4.4 Article

Spatial and temporal changes of primary production in a deep peri-alpine lake

期刊

INLAND WATERS
卷 9, 期 1, 页码 49-60

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/20442041.2018.1530529

关键词

bio-optics; Earth observation; Lake Geneva; MERIS; primary production; remote sensing

向作者/读者索取更多资源

Lake productivity is fundamental to biogeochemical budgets as well as estimating ecological state and predicting future development. Combining modelling with Earth Observation data facilitates a new perspective for studying lake primary production. In this study, primary production was modelled in the large Lake Geneva using the MEdium Resolution Imaging Spectrometer (MERIS) image archive for 2002-2012. We used a semi-empirical model that estimates primary production as a function of photosynthetically absorbed radiation and quantum yield of carbon fixation. The necessary input parameters of the model-concentration of chlorophyll a, downwelling irradiance, and the diffuse attenuation coefficient-were obtained from MERIS products. The primary production maps allow us to study decennial temporal (with daily frequency) and spatial changes in this lake that a single sample point cannot provide. Modelled estimates agreed with in situ results (R-2=0.68) and showed a decreasing trend (similar to 27%) in production in Lake Geneva for the selected decade. Yet, in situ monitoring measurements missed the general increase of productivity near the incoming Rhone River. We show that the temporal and spatial resolution provided by satellite observations allows estimates of primary production at the basin-scale. The phytoplankton annual primary production was estimated as similar to 302 (SD 20) g C m(-2) yr(-1) for Lake Geneva for 2003 to 2011. This study demonstrates that maps of primary production can be obtained even with reduced resolution (1200 m) MERIS data and relatively simple methods, and thereby calls for deeper integration of remote sensing products into conventional in situ observation approaches.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Environmental Sciences

Flushing the Lake Littoral Region: The Interaction of Differential Cooling and Mild Winds

Cintia L. Ramon, Hugo N. Ulloa, Tomy Doda, Damien Bouffard

Summary: The interaction between a uniform cooling rate at the lake surface and sloping bathymetry efficiently drives cross-shore water exchanges. This study examines how moderate winds affect convective cross-shore transport in lakes, revealing that wind can modify the convective circulation and enhance cross-shore exchange.

WATER RESOURCES RESEARCH (2022)

Article Environmental Sciences

A Model-Based Assessment of Canopy-Scale Primary Productivity for the Baltic Sea Benthic Vegetation Using Environmental Variables and Spectral Indices

Ele Vahtmaee, Jonne Kotta, Laura Argus, Mihkel Kotta, Ilmar Kotta, Tiit Kutser

Summary: This study explored the potential of using meteorological variables and spectral indices to predict primary production in benthic ecosystems. The study found that indices using red and blue band combinations, such as 650/450 and 650/480 nm, showed the strongest correlation with chlorophyll concentration. Boosted regression tree models, along with meteorological data, were highly effective in predicting community photosynthesis in different submerged aquatic vegetation classes.

REMOTE SENSING (2022)

Article Environmental Sciences

Toward Automated Machine Learning-Based Hyperspectral Image Analysis in Crop Yield and Biomass Estimation

Kai-Yun Li, Raul Sampaio de Lima, Niall G. Burnside, Ele Vahtmaee, Tiit Kutser, Karli Sepp, Victor Henrique Cabral Pinheiro, Ming-Der Yang, Ants Vain, Kalev Sepp

Summary: This study integrates autonomous computation and AI technologies with a hyperspectral system to estimate crop yield and biomass. The research shows the significant estimation capacity of the AutoML regression model and highlights the economic and environmental benefits of the hyperspectral system in sustainable and intelligent agriculture.

REMOTE SENSING (2022)

Article Environmental Sciences

Deriving Nutrient Concentrations from Sentinel-3 OLCI Data in North-Eastern Baltic Sea

Tuuli Soomets, Kaire Toming, Jekaterina Jefimova, Andres Jaanus, Arno Pollumae, Tiit Kutser

Summary: This study used remote sensing data to estimate nutrient concentrations in Estonian marine waters, with a focus on total nitrogen. The results showed that remote sensing could be a reliable method for monitoring nutrient loads and understanding regional water quality in marine ecosystems.

