4. Personal Project

4.1. Introduction

Choose one of the topics below and email me your choice of the topic. It is obligatory to work in a couple; this means you do all the work together, including writing the report. You will both get the same mark.

Most topics include literature study and modelling. The last topic however includes literature study only.

Before starting, it is important to define research questions. This will determine what modelling work you will do and how you will report on the modelling results. For some topics I give hints for research questions (see below).

Keep your model simple. Note that you have little time to develop your model.

The report should be written as a scientific article with the following structure:

  • Abstract
  • Introduction (problem definition, research questions or objectives, outline of the rest of the paper)
  • Methods (here: description of the model and/or scenarios done)
  • Results (provide results of model simulations, without extensive discussion)
  • Discussion and conclusions (discuss results, compare with other studies, provide main findings)
  • References

For the last topic (without modelling) you are allowed to use a different structure for the paper.

The report should not be longer than 4 pages (12p font, single line spacing). If needed you can provide tabulated data, additional figures, or details on implementation of the model as an appendix.

Note that you do not get extensive support from your tutor(s). However you can ask questions by email (please keep it short). In addition, you could ask other students if you need help programming your model.

4.2. Topics

4.2.1. Land degradation modelling

Indication for the content of the topic: literature study 20%, modelling 40 %, writing report 40%.

The output from rainfall-runoff models can be used to calculate water erosion. Extend the snowmelt model (the one you used in the dynamic modelling exercises) with a component that calculates a map with the total amount of water erosion over the winter season (180 days simulated by the model).

Use the Morgan, Morgan and Finney model described in Morgan, R.P.C., 2005, Soil Erosion and Conservation, Blackwell. You at least need to include detachment of soil by raindrop impact and runoff, ignoring the transport capacity (i.e. assuming everything can be transported).

Compare modelled soil loss with tabulated values from the literature (to see whether the order of magnitude of the modelled values is correct); this could be one of your research questions.

Download dataset and model.

Email me if you would like to borrow the Morgan (2005) book.

4.2.2. Early warning signals of critical transitions

Indication for the content of the topic: literature study 40%, modelling 20 %, writing report 40%.

In the dynamic modelling practicals you developed a vegetation model with a critical transition to lower biomass when a threshold of grazing pressure is exceeded. It is notably difficult to predict such critical transitions as the change in biomass is very low before the transition occurs. However early warning signals exist that show a change well ahead of a transition. These include spatial variance of biomass (you calculated this in the exercise), spatial skewness of biomass, and so-called ‘flickering’.

Study the literature below. Extend the vegetation growth model (the one you constructed during the practicals) with calculation of spatial skewness of biomass (calculated over the map for each timestep, just like variance). Compare the two early warning signals (variance and skewness) regarding their capability to forecast the transition. If you want you can do this for different scenarios of model parameters (e.g., spatial diffusion parameter).

Download dataset and model.

Literature:

  • Dakos V., van Nes E.H., Donangelo R., Fort H. & Scheffer M. (2009). Spatial correlation as leading indicator of catastrophic shifts. Theor. Ecol., 3, 163-175.
  • Guttal V. & Jayaprakash C. (2009). Spatial variance and spatial skewness: Leading indicators of regime shifts in spatial ecological systems. Theor. Ecol., 2, 3-12.
  • Scheffer M., Bascompte J., Brock W.A., Brovkin V., Carpenter S.R., Dakos V., Held H., Van Nes E.H., Rietkerk M. & Sugihara G. (2009). Early-warning signals for critical transitions. Nature, 461, 53-59.

4.2.3. Hydrological model: calibration

Indication for the content of the topic: literature study 5%, modelling 65%, writing report 30%.

In this assignment you will calibrate the snowmelt model developed in the practical exercises. You need to calibrate on the observed discharge at the outflow point. Have a look at the script included in the zip file for some helper functions and explanation of the data set. Choose the calibration method yourself. It is recommended to use a brute force technique. Decide yourself which parameters to calibrate, but be sure to include the snow melt parameter.

