Python for Water and Environment [electronic resource] / by Anil Kumar, Manabendra Saharia.

Por: Kumar, Anil [author.]Colaborador(es): Saharia, Manabendra [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Innovations in Sustainable Technologies and ComputingEditor: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XIX, 288 p. 92 illus., 89 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789819994083Tema(s): Computational intelligence | Python (Computer program language) | Quantitative research | Environmental education | Computational Intelligence | Python | Data Analysis and Big Data | Environmental and Sustainability EducationFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTexto
Contenidos:
Data Analysis in the Water and Environment -- Python Environment and Basics -- Python Essentials -- Exploratory Analysis of Hydrological Data -- Graphical Hydrological Data Analysis -- Curve Fitting and Regression Analysis -- Hydrological Time Series Analysis -- Common Hypothesis Testing -- Uncertainty Estimation -- Introduction -- Surface Flow Models -- Subsurface Flow Models -- Transport Phenomena -- Contaminant Transport Models -- Conclusion.
En: Springer Nature eBookResumen: This textbook delves into the practical applications of surface and groundwater hydrology, as well as the environment. The Part I, "Practical Python for a Water and Environment Professional," guides readers through setting up a scientific computing environment and conducting exploratory data analysis and visualization using reproducible workflows. The Part II, "Statistical Modeling in Hydrology," covers regression models, time series analysis, and common hypothesis testing. The Part III, "Surface and Subsurface Water," illustrates the use of Python in understanding key concepts related to seepage, groundwater, and surface water flows. Lastly, the Part IV, "Environmental Applications," demonstrates the application of Python in the study of various contaminant transport phenomena.
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Data Analysis in the Water and Environment -- Python Environment and Basics -- Python Essentials -- Exploratory Analysis of Hydrological Data -- Graphical Hydrological Data Analysis -- Curve Fitting and Regression Analysis -- Hydrological Time Series Analysis -- Common Hypothesis Testing -- Uncertainty Estimation -- Introduction -- Surface Flow Models -- Subsurface Flow Models -- Transport Phenomena -- Contaminant Transport Models -- Conclusion.

This textbook delves into the practical applications of surface and groundwater hydrology, as well as the environment. The Part I, "Practical Python for a Water and Environment Professional," guides readers through setting up a scientific computing environment and conducting exploratory data analysis and visualization using reproducible workflows. The Part II, "Statistical Modeling in Hydrology," covers regression models, time series analysis, and common hypothesis testing. The Part III, "Surface and Subsurface Water," illustrates the use of Python in understanding key concepts related to seepage, groundwater, and surface water flows. Lastly, the Part IV, "Environmental Applications," demonstrates the application of Python in the study of various contaminant transport phenomena.

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