03085nam a22004935i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050000900153072001600162072002300178072001500201100007400216245009800290250001800388264007200406300006500478336002600543337002600569338003600595347002400631490007000655505045400725520079401179650003201973650004002005650002702045650002902072650003202101650001202133650003202145650004802177700008202225710003402307773002602341776003602367776003602403776003602439830007002475856004602545978-981-99-9408-3DE-He21320251030111506.0cr nn 008mamaa240308s2024    si |    s    |||| 0|eng d  a97898199940837 a10.1007/978-981-99-9408-32doi 4aQ342 7aUYQ2bicssc 7aCOM0040002bisacsh 7aUYQ2thema1 aKumar, Anil.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aPython for Water and Environmenth[electronic resource] /cby Anil Kumar, Manabendra Saharia.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXIX, 288 p. 92 illus., 89 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aInnovations in Sustainable Technologies and Computing,x2731-88180 aData 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.  aThis 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. 0aComputational intelligence. 0aPython (Computer program language). 0aQuantitative research. 0aEnvironmental education.14aComputational Intelligence.24aPython.24aData Analysis and Big Data.24aEnvironmental and Sustainability Education.1 aSaharia, Manabendra.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981999407608iPrinted edition:z978981999409008iPrinted edition:z9789819994106 0aInnovations in Sustainable Technologies and Computing,x2731-881840uhttps://doi.org/10.1007/978-981-99-9408-3