Examensarbete vid Institutionen för geovetenskaper ISSN 1650-6553 Nr 228
Rainfall-runoff Model Application in Ungauged Catchments in Scotland
Alexander Peter Anthony Fionda
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Abstract
Rainfall-runoff model application for ungauged catchments in Scotland
Alexander Peter Anthony Fionda
Department of Earth Sciences, Uppsala University Villavägen 16, SE-752 36 Uppsala, Sweden.
The conceptual rainfall-runoff model Hysim is used to estimate the flow in ungauged catchments in Scotland by Scottish Water. However, there are non-quantified uncertainties associated with the outcomes of the modelling strategy used. In order to identify and quantify these uncertainties it was necessary to use the framework of proxy-basin validation in order to evaluate the performance of different modelling strategies.
The proxy-basin validation test requires hydrologically analogous catchments for the evaluation of models, a Region Of Influence regionalisation method was used in order group selected catchments by Q95(%MF). Four groups of four catchments were established, which covered Q95(%MF) 5-7%, 7-9%, 9-11% and 11-13%.
The allocation of “donor catchment” and “target catchment” for each Q95(%MF) group was accomplished through discussion with Scottish Water with respect to existing Scottish Water modelled catchments. A single donor catchment and three target catchments were therefore indicated for each group.
Two modelling strategies were developed by the study; the first full transposition method used the entire optimised parameter-set from the donor catchment with the exception of the target catchment’s “catchment area” parameter. The second partial transposition method used the entire optimal parameter-set with the exception of the target catchment’s “interception storage”, “time to peak”, “rooting depth” and “catchment area” parameters.
It was found that the full transposition method had the least uncertainty associated its use for flow estimation when the parameter-set was derived from a donor catchment calibration that was excellent. Contrarily, it was found that the partial transposition model method had the least uncertainty associated with flow estimation for parameter-sets that were derived from a relatively poor donor catchment calibration.
Encouraged by this testing framework, this study has suggested the use of catalogue of donor parameter-sets that can be used to estimate flow for catchments that are hydrologically similar. This strategy of hydrological modelling has been recommended to improve existing Scottish Water Hysim methodology.
Keywords
ungauged catchment, proxy-basin validation, region of interest, transposition method, hysim,
rainfall-runoff model, sepa, scottish water, scotland.
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Referat
Användning av en avrinningsmodell i ett skotskt avrinningsområde utan vattenföringsmätningar
Alexander Peter Anthony Fionda
Institutionen för geovetenskaper, Uppsala universitet Villavägen 16, 752 36 UPPSALA.
Scottish Water använder den begreppsmässiga avrinningsmodellen Hysim för att uppskatta vattenföringen i skotska avrinningsområden utan vattenföringsdata. Den valda
modelleringsstrategin har emellertid resulterat i icke-kvantifierade osäkerheter i beräknade vattenföringar. För att identifiera och kvantifiera de osäkerheter som är förbundna med olika modelleringsstrategier var det nödvändigt att använda sig av information från likartade avrinningsområden.
Den valda regionaliseringsmetoden använde hydrologiskt analoga avrinningsområden som definition på likhet. Analogin grundades på “inflytanderegion” (Region of Influence) som erhålls genom att gruppera utvalda avrinningsområden utefter Q95 (% medelflöde). Fyra grupper med fyra avrinningsområden valdes ut grundat på följande Q95-gränser (%
medelflöde): 5-7%, 7-9%, 9-11% and 11-13%.
Fördelningen av analoga avrinningsområden (områden med vattenföringsmätningar vars parametervärdesuppsättningar skulle överflyttas) och målområden (utan mätningar) för varje Q95-grupp erhölls efter diskussion med Scottish Water från områden där Scottish Water modellerat vattenföringen. Ett analogt område och tre målområden valdes ut för varje grupp.
Studien använde två modelleringsstrategier. Den första metoden, “total överflyttning”, använde hela parametervärdesuppsättningen från det analoga området med undantag av målområdets area. Den andra metoden, ”partiell överflyttning”, använde hela
parametervärdesuppsättningen med undantag för målområdets interceptionslager, tid till högflöde, rotdjup och area.
Den totala överflyttningsmetoden hade lägst osäkerhet när parametervärdesuppsättningen härleddes från ett område med utmärkt kalibrering. Den partiella överflyttningsmetoden hade, å andra sidan, lägst osäkerhet när parametervärdesuppsättningen härleddes från ett område med dålig kalibrering.
Efter att ha provat de två metoderna utmynnade studien i ett förslag till en katalog med parametervärdesuppsättningar för områden som kan bedömas som hydrologiskt lika. Denna strategi för hydrologisk modellering har rekommenderats som förbättring av befintlig Hysim- metodik hos Scottish Water.
Nyckelord
Avrinningsområde utan vattenföringsdata, validering mot likartade områden,
inflytanderegion, överflyttningsmetod, hysim, avrinningsmodell, SEPA, Scottish Water,
Skottland.
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Contents
1. Introduction ... 1
1.1 Research objectives ... 1
1.1.2 Scottish Water and its resource systems ... 2
1.1.2 The role of hydrologic modelling in Scottish Water ... 5
1.2 The use of Hysim rainfall-runoff modelling by Scottish Water ... 12
1.2.1 Quantifying the uncertainty associated with parameterisation ... 13
1.2.2 Modelling flow in ungauged catchments ... 15
1.3 Key questions and summary of methods ... 16
2 Materials and Methods ... 18
2.1 Analogue and target site selection from SEPA catchments ... 18
2.2 The Hysim conceptual rainfall-runoff model ... 21
2.3 Derivation of inputs ... 24
2.4 Hysim model calibration ... 26
2.5 Development of parameter transposition methods ... 27
2.6 Evaluating model performance using the proxy-basin test ... 28
3 Results ... 29
3.1 Hydrological statistics of mega-zones and SEPA catchments ... 29
3.2 Calibration quality of donor catchments ... 31
3.3 Evaluating model performance with transposition method chosen ... 39
3.4 Evaluating model performance with selection of target catchment ... 44
4 Discussion ... 47
4.1 Hydrological statistics of mega-zones and SEPA catchments ... 47
4.2 Calibration quality of donor catchments ... 48
4.3 Uncertainty identified with selection of target catchment ... 53
4.4 A more pragmatic methodology for estimations of flow ... 54
5 Conclusion ... 56
6 Acknowledgements ... 58
7 References ... 59
8 Appendices ... 63
Appendix A: Hysim operational notes ... 63
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Appendix B: Parameter-set references ... 64 Appendix C: Results of validation ... 65
Definition of terms
MF - the mean flow.
