標(biāo)題: Titlebook: Hydrological Processes Modelling and Data Analysis; A Primer Vijay P. Singh,Rajendra Singh,Srishti Gaur Textbook 2024 The Editor(s) (if app [打印本頁] 作者: Adentitious 時(shí)間: 2025-3-21 18:42
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作者: 多嘴 時(shí)間: 2025-3-22 00:06
Vijay P. Singh,Rajendra Singh,Srishti GaurElucidates the principles and procedures for hydrological modelling and data analysis.Provides essential know-how and fundamentals, including‘data acquisition and processing.Includes detailed case stu作者: 巧思 時(shí)間: 2025-3-22 02:38
Water Science and Technology Libraryhttp://image.papertrans.cn/h/image/430461.jpg作者: Exploit 時(shí)間: 2025-3-22 07:08 作者: 放逐某人 時(shí)間: 2025-3-22 10:30
Hydrological Processes Modelling and Data Analysis978-981-97-1316-5Series ISSN 0921-092X Series E-ISSN 1872-4663 作者: 乞丐 時(shí)間: 2025-3-22 13:53
Introduction,ements of hydrologic modelling, including different kinds of models, parameter estimation, model calibration and validation, sensitivity analysis, and error analysis. Various kinds of hydrologic data needed for modelling are outlined. The chapter is concluded with the organisation of the book.作者: 保留 時(shí)間: 2025-3-22 21:00
Textbook 2024al data collection, including the use of drones and smartphones. The foremost objective of the book is to present the hydrological data analysis procedures. It explains the steps involved in data analysis for easy understanding of the reader, including students and professionals. This book presents 作者: SUE 時(shí)間: 2025-3-22 23:09
Vijay P. Singh,Rajendra Singh,Pranesh Kumar Paul,Deepak Singh Bisht,Srishti Gaurar in Spin Labeling: 2001. Lastly it is a pleasure to honor two scientists whose contributions were both pioneering and pivotal to the spin label technique: Pro978-1-4757-8083-3978-0-306-47072-1Series ISSN 0192-6020 Series E-ISSN 2512-2215 作者: 運(yùn)動吧 時(shí)間: 2025-3-23 04:10 作者: Ganglion-Cyst 時(shí)間: 2025-3-23 07:19 作者: WATER 時(shí)間: 2025-3-23 11:45 作者: Rejuvenate 時(shí)間: 2025-3-23 17:11
0921-092X the book is to present the hydrological data analysis procedures. It explains the steps involved in data analysis for easy understanding of the reader, including students and professionals. This book presents 978-981-97-1318-9978-981-97-1316-5Series ISSN 0921-092X Series E-ISSN 1872-4663 作者: 新字 時(shí)間: 2025-3-23 21:58
Vijay P. Singh,Rajendra Singh,Pranesh Kumar Paul,Deepak Singh Bisht,Srishti Gaur作者: 侵害 時(shí)間: 2025-3-24 00:06
Vijay P. Singh,Rajendra Singh,Pranesh Kumar Paul,Deepak Singh Bisht,Srishti Gaur作者: verdict 時(shí)間: 2025-3-24 03:19 作者: 微枝末節(jié) 時(shí)間: 2025-3-24 06:54
Vijay P. Singh,Rajendra Singh,Pranesh Kumar Paul,Deepak Singh Bisht,Srishti Gauratures from the NMR point of view. The NMR methodology made rapid progress during the past decade using high frequencies of operation that became possible with the advent of superconduc-ting magnets and employing Fourier transform methods coupled with computers for signal averaging and data processi作者: 個(gè)阿姨勾引你 時(shí)間: 2025-3-24 13:15
Vijay P. Singh,Rajendra Singh,Pranesh Kumar Paul,Deepak Singh Bisht,Srishti Gaur and sugars are dominated by nitrogen-nitrogen or nitrogen-oxygen interactions by way of hydrogen bonds, the best-known of these being the Watson-Crick H-bonds needed for the transfer of the genetic information. The special electronic properties of nitrogen are of importance in many coenzymes. Nitro作者: INCH 時(shí)間: 2025-3-24 15:34
Vijay P. Singh,Rajendra Singh,Pranesh Kumar Paul,Deepak Singh Bisht,Srishti Gauratures from the NMR point of view. The NMR methodology made rapid progress during the past decade using high frequencies of operation that became possible with the advent of superconduc-ting magnets and employing Fourier transform methods coupled with computers for signal averaging and data processi作者: 小隔間 時(shí)間: 2025-3-24 22:55
Vijay P. Singh,Rajendra Singh,Pranesh Kumar Paul,Deepak Singh Bisht,Srishti Gaureters, as well as new spectral assignment techniques such as two-dimensional NMR methods, have enabled researchers to make almost complete assignments of the .H NMR spectra of peptides containing up to ca. fifteen amino acid residues. The .H NMR spectra of larger peptides and proteins remain only pa作者: Infirm 時(shí)間: 2025-3-25 02:59
Vijay P. Singh,Rajendra Singh,Pranesh Kumar Paul,Deepak Singh Bisht,Srishti Gaureters, as well as new spectral assignment techniques such as two-dimensional NMR methods, have enabled researchers to make almost complete assignments of the .H NMR spectra of peptides containing up to ca. fifteen amino acid residues. The .H NMR spectra of larger peptides and proteins remain only pa作者: capsaicin 時(shí)間: 2025-3-25 05:01 作者: Kidney-Failure 時(shí)間: 2025-3-25 10:33 作者: Airtight 時(shí)間: 2025-3-25 12:34 作者: engrossed 時(shí)間: 2025-3-25 16:46 作者: 植物群 時(shí)間: 2025-3-25 21:07 作者: nascent 時(shí)間: 2025-3-26 01:07
