Rainfall-Runoff modelling: the Primer(Chapter 1)


1. The future in rainfall-runoff modeling is therefore one of uncertainty, but this then implies a future question as to how best to constrain that uncertainty.

2. There have certainly been important and interesting advances in rainfall-runoff modeling techniques, but we are still very dependent on the quantity and quality of the available data.

3. One of the reasons why there has been little in really fundamental advances over the last decade is that hydrology remains constrained by the measurement techniques available to it.

4. The nature of hydrological modeling is going to change: programming is so much easier;cover a range of scales and coupled processes to satisfy integrated catchment management; increased involvement of local stakeholders; constrain the uncertainty in local predictions to satisfy local stakeholders.

Why Model ?

The limitations of hydrological measurement techniques; thus, extrapolation of available measurements is both space and time, to ungauged catchments and into future.

Improve our understanding about hydrological systems.

Improve decision making about a hydrological problem.

The Modeling Process

modeling process

Perceptual Models of Catchment Hydrology

Hydrological systems are sufficiently complex that each hydrologist will have his own impression or perceptual model of what is most important in rainfall-runoff process so that different hydrologists may not agree about what are the most important processes or the best way of describing them. One problem involved in having a complete understanding of hydrological systems is that most water flows take place under ground in the soil or bedrock. One way of gaining further understanding is to examine a pat of the system in much greater detail. The perceptual model is a set of qualitative impression and therefore some assumptions must be made in moving to a set of equations defining a conceptual model. There are wide range of possible hydrological responses that may occur in different environments or even in different parts of the same catchment at different times. Traditionally, it has been usual to differentiate between different conceptualizations of catchment scale response based on the dominance of one set of processes over another. According to the dominant hydrological process, the process mechanism in the responses of hillslopes to rainfalls can be classified to be five types, i.e., infiltration excess overland flow, partial area infiltration excess overland flow, saturation excess overland flow, subsurface stormflow and perched subsurface stormflow. Attempts have been made to suggest which mechanism might be dominant in different environments (See Figure 1.5) but there may still be much to learn from direct observations of runoff processes in a catchment of interest.


Flow Process and Geochemical Characteristics

One of the most influential factor in revising hydrological thinking in the last 30 years has been the use of geochemical characteristics to provide additional information on flow processes. The environmental isotopes of oxygen are often used in catchment scale studies. Through this method, it is found that an important part of the hydrograph may be made up of ‘old’ water and may not be rainfall flowing directly to the stream. Certainly, it should not be assumed that fast runoff is always the result of overland flow or surface runoff on the hillslopes of a catchment.

Runoff Generation and Runoff Routing

Every hydrological model requires two essential components: one to determine how much of a rainfall becomes part of the storm hydrograph (the runoff generation component), the other to take account of the distribution of that runoff in time to form the shape of the storm hydrograph (the runoff routing component). The boundary between those two components is not a very precise one. In general, it is accepted that the runoff generation problem is the more difficult and that relatively simple models for the routing may suffice.

The Problem of Choosing a Conceptual Model

There are two basic classification of model types. One is lumped or distributed model; the other is deterministic or statistical model. The following steps are suggested to choose a conceptual model. (1) Prepare a list of the models under consideration;(2)Prepare a list of the variables predicted by each model;(3)Prepare a list of the assumptions made by the model;(4) Make a list of the inputs required by the model; (5)Determine whether you have any models left on your list.

Model Calibration and Validation Issues. 

There are two major reasons for the difficulties in calibration. One is that the scale of the measurement techniques available is generally much less than the scale at which parameter values are required. The other is the optimization of the parameter: the observed discharge may not enough to support the robust optimization; the model structure and the observations are not error free; the observed data available for use in a model calibration exercise may not be useful. The idea of an optimum parameter set has been found to be generally ill-founded in hydrological modeling and can be rejected in favor of the concept of the equalfinality of different models and parameter sets. It is expected that, at the end of the model evaluation process, there will not be a single model of the catchment but a number of acceptable models (even if only using different parameter sets within one chosen model structure) to provide predictions.

Updated: 2015-11-18 — pm9:20

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