Putting hydrological modelling practice to the test / Lieke Anna Melsen.
Language: English Summary language: English, Dutch Publisher: Wageningen : Wageningen University, 2017Description: 170 pages : figures, diagrams ; 24 cmContent type:- text
- unmediated
- volume
- 9789463431224
- 9463431225
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|
BOOK
|
NCAR Library Foothills Lab | GB656.2 .H9 .M528 2017 | 1 | Available | 50583020006650 |
Ph. D. Wageningen University 2017 2017-04-19 6626
Includes bibliographical references. With summaries in English and Dutch.
Six steps can be distinguished in the process of hydrological modelling: the perceptual model (deciding on the processes), the conceptual model (deciding on the equations), the procedural model (get the code to run on a computer), calibration (identify the parameters), evaluation (confronting output with observations), and uncertainty analysis (estimate uncertainty in the model and its output). An engineer conducts these steps different than a scientist, because the goal of an engineer is to solve practical problems, while the goal of a scientist is to increase the understanding of the system. The difference between scientists and engineers is most pronounced in the perceptual modelling step. However, in many of the current hydrologic sciences studies, engineering and scientific approaches are mixed. As a scientist, three common philosophies of science can be adopted: verificationism, falsificationism, and Bayesianism. It was demonstrated that verificationism most closely resembles engineering in the modelling steps, while falsificationism and Bayesianism call for a different practice.
In this thesis, several of the modelling steps have been investigated in more detail. In order to investigate these modelling steps, we applied widely used hydrological models (Chapter 2). These models vary in complexity, and have been applied to catchments with varying temporal and spatial scales...
The results from all the studies can be summarized in three points: Not only the model choice, but also the configuration of the model determines the outcome of the model; sufficient data are needed to constrain and evaluate a model; and the large uncertainty in modelling studies provides a strong motivation to increase our understanding - i.e., to focus on science rather than on engineering. In order to establish this, models should be related to theories (hypotheses), which should be tried to falsified. The model set-up should be considered an element of the tested theory. Novel observation technologies provide the opportunity to test and falsify these theories, and can lead to the formulation of new theories.