Application of indicators of hydrologic alteration in Portuguese
rivers impacted by dams
Joana Saldanha Lopes Lourenço Cardoso
Thesis to obtain the Master of Science Degree in
Civil Engineering
Jury
Chairperson: António Alexandre Trigo Teixeira, PhD
Supervisors: Maria Manuela Portela Correia dos Santos Ramos da Silva, PhD
Francisca Constança Frutuoso de Aguiar, PhD
Members of the Commitee: Maria João Teixeira Martins, PhD
Francisco Carlos da Silva Nunes Godinho, PhD
December 2013
Cover image: Vilarinho das Furnas watershed, Braga, Portugal (Photography taken in 2013)
ABSTRACT
The aim of the current work was to characterize dam-induced changes in different Portuguese river reaches
through the application of indicators of hydrologic alteration. Besides that, it also intended to provide the
background to assess the consequences that those changes may have on the fluvial ecosystems.
Dams have been constructed to regulate the intra- and inter-annual variability of the flow regimes and also for
other purposes such as energy production. In spite of their wide utility, they also raise some concerns as they
induce alterations in the natural hydrologic regime.
The Indicators of Hydrologic Alteration are numerical indicators that summarize the main characteristics of the
hydrologic regime, thus allowing the comparison between natural and modified conditions either within a
given river or among different rivers.
In the present study, nine rivers reaches impacted by dams used mainly for hydropower production located in
mainland Portugal and having series of daily flow data upstream (inflows) and downstream the dams (outflows)
were selected as case studies. The inflows were considered to represent the natural flow regime. Based on the
outflows, the modified flow regimes were established. The indicators were computed and compared within
and among the case studies through different approaches.
It was confirmed that the storage dams, especially those transferring water among different watersheds,
induce the most severe hydrologic changes. The indicators of hydrologic alteration proved to be a useful
approach, capable of focusing, comparing and establishing levels of dam-induced hydrologic disturbances.
Keywords: dams; dam-induced changes; indicators of hydrologic alteration; river flow regime; natural
conditions; modified conditions.
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RESUMO
A presente tese tem como objectivo caracterizar os efeitos no regime hidrológico em troços de rios a jusante
de barragens portuguesas através da aplicação de indicadores de alteração hidrológica. A par dessa
caracterização, procura-se rever os principais conhecimentos neste âmbito, focando algumas das
consequências que estas alterações podem ter nos ecossistemas fluviais.
Em resultado da elevada variabilidade temporal (inter-anual e sazonal) que caracteriza o clima de Portugal
Continental, têm sido construídas barragens com o objectivo de regularizar os caudais naturais, bem como para
a produção de energia. Apesar da sua incontestável utilidade, as barragens constituem necessariamente uma
perturbação nos corredores fluviais que, para além de outros aspectos, resulta muito frequentemente na
alteração das características do regime hidrológico. Os Indicadores de Alteração Hidrológica são valores
numéricos passíveis de sumariar as principais características do regime hidrológico, permitindo uma
comparação entre os regimes em condições naturais e modificadas ao longo de um rio ou entre rios.
Nesta dissertação, seleccionaram-se nove troços de rios em Portugal regularizados por barragens utilizadas
sobretudo para produção de energia hidroeléctrica e que dispusessem de períodos com dados hidrométricos
minimamente representativos dos regimes fluviais diários. As afluências foram consideradas representativas do
regime de caudais existente anteriormente à construção das barragens (caudais naturais), e com base nos
caudais efluentes, estabeleceram-se os regimes de caudais modificados. Os indicadores foram calculados e
comparados entre os diferentes casos de estudo, utilizando várias metodologias.
Confirmou-se que os aproveitamentos com maior capacidade de transferência temporal de afluências e que
executem transvases entre bacias são obviamente os que induzem maior alteração nos regimes hidrológicos,
contrariamente aos aproveitamentos com exploração a fio-de-água. Os indicadores de alteração hidrológica
revelaram ser uma abordagem útil e eficaz na comparação e estabelecimento do grau de alteração hidrológica
induzido por diferentes tipos de barragens.
Palavras-chave: regime hidrológico; barragens; indicadores de alteração hidrológica; regimes naturais; regimes
modificados.
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To my dear grandfather
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ACKNOWLEDGMENTS
First of all, I would like to thank Professor Maria Manuela Portela, for guiding me through my research. I owe
her my sincere gratitude for the great opportunities given to me with no hesitation and all the persistent help,
confidence, discipline and patience transmitted throughout this year, which provided me an opportunity to
grow in many senses.
Secondly, I thank Francisca Aguiar, for all the dedication and support provided. I also acknowledge her expert
advices and attention to detail which were a valuable contribution to the dissertation.
Also, to Maria Dolores Bejarano Carríon and Maria João Martins whose observations also contributed positively
to the research carried out. Artur Silva also deserves a word of acknowledgement, given his availability and
support during this time.
I likewise want to thank Fundação para a Ciência e a Tecnologia (FCT), for funding PTDC/AACAMB/120197/2010 - Project OASIS - “how to run regulated rivers in semi-arid regions?” where this research is
included.
To my friends and colleagues, I would like to thank all the support, affection and enjoyable moments during
these years. Among them I would like to mention Rita, Miguel, João Telo, Guilherme, Miguel Duarte, Elisa,
Francisco, Paulo, Carolina, Mariana, Catarina, João Sampayo and André Ramos. A very special thank you goes
to Margarida for all the motivation and encouragement given. I express my deepest thankfulness to António
too, for being there unconditionally and for his priceless care and support.
Finally, I have no words to express my gratitude towards my family, for all the love and care, and also for the
values transmitted since my early days. I thank my mother, for listening with never-ending patience and always
having the perfect words. I thank my father, for the discipline he used me to and which helped me grow. I also
thank my sister, Sofia, for all the happy moments shared and for knowing me so well.
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TABLE OF CONTENTS
CHAPTER I. INTRODUCTION ........................................................................................... 1
I.1
SCOPE ..........................................................................................................1
I.2
OBJECTIVES.....................................................................................................1
I.3
STRUCTURE OF THE DISSERTATION ..............................................................................2
CHAPTER II. BACKGROUND ........................................................................................... 3
II.1
OVERVIEW ......................................................................................................3
II.2
MEASURING THE LEVEL OF ALTERATION: APPROACHES ..........................................................8
II.3
INDICATORS OF HYDROLOGIC ALTERATION (IHA)............................................................. 10
II.3.1 The software............................................................................................. 10
II.3.2 The indicators ........................................................................................... 11
II.4
INDICATORS OF HYDROLOGIC ALTERATION IN RIVERS (IHAR) ............................................. 14
CHAPTER III. CASE STUDIES AND BASIC DATA ........................................................................ 17
III.1
CASE STUDIES ................................................................................................. 17
III.2
BASIC DATA FOR UPSTREAM VERSUS DOWNSTREAM COMPARISON .............................................. 25
III.3
COMPLEMENTARY INFORMATION ON VILARINHO DAS FURNAS CASE STUDY ...................................... 27
CHAPTER IV. IHA APPLICATION: SPATIAL COMPARISON ............................................................. 29
IV.1
INTRODUCTION ............................................................................................... 29
IV.2
PRESENTATION OF THE PROCEDURE BASED ON ALTO LINDOSO CASE STUDY .................................... 29
IV.2.1. Dimensionless 25% and 75% percentiles ........................................................... 32
IV.2.2. Dimensionless medians ............................................................................... 34
IV.2.3. Mean daily flow duration curves ................................................................... 35
IV.2.4. Mean daily flow per month .......................................................................... 36
IV.2.5. Ratio between indicators ............................................................................ 37
IV.3
RESULTS ...................................................................................................... 38
CHAPTER V. VILARINHO DAS FURNAS CASE STUDY: TEMPORAL COMPARISON ....................................... 41
V.1. INITIAL CONSIDERATIONS ........................................................................................ 41
V.2. ANALYSIS BASED ON THE RECORDS AT COVAS STREAM GAUGING STATION ......................................... 41
V.3. ANALYSIS BASED ON THE RECONSTRUCTION, FOR THE POST-DAM PERIOD, OF THE NATURAL REGIME AT COVAS
STREAM GAUGING STATION ............................................................................................ 43
CHAPTER VI. CONCLUSIONS AND FUTURE DEVELOPMENTS .......................................................... 49
BIBLIOGRAPHY........................................................................................................ 51
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LIST OF FIGURES
Figure 1 - Main stages of the methodology proposed .......................................................................................... 14
Figure 2 - Scheme of hydraulic powerhouse functioning. .................................................................................... 17
Figure 3 - Case studies: (1) Alto Lindoso, (2) Touvedo, (3) Vilarinho das Furnas, (4) Paradela, (5) Vilar, (6)
Caldeirão, (7) Fronhas, (8) Cabril and (9) Pracana. ............................................................................................... 18
Figure 4 - Case studies 1 - Alto Lindoso (left) and 2 - Touvedo (right). ................................................................. 19
Figure 5 - Case study 3 - Vilarinho das Furnas....................................................................................................... 20
Figure 6 (up) - Case study 4 - Paradela and Figure 7 (down) - Case study 5 - Vilar ............................................... 21
Figure 8 - Case study 6 - Caldeirão ........................................................................................................................ 22
Figure 9 - Case study 7 - Fronhas .......................................................................................................................... 23
Figure 10 - Case study 8 - Cabril ............................................................................................................................ 23
Figure 11 - Case study 9 - Pracana ........................................................................................................................ 24
Figure 12 - Vilarinho das Furnas case study and Covas stream gauging station. .................................................. 28
Figure 13 - Example, based on Alto Lindoso case study, of the web diagrams for the dimensionless 25% and 75%
percentiles............................................................................................................................................................. 33
Figure 14 - Example, based on Alto Lindoso case study, of the web diagrams representative of the
dimensionless median. ......................................................................................................................................... 35
Figure 15 - Example based on Alto Lindoso case study. Dimensionless flow duration curves for the natural and
modified regimes. ................................................................................................................................................. 36
Figure 16 - Example based on Alto Lindoso case study. Monthly mean daily flows for the natural and modified
regimes.................................................................................................................................................................. 37
Figure 17 - Schematic representation of the periods with daily flow data from the SNIRH (Covas S.G.S.) and
from EDP. .............................................................................................................................................................. 41
Figure 18 - Duration curves for EDP and Covas results (for Vilarinho das Furnas). .............................................. 43
Figure 19 - Mean annual flow duration curves: a) at the 54 Portuguese stream gauging stations (left); and from
those stations at the b) 26 and c) 28 with mean annual flow depths respectively higher and smaller than
400 mm (right) ...................................................................................................................................................... 44
Figure 20 - Scheme including the data suitable for the analysis considering the reconstruction of Covas natural
regime after 1972. ................................................................................................................................................ 45
Figure 21 - Daily (a), monthly (b) and annual (c) flows at Covas stream gauging station. Registered and
reconstructed based on Fragas da Torre. ............................................................................................................. 46
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LIST OF TABLES
Table I - Ecological responses to alterations in components of natural flow regime ............................................ 5
Table II - Outputs returned by IHA Version 7.1 software (for non-parametric analysis). ..................................... 11
Table III - Indicators of Hydrologic Alteration, for one year of daily records. ...................................................... 11
Table IV - Definition of the Indicators of Hydrologic Alteration for one year of daily records. ............................ 12
Table V - Main influences of each IHA group on the ecosystem properties and biotic components ................... 13
Table VI - Parameters for the characterization of the flow regime ...................................................................... 15
Table VII - Indicators of Alteration in Rivers for contemporary regimes. ............................................................. 16
Table VIII - Characteristics of the case studies ...................................................................................................... 24
Table IX - Years considered for each case study. .................................................................................................. 26
Table X - Natural and modified modulus. ............................................................................................................. 26
Table XI - Example, based on Alto Lindoso case study, of the data to introduce in IHA version 7.1. natural flow
regime. .................................................................................................................................................................. 29
Table XII - Example, based on Alto Lindoso case study, of the results given by IHA7 software for the natural flow
regime for the period of analysis (reproduced as given by the software): non-parametric IHA scorecard (“sco”).
.............................................................................................................................................................................. 30
Table XIII - Example, based on Alto Lindoso case study, of the results given by IHA7 software for the natural
flow regime organized in percentiles (reproduced as given by the software): IHA percentile data table (“pct”).31
Table XIV - Example, based on Alto Lindoso case study, of the results achieved for the dimensionless 25% and
75% percentiles. .................................................................................................................................................... 32
Table XV - Example, based on Alto Lindoso case study, of the results achieved for the dimensionless median. 34
Table XVI - Example based on Alto Lindoso case study. Dimensionless flow duration curves for the natural and
modified regimes. ................................................................................................................................................. 36
Table XVII - Vilarinho das Furnas modulus for the natural and modified regimes based on the SNIRH and on the
EDP data. ............................................................................................................................................................... 42
Table XVIII - Important information on Covas and Fragas da Torre gauging stations........................................... 44
Table XIX - Vilarinho das Furnas case study. Ratios of alteration for EDP (i), Covas (ii) and for the period after
1972 based on the reconstructed natural regime and on the registered modified regime (iii). .......................... 47
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LIST OF SYMBOLS
Acronyms
IHAR
Indicators of Hydrologic Alteration in Rivers
IHA
Indicators of Hydrologic Alteration
ICOLD
The International Commission on Large Dams
ELOHA
Ecological Limits of Hydrological Alteration
WFD
Water Framework Directive
SNIRH
Sistema Nacional de Informação de Recursos Hídricos
APA
Agência Portuguesa do Ambiente - Environmental Portuguese Agency
EDP
Energias de Portugal
S.G.S.
