This study presents concepts and problems in soil physics, and provides solutions using original computer programs. In contrast to the majority of the literature on soil physics, this text focuses on solving, not deriving, differential equations for transport. Using numerical procedures to solve differential equations allows the solution of quite difficult problems with fairly simple mathematical tools. It employs an open source philosophy where computer code is presented, explained and discussed, and provides the reader with a full understanding of the solutions. The Python tools provide a simple syntax, Object Oriented Programming techniques, powerful mathematical and numerical tools, and a user friendly environment.


Readership: Teachers, professors and students at universities, as well as researchers in private and public sectors.





2015. “The combination of theory and computer code make this a unique text and reference book for experienced scientists and students alike.” Markus Flury, Professor of Soil Physics and Vadose Zone Hydrology, Washington State University.



2015. “Soil Physics with Python puts a wealth of knowledge about the quantitative functioning of a key environmental system, soils, into the reader’s hand……they entice the reader
to expand and adapt the provided solutions and thereby capacitate him or her to implement and independently explore concepts of the still challenging soil physical processes.” Kurt Roth, Professor, Institute of Environmental Physics, University of Heidelberg.



2016. “…Overall, I believe that the authors have rendered an extremely valuable service to the soil physics community with the publication of this nicely written and appealingly presented text, which I wholeheartedly recommend to soil physics students of all ages. I will definitely not hesitate to use it as a textbook in my own courses. If this great book were adopted widely, it would help train a new generation of soil physicists armed with a very solid understanding of what it really means to use computers to describe soil physical processes, and who would not be at the mercy of commercial software developers to satisfy their computational needs. At this stage, soil physics desperately needs such skilled people to move forward.”
Philippe Baveye, Professor, AgroParisTech, Paris.

Review of Soil Physics with Python:



2021.  “…the book is highly recommended, especially for undergraduate and graduate students who are starting to learn numerical calculus. Mastering this book will require patience and effort, but I guarantee you will be more than rewarded. Furthermore, I hope that the knowledge from this study will be used to create codes and solve new problems. ” Teruhito Miyamoto. Researcher at the National Agriculture and Food Research Organization of Japan. Review (in Japanese) published by the Japanese Society of Soil Physics 

In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behaviour, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis, along with scientific principles and other expert information, guide the specification of mechanistic models that serve to explain real-world behavior rather than merely reproducing it. Often there is a misconception regarding the complexity of the level of mathematics needed to understand and utilize the tools of NLTS (for instance Chaos theory). However, mathematics used in NLTS is much simpler than many other subjects of science,
such as mathematical topology, relativity or particle physics. For this reason, the tools of NLTS have been confined and utilized mostly in the fields of mathematics and physics. However, many natural phenomena investigated I many fields have been revealing deterministic non linear structures. In this book we aim at presenting the theory and the empirical of NLTS to a broader audience, to make this very powerful area of science available to many scientific areas. This book targets students and professionals in physics, engineering, biology, agriculture, economy and social sciences as a textbook in Nonlinear Time Series Analysis (NLTS) using the R computer language.
Readership: Teachers, professors and students at universities, as well as researchers in private and public sectors.

Random Processes Analysis with R

Marco Bittelli, Roberto Olmi and Rodolfo Rosa. Oxford University Press. Under writing


2020. Layered Nature. Assessing and Monitoring the Environment for the Development of an Archaeological Park

Paola Rossi Pisa, Luca Berichillo, Marco Bittelli, Vincenzo Fortunati, Marco Vignudelli. In: An “Integrated Approach for an Archaeological and Environmental Park in South-Eastern Turkey”. Ed.: N. Marchetti, G. Franco, S. F. Musso, and M.B. Spadolini. Springer Nature, Switzerland.

2017. Ruairuen W., G. J. Fochesatto, M. Bittelli , E. B. Sparrow, M. Zhang and W. Schnabel. Evapotranspiration in Northern Agro-Ecosystems: Numerical Simulation and Experimental Comparison. In: “Current Perspective to Predict Actual Evapotranspiration“, Ed. Daniel Bucur, Chapter 4, pp.65-84. ISBN 978-953-51-3174-8, doi: 10.5772/intechopen.68347 .

2016. Bordoni M., C. Meisina, R. Valentino, M. Bittelli, S. Chersich, M. Musetti. Analysis of Hydro-meteorological Monitoring Data Collected in Different Contexts Prone to Shallow Landslides of the Oltrepò Pavese. In: “Advancing Culture of Living with Landslides“, ISBN:9783319534862, vol. 3, pp.357-364, doi:10.1007/9783319534879.

2016. Bordoni M., C. Meisina, M. Bittelli and S. Chersich. Monitoring of hydrological parameters for the identification of shallow landslides triggering: A case study from Northern Italy. In book: Landslides and Engineered Slopes. Experience, Theory and Practice, pp.475-482. DOI: 10.1201/b21520-49.

2014. Bordoni M., D. Zizioli, C. Meisina, R. Valentino, M. Bittelli and S. Chersich. Rainfall-Induced Landslides: Slope Stability Analysis Through Field Monitoring. In: Landslide Science for a Safer Geoenvironment. Eds. K. Sassa, P. Canuti and Y. Yin, pp. 273-279, Springer.
ISBN: 978-3-319-04995-3 (Print), 978-3-319-04996-0 (Online).

2011. Bittelli, M.,A. Pistocchi, F. Tomei, P. P. Roggero, R. Orsini, M. Toderi, G. Antolini and M. Flury. CRITERIA-3D: A Mechanistic Model for Surface and Subsurface Hydrology for Small Catchments. In: “Land Use and Agriculture Measurement and Modelling”. Ed. M. K. Shukla, CABI Publishing. ISBN: 184593797X.

2009. M. Bittelli, Georadar, In: “Groma 2. In profondità senza scavare”, Ed. E. Giorgi, Casa Editrice BraDypUS, Bologna,
pp. 251-272.

2008. Paola Rossi Pisa, Gabriele Bitelli, Marco Bittelli, Maria Speranza, Lucia Ferroni, Pietro Catizone and Marco Vignudelli. Environmental Assessment of an Archaeological Site for the Development of an Archaeological Park. ARCHAIA. “Case studies on Research Planning, Characterisation, Conservation and Management of Archaeological Sites”. Ed. N. Marchetti and I. Thuesen. Archaeopress, Oxford, England.