Q95 - the 95th percentile of mean flow; the flow exceeded or equalled 95 % of the time.
Q95(%MF) - the 95th percentile of mean flow as a percentage of mean flow.
Source catchment - a catchment containing source of water, which is utilised by Scottish Water.
Donor catchment - the catchment for which an optimal parameter-set is achieved through calibration.
Target catchment/analogue - a catchment chosen through a method of regionalisation to be similar in character to the donor catchment.
Model – a software based representation of a physical system. Model software consists of a programmed framework, into which physical data and estimated parameters are placed, in order to represent a physical system. This study evaluates “model” performance, where a model consists of the programming, input data and parameters as a whole. This status is stored by Hysim –the model programming- as a single project file, which is referred to as a model in its own right.
Parameter-set - a set of estimated parameter values that may be adjusted in order to manipulate the outcomes of a model.
Optimal parameter-set - a set of parameter values that provide the best estimation of flow, commonly achieved through the calibration of a model.
Transposition – the process of transferring parameter values from a donor catchment optimal parameter-set to a target catchment parameter-set.
Full Transposition Method (FTM) - a method describing the transposition of every parameter from the donor catchment’s optimal parameter-set to the target catchment parameter-set. The catchment area of the target is maintained as a parameter for the target catchment parameter-set.
Partial Transposition Method (PTM) - a method describing the transposition of part of the donor catchment’s optimal parameter-set to the target catchment parameter-set. catchment area, time to peak, rooting depth and interception storage of the target are maintained as parameters for the target catchment parameter-set.
Uncertainty - A state of having limited knowledge where it is impossible to exactly describe existing state or future outcome; in this study this is quantified by evaluating model performance, using accuracy between estimated and recorded flow.
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1. Introduction
The benign human curiosity in the future drifts in and out of focus in society. It can enthral as the subject of films and can spell boon or doom in the media. As a species capable of producing much of what we utilise in our day to day existence it is our privilege to be able to successfully predict the outcomes of what we create and control. In order to do so, we rely on the continual development of the mathematical model. However, when we attempt to utilise the environment around us, there is the desire, and often assumption, that a similar level of prediction is available. We necessitate accurate environmental prediction, whether it may concern the local weather next week or global climate in the next century. Unfortunately, the natural world is almost infinite in its scale of complexity and cannot be represented in its entirety by any model. As such, the outcomes of mathematical models that attempt to tell us more about the future is discussed more as a form of prophecy than prediction (Beven, 1993).
Hydrological variables are but one aspect of the natural world. Mathematical models, especially conceptual rainfall-runoff models, are a capable means of narrowing down future states of
hydrological variables for a given area. For water management companies this is essential, as
predictions of the likely states of variables are invaluable in resource planning. It is within the realms of prediction that rainfall-runoff models, capable of simulating flow in areas that are ungauged, are best suited.
Models of hydrological systems have been progressing for the best part of three decades. One branch of development of modelling tools leads to the prediction rainfall and consequential runoff in a hydrological system. Conceptual rainfall-runoff models are among the most ubiquitously used tools in hydrology. Input data is more readily available for their application unlike their counterparts: the complex, physically based, distributed models. Conceptual models are often comparatively simple and easy to use, that said, the drawbacks of model parameters being inter-correlated or over-
parameterised is not uncommon. It is the case that some model parameters will have a physical bias that ties directly to variations on the catchment scale. Due to the fact that such variations are virtually unquantifiable in the field, calibration is an essential step in representing real runoff calculations. This leads to the pursuit of the optimal parameter-set that produces the greatest closeness to reality and a process of parameter alteration that inevitably brings about multiple solutions with different sets of parameters. Uncertainty therefore arises in modelling, it is discussed as the confusion as to which set of parameters to choose for application by Beck, 1987. This study aims to elaborate upon the
uncertainty associated with parameter selection by testing parameter-sets that have been derived by various methods. It will then be possible to quantify this uncertainty by the comparison of the accuracy of these methods.
1.1 Research objectives
This study is undertaken in cooperation with Scottish Water -the publically owned water authority for Scotland, who expressed considerable interest in improving the efficiency of their rainfall-runoff modelling strategy for various operations. This study aims to evaluate “model” performance, where a model consists of the programming, input data and parameters as a whole. In doing so, the focus of evaluation will be on changes made to the parameter-set and potentially data. In literature surrounding model evaluation, the model software itself is usually under scrutiny and described as the “model”;
such analysis is not the focus of this study.
A review of the current internal and external publications on Scottish Water’s modelling strategy
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reveals non-quantified uncertainties in the input, parameterisation and calibration of their modelling scheme that require addressing. This paper attempts to identify and quantify the uncertainty
surrounding parameterisation by testing the accuracy of various methods of parameter-set derivation.
Furthermore, this uncertainty evaluation may then be used to infer an improved, more pragmatic method for modelling the flow in ungauged catchments.
Using the framework of proxy-basin validation to evaluate the uncertainties associated with flow estimations in ungauged catchments requires the following aims to be fulfilled:
i. Select catchments for experimentation that are both approved by a monitoring agency in terms of quality and that represent typical Scottish Water source catchments. Use a method of regionalisation to group hydrologically analogous catchments in compliance with the proxy- basin framework
ii. Identify catchments that are suitable for deriving parameter-sets and those that are suitable as the target of the evaluation process; so called “donor” and “target” catchments. Update the input data and data selection periods and improve the calibration of existing Scottish Water models for those catchments identified as donor catchments.
iii. Develop two methods of parameter transposition and test parameter-sets upon target
catchments in order to evaluate accuracy and quantify uncertainty associated with parameter- set selection. Interpret whether uncertainties are quantified enough for the recommendation of using a single method of parameter-set derivation for the estimation of flow in all
hydrological analogous, ungauged catchments.
In completing these objectives, it is possible to identify a single donor parameter-set for each hydrologically similar group that can be used to estimate flow in ungauged catchments with hydrological similarity to a quantified level of accuracy. A library of models would then exist that would each represent a range of hydrological similarity that could be used whenever flow was needed to be estimated in an ungauged catchment. This builds upon suggestions by Jacobs (2010); the ability to approve this as an outcome would recommend a more pragmatic Hysim methodology for Scottish Water’s estimation of flow in ungauged catchments.
For the objectives of this report to be upheld it is important to address some additional vulnerability within the current scheme of Hysim modelling that Scottish Water employs. A detailed method for the calibration of Hysim models must be documented and made consistent with Scottish Water
guidelines; however the method should be seen to improve existing modelling procedure in order to assist with future Hysim modelling studies. Where there are pre-existing calibrations models for catchments, it is an aim of this to update or improve these models where possible. This may be achieved through taking advantage of the improved rating and record of evapotranspiration or precipitation data records or by alterations in the model construction process.