Stream gauging station
Symbols
3
Qmod
Long-term average of the mean daily flows or, in other words, the modulus (m /s)
Qmod Natural
Natural condition modulus (m /s)
Qmod Modified
Modified condition modulus (m /s)
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3
Indicator of Hydrologic Alteration for natural conditions
Indicator of Hydrologic Alteration for modified conditions
RA
Ratio of alteration (-)
̅
Mean annual flow depths (mm)
A
Watershed area (km )
2
Mean daily flow on Julian day i, for the section respecting to
Natural modulus considering
3
gauging station (m /s)
3
gauging station (m /s)
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LIST OF APPENDICES
Appendix A. - Results relative to Chapter IV
Appendix B. - Results relative to Chapter V
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CHAPTER I. INTRODUCTION
I.1
SCOPE
Climate of mainland Portugal is mostly Mediterranean, with around 80% of the surface runoff occurring during
the wet semester (from October to March). Besides the water scarcity in summer, there is a marked
inter-annual variability of flow regime, which affects the efficient use of river runoff. River regulation by dams
plays a major role in this scope to surmount these climatic constraints. Dams are built for various purposes,
being the most important the hydropower production, the water storage to satisfy the urban, industrial and
agricultural water requirements, though flood control and recreation may also be envisaged.
Despite their importance to meet present human water demands, dams impair aquatic and riparian
ecosystems, as they induce alterations in the flow regime of rivers. Hydrologic alterations caused by regulation
affect the structure, composition, diversity and functioning of aquatic and riparian communities (e.g. fish,
macro invertebrates, vegetation) and alter the physical components of fluvial systems (e.g. geomorphology,
bank stability, substrate).
Given that fluvial ecosystems are “legitimate users” of water, there is a clear conflict between conservation and
exploitation of freshwater resources, which certainly requires the support of hydrologic studies to be
overcame. Nevertheless, few studies have documented the hydrologic alterations to the natural flow regime
induced by dams in Portugal.
In this context, the present study aims to characterize the changes in flow regime caused by regulation in
different case studies, thus seeking a contribution to a better understanding on the impacts of dams.
I.2
OBJECTIVES
The general goal of the present research is to improve our understanding of the hydrologic characteristics of
the flow regimes and how they are affected by river damming.
For that purpose, the methodology used included:
1.
Framing of the subject and the main underlying concepts, including the natural flow regimes, the
dam-induced alteration on such regimes and the resultant consequences. The approaches applied are
presented as well.
2.
Selection of case studies in mainland Portugal, their characterization in relation to location, date of
dam construction, regulation capacity, and other important information that support the results and
their discussion.
3.
Gathering daily flow data that can accurately support the analysis.
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4.
Application of indicators of hydrologic alteration to the selected case studies. Additionally, a more
detailed study in a particular case study is presented, given the availability of a long-time series of flow
data - Vilarinho das Furnas dam.
This research will contribute to the analysis and understanding of hydrologic alterations induced by dams in
Portugal.
I.3
STRUCTURE OF THE DISSERTATION
This dissertation is structured into six chapters, being their specific contents described below.
Chapter I briefly introduces the scope and the main objectives of the present study, as well as its structure.
Chapter II provides the background information relative to hydrologic alteration with interest to the research.
It includes the state-of-art and the methodological approaches that have been developed to measure the level
of flow alteration in rivers, as well as an overview of the ecological responses of aquatic and riparian
communities. In addition, two sets of indicators of hydrologic alteration - IHAR and IHA - and the software that
allow their calculation are presented.
Chapter III presents the selection of case studies and the basic data that support the analysis carried out. In
addition, complementary information about a specific case study, Vilarinho das Furnas, is provided.
Chapter IV refers to IHA application, including an example of the procedure applied to a case study. The
methodological approach is detailed and the discussion of the overall results for all case studies is presented.
Chapter V addresses Vilarinho das Furnas case study in a more thorough way based on the stream gauging
station of Covas, located in the dammed River, a few kilometres downstream the dam.
Chapter VI presents a summary of the main conclusions of this research.
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CHAPTER II. BACKGROUND
II.1
OVERVIEW
In the past last years, water has become a recurrent topic with an increasing interest at the societal, economic
and ecological levels. It is an established fact that water is essential to life, the same way that its wide presence
around the globe is. However, though this element covers most of the Earth’s surface, only 2,5% are
freshwaters, and 98,8% of that water is in ice and groundwater.
Even for using this little part of the freshwater resources, humans must rely on the time factor due to an
inherent variability of the flow regimes, meaning that a river or a lake with water on a certain moment may be
dry on another. This fact assumes a more expressive importance when considering Mediterranean regimes, as
it happens in Portugal, since they are characterized by dry summers and intense autumn-winter floods, along
with pronounced interannual rainfall variability. This situation sometimes leads to dry winters and
consequently to supra-seasonal droughts (Belmar Díaz, 2013). According to that, it is extremely important to
find ways to create water reservoirs in order to assure its availability over time either for drinking, irrigation,
industrial uses or recreational purposes. Dams assume a major position in this context, becoming a solution to
this kind of constraints.
Besides their role of creating water reservoirs, the interest of such infrastructures goes far beyond that, also
assuming a fundamental position in flood control and energy production. In one hand, once their interest is
flood control, they are able to regulate river levels and flooding by temporarily storing the flood volume
upstream and releasing it later. On another hand, dams are also conceived as a way to produce energy by
means of hydroelectric power plants. The increasing interest in sustainability has led people to drown their
attention to “cleaner” types of energy, which is the case of hydropower. In fact, this is by very far the largest
renewable energy source in the world since more than 90% of the world's renewable electricity comes from
dams (The International Commission on Large Dams - ICOLD). Besides, hydropower also offers unique
possibilities to manage the power network by its ability to quickly respond to peak demands. These remarks
stress the huge importance of such infrastructures to satisfy the nowadays water needs.
Portugal has invested a lot in this domain over the recent years, constructing dams and power plants all over
the country. Independently from the construction’s purpose, there is a human perturbation taking place
upstream and bringing form to an alteration on the downstream flow regime, which stops being considered
natural to become modified instead. The natural flow regime is then the one that would exist if there was no
perturbation, becoming extremely important to understand its components, as it defines the hydrologic
variability patterns. These patterns reveal the interaction between the climatic regime - especially precipitation
and temperature - and the characteristics that regulate runoff - as geomorphology, lithology and vegetation.
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There are five main attributes that characterize the hydrologic regime of a river (Richter, et al., 1996):
1.
Magnitude: volume of water that circulates through a point per unit of time.
2.
Frequency: number of times that a flow condition occurs during a time interval.
3.
Duration: period of time associated with the flow condition.
4.
Timing or predictability: measure of the regularity of the flow condition.
5.
Rate of change: pointer of the velocity of change between distinct flow conditions.
The sustainability of the natural biodiversity and integrity of aquatic and riparian ecosystems depends on such
attributes. In fact, it relies on specific regime features, such as magnitude and frequency of extreme flows,
timing of high and low flows, flow duration, water table depth, intra- and inter-annual variability, groundwater
depth and sediment flux (Merritt, et al., 2010).
As already mentioned, dams consist on an environmental disturbance, interfering with these attributes, by
reducing flow magnitude and variability, sometimes also inverting seasonal patterns. Besides that, dams also
retain sediments upstream, alter channel dynamics and organic debris deposition, and have both upstream and
downstream effects on ecosystems and biota. Once a modification on hydrologic regime takes place, it results
in a widespread geomorphological and ecological impact on the aquatic and riparian communities. Movements
and migration of fish and other organisms, are obstructed or strongly limited due to the channel fragmentation
in an extent dependent on the type and dimension of the dam (Branco, et al., 2012). In addition, seed
germination, dispersal of seeds and propagules and riparian plant regeneration processes are also constrained
by those alterations (Bejarano, et al., 2012). These impacts, and many others, may be more or less severe,
depending on the changes experienced by the physical habitat due to the velocity of the water, the turbulence,
the temperature, the grain size, among other, and also depending on the ability of the aquatic and riparian
species to evolve in responses to those changes (Bunn & Arthington, 2002).
The riparian species aforementioned are those established on the riparian zones, which constitute a transition
or interface zone between the terrestrial and the aquatic ecosystems. The riparian corridors are complex,
dynamic and diverse habitats, possessing a biologically, economical and societal importance, that makes them
key ecosystems for preserving the overall biodiversity of fluvial landscapes. As a result, when analysing the
impacts on fluvial ecosystems, it becomes especially pertinent to attend to the alterations on the riparian
corridor, once it reflects strongly the changes undergoing. Inherently they have three articulated principles, as
proposed by Nilsson & Svedmark, 2002: (1) the flow regime determines the successional evolution of riparian
vegetation and ecological processes; (2) the riparian corridor serves as a pathway for distribution of organic
and inorganic material that influences plant communities along rivers; (3) the riparian system is a transition
zone that is disproportionately rich in terms of plant species when compared to surrounding ecosystems.
The changes induced by river damming assume a myriad of forms in the aquatic and riparian habitats (Belmar
Díaz, et al., 2013). The flood and variability reduction, for example, may induce significant alterations in life
cycles of many plant species (Greet, et al., 2012) and facilitate the intrusion and successful establishment of
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exotic species (Stromberg, et al., 2007). The modifications can also have other repercussions on the
ecosystems. High and low flow events constitute critical stresses, creating opportunities for a wide range of
riverine species. In this way, the frequency and intensity of flows determine the composition and relative
abundance of species (Greet, et al., 2012). The duration of a certain condition, in its turn, defines its ecological
relevance and also the species occurrence depending on their level of tolerance and resilience. Another
example is the fact that many riverine animals and plants attend to certain timings, meaning that they need a
stimulus from the habitat to pass through specific transitions of their life cycle. Another mentionable situation
is the fact that the indirect geomorphological alterations on the stream channel lead to altered composition of
vegetation communities, and usually experiment biodiversity loss (Rood, et al., 2010).
Many studies have been developed in this scope, aiming to relate the alteration in the components of natural
flow to the ecological responses associated with them. The most representative ones according to the reviews
from Poff, et al., 1997 and Poff & Zimmerman, 2010 are presented in Table I.
Table I (1/2) - Ecological responses to alterations in components of natural flow regime (adapted from Poff, et al., 1997;
Poff & Zimmerman, 2010).
Flow attribute
Specific alteration
Increased variation
(low/high flows; peak flows)
Magnitude and
frequency
Flow stabilization
Timing
Loss of seasonal flow peaks
Ecological response
Wash-out and/or stranding
Loss of sensitive species
Increased algal scour and wash-out of organic matter
Life cycle disruption
Altered energy flow
Unseasonal and reduced reproduction
Decreased fish abundance and decrease of native and endemic species
Shifts in community composition
Invasion or establishment of exotic species, leading to:
Local extinction
Threat to native commercial species
Altered communities
Reduced water and nutrients to floodplain plant species, causing:
Terrestrialization of flora
Seedling desiccation
Failure of seed establishment
Ineffective seed dispersal
Loss of scoured habitat patches and secondary channels
needed for plant establishment
Encroachment of vegetation into channels
Increased riparian cover
Disrupt cues for fish:
Spawning
Egg hatching
Migration
Loss of fish access to wetlands or backwaters
Modification of aquatic food web structure
Reduction or elimination of riparian plant recruitment
Invasion of exotic riparian species
Reduced plant growth rates
Decreased reproduction and recruitment
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Table I (2/2) - Ecological responses to alterations in components of natural flow regime (adapted from Poff, et al., 1997;
Poff & Zimmerman, 2010).
Flow attribute
Specific alteration
Ecological response
Prolonged low flows
Concentration of aquatic organisms
Reduction or elimination of plant cover
Diminished plant species diversity
Desertification of riparian species composition
Physiological stress leading to reduced plant growth rate,
morphological change, or mortality
Change in juvenile fish assemblages and decreased abundance of
young fish
Loss of floodplain specialist mollusk assemblages
Increased abundance of exotic species
Prolonged base flow “spikes”
Downstream loss of floating eggs
Altered inundation duration
Altered plant cover types
Duration
Prolonged inundation
Rapid changes in river stage
Rate of change
Accelerated flood recession
Change in vegetation functional type
Tree mortality
Loss of rifle habitat for aquatic species
Wash-out and stranding of aquatic species
Decreased germination survival and growth of plants
Low abundance and shifts in waterbird assemblages
Failure of seedling establishment
Increase in crayfish abundance
It is extremely important to recognise these river alterations and how strong they are, in order to step in and
find ways to control the environmental degradation that they lead to. The control can rather involve a
proactive strategy, where the objective is to maintain the hydrologic regime as close as possible to natural
conditions or a reactive strategy that aims to restore certain flow and ecosystem characteristics for previously
modified regimes (Belmar Díaz, 2013).
The strategies mentioned comprise the definition of “environmental flows”. This concept, widely used in this
scope covers the quality, quantity, and timing of water flows required to maintain the components, functions,
processes and resilience of aquatic and riparian ecosystems, as was defined in the Bisbane Declaration, 2007.