Extreme Event Analysis,del these extremes, and emphasises the significance of hazard and risk assessments in disaster risk reduction. Furthermore, this chapter describes the critical elements in conducting these assessments while providing an overview of real-time flood and drought forecasting to present the practical app作者: 推測 時(shí)間: 2025-3-26 07:12
Hydrological Processes Modelling and Data AnalysisA Primer作者: Atheroma 時(shí)間: 2025-3-26 09:39 作者: Soliloquy 時(shí)間: 2025-3-26 13:24
Remote Sensing and Geographic Information Systems Driven Data Analysis,ighted. Besides, a few prevalent commercial and open-source GIS and remote sensing software are enlisted. The chapter includes the RS and GIS applications in flood management, drought monitoring, water quality monitoring and water body mapping.作者: 表皮 時(shí)間: 2025-3-26 18:22 作者: 吃掉 時(shí)間: 2025-3-26 21:51
Emerging Fields in Hydrology,ed to the development of data science, tools of analysis, fields of application of hydrology, modelling technology, or the discovery of new concepts. This chapter provides a snapshot of fields deemed to be emerging in hydrology.作者: 色情 時(shí)間: 2025-3-27 03:16
Case Studies,nging climate for the Indian mainland, analyse water balance components under LULC change conditions using Soil and Water Assessment Tool (SWAT), and finally, uncertainty analysis of hydrologic model simulations of SWAT model using quantile mapping.作者: Consequence 時(shí)間: 2025-3-27 09:13 作者: linguistics 時(shí)間: 2025-3-27 13:20
Machine Learning (ML) in Water Resources,f ML algorithms, the history of ML, and day-to-day examples of the usage of ML techniques. Besides, the chapter briefly introduces a few ML techniques/algorithms. Among these, support vector machines (SVMs), convolutional neural networks (CNNs) and random forests appear to be the most actively investigated algorithms, but new ones are emerging.作者: 夾死提手勢 時(shí)間: 2025-3-27 16:15
Integrated Modelling Systems,e emerging techniques like explainable machine ML and physics-constraint ML that are useful in interpreting the black-box ML models and making the process opaque. Incorporation of these techniques can leverage the strengths of hybrid models.作者: Antioxidant 時(shí)間: 2025-3-27 19:04
Textbook 2024nge of practical applications. The book is driven by the realisation that science, technology, engineering, and mathematics (STEM) concepts are essential in engineering hydrology to produce well-trained hydrologists. Such hydrologists will be equipped to face future societal challenges that require 作者: Parallel 時(shí)間: 2025-3-27 22:47
Introduction,ements of hydrologic modelling, including different kinds of models, parameter estimation, model calibration and validation, sensitivity analysis, and error analysis. Various kinds of hydrologic data needed for modelling are outlined. The chapter is concluded with the organisation of the book.作者: 根除 時(shí)間: 2025-3-28 04:17
Data Availability and Aquisition, However, the constraints and scarcity of data present significant challenges in achieving the desired accuracy and reliability. Researchers have leveraged various data sources to overcome data constraints, including ground-based observations, global and reanalysis datasets, and remote sensing infor作者: Mundane 時(shí)間: 2025-3-28 08:54
Time Series Analysis,nd trends in the data, which may enhance the prediction of future water availability and flood or drought risk. The chapter introduces different types of time series data and discusses the decomposition of a time series into its constituent components like trend, cycle, seasonality, and irregularity作者: 冷峻 時(shí)間: 2025-3-28 13:04
Remote Sensing and Geographic Information Systems Driven Data Analysis,roduces the basic concepts of the RS and GIS. The earth observation satellites and missions, image processing techniques, and spectral indices are discussed. Similarly, the popular GIS spatial and attribute data models are presented. Data sources for hydrology and water resources modelling are highl作者: vasospasm 時(shí)間: 2025-3-28 18:13 作者: Organization 時(shí)間: 2025-3-28 19:11
Land Use Land Cover (LULC) Change Analysis, and popular modelling software. The chapter also attempts to identify the limitations, challenges, and novel opportunities in LULC modelling. The main recommendation from the chapter is the utilisation of integrated modelling systems for LULC changes, along with the consideration of uncertainty ass作者: 入會 時(shí)間: 2025-3-29 02:58 作者: 微生物 時(shí)間: 2025-3-29 03:40 作者: 性別 時(shí)間: 2025-3-29 08:45 作者: 有節(jié)制 時(shí)間: 2025-3-29 13:49 作者: 碎片 時(shí)間: 2025-3-29 18:26
Emerging Fields in Hydrology,ing the past half a century. Several areas that had not taken birth earlier are now considered integral to hydrology. Examples are social hydrology, global hydrology, ecohydrology, remote sensing hydrology, hydrology of disasters, and nuclear hydrology. The emergence of some of the areas can be trac作者: MAIM 時(shí)間: 2025-3-29 20:25
