Geoscience Reference
In-Depth Information
hydrological theory (see also Flury
et al.
, 1994; Zehe and Fl uhler, 2001; Weiler and Naef, 2003; Kim
et al.
, 2006; Blume
et al.
, 2009). Whenever detailed studies of flow pathways are carried out in the field
we find great complexity. We can perceive that complexity quite easily, but producing a mathematical
description suitable for quantitative prediction is much more difficult and will always involve important
simplication and approximation. This initial chapter will, therefore, be concerned with a perceptual model
of catchment response as the first stage of the modelling process. This complexity is one reason why
there is no commonly agreed modelling strategy for the rainfall-runoff process but a variety of options
and approaches that will be discussed in the chapters that follow.
1.2 How to Use This Topic
It should be made clear right at the beginning that this topic is not only about the theory that underlies
the different types of rainfall-runoff model that are now available to the user. You will find, for example,
that relatively few equations are used in the main text of the topic. Where it has been necessary to show
some theoretical development, this is generally presented in boxes at the ends of the chapters that can
be skipped at a first reading. The theory can also be followed up in the many (but necessarily selected)
references quoted, if necessary.
This is much more a topic about the concepts that underlie different modelling approaches and the
critical analysis of the software packages that are now widely available for hydrological prediction. The
presentation of models as software is becoming increasingly sophisticated with links to geographical
information systems and the display of impressive three-dimensional graphical outputs. It is easy to be
seduced by these displays into thinking that the output of the model is a good simulation of the real
catchment response, especially if little data are available to check on the predictions. However, even the
most sophisticated models currently available are not necessarily good simulations and evaluation of the
model predictions will be necessary. It is hoped that the reader will learn from this topic the concepts
and techniques necessary to evaluate the assumptions that underlie the different modelling approaches
and packages available and the issues of implementing a model for a particular application.
One of the aims of this topic is to train the reader to evaluate models, not only in terms of how well the
model can reproduce any data that are available for testing, but also by critically assessing the assumptions
made. Thus, wherever possible, models are presented with a list of the assumptions made. The reader is
encouraged to make a similar list when encountering a model for the first time. At the end of each chapter,
a review of the major points arising from that chapter has been provided. It is generally a good strategy
to read the summary before reading the bulk of the chapter. Some sources of rainfall-runoff modelling
software are listed in Appendix A. A glossary of terms used in hydrological modelling is provided in
Appendix B. These terms are highlighted when they first appear in the text.
This edition has been extended, relative to the first edition, particularly in respect of the chapters
labelled “Beyond the Primer”. New material on the next generation of hydrological models, modelling
ungauged catchments, and modelling sources and residence time distributions of water have been added.
In addition, there has been a lot of research in the last decade on the use of distributed models and
the treatment of uncertainty in hydrological predictions so that Chapters 5, 6 and 7 have also been
substantially revised.
1.3 The Modelling Process
Most topics on modelling start with the choice of model to be used for a particular application. Here,
we start at an earlier stage in the modelling process with the
perceptual model
of the rainfall-runoff
processes in a catchment (see Figure 1.2). The perceptual model is the summary of our perceptions of