1.1.2 Scottish Water and its resource systems
Scotland, with respect to global water availability, is a water rich country. In terms of actual water availability Northern Europe has 34.6 x 103m3 per year per capita average for the past 60 years; when compared to the average for the entire of Europe (4.9 x 103m3) it is clear that there is a uneven geographic distribution of available water throughout Europe (Gleik, 1993). It is important not to
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construe this data as a reflection of unlimited water resource capability; there are problems with water resources in relation to the public supply of water. A wide variability exists in the ability for the water authority, Scottish Water, to maintain water supply during peak demands and during droughts.
In 2002, Scottish Water was crated by the merger of three water authorities in accordance with the Water Industry [Scotland] Act 2002. Scottish Water is accountable to the Scottish Parliament through the Scottish Ministers, it is publically owned. It remains a product of the amalgamation of 210 water boards and local councils since 1968. This unification provides the authority with a unified, consistent and strategic approach to Water Resource Planning that strengthens the operations it defines from its Water Resource Plan (WRP). The WRP (Scottish Water, 2009) is a regulatory document that has been developed in collaboration with the Scottish Environmental Protection Agency (SEPA). Its aims are to:
• Define Scottish Water’s long term water resources strategy to ensure the consistent supply of drinking water to protect public health and facilitate economic growth, while abstracting and using water in a sustainable way to provide a value for money service for customers.
• Provide a twenty five year assessment of the Supply Demand Balance across Scotland at a zone-level that is consistent with good practice in the UK.
• Justify investment to restore deficits in the Supply Demand Balance in a prioritised water resource zones during the next investment period and beyond.
The WRP therefore represents the interests of: environmental and water resource regulation, economic regulation, customer interests and consumer quality respectively (Scottish Water, 2009).
The Water Resource Plan is subject to the model of planning guidance SEPA provides. As such, Scottish Water is requested to produce data for all Water Resource Zones (WRZs) defined within Scotland. WRZs are defined as “the largest possible zone… in which all customers experience the same risk of supply failure from a resource shortfall” (Scottish Water, 2009). For the 2007/2008 period, 230 water resource zones exist across Scotland. Due to the low population density in Scotland, there is a large variation in the distribution of WRZs. A large quantity of WRZs are located in the Highlands and Islands, which supply isolated communities; contrasting with the eleven centrally located WRZs that supply almost half the population of Scotland (Scottish Water, 2009). Such an extensive collation of WRZs is unfamiliar to the majority of water management authorities; in England and Wales companies usually have one to ten WRZs. Therefore, the environmental agency guidelines that request data on all WRZs seems a task implicated with difficulties on a number of levels: specifically the collation of data for 230 WRZs and their constituent water sources.
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Average Demand (Ml/d)
Argyll and Bute 46
Ayrshire and Inverclyde 66
Central Scotland 110
Dumfries and Galloway 31
East Lothian and Borders 25
Fife 26
Fort William 21
Grampian 36
Inverness and Central Highlands 28
North West Coast 21
Orkney 18
Shetland 23
Skye and Lochalsh 32
Tayside and Rural Forth Valley 18
Western Isles 23
Wick 8
Scotland Total 2009/10 481
13.9 28.7 7 7
2,044 5,035 220 278
127 372.6 13 16
13.4 26.8 22 22
10.7 22 13 14
6.7 14.6 28 28
3.3 7.5 19 19
8.7 19.6 10 11
148.5 420.2 11 17
86.2 201.6 20 24
143 357.3 1 11
8.9 17.9 19 19
78.3 131.1 5 18
59.5 145.3 11 17
255.8 440.4 8 14
1,265.40 2,712.20 11 30
Average Demand (ml/d)
Population (000’s)
Number of WRZs
Number of WTWs
Number of Sources
41.8 65.9 32 33
FIGURE 1.2.1:SCOTTISH WATER MEGA-ZONE REGIONAL GROUPING WITH ALLOCATED WATER RESOURCE ZONES (WRZS).IMAGES USED WITH PERMISSION (SCOTTISH WATER,2009).
Water resource zones are grouped geographically into sixteen mega-zones, shown in figure 1.2.1. The disparity of population density across Scotland is notably significant, elucidating the need for an additional WRZs for every small pocket of population across a large area; these are classified as standalone zones. In studying the population given in thousands it is a frequent trend that a smaller population per mega-zone have a greater number of WRZs i.e. the population of central Scotland:
2,712,200, which is supplied by 11 WRZs whereas Argyle and Bute have a population of 41,800 and are supplied by 32 WRZs. However, this is not a rule as such; some low populations also have a low number of WRZs i.e. Wick, a population of 28,700 and 7 WRZs (Scottish Water, 2009).
Water resource zones are supplied by Water Treatment Works (WTW), the distribution of which is directly influenced by the occurance of standalone zones. Each standalone zone is supplied directly by a single WTW, making 202 WTW zones that are supplied by a sole WTW across Scotland. The remaining 28 WRZs have more than one WTW. The Central Scotland mega-zone incorporates the cities of Edinburgh and Glasgow; the 11 WRZs within Central Scotland contain 30 WTW and serve 54% of the household population of Scotland (Scottish Water, 2009). The interconnectivity provided between these zones reduces the risk of supply failure within the mega-zone; although, there is a difference in risk between certain zones over others (Scottish Water, 2009). The risk of supply failure is considerably greater in the standalone zones as there is limited or no connectivity between the WTW. Efforts are being made by Scottish Water to further plans that would ensure a greater
interconnectivity between standalone zones and reduce the risk of supply failure amongst these areas.
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The supply demand balance from raw water sources to the water treatment works output for each water resource zone is essential for effective water management across Scotland. A suppy system incorporates the assets of collection, storage, transfer and treatment up to the output of the water treatment works (Scottish Water, 2009). It is the part of the supply system concerning collection that is of greatest interest for defining water sources in Scotland. Scottish Water Report that for 2007/2008 there were 532 sources providing water for supply to the population of Scotland; see figure 1.2.2.
Large population centres in Central Scotland, such as Edinburgh, Glasgow, Dundee and Stirling are supplied by a small number of large reservoirs, whereas isolated communities in remote parts of Scotland rely upon numerous small reservoirs. This follows the trends identified from the disparate state of WRZ distribution across Scotland.
FIGURE 1.2.2:SURFACE WATER SOURCES UTILISED BY SCOTTISH WATER.IMAGE USED WITH PERMISSION (SCOTTISH WATER,2009).
