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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.
Sommario
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.
Info autore
Samuel Chukwujindu Nwokolo, with a solid physics background, is a prominent advocate for renewable energy and climate action. His extensive research and practical insights make him an asset for greener solutions. Through speaking, publishing, and environmental involvement, he champions renewable energy's role in combating climate change. With 9 years in renewable energy research, he's published 50+ articles in reputable journals. He instructs graduate students on climate science at the University of Calabar, Nigeria.
Rubee Singh, an Assistant Professor at GLA University in India, is currently pursuing Post-Doctoral Research (D. Lit) at Kumaun University, Nainital, India. She holds an MBA in HR from Dr APJ Abdul Kalam Technical University, U.P, India a PhD in Management from Noida International University, Greater Noida, India, with memberships in multiple international organisations. In addition to her academic roles, she serves as a Managing Editor, Advisory Board Member, and reviewer for journals.
Shahbaz Khan, an Assistant Professor at GLA University (India), excels in Operations Management and Business Analytics. A prolific researcher, he's published 65+ articles in top journals, showcasing a strong research track record. His expertise in Supply Chain Management, Circular Economy, and Industry 4.0 is evident in his academic books and editorial roles. His accolades, including a gold medal and H-index of 25, underscore his significant contributions to the field.
Anil Kumar, a Reader at London Metropolitan University (UK), is an accomplished researcher in Management Science. With a Ph.D. from ABV-IIITM Gwalior and extensive teaching and research experience, he's published 150+ papers in renowned journals. Recognized globally, he's listed in Stanford's top 2% researchers and UK rankings. As an Associate Editor and researcher, his work covers diverse areas like operations management, transportation, and more.
Sunil Luthra, Director at AICTE (India), isa prolific researcher in Technical Education. With 180+ papers and an impressive H-index of 65, his contributions are highly cited. As a Guest Editor and editorial board member, he influences journals such as Production Planning & Control, and Technology Forecasting & Social Change. His expertise spans sustainable production, circular supply chains, and Industry 4.0, evident through numerous publications and prestigious honors.
Riassunto
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.