The environmental flows shall be implemented as a way to protect and restore these ecosystems, and
minimize the impacts caused by human activities, but do not necessarily require restoring the natural, pristine
flow patterns.
The environmental flows have an inherent complexity and can be defined according to various methods that
have appeared sequentially. Such methodologies can be divided into five main groups, here presented by order
of appearance, starting from the most simple: (1) Hydrologic methods; (2) Hydrologic ratings or habitat
retention methods; (3) Habitat simulation methods; (4) Holistic methods and (5) Hybrid model frameworks
(Tharme, 2003; Arthington, et al., 2006).
The hydrologic methods (1) are based on flow data series analysis and use statistics to describe river regimes
and define management targets (for example, a range of variation). Nevertheless being the lowest resolution
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methods, these methods are rapid and non-resource intensive, which makes them very appropriate at the
planning level or for preliminary flow targets definition in low controversy situations.
The hydrologic ratings methods (2) are based in changes in simple variables (for example the wetted perimeter
or maximum depth) to represent habitat factors that have a severe influence in target biota. In their turn, the
habitat simulation methods (3) integrate hydrologic and habitat simulation models that evaluate changes in
habitat indicators. These models allow the evaluation of the sustainability of such conditions attending certain
target species that can rather be a fish, a macro invertebrate or even a non-biotic component, as sediment
dragging. Thus, different scenarios of water management may be considered with the outputs from the
models. The holistic methods (4) are those with a more complexity associated, as they encompass the whole
ecosystem instead of what happens with the other methods, where only specific aspects based on target
species are considered. The Hybrid model frameworks (5) is a framework of models that are linked together to
estimate environmental impacts by integration of the above cited categories (1) to (4) (Arthington, et al.,
2006). The more complex the method applied is, the more complete is the analysis and, consequently, more
reliable are the environmental flows obtained. Recently, in the determination of environmental flows, there
are a general consensus on the need to search for flow alteration-ecological response relationships that reflect
the direct and indirect effects of hydrologic alteration on both ecological processes and ecosystems at regional
scales. These methodological approaches are gathered in the Ecological Limits of Hydrologic Alteration
approach, ELOHA (Arthington, et al., 2006; Poff, et al., 2009).
According to what was stated above, it is crucial to understand the impacts generated by the human activities
so that those impacts can be mitigated and controlled. The environmental flows appear in this scope and there
are some countries that have developed specific legislation in this context, establishing the value of the
environmental flow or the methodologies that shall be used for that effect. From these countries, France, Swiss
and United States of America can be stated. The implementation of adequate environmental flows is implicit in
the Water Framework Directive, WFD (European Commision, 2000), which was transposed to the Portuguese
legislation by the Lei da Água (Lei n.º 58/2005). The WFD is an important legislative tool that provides
mechanisms able to protect and restore degraded freshwater ecosystems. In Portugal, flow requirements are
frequently based in empirical thresholds and few studies have been using eco-hydraulic habitat simulations
(Alves & Bernardo, 2002).
Besides the Lei da Água (and the WFD), the national legislative framework relative to the environmental flows
includes:
Lei das Pescas - Lei n.º 7/2008, Capítulo II, Artigo 12.º - 15 de Fevereiro de 2008 (Lei n.º 7/2008) that
refers that the hydraulic infrastructures, independently from their use, are obliged to maintain an
exploration regime and an environmental flow, so that the modified regime assures the maintenance
of the life cycle of the aquatic species, as well as the integrity of the aquatic ecosystem. It also refers
that the environmental flow evaluation shall be assured by the owners or users allowing the
adaptation of the environmental flow in order to assure its efficiency.
7
Portaria n.º 1450/2007 - 12 de Novembro (Portaria n.º 1450/2007) that refers the mandatory
installation of the devices associated to the hydraulic infrastructures necessary to release the
environmental flows.
Decreto-Lei n.º 311/2007 - Capítulo III, Artigo 9,º - 17 de Setembro de 2007 (Decreto-Lei n.º 311/2007)
which mentions that in a concession contract for multiple-purpose projects, the concessionaries are
obliged to implement environmental flow regimes.
II.2
MEASURING THE LEVEL OF ALTERATION: APPROACHES
In the context previously mentioned, it becomes extremely important to measure the level of alteration of the
river due to the perturbation associated to river damming both in magnitude and temporal variability. This can
be done in many ways, each one of them with their inherent complexities and limitations. Below there are
some of the kinds of possible approaches to characterize the impacts of river damming (Braatne, et al., 2008):
(1)
upstream versus downstream reaches (spatial comparison);
(2)
progressive downstream patterns (spatial comparison);
(3)
dammed river versus an adjacent free-flowing or differently regulated river(s) (spatial
comparison);
(4)
pre- versus post-dam (temporal comparison);
(5)
sequential post-dam conditions (temporal comparison);
(6)
flow/sediment modifications (causal associations);
(7)
process-based modelling.
Spatial comparisons involve assessments of different reaches along a particular river or comparisons with
nearby reaches of different rivers. This type of comparison is based on the premise that river reaches situated
in the same region reveal similar ecologic characteristics as they share hydrologic and geomorphic context,
have similar climatic regimes and at least prior to damming, share some ecosystem communities
(Braatne, et al., 2008).
When it comes to temporal comparisons, they involve analyses over time that can be done with recourse to
comparative field measurements, indirect records or ecological elements from which chronological sequences
can be obtained. The assumption underlying temporal comparisons is the fact that a particular region should
reveal constant ecological patterns over time. With this in mind, the changes registered in a river course after
constructing a dam may be interpreted as the impacts caused by damming and flow regulation.
Besides their interest, these two approaches have limitations: on one hand, spatial comparisons are very
dependent on the environmental similarity within the reaches considered; on another hand, temporal
comparisons are hindered by sparse historic data. For these reasons, both types of approaches sometimes lose
applicability and then a flow/sediment modifications analysis, providing causal associations, or even
process-based modelling can be considered.
8
Once there is enough information, one of the most direct approaches consists on a spatial comparison
between river reaches upstream and downstream from a dam and reservoir (1). This is the approach most
extensively explored in this research and relates the impact of the dam with responses in the river course. In
fact, the dam results in fragmentation of the river corridor affecting both the upstream and downstream
reaches, physically and biologically. Although it affects both reaches, the upstream reach is unaltered relatively
to the fundamental fluvial processes of hydrology and sediment flux. There is, consequently, an expectation
that the upstream reach will continue to function in a natural manner, similar to the condition without the
dam. In contrast, the downstream reach is impacted by aspects such as sediment depletion and hydrologic
changes that reflect the pattern of dam operation (Braatne, et al., 2008). In spite of its wide application, it is
necessary to apply this type of comparisons sparingly, since it is limited by the fact that the selection of the
dam location is not random and they are often situated at geomorphic transitions.
Another common and also direct approach consists on a temporal comparison between pre- and post-dam
situations. This is a very reliable analysis but is strongly limited both in pre-project ecological conditions’
inventories and also in duration. The first fact is explained by the fact that many dams were constructed before
comprehensive environmental analyses were required as the ecologic awareness was not the same that exists
nowadays. This approach has a lot of potential and in this study it is applied and fully addressed in Chapter V.
Sets of hydrologic metrics were developed elsewhere to characterize the regime and the alterations
undergoing such as: The Indicators of Hydrologic Alteration - IHA - (Richter, et al., 1996) and the Indicators of
Hydrologic Alteration in Rivers - IHAR - (Martínez Santa-María & Fernández Yuste, 2006). These two sets of
metrics will be further discussed, as well as the both software that allow their calculation.
The two sets of metrics mentioned - IHA and IHAR - appear in this context, as a way to compare natural and
modified regimes or upstream and downstream reaches according to the spatial comparison aforementioned
or pre- and post-dam regimes in the temporal comparison case. These are hydrologic indexes with ecological
interest, statistically estimated based on the daily flow data available for each regime, and applied to
characterize intra-annual and inter-annual variation of hydrologic conditions. In fact, flow is a major
determinant of physical habitat in streams, which in turn is a major determinant of the distribution, abundance
and diversity of stream and river organisms (Bunn & Arthington, 2002). The ecologic interest inherent to the
mentioned indicators is the fact that they can incorporate the series of fundamental attributes of the flow
regime that can be further related to biotic components.
IHAR and IHA are two of the most widely used metrics to analyse river alteration. The IHA and IHA Version 7.1
software are presented in Chapter II.3 in an extensive way since they were used in the analysis carried out in
the present research. The IHAR are presented in Chapter II.4, in a briefer way, along with the IHARIS 2.2
software, which allows their calculation. Though both metrics are adequate for the purpose of this study, the
IHA (Richter, et al., 1996) were chosen since they come from the pioneer methodology and more widely
referred, at least in the bibliography covered, whereas IHAR consist in an adaptation of IHA. Besides that, the
IHA software developed by The Nature Conservancy is very complete and functional.
9
II.3
INDICATORS OF HYDROLOGIC ALTERATION (IHA)
II.3.1 T HE SOFTWARE
IHA Version 7.1 software, as well as IHARIS 2.2 used for IHAR, is used in order to understand the hydrologic
alterations with ecological significance. Its application provides statistical information on the regime, through
the Indicators of Hydrologic Alteration, based on daily flow data, which allows an analysis of the modifications
concerning different characteristics of the regime. Besides flow data, it also admits other types of inputs, such
as river phases, groundwater levels or lake levels. One of the surpluses of the software is the expeditious way it
provides the calculation, based on the series of daily hydrologic data, of a total of 67 parameters capable of
characterizing the flow regime. Note that for each non-existent daily data on the series, the software can
automatically fill the gap by recourse to a linear interpolation. Such parameters are subdivided into two groups,
34 Environmental Flow Components (EFC) parameters and the 33 IHA.
There are five different types of EFCs: low flows, extreme low flows, high flow pulses, small floods and large
floods. This classification is based on the fact that each one of these groups consists on a flow event
characteristic of the natural river hydrograph and ecologically meaningful. The EFCs constitute then, a suite of
non-traditional hydrologic statistics designed specifically to communicate ecologically-significant hydrologic
events in terms that non-hydrologists can understand and hydrologists can analyse.
Moreover, IHA software also returns the set of 33 IHA that will be detailed further.
Although being a very simple program, IHA gives a lot of information and allows:

Comparing characteristics of the regime before and after the perturbation (a weir, a dam or other type
of infrastructure within the river course), and therefore analysing the impact caused by that
modification.

Implementing the "Range of Variability Approach" (RVA), that consists on defining categories liable of
indicating how adjusted the post-impact parameters are to the pre-impact parameters distribution.
Thus, different kinds of analysis can be carried out:

IHA (single period); IHA (pre- and post-impact comparison); RVA (range of variation approach); trend
analysis (no impact date defined).
Besides displaying different sorts of approaches, the program also comprises two types of statistics: parametric
and non-parametric. The first one is associated with mean values whereas the non-parametric refers to median
values. It is recommended to use a non-parametric analysis to attend to the possible skewed character of the
distribution. Once the daily series are included, the software IHA Version 7.1 returns the parameters in the
form of tables and graphics. These outputs are discriminated in Table II for a non-parametric analysis, either for
single period and pre- and post-impact comparison (or upstream and downstream in other cases).
10
Table II - Outputs returned by IHA Version 7.1 software (for non-parametric analysis).
Single period analysis
Tables
Annual summaries table (“ann”)
Scorecard table (“sco”)
Regression table (“lsq”)
Percentile table (“pct”)
EFC daily table (“daily efcs”)
Flow duration curve data table (“fdc”)
Graphics
IHA parameters annual data
EFC parameters annual data
Daily data
Flow duration curves
Pre- and post-impact comparison analysis
Annual summaries table
Scorecard table
RVA table
Box-and-Whisker table
Regression table
Percentile table
EFC daily table
Flow duration curve data table
IHA parameters annual data
EFC parameters annual data
Hydrologic alteration
Monthly averages
Daily data
Flow duration curves
II.3.2 T HE INDICATORS
IHA are metrics obtained statistically and that encompass the five attributes inherent of the flow regime
mentioned before: magnitude, frequency, timing, duration and rate of change. They are thirty-three indicators
in total and may be organized into five groups, as shown in Table III. Each of these indicators can be obtained
by a statistical analysis of the set of daily flow data, which is described in Table VI. The statistical analysis can be
either parametric or non-parametric, and as a non-parametric approach was chosen, the description in
question is consistent with this kind of analysis.
Table III (1/2) - Indicators of Hydrologic Alteration, for one year of daily records.
IHA group
1. Magnitude of monthly
water conditions
Flow regime characteristics
Magnitude/
timing
Indicators of Hydrologic Alteration, IHAi
1
IHA1 to IHA12 Mean value for each calendar month
IHA13 Annual minima, 1-day mean
IHA14 Annual minima, 3-day means
IHA15 Annual minima, 7-day means
IHA16 Annual minima, 30-day means
IHA17 Annual minima, 90-day means
2. Magnitude and duration
of annual extreme water
conditions
Magnitude/
duration
IHA18 Annual maxima, 1-day mean
IHA19 Annual maxima, 3-day means
IHA20 Annual maxima, 7-day means
IHA21 Annual maxima, 30-day means
IHA22 Annual maxima, 90-day means
IHA23 Number of zero-flow days
IHA24 Base flow index
3. Timing of annual extreme
water conditions
Timing
IHA25 Julian date of each annual 1-day minimum
IHA26 Julian date of each annual 1-day maximum
11
Table III (2/2) - Indicators of Hydrologic Alteration, for one year of daily records.