Download dataset and model.

4.2.4. Land use change modelling using cellular automata

Indication for the content of the topic: literature study 10%, modelling 60%, writing report 30%.

Cellular automata is a type of model that uses local neighbourhood interactions to simulate the larger scale behaviour of a spatio-temporal system. These local neighbourhood interactions are given by transition rules valid for each cell on a grid of cells, where the state of a cell changes over a timestep as a function of the state of cells of directly neighouring cells. Cellular automata are widely used in the spatial sciences, e.g. for modelling plant growth and spread, modelling forest fire spreading, modelling growth of bacteria on leaves of vegetation, modelling socio-economic systems. The aim of this topic is to learn more about cellular automata modelling in general, by studying literature. In addition you will construct a simple cellular automata model of expansion of cities (Randstad, the Netherlands). Start with the landuse situation in 2000 (as represented by the data set) and try to simulate the change in landuse over the coming decennia. Use simplified landuse change transition rules - the approach is more important than the outcome! Alternatively, there is a possibility of using an existing (large) land use change model that you can use for a case study area in Mozambique (e.g. for a scenario analysis).

Literature:

Torrens, P.M., 2000, How cellular models of urban systems work (1. theory). Centre for advanced spatial analysis, working paper series. Paper 28. Available at http://www.bartlett.ucl.ac.uk/casa/publications/working-paper-28

Batty M., Xie Y., Sun Z., 1999. Modeling urban dynamics through GIS-based cellular automata. Computers, Environment and Urban Systems 23:205-233. To retrieve this paper, email me and I will email you the pdf.

White, R. 1998. Cities and Cellular Automata. Discrete dynamics in Nature and Society 2:111-125. To retrieve this paper, email me and I will email you the pdf.

Download dataset and model.

Download information regarding the data set.

4.2.5. Validation of models in the earth sciences

Indication for the content of the topic: literature study 50%, writing report 50%.

In 1994 Oreskes et al published a paper discussing validation of numerical models in the earth sciences. Their main message was that validation of models is not possible. This raised a lot of dicussion in the earth science community. You can find hundreds of papers citing the Oreskes paper. Read the paper by Oreskes and collect a number of other papers on the same topic (e.g. those that cite Oreskes). In your report either provide a review of these papers or provide a discussion on validation of models in the earth sciences. This topic is a good choice if you are interested in philosophy of science.

Literature:

  • Oreskes N., Shrader-Frechette K. & Belitz K. (1994). Verification, validation, and confirmation of numerical models in the earth sciences. Verification, validation, and confirmation of numerical models in the earth sciences, Science, 263, 641-646.