The distributions of raw water sources across Scotland are illustrated by map of WTW localities across the country; see figure 1.2.3. The majority of the 59 loch sources are located in the northwest of Scotland. Groundwater sources are found throughout Scotland; there are 42 spring sources and 54 borehole systems that make up 96 in total. 207 river sources are divided into: 103 indirect sources, which feed reservoirs and 104 pure river sources, which are generally larger in the east and smaller in the west. Impounding reservoirs, of which there are 170, and their contributing feeder river sources provide 82% of raw water to water treatment works in Scotland. Direct river sources provide 10% of raw water, whilst lochs and groundwater each provide 4% and 4% respectively (Scottish Water, 2009).
1.1.2 The role of hydrologic modelling in Scottish Water
Hydrological assessment occurs on a variety of levels dependent upon the project at hand. Scottish Water (2009) identified various scenarios where hydrological assessment is required for a water management authority. There is a division highlighted between internal projects i.e. a Scottish Water capital project with water quality or growth considerations and Scottish Water capital projects with environmental consideration. This study will focus on hydrological assessment associated with the eventual calculation of yield; a requisite for the supply-demand balance for all Scottish Water capital projects including Scottish Water’s Water Resource Plan (Scottish Water, 2009).
Yield is expressed in terms of the maximum continuous output that can be supplied in drought severe enough that on average its occurrence would cause a failure of supply one in forty years (Scottish Water, 2009). The use of conceptual rainfall-runoff models, such as Hysim, for estimation of stream flows is universal in water management authorities. This flow data requires some method of
transformation before yield can be calculated. The estimation of yield requires either the estimation of
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a natural flow duration curve (FDC) or its 95 flow percentile (Q95). Software such as Hysim-Aquator is capable of yield estimates directly from Hysim simulation data, whilst the “Report 108 based Method” (Institute of Hydrology, 1992) may also be used to estimate yield using one regression equation (Gustard et al., 1992). In addition, Scottish Government Directions on Environmental Standards (SGES) determine an allowance of abstraction given as a percentage of the FDC (Scottish Water, 2009). There is therefore a great necessity to represent catchment flow data in its Q95 and FDC form. Techniques from which an FDC may be obtained are: gauged records, Hysim modelling and Low Flows Enterprise calculation.
A long term record of gauged flow for the focus catchment is undoubtedly the most accurate, reliable and practical method of FDC production. Empirical observations will always be of greatest value to the hydrologist, yet lengthy continuous gauged flow data for Scotland, and indeed much of the world, is not available. Furthermore, in the context of individual water management authorities such as Scottish Water, their abstraction sites are not close enough to long term gauges for representative FDCs to be derived. Where funding and time permits, it is beneficial to initialise flow gauging for sites (Mott Macdonald, 2010). It is suggested that there is suitability in short term direct flow gauging if enough analysis into finding a suitable analogue is undertaken. For the implementation of flow gauging to be effective in a project there must be a local, long term analogue. If such an analogue cannot be found then the gauging period for the catchment in focus must be greater than four years, which may extend beyond practical means for the project. If a local, long term analogue can be found and gauged data is provided that is over three years in length then transposition will be used between catchments and allow a revised FDC that better represents the focus catchments. Methods of
transposition between catchments are detailed by Jacobs (2010); however there is no comparison between the efficacies of this procedure compared to the representation of the focus catchment by a rainfall-runoff model. A modelling strategy would inevitably require, and use, the same proximal, long term target catchment. Comparison between the resulting FDC would illustrate the value of initiating flow gauging at a focus site.
Low Flows Enterprise (LFE), developed by Centre for Ecology and Hydrology (CEH), is a software package that is used to estimate the flow duration curve at ungauged sites. Wallingford
Hydrosolutions currently maintain this software. The Scottish Environmental Protection Agency use LFE as the elected method for FDC derivation at ungauged sites in Scotland. Scottish Water has purchased LFE and is capable of providing LFE estimates on request. LFE obtains FDC through the selection of 5 Region-Of-Influence (ROI) gauged catchment sites, which must be determined to be similar to the donor catchment’s hydrological statistics. These five ROI provide an individual FDC, which is rescaled by the mean flow for the subject site; this is calculated by a separate model within the LFE software.
Hysim-Aquator permits the transfer of flow data and its derivative FDC or Q95 to calculate a yield.
Aquator achieves this through the simulation of daily transfers and abstractions for a given WRZ and represents this as a one in forty yield. The Hysim-Aquator method for yield calculation was developed in 2001, as a Scotland and Northern Ireland Forum for Environmental Research (SNIFFER) project. It is a combined software package comprising of the hydrological rainfall-runoff simulation model Hysim and Aquator, which is a water resource system model.
Hysim as stand-alone software is a daily rainfall-runoff model. Its intended use is to simulate a historic daily river flow series based on historic daily rainfall and potential evapotranspiration; whilst taking into account artificial influences such as: groundwater abstractions, river abstractions or river discharges (Manley, 1978).
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Aquator was developed especially for the aforementioned SNIFFER project. It uses output from the Hysim model as an input for the simulation of a water resource system; Hysim was also specially adapted for this project. The daily storage of a reservoir or loch may be simulated based upon a balance of inputs and outputs in terms of demands, compensation and freshets. Aquator is capable of modelling a number of demand centres as well as the key components of a resource system, such as:
pumping stations, water treatment works, pipelines, hydro-generators, river abstractions and
groundwater abstractions (Manley, 1978). The application and accuracy of Hysim-Aquator is limited by the availability of good quality input variables and parameters; guidance is provided by Scottish Water on the processing of input data.
Background of Scottish Water’s Hysim models
31 individual Hysim rainfall-runoff models are currently in use for 70 WRZs. These models are consequently responsible for covering 250 “source catchments”, which in turn feed 90 WTWs For the 31 independent donor catchments there are three catchments that provide gauged data for the implementation of 40% of the Hysim models; these are: Green Burn located at Loch Dee, data is used for 29 catchments and 8 WRZ models, River Creed located at Creed Bridge, data is used for 18 catchments and 12 WRZ models, River Calder located at Muirshiel, data is used for 35 catchments and 6 WRZ models. Other source catchments are used for Hysim model calibration; however these catchments have been applied to two or three models only (Scottish Water, 2009).
The 31 Hysim models were developed as part of larger studies than the models themselves; in these studies it was thought pragmatic to apply a single calibrated model to a range of catchments, despite more representative catchments being available for calibration. The models that use Green Burn and River Calder for calibration –amongst others- have not been critically reviewed in order to assess the on-going validity of these calibrations since there original development in 2001 and 2002. However, the necessity of applying a single model to a number of hydrologically different catchments such as Creed Bridge illustrates the lack of alternative gauged catchments available on the Western Isles and Northern Isles.