IHA group
Flow regime characteristics
4. Frequency and duration of
high/low pulses
Magnitude/
frequency/
duration
Indicators of Hydrologic Alteration, IHAi
IHA27 Number of low pulses
1
IHA28 Mean duration of low pulses (days)
IHA29 Number of high pulses
1
IHA30 Mean duration of high pulses (days)
5. Rate and frequency of
water condition changes
Frequency/
rate of change
IHA31 Rise rates
IHA32 Fall rates
IHA33 Number of hydrologic reversals
1
In the case of the non-parametric study, instead of mean values, median values are used in order to take into account the
skewness of the distribution, especially at minor time scales.
Table IV - Definition of the Indicators of Hydrologic Alteration for one year of daily records.
Indicator of Hydrologic Alteration, IHAi
IHA1 to IHA12
IHA13
Median flow value for each calendar
month
Annual minima, 1-day
IHA14 Annual minima, 3-day means
IHA15 Annual minima, 7-day means
IHA16 Annual minima, 30-day means
IHA17 Annual minima, 90-day means
IHA18 Annual maxima, 1-day
IHA19 Annual maxima, 3-day means
IHA20 Annual maxima, 7-day means
IHA21 Annual maxima, 30-day means
IHA22 Annual maxima, 90-day means
Median daily flow for each calendar month
Minimum flow value of the year
Minimum value for the mean daily flow of 3 consecutive days
of the year
Minimum value for the mean daily flow of 7 consecutive days
of the year
Minimum value for the mean daily flow of 30 consecutive days
of the year
Minimum value for the mean daily flow of 90 consecutive days
of the year
Maximum flow value of the year
Maximum value for the mean daily flow of 3 consecutive days
of the year
Maximum value for the mean daily flow of 7 consecutive days
of the year
Maximum value for the mean daily flow of 30 consecutive
days of the year
Maximum value for the mean daily flow of 90 consecutive
days of the year
IHA23 Number of zero-flow days
Number of days in the year when the daily flow is zero
IHA24 Base flow index
(Annual minima, 7 - day means) / Mean annual flow
Order number of the day of the year when the minimum flow
was registered
Order number of the day of the year when the maximum flow
was registered
Number of times in a year that the flow is lower than the 25%
percentile of the flows of the period in analysis
IHA25 Julian date of each annual 1-day minimum
IHA26 Julian date of each annual 1-day maximum
IHA27 Number of low pulses
IHA28 Median duration of low pulses (days)
IHA29 Number of high pulses
IHA30 Median duration of high pulses (days)
IHA31 Rise rates
IHA32 Fall rates
IHA33 Number of hydrologic reversals
12
Description of the indicator
(for a non-parametric analysis)
Median of the duration of the low pulses
Number of times in a year that the flow is higher than the 75%
percentile of the flows of the period in analysis
Median of the duration of the high pulses
Median of all positive differences between consecutive daily
values
Median of all negative differences between consecutive daily
values
Number of times that the tendency of the daily flow changes
Table V provides an appraisal of the main influences of IHA groups in the ecosystem and biota (mainly based in
The Nature Conservancy, 2009).
Table V - Main influences of each IHA group on the ecosystem properties and biotic components (adapted from The
Nature Conservancy, 2009).
IHA group
Ecosystem influences
Habitat availability for aquatic organisms
Soil moisture availability for plants
1. Magnitude of
monthly water
conditions
Availability of water for terrestrial animals
Availability of food/cover for furbearing mammals
Reliability of water supplies for terrestrial animals
Access by predators to nesting sites
Influences on water temperature, oxygen levels, photosynthesis
Balance of competitive, ruderal, and stress- tolerant organisms
Creation of sites for plant colonization
Structuring of aquatic ecosystems by abiotic vs. biotic factors
Structuring of river channel morphology and physical habitat conditions
2. Magnitude and
duration of annual
extreme water
conditions
Soil moisture stress in plants
Dehydration in animals
Anaerobic stress in plants
Volume of nutrient exchanges between rivers and floodplains
Duration of stressful conditions such as low oxygen and
environments
concentrated chemicals in aquatic
Distribution of plant communities in lakes, ponds, floodplains
Duration of high flows for waste disposal, aeration of spawning beds in channel sediments
Compatibility with life cycles of organisms
3. Timing of annual
extreme water
conditions
Predictability/avoidability of stress for organisms
Access to special habitats during reproduction or to avoid predation
Spawning cues for migratory fish
Evolution of life history strategies, behavioural mechanisms
Frequency and magnitude of soil moisture stress for plants
Frequency and duration of anaerobic stress for plants
4. Frequency and
duration of high and
low pulses
Availability of floodplain habitats for aquatic organisms
Nutrient and organic matter exchanges between river and floodplain
Soil mineral availability
Access for waterbirds to feeding, resting, reproduction sites
Influences on bedload transport, channel sediment textures, and duration of substrate disturbance
(high pulses)
5. Rate and
frequency of water
condition changes
Drought stress on plants (falling levels)
Entrapment of organisms on islands, floodplains (rising levels)
Desiccation stress on low-mobility streamedge (varial zone) organisms
13
II.4
INDICATORS OF HYDROLOGIC ALTERATION IN RIVERS (IHAR)
The IHA were the indicators considered in the present study. However, it becomes pertinent to present the
Indicators of Hydrologic Alteration in Rivers - IHAR - as well, in order to provide a global overview of another
set of indicators which could be used for the analyses. This chapter addresses the IHAR, which can be obtained
with recourse to software named IAHRIS 2.2. It was developed by Martínez Santa-María & Fernández Yuste,
2010 in order to obtain the hydrologic characteristics of the natural regime and evaluate the hydrologic
How do we evaluate the alteration of the
flow regime?
How to characterize the
natural regime?
alteration. The methodology is summarized in Figure 1.
Select the most environmentally significant components of the hydrologic regime
Define the most suitable parameter to measure each of the chosen aspects
Obtain the values of the parameters for the
natural regime: reference condition
Obtain the values of the parameters for the
altered regime: actual condition
Compare the reference condition with the actual state: Define the partial IHA
Systematize and simplify: Global alteration indicators
Evaluation of the hydrologic level
Environmental diagnosis
Figure 1 - Main stages of the methodology proposed (adapted from Martínez Santa-María & Fernández Yuste, 2010).
The IHAR are based on 19 parameters that are divided into three categories: the habitual data, the extreme
data relative to floods and the extreme data relative to droughts. These parameters are summarized in
Table VI.
14
Table VI - Parameters for the characterization of the flow regime (adapted from Martínez Santa-María & al., 2010).
Regime component
Habitual
data
Monthly or
annual
volumes
Daily flow
Aspect
Magnitude
Average of the annual volumes
Variability
Difference between the maximum and the
minimum monthly volume along the year
Seasonality
Month with the maximum and the minimum
water volume along the year
Variability
Magnitude
and
frequency
Maximum
values of the
daily flows
(Floods)
Variability
Duration
Extreme
data
Seasonality
Minimum
values of the
daily flows
(Droughts)
Parameter
Magnitude
and
frequency
Duration
Seasonality
Difference between the average flows
associated to the percentiles 10% and 90%
Average of the maximum daily flows along the
year
Effective discharge
Connectivity discharge
Flushing flood
Coefficient of variation of the maximum daily
flows along the year
Coefficient of variation of the ordinary floods
series
Maximum number of consecutive days
in the year with flow higher than Q5%
Average number of days in the month
with flow higher than Q5%
Average minimum daily flows along the year
Ordinary drought discharge
Coefficient of variation of the minimum daily
flows along the year
Coefficient of variation of the ordinary
droughts series
Maximum number of consecutive days in the
year with flow lower than Q95%
Average number of days in the month with a
daily flow equal to zero
Average number of days in the month
with flow lower than Q95%
Wet year
Normal year
Dry year
Weighted year (P1)
Wet year
Type of
Normal year
year
Dry year
Weighted year (P2)
Wet year
Type of
Normal year
year (P3)
Dry year
Type of
year
Q10%-Q90% (P4)
Qc (P5)
QGL (P6)
QCONEC (P7)
Q5% (P8)
CV (Qc) (P9)
CV (Q5%) (P10)
Flood duration (P11)
12 values (one for each
month) (P12)
Qs (P13)
Q95% (P14)
CV (Qs) (P15)
CV (Q95%) (P16)
Droughts duration (P17)
12 values (one for each
month) (P18)
12 values (one for each
month) (P19)
Note: The x% percentile indicates the value below which a given percentage x of observations in a group of observations fall.
15
Table VII - Indicators of Alteration in Rivers for contemporary regimes (adapted from Martínez Santa-María & Fernández
Yuste, 2010).
Aspect
IHAR i
Magnitude
Habitual
Values
Variability
Seasonality
Magnitude and frequency
Floods
Variability
Duration
Seasonality
Magnitude and frequency
Variability
Droughts
Duration
Seasonality
1
IHAR 1
IHAR 2
IHAR 3
IHAR 4
IHAR 5
IHAR 6
IHAR 7
IHAR 8
IHAR 9
IHAR 10
IHAR 11
IHAR 12
IHAR 13
IHAR 14
IHAR 15
IHAR 16
IHAR 17
IHAR 18
IHAR 19
IHAR 20
IHAR 21
Description
Magnitude of annual volumes
Magnitude of monthly volumes
Habitual variability
Extreme variability
Seasonality of maximum values
Seasonality of minimum values
Magnitude of the maximum floods
Magnitude of the effective discharge
Magnitude of the connectivity discharge
Magnitude of the flushing floods
Variability of the maximum floods
Variability of the flushing floods
Floods duration
1
Floods seasonality
Magnitude of the extreme droughts
Magnitude of the habitual droughts
Variability of the extreme droughts
Variability of the habitual droughts
Droughts duration
1
Number of days with null flow
1
Droughts seasonality
Source
parameter
P1
P4
P2
P3
P5
P6
P7
P8
P9
P10
P11
P12
P13
P14
P15
P16
P17
P18
P19
with 12 values, one for each month
The 21 IHAR exposed are based on a comparison between natural and modified regimes according to the
respective parameters, as the previous table presents.
16
CHAPTER III. CASE STUDIES AND BASIC DATA
III.1
CASE STUDIES
The next step consisted of the choice of case studies within the spectrum of dams existing in mainland
Portugal. This procedure was particularly difficult as many of the Portuguese dams are for irrigation purposes,
especially in the south of the country, meaning there is no flow data available for the river reaches they respect
to. With this constraint in mind, the selection of case studies was done within the set of Portuguese
hydroelectric dams, considering those with sufficient flow records, liable to perform the characterization.
This type of dams (hydroelectric) consists on infrastructures where electric energy is produced by transforming
the potential energy of the rivers and lakes water. For that purpose, the water stored in the reservoirs created
by such infrastructure is directed, through a hydraulic circuit, normally constituted by a tunnel or a penstock, to
a power plant where moving water boosts the blades of a hydraulic turbine. Once this takes place, the rotation
induced by the turbine to the rotor causes an induction phenomenon, which leads to high electrical currents in
the fixed piece of the alternator (stator). The voltage of the electricity produced is raised through transformers
to a voltage level more appropriate to the transmission of electricity over long distances (Faria, 2003). The
amount of electricity produced depends on the potential energy of the water, which depends in its turn on the
heights of water, or the head, and the volume of water flowing.
Dam
Hydraulic
energy
Turbine
Mechanic
energy
Alternator
Electric
energy
Figure 2 - Scheme of hydraulic powerhouse functioning.
Among the hydropower dams universe, there are different types of facilities: run-of-river, reservoir and
pumped-storage. Run-of-river facilities are those where the dam does not create a large reservoir upstream, as
the inflows are held for short periods of time or even sent directly to the turbine. This means that the storage
capacity is very small or inexistent, being the energy generated by the natural flow of water. With this in mind,
once the flow leaves the power plant, water is returned to the river without significantly altering flow or water
level that would exist prior to the construction of the dam. On the contrary, reservoir types are characterized
for flooding large areas of land, creating a reservoir upstream the dam. Finally, pumped-storage facilities are
those which usually have two reservoirs - an upper one, that works like the ones from the facilities described
previously, and a lower one. They use reversible turbines to pump water back to the upper reservoir, allowing
the water to be available again to re-generate energy, which becomes a solution particularly useful in
consumption peak hours (Bonsor, 2008).
17
In this context, nine river reaches affected by an upstream hydropower dam and having daily flow data were
selected (Figure 3).
N
Figure 3 - Case studies: (1) Alto Lindoso, (2) Touvedo,
(3) Vilarinho das Furnas, (4) Paradela, (5) Vilar, (6)
Caldeirão, (7) Fronhas, (8) Cabril and (9) Pracana.
Such case studies consist on hydroelectric dams, being each one of them part of a specific plant which in its
turn is included in a hydroelectric system. The nine cases are divided into the following three systems:
Cávado-Lima, Douro and Tejo-Mondego. Each of them has particular characteristics and behaviour and
different exploitation modes. A brief summary of each dam and of the systems where they are incorporated is
presented below so that the differences between them can be more understandable.
