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Application of data science in the prediction of solar energy for the amazon basin:a study case

Clean Energy 2023年第6期7卷 1344-1355页

作者： AndréLuis Ferreira Marques Márcio JoséTeixeira Felipe Valencia de Almeida Pedro Luiz Pizzigatti Corrêa Polytechnic School of the University of Sao Paulo Av.Prof.Luciano Gualberto380-ButantaSao Paulo-SP05508-010Brazil Institute of Physics of the University of Sao Paulo Brazil

The need for renewable energy sources has challenged most countries to comply with environmental protection actions and to handle climate *** energy figures as a natural option,despite its *** has a green energy matrix with significant expansion of solar form in recent *** preserve the amazon basin,the use of solar energy can help communities and cities improve their living standards without new hydroelectric units or even to burn biomass,avoiding harsh environmental *** novelty of this work is using data science with machine-learning tools to predict the solar incidence(W.h/m^(2))in four cities in amazonas state(north-west Brazil),using data from NASA satellites within the period of ***-tree-based models and vector autoregressive(time-series)models were used with three time aggregations:day,week and *** predictor model can aid in the economic assessment of solar energy in the amazon basin and the use of satellite data was encouraged by the lack of data from ground *** mean absolute error was selected as the output indicator,with the lowest values obtained close to 0.20,from the adaptive boosting and light gradient boosting algorithms,in the same order of magnitude of similar references.

关键词： solar energy renewable energy amazon basin machine learning time series data science decision-trees ensemble vector autoregression

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Crustal vertical deformation of amazon basin derived from GPS and GRACE/GFO data over past two decades

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Geodesy and Geodynamics 2021年第6期12卷 441-450页

作者： Jun Fang Meilin He Wei Luan Jiashuang Jiao School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China

In this study,the Gravity Recovery and Climate Experiment(GRACE)satellite observations,combining 71 continuous Global Positioning System(CGPS)data,are used to detect surface vertical loading deformation of the amazon basin during *** results show that the maximal annual amplitude of the surface mass changes derived by GRACE is more than 80 cm in terms of the equivalent water height(EWH)in the amazon *** part of amazon experiences mass gain,especially the amazon River,while there is little mass loss in the northern and eastern *** the Pearson correlation analysis,the monthly de-trended time series of GPS-observed vertical deformation and GRACE-derived mass loading are in good agreement with an average correlation coefficient of about 0.75 throughout the amazon *** common seasonal signals of GPS vertical displacements and GRACE/GFO loading deformations are extracted using the stack *** two kinds of common seasonal signals show a good consistency,and together indicate approximate 20 mm peak-to-peak seasonal *** annual variations are identified both in the monthly GPS and GRACE/GFO data by the wavelet ***,the time-frequency spectrum of GPS has more signal details and more significant semi-annual variations than that of GRACE/*** results may contribute to the understanding of secular crustal vertical deformation in the amazon basin.

关键词： amazon basin GRACE/GFO GPS Pearson correlation analysis Loading deformation

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Impacts of land use and land cover changes on hydrological processes and sediment yield determined using the SWAT model

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International Journal of Sediment Research 2022年第1期37卷 54-69页

作者： Edivaldo Afonso de Oliveira Serr?o Madson Tavares Silva Thomás Rocha Ferreira Lorena Concei??o Paiva de Ataide Cleber Assis dos Santos Aline Maria Meiguins de Lima Vicente de Paulo Rodrigues da Silva Francisco de Assis Salviano de Sousa Denis José Cardoso Gomes Academic Unit of Atmospheric Sciences Federal University of Campina Grande Department of Physics Center for Natural and Exact Sciences Federal University of Santa Maria Institute of Technology Civil Engineering Graduate Program Federal University of Pará Earth System Science Center National Institute of Space Research Institute of Geosciences Federal University of Pará

Land use and land cover (LULC) changes strongly affect local hydrology and sediment *** current study focused on a basin in the Brazilian amazon and had the following three objectives:(1) to perform an effective diagnosis of flow and sediment yield,(2) to evaluate the impacts of LULC changes over the last 40 years on the hydro-sedimentological variables,and (3) to investigate the impacts of the possible trends or breaking points in the flow,surface runoff,and sediment yield *** Soil and Water Assessment Tool (SWAT) model validation showed that the simulated results were consistent with the data measured in the dynamic reproduction of flow ***,changes in LULC altered surface runoff,sediment yield,and flow according to the Mann-Kendall and Pettitt non-parametric *** was also observed that the sub-basins in which pastureland is predominant are more susceptible to increased surface runoff and sediment *** to trend and homogeneity tests,these sub-basins had break points in the time series of these *** the other hand,in the sub-basins whose land cover is predominantly forest,the time series is homogeneous and *** current study highlighted the impacts that 40 years of LULC changes in an amazonian basin had on hydro-sedimentological variables,which,in turn,can play an important role in changing the hydrological cycle,consequently these changes can also impact diverse human activities in the region,such as agribusiness,livestock,energy production,food security,and public water ***,it is concluded that the SWAT model is a good estimator of hydro-sedimentological processes in amazonian basins and can be used by decision makers in the management of water and environmental resources.

关键词： Hydrological modeling Sediment yield amazon basin SWAT model

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Short-term microbial responses to soluble inorganic P input in a tropical lowland rain forest in amazonia

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Pedosphere 2021年第6期31卷 964-972页

作者： Yuri W.L.DE SOUSA Erika BUSCARDO Carlos A.N.QUESADA Henrique E.M.NASCIMENTO Laszlo NAGY National Research Institute for amazonia Manaus 69067-375(Brazil) Department of Forestry University of BrasiliaBrasilia 70910-900(Brazil) Centre for Functional Ecology University of CoimbraCoimbra 3000-456(Portugal) Department of Animal Biology University of CampinasCampinas 13083-862(Brazil)

In non-flooded lowland rain forests with low soil phosphorus(P)in parts of amazonia,P cycling largely occurs via leaf litter recycling by arbuscular mycorrhizal(AM)fungal *** high input of P into these ecosystems occurs during drought years with increased *** the length and frequency of drought events are projected to increase in the region,a single-dose nutrient addition experiment was carried out to test how this would impact P *** application rate of 4 kg P ha^(-1) was used,which corresponds to twice the amount of litter-derived P in an average *** was hypothesized that i)the added mineral P would be immobilized by soil microorganisms,leading to measurable increase in soil microbial biomass carbon(C)and P and ii)AM colonization rate would be reduced by the pulse in mineral P available for plant *** results did not support either of our *** addition of P did not have an effect on AM root colonization,nor was P immobilized by soil microbiota during the experimental *** lack of a difference between the control and treatment at our study site could be attributed to the relatively low one-off dose of P applied that did not change either the colonization rate of roots by AM fungi or the amount of soil available labile *** obtain a mechanistic understanding of the availability,capture,and use of P by plant-symbiont associations in tropical rain forest ecosystems,further integrated studies of the soil-plant system combining long-term nutrient manipulations,modeling,and experimental approaches are required.

关键词： amazon basin arbuscular mycorrhizal fungi nutrient addition phosphorus cycling soil microbial biomass

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