To continue the discussion of validity, the data quality upon which the models are based is also in question. The River Calder gauging station at Muirshiel is noted to be downstream of the River Calder abstraction intake and is therefore artificially impacted; the catchment is also identified by SEPA as unsuitable for use as an analogue. This issue is not brought to attention in the 2001 report by
Camphill, from which the River Calder calibration is derived. There is significant reason to question the validity and revisit the calibration considering the wide scope of its application.
Short term gauges have been used for the calibration of Hysim models: using one year of gauged data, the Geimisgarve and Clibh catchments are applied. These short term gauges were developed
specifically for the Water Framework Directive (WFD) WR1 SR06 project (Scottish Water, 2006), which required models for a large number of remote islands in Scotland. These short term gauges were used as alternative calibrations for comparison with an adopted Creed Bridge model. The calibration for Clibh was accepted in three models and Geimisgarve was accepted for a single model.
This position highlights the difficulty in establishing good Hysim donor parameter-sets for the large number of remote sites in the North Western Isle, the Western Isles and the Northern Isles. It has meant that the normal practise for Hysim calibration cannot always be followed i.e. the recommended record length would usually require at least 5 years of representative, gauged data.
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A program of additional Scottish Water flow gauging sites was implemented since 2006 as a direct result of the conclusions drawn by the WFD WR1 SR06 project. This aided the confirmation of river flows at key project sites, which was not previously possible and helped strengthen observations made in those catchments. The resulting flow records cannot be used for direct calibration of Hysim models until the representative record length exceeds 5 years; ideally 7 years. However, the flow records may be used for indirect validation of existing Hysim flow records in order to help agreement upon a FDC for specific water sources during consultation with SEPA. SEPA will use the LFE instead of this FDC unless flow gauging can provide a high level of confidence to the Hysim modelled flow.
Hysim-Aquator models are developed for reservoir or loch multiple-source system and generally not used for WRZs that are only supplied by river intakes. The criteria for their disuse is a system for which there is no storage available; exceptions do exist, such as the River Dee sources, which are used to extend gauged flow records. The rationale for excluding rivers is that river sources are generally smaller with low yields and therefore lower priority. It has been a concern that Hysim models do not perform well around the 99th percentile of flow (Q99). This issue is not as critical in systems with low storage as it is normally the combined impact of the whole flow regime and storage capacity available that determines the system yield. In contrast, a river with no storage has a yield that is determined based on the lowest daily flow values from the driest 3 or 4 years within the flow record. Therefore, any poor model performance at these very lowest flows can have a significant impact on yield sensitivity for river-only systems (Scottish Water, 2009).
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FIGURE 1.2.3:THE DISTRIBUTION OF SCOTTISH WATER CALIBRATION GAUGES AND MODELLED WATER TREATMENT WORKS THROUGHOUT MAINLAND SCOTLAND AND ISLANDS.IMAGE TAKEN FROM JACOBS (2010).
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Region of influence: identifying hydrological similarity without geographical constraints SEPA quality approved catchments are presented on figure 1.2.4. These catchments are categorised by their LFE derived Q95(%MF) flow descriptor, which is used to identify LFE ROI groupings across Scotland. The purpose of using Q95(%MF) is to eliminate the requisite for regional boundary grouping and can allow a number of catchments to be regionally grouped without boundaries. This is important due to the number of isolated source catchments in Scotland, such as islands, which would be
unaccounted for if boundary regionalisation of catchments was pursued. LFE ROI catchments are mapped based upon Q95(%MF) values, which reflect regional variation in hydrological regimes. Five main regional groups are established, grouped by Hydrometric Area (HA) boundaries. Such a simplification of grouping causes a few stations to be in the wrong grouping such as Killing and Cultybraggan (Scottish Water, 2009). These stations have more hydrological similarity to stations in the North West region, yet are included in the central region due to the HA being of the Tay. In addition, Alness and Diriebught House stations have a better hydrological fit with the North East Region (Scottish Water, 2009).
Further elaborations on using ROI as an alternative for regionalisation are discussed in subsequent chapters that discuss the literature surrounding catchment selection for parameter derivation and application. Scottish Water adopts this scheme of LFE ROI groups across Scotland in order to identify suitable catchments for use in the validation of optimal parameter-sets. If the desire is to estimate flows for an ungauged catchment with a Q95(%MF) of 6% it is possible to refer to the 5% – 10% Q95(%MF)
group and establish a number of target catchments for validation. This is useful tool as there is a reliable potential analogue gauge available that represents natural flow regimes that are mostly checked for hydrometric quality. In this LFE approach for obtaining suitable catchments, a distance factor is neglected unlike the SEPA analogue selection tool as it was developed to be reliant on proximity between catchments.
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FIGURE 1.2.4:LOW FLOWS ENTERPRISE (LFE)REGION OF INFLUENCE (ROI) STATIONS AND SUGGESTED ANALOGUES BY THE SCOTTISH ENVIRONMENTAL PROTECTION AGENCY (SEPA).95th PERCENTILE OF FLOW AS A
PERCENTAGE OF MEAN FLOW (Q95(%MF)) IS ILLUSTRATED BY THE COLOUR AND SIZE KEY.TAKEN FROM JACOBS (2010).
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1.2 The use of Hysim rainfall-runoff modelling by Scottish Water
Scottish Water rely upon the use of a conceptual hydrological rainfall-runoff that is calibrated to nearby hydrologically analogous catchments in order to produce yield estimations for the majority of surface water supply systems in Scotland. Yield is defined as the maximum continuous output for given surface water source that can be supplied during a dry period of a stated severity. Yield estimations require flow data and, due to the lack of long term site specific flow gauging within a reasonable proximity to abstraction sites, representative target catchments are required for flow estimation in ungauged rivers. Unlike other locations in Britain such as England, there is not the same length or level of detail to historical flow records that affords the direct use of flow gauging records for yield estimation. These direct flow gauging installations are usually restricted to timescales under three years and are not suitable for direct application in model calibration. A requisite for model calibration is a good record of at least seven years of gauged flow data (Scottish Water, 2009).
Therefore, direct flow gauge installations are usually used exclusively to provide validation of the optimal parameter-set for the catchment.
The conceptual rainfall-runoff hydrological simulation modelling software used by Scottish Water is Hysim, which is continuously developed by Water Resource Associates. Hysim can be integrated within Oxford Scientific’s water resource system model Aquator in order to produce estimations of yield for a given catchment. It is the case that uncertainties in Hysim modelling strategy and procedures have the potential to significantly undermine the confidence in Scottish Water’s yield estimates. This has the implication of making any planning or investment schemes, based on the estimation of yield, less reliable. The Hysim-Aquator yield modelling process has been used by Scottish Water for over 10 years and it is understood that there is a lack of repeatability in some of their Hysim models. It is assumed that this is due to the number of times certain models have been updated or even the lack of a consistent guidance framework for application, which is often protracted by the use of different consultants.