Starting by the first four case studies (1, 2, 3 and 4), they are all part of the nine dams included in Cávado-Lima
system, which comprises the watersheds of the two rivers with the same name - Cávado River (Cávado,
Rabagão and Homem Rivers) and Lima River.
Case study number 1, Alto Lindoso (Figure 4), has presently the highest installed capacity in Portugal. It is
located in Lima River, a few thousand of meters from the border with Spain and approximately 17 km upstream
there is Touvedo dam, the case study number 2.
Case number 2, Touvedo (Figure 4), is used for production of energy as well, but it also has a leading role with
regard to the regulation of the high flows turbined by Alto Lindoso dam. Touvedo is considered a run-of-river as
its storage capacity is really small when compared with the inflow volume. Alto Lindoso powerhouse is located
7 km downstream the dam, while Touvedo powerhouse is contiguous to the dam. However, in both
powerhouses the flows are turbined to the same river where the dams are located - the Lima River.
18
N
Alto Lindoso dam
Alto Lindoso powerhouse
Touvedo dam
2 km
Legend:
Figure 4 - Case studies 1 - Alto Lindoso (left) and 2 - Touvedo (right) (Comissão Nacional Portuguesa das Grandes
Barragens).
Case study number 3, Vilarinho das Furnas, is also part of the Cávado-Lima system, being is located in Homem
River, in Cávado basin. The design of the dam begun in the 1950s with terrain surveys and test drilling; the
construction was completed in 1972. Upstream there used to be a village also named Vilarinho das Furnas that
was submerged by the reservoir created by the dam; the ruins of the village can be partially observed during
very low water periods. In this case, the water stored in the reservoir is diverted through a tunnel with 6800 m
length that crosses Gerês Mountain and that continues by a penstock with 890 m length. This circuit connects
the dam to the powerhouse. Both the dam and the powerhouse are schematically located in Figure 5.
19
N
Vilarinho das Furnas dam
Vilarinho das Furnas powerhouse
1 km
Legend:
Figure 5 - Case study 3 - Vilarinho das Furnas.
Case study number 4, Paradela, is also located in Cávado basin, but in Cávado River. The dam scheme includes
a hydraulic circuit that diverts water to a reservoir located downstream, in the confluence of Cávado and
Rabagão Rivers. From this reservoir, water is diverted to Vila Nova powerhouse, as represented in the map
included in Figure 6. The Paradela dam includes a pit discharger, a frontal discharger and a spillway. The
discharges from pit discharger return to the Cávado River, about 120 meters downstream the dam, while the
discharges from the frontal spillway are diverted to Sela stream, tributary of the right bank of Cávado River. In
addition to the dam, the scheme also includes a set of seven complementary weirs which divert water from
tributaries of the right bank of Cávado River to the main reservoir.
Another system working in the North of Portugal is Douro system, which includes ten facilities in Douro
watershed, from which seven are situated in national area and the rest are included in the Spanish or in the
borderer territory. From the overall case studies, only number 5, Vilar, is part of this system. The dam is located
in Távora River, a tributary at the left bank of Douro River. The scheme started operating in 1965. Besides the
dam, it includes the underground powerhouse of Tabuaço connected to the dam by a penstock with 15,6 km
length. The tail race of Tabuaço powerhouse, meaning the structure that carries water away from the turbine
and returns it to the river, is located 2 km downstream. Figure 7 illustrates this scheme.
20
N
Paradela dam
Vila Nova
powerhouse
1 km
N
Confluence of
Douro and Távora
Rivers
Tabuaço powerhouse
Vilar dam
2 km
Legend:
Figure 6 (up) - Case study 4 - Paradela (EDP) and Figure 7 (down) - Case study 5 - Vilar (Comissão Nacional Portuguesa das
Grandes Barragens).
21
Besides the two systems mentioned above - Cávado-Lima and Douro - there is also the Tejo-Mondego system
which includes the schemes from Tejo and Mondego watersheds in a total of eight. Case studies number 6, 7, 8
and 9 are part of that system.
Case study number 6 is situated near Guarda, in Caldeirão stream, a tributary of the right bank of Mondego
River. It was constructed for multiple purposes, including water supply, irrigation and energy production. The
scheme comprehends a weir which diverts water from Mondego River to Caldeirão reservoir through a tunnel
with 2,67 km; a dam located 900 m upstream the confluence between Caldeirão stream and Mondego River;
and a powerhouse located 650 m upstream the same confluence (Figure 8). The turbined flows are delivered
just downstream the powerhouse in Mondego River. The discharges from the dam, on another hand, are
delivered downstream in Caldeirão stream, while the ones coming from the weir are delivered in Mondego
River, downstream the weir.
N
Caldeirão powerhouse
Confluence of Caldeirão and
Mondego Rivers
Caldeirão dam
200 m
Legend:
Figure 8 - Case study 6 - Caldeirão (EDP, 2009).
Case study number 7, Fronhas, is also part of Tejo-Mondego system. This is a very particular scheme for
interbasin transfer, meaning it diverts water from Alva River to the Aguieira reservoir located in another river
course, namely in Mondego River. The water diverted is turbined in Aguieira powerhouse, inaugurated in 1981.
The diversion tunnel between Fronhas and Aguieira is 8,2 km long. Both the dam and the powerhouse are
schematically shown in Figure 9.
22
N
Aguieira powerhouse
Confluence of Alva and Mondego Rivers
Fronhas dam
2 km
Legend:
Figure 9 - Case study 7 - Fronhas (Comissão Nacional Portuguesa das Grandes Barragens).
Located in Zêzere River, case number 8, Cabril (Figue 10), has a dam with 132 m high, the highest in Portugal.
The powerhouse is located in the base of the dam.
N
Cabril dam
1 km
Legend:
Figure 10 - Case study 8 - Cabril (Comissão Nacional Portuguesa das Grandes Barragens).
23
Finally, case study number 9, Pracana (Figure 11) is located in Ocreza River, a tributary at the right bank of Tejo
River. The scheme includes a dam and a central located in its base.
N
Pracana dam
500 m
Confluence of
Ocreza and Tejo Rivers
Legend:
Figure 11 - Case study 9 - Pracana (Comissão Nacional Portuguesa das Grandes Barragens).
From the brief summary of the nine case studies, it can be concluded that each case is a case, with very specific
features and exploitation modes. In fact, case number 2 is of the run-of-river type while all other cases have
reservoirs. In cases number 3, 6 and 7 water is transferred from a given river to a different one, while in cases
number 1, 2, 4, 5, 8 and 9 the water is delivered to the same river where the dam is located. Among the cases
without water transfer between rivers, the cases 2, 8 and 9, have toe of the dam powerhouses while the
remaining have relatively long hydraulic circuits. These last ones can be divided into those where the water is
delivered directly to the river (case studies 1 and 5) and those where the water is delivered to a reservoir (case
study 4). Table VIII contains a synthesis of what was mentioned above along with some additional information
considered relevant.
Table VIII - Characteristics of the case studies (1/2).
Dam
Case study
Powerhouse
System
Main
watershed
River
Watershed
area (km²)
Uses
Starting operation
date
Installed
capacity
(MW)
1
Al to Li ndos o
Cá va do‑Li ma
Li ma
Li ma Ri ver
1525
Energy
1992
630
2
Touvedo
Cá va do‑Li ma
Li ma
Li ma Ri ver
1700
Energy/i rri ga tion/fl ood protection
1993
22
3
Vi l a ri nho da s
Furna s
Cá va do‑Li ma
Cá va do
Homem Ri ver
77
Energy
1972 a nd 1987
125
4
Pa ra del a
Cá va do‑Li ma
Cá va do
Cá va do Ri ver
168
Energy
1956¹/1958²
54
5
Vi l a r
Douro
Douro
Tá vora Ri ver
359
Energy
1965
58
6
Ca l dei rã o
Tejo-Mondego Mondego
Ca l dei rã o Strea m
38
Wa ter s uppl y/i rri ga tion/energy
1993¹/1994²
40
7
Fronha s
Tejo-Mondego Mondego
Al va Ri ver
652
Energy
1985
-
8
Ca bri l
Tejo-Mondego
Tejo
Zêzere Ri ver
2340
Energy
1954
108
9
Pra ca na
Tejo-Mondego
Tejo
Ocreza Ri ver
1410
Energy
1944/50 a nd 1993³
41
24
Table VIII - Characteristics of the case studies (2/2).
With water transfer between
rivers
Reservoir
Case study
1 Al to Li ndos o
Without water transfer between rivers
Run-of-river or
With storage
Toe of the dam
with small storage To a reservoir Directly to a river
capacity
powerhouse
capacity
Hydraulic circuit relatively long
Water delivered
directly to the river
Water delivered to a
reservoir
4
X
X
2
Touvedo
3
Vi l a ri nho
da s Furna s
X
X
X
4
Pa ra del a
X
5
Vi l a r
X
6
Ca l dei rã o
X
7
Fronha s
X
8
Ca bri l
X
X
9
Pra ca na
X
X
X
X
X
X
X
Dates according to: 1EDP - Energias de Portugal; 2CNPGB - Comissão Nacional Portuguesa das Grandes Barragens; 3This facility
was disabled in 1980, having re-entered into operation in 1993, after a huge renovation; 4Once the outflow data addresses to the
river section immediately downstream the powerhouse, this case study has the same behavior as if it had a toe of the dam
powerhouse.
III.2
BASIC DATA FOR UPSTREAM VERSUS DOWNSTREAM COMPARISON
In order to proceed with the characterization of the alteration in the flow regime of a river due to a specific
dam, it is essential to have sufficient and valid flow data for the river reach where that dam is located. This is
most of the times the main limitation of this kind of studies, as often there are no flow records available or
sometimes when they exist, they are not continuous.
In this case, daily flow data was obtained from two different sources: the National Information System for
Water Resources, SNIRH (Sistema Nacional de Informação de Recursos Hídricos) and the EDP (Energias de
Portugal SA). The first one is an online database (http://snirh.pt) of the Portuguese Environment Agency (APA).
The flow data from EDP was provided directly by that company. The additional information regarding the
general layouts of the schemes is available online (http://www.edp.pt/).
As the envisaged characterization is based on a statistical analysis across time, it is crucial to have long enough
flow data series so that each sample can be considered representative of the magnitude and natural variability
of the flow regime, thus enabling consistent and coherent conclusions. Therefore, within the set of daily flow
data available for each case study, only years with more than 300 days with records were considered. It should
be stressed that EDP provides continuous data from 2004 to 2011 while the data from SNIRH has gaps. The
daily flow data available for each case study and each year is characterized in the table below, where the
numbers represent the quantity of existent daily records. The years that match the criteria of having more than
300 records per year are highlighted in blue.
25
Table IX - Years considered for each case study.
Case study Flow conditions 1993 1994 1995 1996
Natural
1
Modified
Natural
275 365 365 366
2
Modified
Natural
3
Modified
Natural
4
Modified
Natural
5
Modified
Natural
6
Modified
Natural
7
Modified
Natural
8
Modified
Natural
9
Modified
1997 1998 1999
22 54 156
54 156
365 365 365
56 156
99
53
2000
269
270
366
269
2001
326
329
365
328
2002
301
303
365
300
2003
333
335
333
335
2004
347
347
339
339
366
366
269 177 279 328 321 333 332
273 177 289 334 323 336 334
366
366
366
366
366
366
366
366
366
366
2005
352
350
347
347
365
365
348
348
365
365
365
365
365
365
365
365
365
365
2006
354
344
346
346
365
365
339
340
365
365
365
365
365
365
365
365
365
365
2007
333
333
341
341
365
365
342
342
365
365
365
365
365
365
365
365
365
365
2008
330
330
328
328
366
366
325
325
366
366
366
366
366
366
366
366
366
366
2009
304
304
335
335
365
365
335
335
365
365
365
365
365
365
365
365
365
365
2010
356
356
352
357
365
365
351
356
365
365
365
365
365
365
365
365
365
365
2011
360
360
358
359
365
365
357
358
365
365
365
365
365
365
365
365
365
365
Based on the years highlighted in blue, additional information was obtained. EDP provides inflow and outflow
data, being outflow data organized into turbined (T), discharged (D), ecological (E), and pumped daily flows.
When identifying from that data the parcels that, in each case study, represent the natural flow regime (inflows
to the reservoirs) and the modified flow regime immediately downstream the dam it is important to have in
mind the previous organization, as well as the layout of the scheme, with emphasis for the powerhouse
location relatively to the dam or the existence of water transfers between reservoirs or watersheds. Based on
the combination of the flow data with the layout and exploitation mode of each case study, the information
systematized in Table X was obtained.
Table X - Natural and modified modulus.
Case study
Data source
Qmod Natural Qmod Modified
(m /s)
3
(m /s)
3
1
Alto Lindoso
EDP through SNIRH (02H/01A)¹
39,85
37,84
2
Touvedo
EDP through SNIRH (03G/01A)¹
49,65
43,94
3 Vilarinho das furnas
EDP (D+E)
5,43
0,34
4
Paradela
EDP (D+E)
6,52
0,25
5
Vilar
EDP (D)
3,22
0,14
6
Caldeirão
EDP (D)
2,68
0,02
7
Fronhas
EDP through SNIRH (12I/01A)¹
16,27
3,33
8
Cabril
EDP (T+D)
32,64
33,68
9
Pracana
EDP (T+D)
13,89
13,80
1
Code corresponding to the EDP station, as defined in SNIRH.