4.3. Writing a short paper: checklist, misc. recommendations

  • Use Italics (‘cursief’) for all symbols in equations or in the text. However a vector (‘list of values’) is mostly given in bold. The style in the equations and in the main text should correspond.
  • Avoid multi symbol variables or parameters in equations. E.g. Evap = Soilwater / SoilP . Better: E = s/a. Use subscribts when you have many parameters and variables. Note however that in programming, the use of long variable names (that describe the content of the variable) names is recommended.
  • Do not write like in a diary (‘First we did this,.... Then we started to realize.. and we did this and that...’).
  • Put larger blocks of computer code (say, more than 2 lines) in a table instead of inserting it in the main text. Whole programs should be given in an appendix.
  • Use a main (cover) title that makes sense.
  • Provide quantitative data in figures (bar graphs, line graphs, scatter plots, use e.g. Excel, Splus), not tables. It is allowed using a table but it is almost always better using figures.
  • If you write the report with Microsoft Word, use Microsoft Equation editor (available in Word) for equations. Do not copy paste bitmaps (gif or tifs) of equations from other docs into your paper.
  • Number equations - always (provide the number after the equation, e.g, (3)).
  • Check out an article from a scientific journal (e.g. from your reader) and use that as an example for formatting, layout, use of figure captions, literature references, etc.
  • Do not use language as if you are talking (spreektaal)
  • When you submit your report by email, put everything in one file (word or pdf). Do not send a whole bunch of files (it is too much work printing everything).
  • Describe content in a logical order, instead of describing content in the order you dealt with it while modelling. So, do not use sentences like ‘eerst deden we dit, toen zijn we dat gaan doen, etc..).
  • Use a spellchecker (always)
  • A caption of a figure or table should at least explain all symbols used in the figure or table. The same holds for an appendix. In principle, the table/figure should be understandable without reading the main text (although there are exceptions to this rule)
  • Provide figure legends (always)
  • If a figure contains a map, provide a scale (scale bar)
  • Do not hand in black and white prints of color figures (never.., even not when emailing originals..)
  • Use the same format for each reference in your literature list and refer to the references in the text.
  • Number the sections in your report, provide these numbers also in the contents Preferably use some kind of hierarchical numbering, for instance 1 1.1 1.1.1 1.1.2 2 2.1 2.2 etc
  • Number figures and tables. In the main text, refer to figures or tables by using these numbers.
  • All literature refered to in the main text should appear in the literature/references section at the end of the report. Check this in detail before handing in!
  • Do not mix past and present tense. Sometimes it is possible, but in many cases it is better to stick to past or present tense.
  • Avoid the use of ‘I’ or ‘we’ (1e persoon). However you can use it sometimes (if you really want and think it is apprpriate).
  • If you use a figure from a book or another report, always provide the reference.
  • Do not use English terminology in a report written in Dutch when correct Dutch terms are available (e.g. ‘catchment’ = ‘stroomgebied’)
  • Have a look at comments on earlier papers you wrote. Take them into account when writing your next paper.
  • Provide units (all variables in equations)!
  • Avoid the use of abbreviations.
  • Do not use ‘etc.’ Just don’t.
  • Provide page numbers.
  • Write concise. Also, do not add figures that could be left out. And, if possible combine to figures in one figure (e.g. two lines (of the same attribute) in a graph is better than two graphs each with one line). You can also use panels, Fig 1A, Fig 1B, etc.
  • Use every page from top to bottom (apart from last pages of very long sections), do not include too much whitespace!
  • Do not just copy-paste figures (maps) from screen. Adjust colors, add a legend, remove MS Windows bars, buttons, check size of text or modify text, etc. Use a graphics package (e.g. Freehand, Paintshop or whatever).
  • Try to come up with interesting results (do not just list all results from your model, but try to emphasize the most interesting results). But note that this should always fit with the goals of your research (if needed adjust these goals).
  • Use courier font for computer code, PCRaster scripts, or filenames. Also in the main text (not just in tables).
  • In a paper reporting research in the geosciences, you should avoid the use of computer code to explain calculations. Many people will not know the programming language you used, and they won’t understand the code. Instead, explain calculations using mathematical equations. If you write a report on a geoinformatics related topic (e.g. how you construct a piece of software) you can however include code as code is the topic of your research.
  • Use a good dictionary. If you do not have one, buy one. I could recommend Longman Dictionary of Contemporary English (http://www.longman.com/ldoce). Or use the online version at http://www.ldoceonline.com. Google translate is also useful.
  • Read through the text and correct all small (or large..) errors (typos for instance) before handing in!
  • Do not use a title that ends with a ‘:’. For instance, do not use the title ‘Discussie:’
  • Do not come up with things in the Conclusions section that have not been described earlier in the paper.
  • ‘Introduce’ an equation. Do not just put your equations somewhere between the text. You need to introduce it by stating e.g. ‘Evapotranspiration is calculated as: ‘. Below the equation be sure to explain ALL symbols (except if they were explained earlier, however it does not hurt explaining a symbol again if it was explained 10 pages back..).
  • Do not write ‘wouldn’t’, ‘doesn’t’, etc. Just don’t.