Qube uses Local Data Gauges (LDG) to improve the estimation of natural flows within a catchment. At a minimum these include all gauging stations within the ROI Dataset as well as a number of strategic LDG, for example, where groundwater model outputs have been used to override the natural estimation of flows within a catchment.
The main source of LDG data is in the form of gauging station data which has been naturalised using the artificial influence (AI) data within Qube. Whilst it is advantageous to add additional gauging stations to Qube, the addition of inappropriate gauging stations may have a detrimental impact on the quality of the estimates of natural (and influenced) flow.
The following guidance describes how an assessment of hydrometric quality and the degree of influence can be used to determine whether it may be appropriate to add a gauging station as an LDG. Each of these two aspects are considered separately with the final suitability assessment combining the two.
The guidance is based on Gustard et. al. (1992), which classified gauging stations relating to hydrometric quality and degree of influence as part of research into low flow estimation in the UK. This classification was retained through the development of LowFlows Enterprise and Qube. For ease of application the grading from A to C is replaced with a Low, Medium and High categorisation, with associated values of 1 to 3.
Hydrometric Quality
The hydrometric quality of the gauging station, that is the ability of the gauging station to provide high quality flow data, should be considered as part of the assessment. The assessment should focus on the ability of the gauging station to measure low flows.
The hydrometric quality can be categorised as being ‘Low’, ‘Medium’ or ‘High’ as presented within Table 1.
Table 1. Hydrometric Quality (Specifically at low flows)
| Hydrometric Quality | Unknown | Low | Medium | High |
|---|---|---|---|---|
| Score | Subjective Assessment Only | 3 | 2 | 1 |
Two sources of information which provide both descriptive information and more objective assessments of hydrometric quality are the NRFA (National River Flow Archive) and GSDQ (Gauging station data quality classification).
The NRFA provides information on the hydrometry of each of the gauges for which they hold information. This includes a ‘Hydrometric Description’ and ‘Station Type’ which can be useful in determining the hydrometric quality of a site. In addition, the ‘Sensitivity’ of the site, when provided, can provide a more objective measure. The sensitivity is the percentage change in flow associated with a 10mm increase in stage at the Q95 flow thus is a very useful measure of the ability of the gauging site to accurately measure the low flows. A ‘High’ hydrometric quality would have a sensitivity less than 20%, ‘Medium’ below 50% and ‘Low’ would have a sensitivity greater than this.
The GSDQ Register can also provide both subjective and objective information for the assessment of hydrometric quality. As well as information on the type of gauging station an objective measure of how good a gauging station is at low flows is also provided. Within this scoring scheme, scores of 4 and 5 would correspond with a ‘High’ hydrometric quality, 2 and 3 ‘Medium’ and 1 would be ‘Low’.
Degree of Artificial Influence
LDG represent the ‘natural’ flows at a location. Therefore the flows need to be either from a natural gauging station or for a gauged record where there is a high confidence in the characterisation of influences used to naturalise the gauged flows is high.
Table 2 presents the categorisation of a gauging station with regards to both the degree of influence and the how well these are characterised. The lower the score the ‘better’ the gauging station is as a candidate for being an LDG.
Table 2. Artificial Influence Categorisation
| Degree of AI influence | |||||
|---|---|---|---|---|---|
| Low | Medium | High | Unknown | ||
| How well AI are characterised | Low | 2 | 3 | 3 | Subjective assessment only |
| Medium | 1 | 2 | 3 | ||
| High | 1 | 1 | 2 | ||
| Unknown | Subjective assessment only | ||||
The NRFA have a ‘Factors Affecting Runoff’ section for most gauging stations for which they hold data. This will give an indication of the types of hydrological influences within the catchment. The ‘Flow Regime Description’ may also provide a description relating to the size of the influences on the natural flow regime to allow a more subjective assessment.
An assessment of the magnitude of both individual influence and the overall influence on the flow regime may also be available within Qube. A general rule is that the degree of influence is ‘Low’ where the gauged Q95/mean flow ratio differs by less than 20%, ‘Medium’ less than 50% and ‘High’ above this.
The assessment of how well the AI are categorised could be made by looking at the source of the AI data within Qube, e.g. whether they have been characterised using estimated or observed datasets.
Overall Suitability
The combined score from the hydrometric quality and degree of influence can give an overall suitability assessment score, related to whether the gauging station is likely to be suitable as an LDG. The lower the score, the more suitable the site is likely to be. This is presented in Table 3.
Table 3. Overall suitability assessment
| |
Hydrometric Quality Score |
|||
|---|---|---|---|---|
| Low (3) |
Medium (2) |
High (1) |
||
| Artificial Influence Score |
Low (1) |
4 |
3 |
2 |
| Medium (2) |
5 |
4 |
3 |
|
| High (3) |
6 |
5 |
4 |
|
This guidance provides a structure for use when assessing the suitability of a gauging station for use as an LDG. The overall decision is likely to be a combination of both subjective and objective assessments at a gauging station.
Two additional questions may also be used as a guide for how in-depth such an assessment should be:
-
Are there are other gauged sites locally (and are they loaded as LDG)? Are the LDG and proposed LDG in agreement with one another? i.e. it is important to ensure that the inclusion of the LDG produces hydrologically sensible and spatially consistent flows.
-
Are the mean flow and Q95 flows very different from the natural (without LDG) flow estimates? If so, then the inclusion of the LDG will have a large impact on the estimated flows. This may be an indication that it is particularly ‘valuable’ as an LDG, or conversely it could be an indication that there are errors within the gauged record or naturalisation process. Given the impact on the estimation of flows, you should be confident that the addition of the LDG will represent an improvement in the estimation of the natural flows within the catchment.
LDG are loaded to improve the estimation of natural flows within a catchment and may not always be associated with a gauging station record that has been naturalised within Qube. Additional sources of LDG data may include:
- Naturalised datasets produced externally to Qube.
- Modelled datasets from a hydrological model (regionalised or calibrated).
- Outputs from groundwater models.
It is still advisable to use the above framework and additional questions for these and other sources of LDG data, when assessing the suitability of the data to be used as local data.