In the table, Qmod represents the modulus either of the inflows to the dam which are considered to represent
the natural or non-modified flow regime (Qmod Natural) or of the modified flow regime, immediately downstream
the dam (Qmod Modified).
26
The respective modulus were obtained with the software already mentioned - IHA Version 7.1 - meaning they
incorporate the missing records that were automatically filled by linear interpolations. In five of the case
studies - Vilarinho das Furnas, Paradela, Vilar, Caldeirão and Fronhas (highlighted in bold) - the values of the
modulus show a very clear difference between natural and modified regimes. This suggests that such dams
modify greatly the natural flows of the rivers where they are located; sometimes even almost drying the river
reaches downstream. The fact that in Cabril case study the modified modulus is slightly higher than the natural
one may be explained by the great dimension of its watershed plan.
According to the characteristics of the case studies previously mentioned, since Alto Lindoso powerhouse is
located a few kilometres downstream the dam, it was expected that this case study would present a noticeable
difference, in terms of modulus, between natural flows and modified flows immediately downstream the dam,
which does not happen. This situation can be explained as the only flow data available in SNIRH that could be
used to characterize the outflows also incorporate the turbined flows. Therefore, the analysis carried out for
this case study compares the natural flows to the modified flows downstream the powerhouse and not
immediately downstream the dam.
III.3
COMPLEMENTARY INFORMATION ON VILARINHO DAS FURNAS CASE STUDY
As pointed out before, Vilarinho das Furnas scheme diverts water from Homem River, where the dam is
located, to Caniçada reservoir, where the powerhouse is installed. For this reason, immediately downstream
the dam of Vilarinho das Furnas there are only discharged flows and environmental flows.
Contradicting the usual lack of data, Vilarinho das Furnas case study has the particularity of having data
accessible in SNIRH from a near stream gauging station (S.G.S.) named Covas (03H/04H). This station is located
downstream Vilarinho das Furnas dam and has daily flow data since 1955 until 2004, which includes a pre-dam
period (from 1955 to 1972) and a post-dam period (from 1972 onwards). Figure 12 shows the schematic
location of the S.G.S. (geographic coordinates 41.724º N and -8.298º W, for latitude and longitude,
respectively) and of the location of the dam.
Based on the daily records at Covas stream gauging station, a more comprehensive analysis can be carried out
for this scheme and its subsequent impacts on the river flow. Among other aspects, such analysis will include
the comparison of results based on the EDP flow data and on the SNIRH flow data. This issue will be further
detailed in Chapter V.
27
N
Vilarinho das Furnas dam
Covas Stream Gauging Station
Vilarinho das Furnas powerhouse
Confluence of Homem and Cávado Rivers
2 km
Legend:
Figure 12 - Vilarinho das Furnas case study and Covas stream gauging station.
Also related with the additional analysis performed for Vilarinho das Furnas, another stream gauging station
with records given by the SNIRH was used, as further justified: the S.G.S. of Fragas da Torre located in Paiva
River (40.941º N and -8.180º W, for latitude and longitude, respectively) which is a tributary of Douro River in
its left bank. The daily flow data available at such station (from 1946 to 2006) was adopted to reconstruct the
natural daily flow regime of Covas after 1972, that is, after the construction of Vilarinho das Furnas dam. As it
was already mentioned, Covas gauging station has flow records available for the years before and after
Vilarinho das Furnas dam construction (1972), being these last modified flows.
The analysis carried out for Vilarinho das Furnas case study comprehended two additional aspects. In the first
one the daily records at Covas stream gauging station were used to validate the analysis based on the EDP
data. In the second aspect, the natural flow regime at the river section of Covas after the construction of
Vilarinho das Furnas dam was reconstructed based on the transposition of the daily flow records at Fragas da
Torre. The reconstructed natural flow regime was then compared with the modify flow regime. These two
aspects will be covered more extensively in Chapter V.
28
CHAPTER IV. IHA APPLICATION: SPATIAL COMPARISON
IV.1
INTRODUCTION
As described in Chapter II, IHA Version 7.1 provides a large amount of information, from which the IHA were
selected. In fact, the software could be utilized to provide much more indicators than those of IHA which would
complicate the analysis unnecessarily, as the IHA comprises already the required information to address the
comparison either between unchanged flow and changed flow regimes or among case studies, considering
their inherent characteristics. However, the IHA values need to the synthesized and systematized in order to
become more readable.
In the next section - Chapter IV.2 - case study 1 - Alto Lindoso is used as an example to describe extensively the
way the rough data is introduced in the software and how the results obtained are analysed and synthetized.
Different methodologies and approaches were applied for that purpose. The general results obtained for all the
case studies according to those methodologies are presented in Appendix A and discussed in Chapter IV.3.
IV.2
PRESENTATION OF THE PROCEDURE BASED ON A LTO LINDOSO CASE STUDY
As the procedure applied to the nine case studies was the same it was decided to exemplify it based on a case
study. For that purpose, the case study number 1 - Alto Lindoso was selected.
The first step was to collect and organize the daily flow data for the period of analysis (see Table IX), as
exemplified in Table XI. As it was previously mentioned, the natural flow regime was assigned to the inflows to
the reservoir and the modified flow regime to the outflows that are delivered to the river immediately
downstream of the dam.
Table XI - Example, based on Alto Lindoso case study, of the data to introduce in IHA version 7.1. natural flow regime.
Date
01-01-2001
03-01-2001
04-01-2001
05-01-2001
06-01-2001
08-01-2001
09-01-2001
10-01-2001
11-01-2001
12-01-2001
13-01-2001
3
Inflow (m /s)
499,82
451,56
373,2
920,14
FALSE
174,53
240,66
239,3
311,14
FALSE
152,99
(…)
Date
3
Inflow (m /s)
(…)
25-12-2011
22,91
26-12-2011
30,52
27-12-2011
17,93
28-12-2011
24,19
29-12-2011
18,98
30-12-2011
17,05
31-12-2011
23,02
The values presented in the previous table respect to the natural flow regime; the format for the modified flow
regime is the same. As it was mentioned, when selecting the period of analysis, some days do not have flow
29
records. The missing data are automatically filled by the program based on linear interpolations between the
flows that immediately precede and succeed the period without data. Besides the days with no records, there
are those only with inflows and no outflows and contrariwise. In these cases, the days without data are filled
with “FALSE” so that the software can recognize the gap as missing data, instead of considering it equal to zero.
These are the cautions that should be kept in mind when preparing the data to include in the software.
By applying the software to the input data a considerable amount of output data is returned. The results, from
the output data, that are relevant for both the characterization of each case study and the comparison among
case studies are presented next, in the same exact format as they are presented by the software. Although
there is an option available in the software that allows comparing directly the two regimes - the natural and
the modified - it was chosen to run separately the software for those regimes and then to compare the
indicators thus obtained. This option stems from the fact that the analysis carried out is not temporal but
spatial instead, as it was stated in Chapter II.2. Thus, instead of pre- and post-dam flows - temporal comparison
- the present case refers to upstream and downstream flows concerning the same period of time - spatial
comparison. The results obtained for the natural regime in Alto Lindoso are presented in Table XII, for the
period of analysis, and in Table XIII, when grouped by percentiles. In the first table “Coeff. of Disp.” means
coefficient of dispersion. The units of the values are clarified as well in the same table.
Table XII - Example, based on Alto Lindoso case study, of the results given by IHA7 software for the natural flow regime
for the period of analysis (reproduced as given by the software): non-parametric IHA scorecard (“sco”).
Non-Parametric IHA Scorecard
1 entrada
Period of Analysis: 2001-2011 ( 11 years)
NormalizationFactor
1
Mean annual flow
39,85
Non-Normalized Mean Flow
39,85
Annual C. V.
1,69
Flow predictability
0,44
Constancy/predictability
0,49
% of floods in 60d period
0,32
Flood-free season
45
Medians
Parameter Group #1
January
February
March
April
May
June
July
August
September
October
November
December
30
34,15
49,01
43,12
26,32
15,96
13,16
13,78
7,22
6,535
15,06
28,79
30,52
Parameter Group #2
1-day minimum
3-day minimum
7-day minimum
30-day minimum
90-day minimum
1-day maximum
3-day maximum
7-day maximum
30-day maximum
90-day maximum
Number of zero days
Base flow index
0,43
1,573
2,659
4,801
8,185
373,1
317,6
244,2
137,1
87,84
0
0,07111
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
days
-
4,372
1,574
1,035
0,5644
0,4042
0,787
0,6688
0,7492
0,6388
0,7071
0
1,049
Parameter Group #3
Date of minimum
Date of maximum
253
21
days
days
0,112
0,2896
Parameter Group #4
Low pulse count
Low pulse duration
High pulse count
High pulse duration
Low Pulse Threshold
High Pulse Threshold
24
2
9
2
9,55
43,85
days
days
0,2917
0,25
0,4444
0,5
Parameter Group #5
Rise rate
Fall rate
Number of reversals
3,7
-4,36
188
m 3/s
m 3/s
-
0,373
-0,3716
0,09574
Coeff. of Disp.
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
2,943
0,9678
0,9956
1,364
0,7149
0,6648
0,5254
0,8982
0,6128
2,201
1,091
1,944
Table XIII - Example, based on Alto Lindoso case study, of the results given by IHA7 software for the natural flow regime
organized in percentiles (reproduced as given by the software): IHA percentile data table (“pct”).
IHA Percentile Data
1 entrada
Period of Analysis: 2001-2011 ( 11 years)
10%
25%
Period of Analysis
50%
75%
90%
Parameter Group #1
January
February
March
April
May
June
July
August
September
October
November
December
15,92
12,07
11,17
12,62
12,95
7,864
6,012
1,314
3,259
3,544
4,096
4,786
19,61
17,61
15,89
18,03
14,89
8,59
9,51
3,905
4,35
6,75
17,09
15,08
34,15
49,01
43,12
26,32
15,96
13,16
13,78
7,22
6,535
15,06
28,79
30,52
120,1
65,04
58,82
53,92
26,3
17,34
16,75
10,39
8,354
39,89
48,51
74,41
218,3
105,1
233,7
57,35
41,58
22,67
21,86
14,04
9,19
53,55
82,55
152,7
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
Parameter Group #2
1-day minimum
3-day minimum
7-day minimum
30-day minimum
90-day minimum
1-day maximum
3-day maximum
7-day maximum
30-day maximum
90-day maximum
Number of zero days
Base flow index
0
0,01667
0,1857
1,943
4,556
182,7
143,8
109,8
49,47
30,79
0
0,00692
0,04
0,49
1,68
3,389
6,27
275,2
226,2
138,7
82,02
39,05
0
0,03577
0,43
1,573
2,659
4,801
8,185
373,1
317,6
244,2
137,1
87,84
0
0,07111
1,92
2,967
4,431
6,099
9,578
568,9
438,6
321,7
169,6
101,2
0
0,1104
2,238
3,176
5,041
8,573
12,03
1004
761,6
582,8
318,4
241,4
6,8
0,1807
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
m 3/s
days
-
Parameter Group #3
Date of minimum
Date of maximum
174
302,6
225
341
253
21
266
81
286,4
104,6
days
days
Parameter Group #4
Low pulse count
Low pulse duration
High pulse count
High pulse duration
15,4
1
4,4
1,1
19
1,5
8
2
24
2
9
2
26
2
12
3
33,4
2
15
4,9
days
days
Parameter Group #5
Rise rate
Fall rate
Number of reversals
2,676
-6,417
155,6
3,16
-5,02
182
3,7
-4,36
188
4,54
-3,4
200
5,684
-3,331
207,6
m 3/s
m 3/s
-
Among the results given by the software presented on the previous tables, based on those values highlighted in
bold, as well as on the ones obtained for the modified regime, additional analysis was accomplished in order to
describe, in a more comprehensive and comparable way, the hydrologic alteration due to Alto Lindoso dam.
Midst the multiple approaches that could be applied for that purpose the one implemented is next described.
31
IV.2.1. DIMENSIONLESS 25% AND 75% PERCENTILES
The first approach utilized the 25% and 75% percentiles expressed in dimensionless forms. For that purpose
the 25% and 75% percentiles of each indicator were divided by the 50% percentile (median) obtained for the
same indicator based on the natural flow - Table XIII.
The dimensionless indicators allow comparing values of a same indicator even when those values differ several
orders of magnitude. The undefined ratios (denominator equal to zero) were excluded, as represented in Table
XIV. The indicators involved are presented in the same table, as well as the values obtained once the ratios are
performed, being these highlighted in bold.
Table XIV - Example, based on Alto Lindoso case study, of the results achieved for the dimensionless 25% and 75%
percentiles.