REMOTE SENSING (2022)

Article Environmental Sciences

Deploying a GIS-Based Multi-Criteria Evaluation (MCE) Decision Rule for Site Selection of Desalination Plants

Mehdi Gholamalifard, Bonyad Ahmadi, Ali Saber, Sohrab Mazloomi, Tiit Kutser

Summary: Water supply is a critical infrastructure for development, and desalination can help satisfy water demands. Iran has limited application of desalination due to unrestricted access to water, while countries in the Persian Gulf have successfully dealt with water shortages through desalination. This study focuses on the coastal area of Hormozgan in Iran, which faces serious water stress and periodic shortages. The objective is to identify suitable sites for desalination plants using a multi-criteria evaluation design, considering various scenarios and constraints. The results indicate that several zones in the region are suitable for the construction of desalination facilities.
Article Oceanography

Effects of different conditions on particle dynamics and properties in West-Estonian coastal areas

Mirjam Uusoue, Martin Ligi, Tiit Kutser, Francois Bourrin, Kristi Uudeberg, Kersti Kangro, Birgot Paavel

Summary: This study used satellite sensors to monitor water in the Baltic Sea and investigated the properties of suspended particulate matter (SPM). The results showed that concentrations, absorption, scattering, and backscattering of SPM varied temporally and spatially, and the spectral backscattering ratio was wavelength-dependent and influenced by particle origin, size distribution, weather conditions, and location.

OCEANOLOGIA (2022)

Article Geosciences, Multidisciplinary

What water color parameters could be mapped using MODIS land reflectance products: A global evaluation over coastal and inland waters

Zhigang Cao, Ming Shen, Tiit Kutser, Miao Liu, Tianci Qi, Jinge Ma, Ronghua Ma, Hongtao Duan

Summary: This study comprehensively evaluated the performance of MODIS R_land products in global inland and coastal waters and found that it overestimates reflectance and cannot accurately estimate chlorophyll-a and suspended particulate matter. Machine learning models showed good performance in estimating suspended particulate matter but unreliable in estimating chlorophyll-a.

EARTH-SCIENCE REVIEWS (2022)

Article Geosciences, Multidisciplinary

Penetrative Convection Modifies the Dynamics of Downslope Gravity Currents

T. Doda, H. N. Ulloa, C. L. Ramon, A. Wuest, D. Bouffard

Summary: This research demonstrates the impact of the interaction between penetrative convection and downslope gravity currents on the fluid dynamics and transport in littoral aquatic systems. The study reveals that convective plumes can penetrate gravity currents, leading to large vertical fluctuations that enhance vertical mixing and erode the stratified flow, thus limiting basin-scale transport.

GEOPHYSICAL RESEARCH LETTERS (2023)

Article Environmental Sciences

Evaluation of remote sensing and modeled chlorophyll-α products of the Baltic Sea

Tuuli Soomets, Kaire Toming, Birgot Paavel, Tiit Kutser

Summary: The Baltic Sea is a complex study object for watercolor remote sensing, and most remote sensing products fail to produce reliable results. Among the tested products, the best performing remote sensing Chl-alpha product is Case(2)/ Regional CoastColour produced from Sentinel-3 OLCI reflectance.

JOURNAL OF APPLIED REMOTE SENSING (2022)

Article Limnology

Detritus-hosted methanogenesis sustains the methane paradox in an alpine lake

Maciej Bartosiewicz, Jessica Venetz, Saskia Laeubli, Oscar Sepulveda Steiner, Damien Bouffard, Jakob Zopfi, Moritz F. F. Lehmann

Summary: The study reveals the existence of methane paradox in oxygenated waters of a lake and identifies the factors contributing to the variability in its magnitude. It also suggests that methanogenesis in zooplankton detritus is stimulated through the addition of methylphosphonate.

