Brazilian semi-arid, eutrophication in reservoirs raises the risk of water scarcity. The reservoirs have also a high seasonal and annual variability of water level and volume, which can have important effects on Chlorophyll-a concentration (Chla). Assessing the influence of climate and hydrological variability on phytoplankton growth can be important to find strategies to achieve water security in tropical regions with similar problems. This study explores the potential of machine learning models to predict Chla in reservoirs and to understand their relationship with hydrological and climate variables. The model is based mainly on satellite data, which makes the methodology useful for data-scarce regions. Tree-based ensemble methods had the best performances among six machine learning methods and one parametric model. This performance can be considered satisfactory as classical empirical relationships between Chla and phosphorus may not hold for tropical reservoirs. Water volume and the mix-layer depth are inversely related to Chla, while mean surface temperature, water level, and surface solar radiation have direct relationships with Chla. These findings provide insights on how seasonal climate prediction and reservoir operation might influence water quality in regions supplied by superficial reservoirs.

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HSPEI: A 1‐km spatial resolution SPEI dataset across the Chinese mainland from 2001 to 2022

Xia,

Sha,

Zhao

et al. 2024

Geoscience Data Journal

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The Standardized Precipitation Evapotranspiration Index (SPEI) is a widely recognized and effective tool for monitoring meteorological droughts. However, existing SPEI datasets suffer from spatial discontinuity or coarse spatial resolution problems, which limits their applications at the local level for drought monitoring research. Therefore, we calculated the SPEI index at meteorological stations, combined with the Global Precipitation Measurement (GPM) Precipitation (Pre), Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST), ERA5‐Land Shortwave Radiation (SR), Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) datasets and Random Forest Regression (RFR) model, developed a high spatial resolution (1 km) SPEI (HSPEI) datasets with multiple time scales in mainland China from 2001 to 2022. Compared to other SPEI datasets, the HSPEI datasets have higher spatial resolution and can effectively identify the detailed characteristics of drought in mainland China from 2001 to 2022. Overall, the HSPEI datasets can be effectively applied to the research of different droughts in China from 2001 to 2022.

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Delineating the relative contribution of climate related variables to chlorophyll-a and phytoplankton biomass in lakes using the ERA5-Land climate reanalysis data

Cited by 32 publications

References 56 publications

Four Decades of Surface Temperature, Precipitation, and Wind Speed Trends over Lakes of Greece

Four Decades of Surface Temperature, Precipitation, and Wind Speed Trends over Lakes of Greece

Uncovering the Influence of Hydrological and Climate Variables in Chlorophyll-A Concentration in Tropical Reservoirs with Machine Learning

HSPEI: A 1‐km spatial resolution SPEI dataset across the Chinese mainland from 2001 to 2022

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