Understanding Mathematical and Statistical Techniques in Hydrology
| Autor: | Harvey Rodda, Max Little |
|---|---|
| EAN: | 9781119076605 |
| eBook Format: | ePUB |
| Sprache: | Englisch |
| Produktart: | eBook |
| Veröffentlichungsdatum: | 02.11.2015 |
| Untertitel: | An Examples-based Approach |
| Kategorie: | |
| Schlagworte: | earth science flooding flood science geology geoscience groundwater hydrogeology hydrological sciences hydrology hydromodeling limnology oceanography river science statistical hydrology statistical modeling time series water resources |
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Pick up any hydrology textbook and it will not be long before you encounter pages listing sequences of equations representing complex mathematical concepts. Students and practitioners of hydrology will not find this very helpful, as their aim, generally, is to study and understand hydrology, and not to find themselves confronted with material that even students of mathematics would find challenging. Often, equations appear to be copied and pasted into hydrological texts in an attempt to give a more rigorous scientific basis to the narrative. However, they are commonly wrong, poorly explained, without context or background, and more likely to confuse and distance the reader than to enlighten and engage them in the topic.
Understanding Mathematical and Statistical Techniques in Hydrology provides full and detailed expositions of such equations and mathematical concepts, commonly used in hydrology. In contrast to other hydrological texts, instead of presenting abstract mathematical hydrology, the essential mathematics is explained with the help of real-world hydrological examples.
Dr Harvey J. E. Rodda graduated in Environmental Science from Lancaster University and completed his PhD in the Department of Geography, Exeter University in 1993 in the field of hydrological modelling. He is currently a director of Hydro-GIS Ltd, a consultancy company providing specialist services in hydrology and GIS mostly within the private sector. Since 2005 he has been a visiting lecturer at University College London, Department of Earth Sciences, teaching a hydrology module as part of the Geophysical Hazards MSc course.
Professor Max A. Little began his career writing software, signal processing algorithms and music for video games, then moved on by way of a degree in mathematics to the University of Oxford. After postdoc positions in Oxford investigating rainfall and biophysical time series data, he won a Wellcome Trust fellowship at MIT to follow up on his doctoral research work in behavioural and biomedical signal processing. He is currently an associate professor of mathematics at Aston University and a visiting professor at MIT's Media Lab.
Understanding Mathematical and Statistical Techniques in Hydrology provides full and detailed expositions of such equations and mathematical concepts, commonly used in hydrology. In contrast to other hydrological texts, instead of presenting abstract mathematical hydrology, the essential mathematics is explained with the help of real-world hydrological examples.
Dr Harvey J. E. Rodda graduated in Environmental Science from Lancaster University and completed his PhD in the Department of Geography, Exeter University in 1993 in the field of hydrological modelling. He is currently a director of Hydro-GIS Ltd, a consultancy company providing specialist services in hydrology and GIS mostly within the private sector. Since 2005 he has been a visiting lecturer at University College London, Department of Earth Sciences, teaching a hydrology module as part of the Geophysical Hazards MSc course.
Professor Max A. Little began his career writing software, signal processing algorithms and music for video games, then moved on by way of a degree in mathematics to the University of Oxford. After postdoc positions in Oxford investigating rainfall and biophysical time series data, he won a Wellcome Trust fellowship at MIT to follow up on his doctoral research work in behavioural and biomedical signal processing. He is currently an associate professor of mathematics at Aston University and a visiting professor at MIT's Media Lab.