The data input, parameterisation and calibration processes for Hysim are aimed to be as objective and consistent as possible, yet these uncertainties are still apparent. The uncertainty and related sensitivity associated with these three key processes of modelling are not quantified. It would seem pertinent to quantify uncertainties and sensitivities within these processes in order to strengthen the reliability and confidence in model flow estimations and thus gain a more accurate yield estimate.
Scottish Water identifies potential uncertainties sourced from inconsistencies in modelling procedure that are related to the project specific circumstances of the model genesis (Scottish Water, 2009). For instance, when genesis lies in large projects, the focus of the project can lay beyond the scope of detailed flow estimation and appraisal of models. Such projects often produce models that have less importance placed upon the quality of the model calibration and input data. It is also the case that Hysim models created and adapted by different companies that offer different approaches to the construction of models and weight internal protocol over guidance available from Scottish Water.
Neuman (2003), states that the bias and uncertainty that result from an inadequate conceptual mathematical model are typically larger than those introduced through an inadequate choice of parameter values; it is essential to choose the correct donor catchment and target catchment for model calibration and transposition respectively. In light of this, there is a strong need to create a clear and pragmatic methodology for the selection of a parameter-set for use on a target catchment that is ungauged. In order to avoid the aforementioned caveats of model construction it would be beneficial to construct a library of Scottish Water acknowledged Hysim models that could be applied to
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ungauged catchments with a good degree of confidence; as outlined in the closing notes of Jacobs (2010).
There is considerable justification for an improvement in the method in which a model is calibrated and applied to an ungauged catchment using an analogue catchment. Without improvement, any future work where Hysim models are updated or new models developed will continue to provide inaccurate estimations of flow for a given catchment. A common recommendation, based on a poor correlation between calibration and direct gauged flows, is to scale the estimated Hysim flow series to agree with SEPA’s low flows enterprise flow duration curve (Scottish Water, 2011). LFE estimates may also be uncertain and lead to misleading yield estimates and be an inadequate result for the estimation of yield by Scottish Water.
1.2.1 Quantifying the uncertainty associated with parameterisation
A number of literature sources discuss methods of validation for models in order to evaluate the uncertainty that exists in a particular model. This paper requires the evaluation of uncertainty associated with parameterisation. Seibert (1999a) gives a thorough review of the meaning and application of the term validation in a hydrological modelling context. A series of applications incorporating all current methods of validation with specific outcomes is detailed. A method for gaining a measure of model parameter uncertainty in between hydrologically similar, gauged
catchments is identified by Seibert (1999a) as the proxy-basin test. Calibration takes place on a single catchment and validation of the optimal parameter-set is achieved by the transposition of these parameters to another gauged catchment. Seibert et al. (1999b) used a conceptual rainfall-runoff model, the Hydrologiska Byråns model (HBV), to calibrate a single catchment and validate this calibration on a further two catchments of similar character in the Black Forest, Germany. An expression of model efficiency was studied for every application of the calibrated parameter-set. In the optimisation of one parameter-set and application on the similar two catchments the average measure of efficiency was 0.76 (1 corresponding to a perfect fit). When calibrated in the
hydrologically analogous catchments and parameters were applied to the original catchment the measure of efficiency was 0.84. These steps are characteristic of the proxy basin method and elucidate that there is less uncertainty associated with the model with 0.84 thus quantifying uncertainties associated with parameter choices.
The proxy-basin test of validation provides a significant solution to the main objective of this investigation: to quantify the uncertainty associated with parameterisation when estimating flow in ungauged catchments. It is essential to use the framework of the proxy-basin test in order to evaluate the uncertainty associated with the parameter-set construction methods that are proposed. As indicated by the aforementioned study by Seibert et al. (2009b) a measure of model efficiency according to the Nash-Sutcliffe Efficiency Criterion is the preferred method of evaluating the performance of a model.
In previous studies commissioned by Scottish Water i.e. Jacobs (2010), the model efficiency for Hysim is not used to calibrate or evaluate the performance of the model; instead the FDC and associated flow descriptor statistics (Q95, MF, Q95(%MF)) are used as a measure of accuracy and therefore an evaluation of the performance of the model with a specific parameter-set. A concern in this approach is highlighted through conference in this study due to the fact that FDCs, unlike model efficiency neglect the temporal aspect of model performance. Additionally, it is possible for an estimated FDC to exactly match a recorded FDC whilst the model efficiency is very poor. However, in studies by Westerberg (2011), which involved the analysis of FDC calibrations in 23 basins, the FDC calibration method was found to have potential for calibration to regionalised FDCs for ungauged basins; reducing the initial model uncertainty by approximately 70% (Westerberg, 2011).
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Therefore the use of FDC in calibration and as a comparative measure of accuracy is used throughout this report.
1.2.2 ROI as a method of regionalisation
Using the framework of proxy-basin validation in order to evaluate the accuracy of parameter-sets -in accordance with the scheme outlined by Seibert et al (1999b)- requires a method of regionalisation for the application of parameter-sets. The process of transferring information from neighbouring catchments to the catchment of interest is generally referred to as hydrological regionalisation (Blóschl and Sivapalan, 1995). It is used to make predictions about hydrological quantities at sites where data are absent or inadequate, frequently for design purposes (Beran, 1990). Three
regionalisation methods are used to identify suitable gauged catchments, from which the optimised parameter values are used to estimate flow for the target ungauged catchment:
i. The regression method establishes a relationship between the optimised parameter values and catchment climate and physical attributes. Parameter values are then estimated for the
ungauged catchment from its attributes and the identified relationship.
ii. The spatial proximity method uses parameter values from the geographically closest gauged catchment because neighbouring catchments are expected to behave similarly due to shared physical and climatic characteristics
iii. The physical similarity method transfers the entire set of parameter values from a physically similar catchment.
Varying the method by which parameters are transferred from the optimal parameter-set of a donor catchment to the target catchment is the source of the full parameter and partial transposition methods that are evaluated for associated uncertainty in this study. Therefore a degree of regionalisation must be factored into the choice of donor and ungauged catchments. The spatial proximity method, where the geographically closest gauged catchment has its parameters transferred to the target catchment would be somewhat adequate for application in Scotland. However, this is unlikely due to the high variation in catchment character across Scotland, owing to underlying geologies and marine landforms for which there are Scottish Water source catchments assigned.