Natural regime
Group
1
2
IHA
From the IHA software
Dimensionless
75%
25%
75%
25%
50%
75%
25%
75%
January
19,61
34,15
120,10
0,57
3,52
16,89
43,86
142,40
0,49
4,17
February
17,61
49,01
65,04
0,36
1,33
9,30
40,83
53,98
0,19
1,10
March
15,89
43,12
58,82
0,37
1,36
0,00
34,56
45,33
0,00
1,05
April
18,03
26,32
53,92
0,69
2,05
8,50
22,18
45,56
0,32
1,73
May
14,89
15,96
26,30
0,93
1,65
0,03
15,11
29,32
0,00
1,84
June
8,59
13,16
17,34
0,65
1,32
10,39
12,81
15,84
0,79
1,20
9,51
13,78
16,75
0,69
1,22
10,37
15,68
23,91
0,75
1,74
August
3,91
7,22
10,39
0,54
1,44
6,46
10,55
13,87
0,89
1,92
September
4,35
6,54
8,35
0,67
1,28
8,54
16,18
20,84
1,31
3,19
October
6,75
15,06
39,89
0,45
2,65
4,40
12,80
15,73
0,29
1,04
November
17,09
28,79
48,51
0,59
1,68
5,78
28,73
71,31
0,20
2,48
December
Annual minima, 1-day
15,08
30,52
74,41
0,49
2,44
8,36
21,35
76,59
0,27
2,51
0,04
0,43
1,92
0,09
4,47
0,00
0,00
0,00
0,00
0,00
Annual minima, 3-day means
0,49
1,57
2,97
0,31
1,89
0,00
0,00
0,00
0,00
0,00
Annual minima, 7-day means
1,68
2,66
4,43
0,63
1,67
0,00
0,00
1,17
0,00
0,44
Annual minima, 30-day means
3,39
4,80
6,10
0,71
1,27
3,34
4,97
9,13
0,70
1,90
Annual minima, 90-day means
6,27
8,19
9,58
0,77
1,17
7,89
12,07
15,10
0,96
1,84
275,20 373,10 568,90
0,74
1,52
143,60 211,40 472,20
0,38
1,27
Annual maxima, 3-day means
226,20 317,60 438,60
0,71
1,38
120,30 183,20 393,50
0,38
1,24
Annual maxima, 7-day means
138,70 244,20 321,70
0,57
1,32
110,30 147,70 290,20
0,45
1,19
Annual maxima, 30-day means
82,02
137,10 169,60
0,60
1,24
74,36
90,63
165,40
0,54
1,21
Annual maxima, 90-day means
39,05
87,84
101,20
0,44
1,15
46,86
56,98
88,44
0,53
1,01
days
0
0
0
-
--
34
69
95
--
--
--
0,04
0,07
0,11
0,50
1,55
0
0
0,03
0,00
0,41
225
253
266
0,89
1,05
1
41
107
0,00
0,42
341
21
81
16,24
3,86
364
36
62
17,33
2,95
--
19
24
26
0,79
1,08
32
37
46
1,33
1,92
days
1,5
2
2
0,75
1,00
1
2
2
0,50
1,00
--
8
9
12
0,89
1,33
22
28
33
2,44
3,67
Median duration of high pulses (days)
days
2
2
3
1,00
1,50
1
1
2
0,50
1,00
Rise rates
m³/s
3,16
3,7
4,54
0,85
1,23
10,93
12,18
15,2
2,95
4,11
Fall rates
m³/s
-5,02
-4,36
-3,4
1,15
0,78
-15,98
-13,67
-9,85
3,67
2,26
--
182
188
200
0,97
1,06
178
184
199
0,95
1,06
July
Annual maxima, 1-day
Julian date of each annual 1-day maximum
Julian date of each annual 1-day minimum
Number of low pulses
5
Percentile
Dimensionless
50%
Base flow index
4
From the IHA software
25%
Number of zero-flow days
3
Modified regime
Percentile
Median duration of low pulses (days)
Number of high pulses
Number of hydrologic reversals
m³/s
m³/s
days
In order to emphasize the differences among the values of the IHA, either for a given case study or for different
case studies, web diagrams of the ratios of the 25% and 75% percentiles were drawn for each one of the
32
groups of indicators, with exception of group 3 that could not be considered as it only includes two indicators.
It is important to stress that the only conclusion that can be drawn from these diagrams are the deviations of
the percentiles with respect to median values of the natural regimes. In this way, they have a limited
application, but yet they show, for each group, how deviated the modified regime is from the natural regime.
In group number 1, for example, which is associated to the magnitude of the monthly flows, sometimes it is
quite visible a shift in the intra-annual variability of the flows, as the months with the highest flows in the
natural and modified regimes can be quite different.
Figure 13 exemplifies the web diagrams based on case study 1 - Alto Lindoso. It also includes a table with the
correspondence between the numbers (indexes) from the web diagrams and the IHA that they represent.
Percentile
Group 1
IHA 12
IHA 1
1,0
Group 2
IHA 2
IHA 24
IHA 13
1,0
Group 4
Group 5
IHA 27
1,0
IHA 14
IHA 31
2,0
0,8
IHA 11
IHA 3
0,5
IHA 23
1,5
0,6
IHA 15
0,5
1,0
0,4
0,2
25%
IHA 10
IHA 4
0,0
IHA 9
IHA 22
IHA 5
IHA 8
IHA 21
IHA 6
IHA 12
IHA 30
IHA 20
IHA 24
2,0
IHA 3
0,0
IHA 33
IHA 13
3,0
IHA 27
2,0
IHA 31
2,0
IHA 14
1,5
1,5
IHA 23
IHA 15
1,0
IHA 32
IHA 29
2,0
IHA 11
0,5
IHA 28
IHA 18
IHA 19
IHA 2
0,0
IHA 17
IHA 7
IHA 1
3,0
IHA 16
0,0
1,0
1,0
1,0
0,5
0,5
75%
IHA 10
IHA 4
0,0
IHA 9
IHA 22
IHA 5
IHA 8
IHA 21
IHA 6
Web index - indicator correspondence
1
IHA
IHA 30
IHA
IHA13 Annual minima, 1-day mean
IHA2 February
IHA14 Annual minima, 3-day means
IHA3 March
IHA15 Annual minima, 7-day means
IHA4 April
IHA16 Annual minima, 30-day means
IHA5 May
IHA17 Annual minima, 90-day means
IHA6 June
IHA18 Annual maxima, 1-day mean
2
0,0
IHA 33
IHA 32
IHA 29
IHA1 January
IHA7 July
IHA 28
IHA 18
IHA 19
Group
0,0
IHA 17
IHA 20
IHA 7
Group
IHA 16
0,0
IHA19 Annual maxima, 3-day means
IHA8 August
IHA20 Annual maxima, 7-day means
IHA9 September
IHA21 Annual maxima, 30-day means
IHA10 October
IHA22 Annual maxima, 90-day means
IHA11 November
IHA23 Number of zero-flow days
IHA12 December
IHA24 Base flow index
Group
IHA
IHA27 Number of low pulses
4
IHA28 Mean duration of low pulses (days)
IHA29 Number of high pulses
IHA30 Mean duration of high pulses (days)
IHA31 Rise rates
5
IHA32 Fall rates
IHA33 Number of hydrologic reversals
Legend:
Figure 13 - Example, based on Alto Lindoso case study, of the web diagrams for the dimensionless 25% and 75%
percentiles.
33
IV.2.2. DIMENSIONLESS MEDIANS
Another procedure applied to each case study utilized the 50% percentile of each regime (modified and
natural) divided by the modulus of the natural regime. The dimensionless medians thus obtained can be
compared either between natural and modified regimes or within different indicators, as they were made
dimensionless based on the same reference value - the modulus of the natural regime. As the ratio uses a flow,
only indicators related with flows - total of 24 - were considered in this analysis. The results achieved based on
the example of Alto Lindoso are presented in Table XV.
Table XV - Example, based on Alto Lindoso case study, of the results achieved for the dimensionless median.
Group
1
Natural regime
Modified regime
January
IHA
0,86
1,10
February
1,23
1,02
March
1,08
0,87
April
0,66
0,56
May
0,40
0,38
June
0,33
0,32
July
0,35
0,39
August
0,18
0,26
September
0,16
0,41
October
0,38
0,32
November
0,72
0,72
0,77
0,54
0,01
0,00
Annual minima, 3-day means
0,04
0,00
Annual minima, 7-day means
0,07
0,00
Annual minima, 30-day means
0,12
0,12
Annual minima, 90-day means
0,21
0,30
Annual maxima, 1-day
9,36
5,30
Annual maxima, 3-day means
7,97
4,60
Annual maxima, 7-day means
6,13
3,71
Annual maxima, 30-day means
3,44
2,27
Annual maxima, 90-day means
2,20
1,43
Rise rates
0,00
1,73
Fall rates
0,00
0,00
December
Annual minima, 1-day
2
5
m3 /s
Web diagrams based on the previous results were also obtained, as exemplified in Figure 14, as well as the
correspondence between the numbers (indexes) from the web diagrams and the IHA that they represent. For
that purpose groups 2 and 5 were represented together as this last group has only two flow indicators. As in
the case of the diagrams for the dimensionless 25% and 75% percentiles, the applicability of the ones for the
medians is also limited. In fact, they only give information about how high/low the median values are when
compared with the modulus of the natural regime. In spite of that, they are very useful to have a first
perception of the alteration under analysis.
34
Group 1
IHA 12
IHA 1
1,0
Groups 2 and 5 (Those envolving flows)
IHA 2
IHA 32
0,8
IHA 3
3,0
IHA 31
0,4
1,0
IHA 4
0,0
IHA 9
IHA 22
IHA 5
IHA 8
IHA 21
IHA 6
IHA 17
IHA 20
IHA 18
Web index - indicator correspondence
IHA 19
IHA
Group
IHA
IHA1 January
IHA13 Annual minima, 1-day mean
IHA2 February
IHA14 Annual minima, 3-day means
IHA3 March
IHA15 Annual minima, 7-day means
IHA4 April
IHA16 Annual minima, 30-day means
IHA5 May
1
IHA 16
0,0
IHA 7
Group
IHA 15
2,0
0,2
IHA 10
IHA 14
4,0
0,6
IHA 11
IHA 13
5,0
IHA6 June
2
IHA17 Annual minima, 90-day means
IHA18 Annual maxima, 1-day mean
IHA7 July
IHA19 Annual maxima, 3-day means
IHA8 August
IHA20 Annual maxima, 7-day means
IHA9 September
IHA21 Annual maxima, 30-day means
IHA10 October
IHA11 November
IHA12 December
IHA22 Annual maxima, 90-day means
5
IHA31 Rise rates
IHA32 Fall rates
Legend:
Figure 14 - Example, based on Alto Lindoso case study, of the web diagrams representative of the dimensionless median.
IV.2.3. MEAN DAILY FLOW DURATION CURVES
So that the distribution of the flows over time becomes more comprehensible visually mean daily flow duration
curves were also adopted. This curve, which is very common in hydrologic studies, gives the average number of
days per year with daily flows equal or greater than each daily flow. A duration curve can be made
dimensionless by dividing the daily flows by the corresponding modulus.
To compare the daily flow regime before and after the construction of each dam the duration curves for the
natural regime and for the modified regime were obtained. To allow the comparison between those curves
were made dimensionless by dividing by the modulus of the natural regime. The results achieved are
exemplified in Table XVI and Figure 15 for the Alto Lindoso case study.
35
Table XVI - Example based on Alto Lindoso case study. Dimensionless flow duration curves for the natural and modified
regimes.
Q/Qmod natural
Q (m 3 /s)
Natural regime Modified regime Natural regime Modified regime
Excendence probability
Days
0,025
0,09
1091,99
1132,79
27,40
28,43
0,050
0,18
920,14
849,75
23,09
21,32
0,075
0,27
765,82
781,51
19,22
19,61
0,100
0,37
671,60
648,77
16,85
16,28
0,124
0,45
651,37
636,08
16,35
15,96
0,149
0,54
633,19
629,05
15,89
15,79
0,174
0,64
617,96
546,48
15,51
13,71
0,199
0,73
568,87
535,34
14,28
13,43
(…)
49,975
182,41
17,89
19,87
0,45
0,50
50,000
182,50
17,89
19,87
0,45
0,50
50,025
182,59
17,88
19,82
0,45
0,50
50,050
182,68
17,86
19,82
0,45
0,50
(…)
99,900
364,64
0,00
0,00
0,00
0,00
99,925
364,73
0,00
0,00
0,00
0,00
99,950
364,82
0,00
0,00
0,00
0,00
99,975
364,91
0,00
0,00
0,00
0,00
39,85
37,84
1,00
0,95
Qmod
5,00
4,50
Daily flow (m3/s)
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
Natural modified
200
250
300
350
Days
Modified regime
Figure 15 - Example based on Alto Lindoso case study. Dimensionless flow duration curves for the natural and modified
regimes.
IV.2.4. MEAN DAILY FLOW PER MONTH
Another way of representing the natural and modified flow regimes and of detecting the differences between
those regimes due to river damming can be based on the diagrams of the monthly mean daily flows (that is,
diagrams of the average of the daily flows in each month). These diagrams show the monthly distribution of
the flows over the year, thus allowing detecting the months most affected by river damming. Figure 16
36
contains the diagram obtained, as an example, for Alto Lindoso case study. It suggests that the temporal
variability of the natural regime over the year is slightly smoothed after river damming as the amplitude of the
Daily flow (m3/s)
mean daily flows along the year somehow decreases in the modified regime.
90
80
70
60
50
40
30
20
10
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Natural regime
Modified regime
Figure 16 - Example based on Alto Lindoso case study. Monthly mean daily flows for the natural and modified regimes.