LIMNOLOGY AND OCEANOGRAPHY (2023)

Article Environmental Sciences

A Bayesian approach for remote sensing of chlorophyll-a and associated retrieval uncertainty in oligotrophic and mesotrophic lakes

Mortimer Werther, Daniel Odermatt, Stefan G. H. Simis, Daniela Gurlin, Moritz K. Lehmann, Tiit Kutser, Remika Gupana, Adam Varley, Peter D. Hunter, Andrew N. Tyler, Evangelos Spyrakos

Summary: In this study, Bayesian probabilistic neural networks (BNNs) were developed for estimating chlorophyll-a concentration (chla) in oligotrophic and mesotrophic lakes. The BNNs provided per-pixel uncertainty percentages and were evaluated through various assessments. The results showed that the BNNs achieved higher accuracy in oligotrophic waters, but the accuracy decreased as nutrient levels increased. The study also demonstrated the importance of uncertainty estimation in improving the quality of the chla result.

REMOTE SENSING OF ENVIRONMENT (2022)

Article Limnology

Alkalinity contributes at least a third of annual gross primary production in a deep stratified hardwater lake

Pascal Perolo, Nicolas Escoffier, Hannah E. Chmiel, Gael Many, Damien Bouffard, Marie-Elodie Perga

Summary: In alkaline freshwater systems, bicarbonates can support gross primary production (GPP) even at low CO2 concentrations. However, the contribution of bicarbonates to GPP in lakes has not been quantified throughout the seasons. This study analyzes the daily stoichiometric ratios of CO2-O-2 and alkalinity-O-2 in a deep hardwater lake, revealing that alkalinity is the dominant inorganic carbon source for GPP in both littoral and pelagic environments during the stratified period.

LIMNOLOGY AND OCEANOGRAPHY LETTERS (2023)

Article Geosciences, Multidisciplinary

Past and future climate change effects on the thermal regime and oxygen solubility of four peri-alpine lakes

Olivia Desgue-Itier, Laura Melo Vieira Soares, Orlane Anneville, Damien Bouffard, Vincent Chanudet, Pierre Alain Danis, Isabelle Domaizon, Jean Guillard, Theo Mazure, Najwa Sharaf, Frederic Soulignac, Viet Tran-Khac, Brigitte Vincon-Leite, Jean-Philippe Jenny

Summary: The long-term effects of climate change on lakes globally include substantial changes in thermal regime and oxygen solubility, which can alter ecosystem processes, habitats, and substance concentrations. Although long-term model projections of climate change effects on lakes have been developed, they are rarely compared with multi-decade observations. Additionally, global-scale forcing parameters in lake models have limitations that require significant downscaling. In this study, the effects of climate change on thermal regime and oxygen solubility were analyzed in the four largest French peri-alpine lakes over a period of 1850-2100. The results indicate a critical alteration in lake thermal and oxygen conditions in the coming decades and underscore the need for better integration of long-term lake observatories data and lake models to anticipate climate effects on lake thermal regimes and habitats.

HYDROLOGY AND EARTH SYSTEM SCIENCES (2023)

Article Geosciences, Multidisciplinary

A Bayesian data assimilation framework for lake 3D hydrodynamic models with a physics-preserving particle filtering method using SPUX-MITgcm v1

Artur Safin, Damien Bouffard, Firat Ozdemir, Cintia L. Ramon, James Runnalls, Fotis Georgatos, Camille Minaudo, Jonas Sukys

Summary: In this study, a new Bayesian inference method is proposed for constructing a three-dimensional model of lakes, considering stochastic weather and high-frequency observational data. By combining Bayesian inference with hydrodynamics software, uncertainty in atmospheric forcing is mitigated, and a bidirectional long short-term memory neural network is used to improve uncertainty quantification in the particle filter.

GEOSCIENTIFIC MODEL DEVELOPMENT (2022)

Article Geosciences, Multidisciplinary

Seasonality of density currents induced by differential cooling

Tomy Doda, Cintia L. Ramon, Hugo N. Ulloa, Alfred Wuest, Damien Bouffard

Summary: This study focuses on the seasonality of lateral transport induced by thermal siphons (TSs) and investigates how seasonally varying forcing conditions control the occurrence and intensity of TSs. Observations from Rotsee, a wind-sheltered temperate lake, show that TSs occur frequently in autumn and efficiently flush the littoral region. The results also reveal a decrease in lateral transport by a factor of 2 due to seasonal changes, and the timing of TSs relates to daily heating and cooling phases.

HYDROLOGY AND EARTH SYSTEM SCIENCES (2022)

暂无数据