Scottish Water utilise ROI as an approach to regionalisation in order to categorise suitable donor catchments and target catchments for parameter transfer. Acreman & Wiltshire, 1987 first suggest this approach with the premise that the technique allows each donor catchment to have a unique set of target catchments, which inclusively constitute the “region” for that catchment. Thus, there are no boundaries indicating a specific variable and donor catchments within a specific area do not need to have the same target catchments. According to Feaster and Tasker (2002) the ROI is defined as a set containing the n closest stations. The ROI is defined as the set of all stations closer than a distance R (in predictor variable or geographic space) from the site or, if the number of stations in that set is smaller than some minimum allowable number n, the n closest stations. Scottish Water use predictor variables such as: location, SAAR and BFI to identify donor and target catchments. In order to test the validity of Q95(%MF) in such a role, Q95(%MF) is used to help select the catchments for parameter transfer.
ROI in application is seen on figure 1.2.4, using gauged values of Q95(%MF). As such, Q95(%MF) ROI will be used as a proxy for regionalisation methods in the allocation of donor and target for the provided SEPA catchments in this study.
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1.2.2 Modelling flow in ungauged catchments, a calibration scheme compatible with Scottish Water and Scotland
A previous study for Scottish Water by Jacobs Engineering UK Limited (Jacobs, 2010) investigated approaches to Hysim rainfall-runoff modelling and the resultant impact on yield sensitivity. The particular focus of this study was to investigate the sensitivity of Hysim models to the choice of target catchment as well as the impact of using different calibration periods (record length and
representativeness). The resulting variable Hysim model outputs were then tested in Aquator water resource system models using different catchment sizes and reservoir storage volume to assess the impact in terms of yield sensitivity and uncertainty. As well as presenting conclusions on model sensitivity and consequential yield sensitivity -the former of which will contribute to the discussion of this paper- the study provides a tailored procedure for flow estimation in ungauged catchments using Hysim for Scottish Water.
As this study is interested in isolating the uncertainty associated with parameterisation it is imperative to adhere to a standard method for input data selection and calibration procedure whilst updating these existing processes where improvements can be made without perturbing the uncertainty in parameter choice. The Jacobs (2010) study is therefore used as the reference of a data processing, selection and model calibration procedure that suits Scottish Water. Using this approved calibration procedure as a framework will allow this paper to take advantage of the outcomes of the Jacobs study and further develop the standard calibration method to suit the objectives of this paper. As there is no method for evaluating the choice of parameter-set in ungauged catchments provided by the Jacobs study it would be useful to extend this calibration procedure to formalise a standard method for testing a donor parameter-set’s ability to estimate flows in an ungauged catchment.
The total process accounted for in the Jacobs (2010) study covered: donor catchment selection, target catchment selection, data acquisition, data quality control, calculation of catchment statistics,
calculation of catchment parameters (catchment area, time to peak, rooting depth and interception storage), the calibration of the donor catchment using Hysim, comparison of estimated flow to recorded flow and final calculation of flow estimation descriptors (Jacobs, 2010). The procedures outlined by Jacobs (2010) serve as a foundation for the development of this study’s methodology due to the bespoke nature of their outcomes to suit Scottish Water guidelines.
Jacobs (2010) aimed to ensure consistency and repeatability in the Hysim calibration procedure by removing the degree of user subjectivity from the process i.e. eliminating the manual adjustment of parameters. It was suggested in the study that an increase in user subjectivity would exist between the calibrations of multiple catchments. Also identified was the trade-off between subjectivity and level of detail, time spent, user experience and quality of the calibration. The calibration process was designed to enable relative differences in resulting yields to be discussed with the same procedure followed in the calibration process. This is important as subjectivity was identified as a key cause of sensitivity in the use of Hysim by Scottish Water (2009). In the calibration methodology for this report it is necessary to achieve the best possible calibration and so manual calibration is essential for some calibrations. However, manual adaptation of parameters beyond the standard calibration procedure must be limited to a number of attempts for best fit between estimated and recorded flow;
thus, limiting the subjectivity. In addition, the Jacobs (2010) report identified that the uncertainty associated with different catchment choice appears to be slightly larger than the uncertainty associated with choice of record length and found that an eight year calibration offered the most reliable
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estimations of flow. Selected catchments for this study therefore have an eight year period of good quality recorded data in order to eliminate the influence of other uncertainties upon the observations of this study’s aims.
Additionally, Jacobs (2010) suggested that there was an increase in yield sensitivity with a reduced flashiness of catchment. It should be noted that, due to the small sample size involved in the study, these conclusions were considered provisional within the report itself. It would be useful to explore these provisional conclusions in this paper’s discussion of uncertainties associated with the character of target of catchments chosen.
A final remark of the Jacobs (2010) study was the suggestion that collating a “library” of pre- calibrated Hysim project files would be an adequate solution to limit uncertainty and reduce the labour involved with detailed calibration for each application. Producing a library of well calibrated Hysim projects, each with a quantified uncertainty and clear construction method would allow Scottish Water or external consultants to use a model where justified. Essentially, this study evaluates the proxy basin methodology for estimating flows in ungauged catchments. If uncertainty is reduced due to the use of single method of parameterisation for hydrologically analogous catchments then this single method can be used to produce a number of calibration parameter-sets that could each be used on a large number of hydrologically analogous catchments with a known level of uncertainty; thus creating a pragmatic and cost effective estimation of flow in ungauged catchments.
1.3 Key questions and summary of methods
In this thesis three key questions are addressed upon completion of the stated objectives of the study:
i. Is it possible to use the proxy-basin test framework to quantify the uncertainties associated with parameter transposition?
ii. Is there a method of parameter transposition that has a lower uncertainty associated with its application?
iii. How can this information be used to create a more pragmatic model application scheme within Scottish Water?
In order to support these hypotheses, the objectives of the report were accomplished with the following procedural methodology:
i. Selection of 16 gauged catchments that are approved by SEPA and are representative of catchments that are utilised by Scottish Water. This is accomplished through the comparison of hydrological statistics between catchments and mega-zones, and supplemented by discussion with Scottish Water.
ii. Use of ROI as a regionalisation method for grouping potential donor and target catchments according to Q95(%MF) flow descriptor. Allocation of “donor” and “target” catchments according to availability and quality of data as well referring to existing use within Scottish Water.
iii. Update and improve existing Scottish Water catchment calibration models if encountered. Update data used in projects where possible and choose a different time period where beneficial.
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iv. Development of two parameter transposition method identified as “full transposition” and “partial transposition” methods. Evaluation of the performance of these parameter-sets on each group of target catchments using one calibrated donor model according to the proxy-basin test framework;
elucidating uncertainty associated with these parameter-sets.
v. Comparison of catchment characteristics in relation to parameter-set performance in order to expand upon conclusions made about uncertainty in target catchment selection mad by previous studies.
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2 Materials and Methods
2.1 Analogue and target site selection from SEPA catchments
Hydrological representativeness
There are 207 Scottish Water river sources within Scotland, of which 103 feed reservoirs and 104 are standard river sources. The standard river sources are directly applicable for the investigation of runoff and approximation of yield for a water source; therefore, 104 rivers distributed throughout Scotland are suitable candidates for flow estimation studies. In total, 24 catchments –referred to as analogue catchments by SEPA- were refined from those selected by SEPA’s analogue selection tool and evaluation expertise at Scottish Water. Data for these 24 catchments were obtained from the respective parties and covered the entire recorded period for flow, precipitation and
evapotranspiration; the specific derivation of which is covered in later chapters.
In order to represent the range of water resource catchments that water authorities in Scotland utilise for water supply in Scotland it was essential to compare the hydrological statistics of catchments to the average statistics of Scottish Water mega-zones that are identified on figure 1.2.1. The
hydrological variables that were studied included:
• A value of catchment area was referenced from the UK Hydrimetric Register (UKHR) delivered by the Centre for Ecology and Hydrology (CEH) (2008).
• Standard annual average rainfall (SAAR) was referenced from the UKHR.
• Base flow index (BFI); a value derived from gauged daily flow data. This represents the contribution of the slow flow or groundwater flow in the total measured runoff at the catchment outlet , giving a degree of flashiness i.e. the frequency and rapidity of short term changes in daily runoff values (Deetris & Lital, 2008). This was referenced from the UKHR.
• Base flow index (BFI HOST SCOT); a base flow value that is derived from Low Flows Enterprise results.
• 95th percentile flow value as a percentage of the mean flow (Q95(%MF)); a value derived from gauged daily flow data where available,else Low Flow Enterprise modelling was used. This value is a commonly used measure of flashiness and other runoff characteristics; it illustrates the flow that is exceeded 95% of the time as a percentage of mean flow.
It should be noted that Polloch, Skeabost and all mega-zones use the calculated BFI hydrology of soil types Scotland (HOST SCOT) value, which is obtained from LFE results. BFI HOST SCOT is not a substitution for gauged BFI and has been flagged as producing inadequate results in uses by Jacobs (2010); however, this does not directly affect the choices made to exclude specific catchments.
Previous studies by Jacobs (2010) critically assessed catchments using factors of: artificial influence, standing water area, record length, Institute of Hydrology grading quality and any further information that would be influential to the suitability of the gauged data for a catchment. This revealed features that could perturb the natural flow of the river and cause error in the evaluation phase of the experiment and were taken into account when selecting catchments for experimentation.
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Confirmation of ROI grouping
Using ROI for Q95(%MF) catchments were grouped into four Q95(%) groups. The plot of aforementioned catchment statistics were observed in order to interpret the suitability of Q95(%MF) for grouping catchments of hydrological similarity. Each group was then elected a donor catchment, chosen for its reliability as a presently used model and representativeness of typical flow per Q95(%MF) group. The remaining catchments within each group would then be denoted as target catchments. In total there were sixteen catchments identified for use in the study: four donor catchments and twelve catchment analogues; these are displayed on table 2.1.1. The distribution of these chosen catchment analogues across Scotland in relation to their Q95(%MF) group is illustrated on figure 2.1.2.
Of the twenty four catchments that refined from SEPA provided analogues there were eight omitted from the study. These eight catchments represented Q95(%MF) groups that were below 5% and above 13%. These catchments were not used for the evaluation of transposition performance; however, they were included in observations of catchment representativeness (see figures 3.1.1 to 3.1.3).
TABLE 2.1.1: DESIGNATION OF DONOR AND TARGET CATCHMENTS.DONOR CATCHMENTS ARE INDICATED IN BOLD, ALL OTHER CATCHMENTS ARE CATCHMENT ANALOGUES.
Group
Station Name
Area (km²)
SAAR (mm)
BFI (gauged)
BFI-HOST (SCOT)
Q95 (%MF)
Braevallich 24.10 2745 0.22 0.22 6.5%
Glen Strae 36.62 2772 0.26 0.21 5.2%
Polloch 8.05 2650 0.23 0.23 5.5%
Deephope 30.99 1486 0.32 0.26 6.1%
Durkadale 19.60 1145 0.28 0.42 8.8%
Barsolus 32.83 1150 0.35 0.38 9.0%
Inverlochy 47.09 2946 0.26 0.24 7.1%
Skeabost 80.55 2218 0.26 0.26 7.9%
Luss 35.47 2296 0.35 0.28 9.4%
Candermill 25.50 1034 0.40 0.31 9.2%
Creed Bridge 44.83 1462 0.25 0.44 9.3%
Dargall Lane 2.07 2439 0.21 0.28 9.8%
Lathro 24.60 1164 0.54 0.43 11.0%
Brockhoperig 38.59 1732 0.37 0.34 11.4%
Kinross 33.60 1266 0.56 0.42 12.1%
Whitburn 31.95 1032 0.32 0.30 11.5%
11 - 13%9 - 11%7 - 9%5 - 7%
Selection of time periods
It was essential to make sure that each chosen catchment had a period of gauged data that was at least ten years in length and that this was of good quality. Ten years was considered the calibration period length for previous studies by Jacobs (2010). Ten years allowed for two years for model warm-up and the eight years of calibration data. Scottish water recommends a minimum of seven years of data record; therefore this is more than satisfactory. The data to be used was: rainfall, evapotranspiration and flow data; making a total of 48 sets of data that would be subject to scrutiny.
The selection of time periods of data was dictated by the availability, quality and representativeness of rainfall, flow and potential evapotranspiration input data. It was chosen that there would be one time period for each Q95(%MF) group, making four time periods in total. Selection was achived by comparing the data between the four catchments in each group then deciding which time period is most complete and which is most respresentative of each individual catchment. It was thought best to keep the time series the same across each four catchments in each Q95(%MF) group in order to similarise climate limits upon inputs across Scotland for the Q95(%MF) group and therefore enable a fair test. If climate
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conditions across Scotland differed from the average for a given day, month or year then these trends would impact all catchments in direct comparison with each other.
In some instances Scottish Water calibrations existed for catchments that this study had allocated donor catchments. It was seen as useful to improve these models by updating existing data where improved data was available and selecting or extending time periods where possible.
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FIGURE 2.1.2:CHOSEN CATCHMENTS FROM SEPA PROVIDED CATCHMENTS, AN INDICATION OF Q95(%MF)ROI GROUPING IS PROVIDED.SUPPLIED BY SCOTTISH WATER ON REQUEST.