IV.2.5. RATIO BETWEEN INDICATORS
The last procedure applied to analyse the results given by the software was based on the ratio between the
mean values for the natural and modified regimes of a given indicator. For the purpose, equations (1) and (2)
were applied:
(1)
(2)
The ratio defined by equation ( 1 ) measures the relative difference between the ideal flow condition of the
river reach (natural regime) and the one that really occurs after the dam construction (modified regime).
Equation ( 2 ) in its turn, provides a direct way to express how far from the natural indicator is the modified
one. The ratios RA1 and RA2 are not defined when
is equal to zero.
Though the given ratios allow a comparison between regimes, they have some limitations. In fact, either
among the different case studies for certain IHA or among the different IHAs for a specific case study, they may
differ several orders of magnitude depending on the relative values of the numerators and denominators and
making such ratios difficult to compare.
Whenever the major interest lies in the fraction (between 0 and 1) of the level of hydrologic alteration, a
modified ratio of alteration is adopted, defined as:
37
{
}
(3)
{
According to this definition, a value of RA3 close to zero means a large amount of hydrologic alteration, while a
value close to one occurs when IHA for the natural and for the regulated river are not very different. Note that
when
the ratio of alteration is zero, even for possibly small values of
that are
not equal to zero, highlighting a very grievous alteration. In case of both IHAs are null, the ratio consists of an
indetermination, being difficult to infer the value of RA3. Therefore, in these cases the ratio given is not
defined.
IV.3
RESULTS
From the aforementioned, it is perceptible that it is very difficult to synthetize the information obtained with
IHA software and to make it comparable between flow regimes or among case studies. This is the reason why
different analysis based on tables and diagrams were conceived and applied. The results thus achieved for the
nine case studies are presented in Appendix A, which includes the web diagrams of the 25% and 75%
percentiles and of the dimensionless medians, along with the mean annual flow duration curves and the
diagrams of the monthly mean daily flows. It also includes a table with the values given by equation (3) for the
ratio RA3.
The observation of the set of web diagrams presented in Appendix A.1 referent to the 25% and 75%
dimensionless percentiles requires special attention, as it is not possible to extract direct conclusions from it.
However, the diagrams allow identifying higher and lower levels of alteration. In fact, there is a notorious
proximity between the modified and natural flow regimes in Touvedo case study which does not appear in the
remaining case studies. That proximity is specially marked for group 5, suggesting that the scheme hardly
interferes with the frequency and the rate of change of the natural regime. In comparison with the other case
studies, the remaining groups of indicators also demonstrate a better agreement between natural and
modified flow regimes. In what concerns the other cases studies, the web diagrams for case studies 4, 5, 6, and
7 show a substantial change between the natural regime and modified flow regime (which is not even visible)
in group 1, both for the 25% and the 75% percentiles. This suggests that those schemes induce a strong
alteration in the magnitude and frequency of the daily flows.
The next set of diagrams - Appendix A.2 - strengthens some of the previous conclusions. In fact, the
dimensionless medians of group 1 show an extreme alteration in case studies 4, 5, 6, 7 and also in case study
number 3. On the contrary, the diagrams for case studies number 1, 2, 8 and 9 reveal a considerable similarity
between the patterns of the natural and modified flow regimes. It should also be stressed the proximity of the
38
patterns of case studies number 1 and 2, which can be explained by the fact that case 2 - Touvedo, of the runof-river type, - is located downstream case 1 - Alto Lindoso, whose huge reservoir regulates the flows.
From the flow duration curves presented in Appendix A.3 two groups are distinguishable: one with a clear
alteration of the river flow regime - cases studies numbers 3, 4, 5, 6 and 7 - and another which a reduced
alteration of that regime - cases studies numbers 1, 2, 8 and 9. In the first group the duration curves for the
modified regime are significantly different from the curves for the natural regime, with the major part of the
year (at least 80%) with zero flows. Among the case studies with reduced alteration of the flow duration curves,
case studies 1 and 2 are the ones showing the smallest changes, with curves for the natural and modified
regimes almost coincident.
The same conclusions can be drawn from the diagrams of the monthly mean daily flows, included in
Appendix A.4. The diagrams relative to case studies 1 and 2 show a reduced alteration between natural and
modified flow regimes and also a similar progress. As previously observed, there is an evident alteration from
the natural to the modified regimes in case studies 3, 4, 5, 6 and 7: in the modified regime the rivers are almost
dried downstream the schemes. In case 3, the modified regime exhibits a regular diagram as a consequence of
the release of almost constant environmental flows. Adding to case studies 1 and 2, cases 8 and 9 also reveal a
reduced level of alteration induced by damming.
Finally, the table with of ratios of alteration R3 presented in Appendix A.5 provides the most complete results,
for the five groups of IHA, revealing the effect of the dams in the different characteristics of the daily flow
regimes. Through a first global look at the given values, it is possible to verify that some of the ratios have
similar values for all the case studies, thus not allowing their distinction, namely those respecting to IHA13 to
IHA15 and IHA23 to IHA25. These indicators are relative to the minimum flows, thus more sensitive to the
changes induced, in accordance to what was mentioned when the RA3 was defined. From the observation of
the general results, the first obvious conclusion is that case studies 3, 4, 5, 6 and 7 induce a higher level of
alteration when compared to the others.
Taking an attentive look at case studies 1 and 2, they both demonstrate reduced levels of alteration, less
significant than the rest of the case studies. Even so, the ratios of groups 4 and 5 suggest a smaller alteration
for case 2 - Touvedo - as it barely changes the natural regime. This is consistent with the small storage capacity
of this case study and the conclusions taken from the previous analyses. On the opposite side are the case
study 3 ratios, showing a high level of alteration where only the magnitudes of the dry months (IHA7 to IHA9)
and minimum flows are less altered. As this last, case study 4 - Paradela - also demonstrates a high level of
alteration, excepting concerning the magnitude of dry months (IHA8 and IHA9), high pulses (IHA30) and rise rates
(IHA30). In addition to the former, cases 5, 6 and 7 exhibit a high level of change, less expressed for this last in
terms of annual maxima (IHA18 to IHA22). Finally, case studies 8 and 9 do not reveal a significant level of
alteration. In fact, when evaluating the alteration ratios, only the results for the magnitude of the dry months
(IHA7 to IHA10) reflect a higher level of alteration.
39
This last set of ratios reinforces the previous conclusions and provides additional information, showing that the
ratios are the most complete approach to analyse and characterize the alteration induced by damming.
40
CHAPTER V. VILARINHO DAS FURNAS CASE STUDY: TEMPORAL COMPARISON
V.1. INITIAL CONSIDERATIONS
In this Chapter, the case study of Vilarinho das Furnas is addressed in detail. As mentioned in Chapter III.3,
Vilarinho das Furnas has the particularity of having, besides the data provided by EDP, a nearby long series of
daily flow data from SNIRH, namely the one registered at Covas stream gauging station. An upstream versus
downstream comparison based on the EDP flow data was previously accomplished to evaluate the level of
alteration induced for the nine case studies (spatial comparison). In the case of Vilarinho das Furnas dam such
comparison can also be done based on measured flow data which, somehow, is more reliable than the one
previously utilized. In fact, except for a scale factor given by the ratio of the watersheds areas at the section of
the dam and at the stream gauging station, the flows measured at the stream gauging station represent the
natural regime and the modified, respectively, before and after the dam construction. Moreover, a hydrologic
model can be applied to reconstruct the natural flow regime at Covas S.G.S. after the dam construction, based
on the transposition of the flows registered at another stream, allowing a more comprehensive analysis of the
alterations induced by Vilarinho das Furnas dam. For that propose the stream gauging station of Fragas da
Torre was selected as further justified.
V.2. ANALYSIS BASED ON THE RECORDS AT C OVAS STREAM GAUGING STATION
The flow data available at the SNIRH data basis for Covas stream gauging station spans from 1955 and 2004. As
Vilarinho das Furnas dam was constructed in 1972, the flow records before that date represent the natural flow
regime and those registered after the modified one (except for the scale factor previously mentioned).
Therefore, a temporal analysis can be performed based on that information.
Figure 17 - Schematic representation of the periods with daily flow data from the SNIRH (Covas S.G.S.) and from EDP.
Table XVII contains the watershed area of Homem River at the sections of the dam and of the stream gauging
station, as well as the modulus computed for the natural, Qmod Natural , and modified, Qmod Modified , regimes
downstream the dam and at the gauging station. The modulus for the natural regime at Covas was computed
based on the daily flows prior to the dam construction - 1956 to 1972. On another hand, for EDP the data
concerning the natural flow regime respects to the inflows given by such entity for the period of 2004 to 2011.
41
Table XVII - Vilarinho das Furnas modulus for the natural and modified regimes based on the SNIRH and on the EDP data.
Data source
Period considered
EDP [1]
1/1/2004 - 31/12/2011
1/1/1956 - 31/12/1971
SNIRH (Covas S.G.S.) [2]
1/1/1972 - 31/12/2003
Ratio
A
Qmod Natural
Qmod Modified
(km²)
3
(m /s)
(m /s)
77,00
5,43
0,34
8,87
-
-
2,86
0,61
0,12
118,15
0,65
3
As showed in the previous table, EDP and SNIRH data refer to different periods of time. However, as the data
report to sections of the same river - the Homem River - relatively near it is expected that the ratio between
the values of the modulus for a given regime would be approximately equal to the ratio between the respective
watersheds areas. Such expectation is confirmed for the natural regime, as, in fact, one would obtain:
Qmod Natural [1] / Qmod Natural [2] = 0,61 and A [1] / A [2] = 0,65.
Therefore, in order to proceed with the analysis of Vilarinho das Furnas based on the flow records at Covas
station and to establish a comparison with the results thus obtained with those derived from EDP data, the
flow data at the stream gauging station must be multiplied by the ratio between watersheds, that is 0,65.
The data thus obtained for the natural and the modified regimes can then be introduced in the IHA software
and its results compared with the ones derived from the EDP data, previously presented in Chapter IV.
Table XVII shows that the ratios between watershed areas and between modified modulus are not similar
(0,12 << 0,65). In fact, the modified flows at Covas are much higher than the outflows from EDP. A possible
explanation for this fact comes from the contribution of the watershed area between the sections of the dam
2
and of the station (approximately 41 km ) which increases the water availability.
Once these concepts are clarified, the flow data is ready to be analysed following the same procedure as
before. In a first step, the daily flows at Covas gauging station both for the period that precede and succeed
1972 were introduced in IHA Version 7.1. As the objective is to accomplish a temporal analysis, the natural and
the modified daily flow series are introduced simultaneously, by selecting a “pre- and post-impact
comparison”.
Based on the results from the program, different kinds of diagrams can be obtained, as previously exemplified
in Chapter IV. In the present case, to support the envisaged comparison, web diagrams and mean daily flow
diagrams were obtained, as showed in Appendix B. The web diagrams exhibit an expressive alteration
according to EDP data, opposing to a moderate alteration according to Covas gauging station.
In this chapter only some of the more relevant results, namely the mean annual flow duration curves and the
values of the ratios of alteration were included - Figure 18 and Table XIX respectively - and analysed more
extensively.
42
Dimensionless flow (Q/Qmod natural)
5
4,5
4
3,5
3
2,5
2
1,5
1
0,5
0
0
50
100
150
200
250
300
Natural regime (EDP)
Natural regime (Covas)
Modified regime (EDP)
Modified regime (Covas)
350
Days
Figure 18 - Duration curves for EDP and Covas results (for Vilarinho das Furnas).
The mean daily flow duration curves of Figure 18 support some conclusions. The most evident one respects to
the proximity of the natural regime regardless the origin of the flow data. The second one relates to the
notorious difference between natural and modified regime which is even more evident when EDP data is under
consideration. As clarified, EDP modified regime refers to the outflow immediately downstream the dam while
in the case of Covas it involves records obtained a few kilometres downstream. As abovementioned, inflows to
the river from tributaries located in intermediate river reach may occur, eventually justifying part of the
differences between modified regimes. In fact, the outflows from EDP suggest that the river reach is almost dry
during the major part of the year, while records from Covas show a temporal pattern which looks like the
natural one, though with smaller volume of water.
The ratios of alteration correspondent to the analysis with Covas gauging station are, in their turn, presented at
the end of this chapter - Table XIX.
V.3. ANALYSIS BASED ON THE
RECONSTRUCTION, FOR THE POST - DAM PERIOD , OF THE NATURAL REGIME
AT COVAS STREAM GAUGING STATION
In this chapter, another approach for Vilarinho das Furnas analysis is presented, consisting in the comparison
between the river regime after the dam construction and the one that would exist if the dam was never
constructed. In order to proceed with this study, the section of Covas was adopted and the natural flow regime
at the same for the post-dam period (1972 onwards) was estimated based on transposition techniques. The
indicators computed for that regime were next compared with the modified ones, derives from the flow
records at the station for the same period.
43
The reconstruction of the natural flow series at a river section without data or with data with gaps can apply
transposition procedures of the flow data - daily, monthly or annual - from a certain section of river with
records to the section under consideration. The transposition imposes that the flow regime at watersheds
defined by the two river sections is natural and affected by equivalent constraints, namely in terms of geology
and climate and that the mean annual flow depths - ̅ (mm) - in the same watersheds are similar. The nearer
the watersheds are, the more similar the mentioned constraints are expected to be and the more accurate the
reconstitution procedure becomes (Portela & Quintela, 2005). Despite the aforementioned requirements, for
mean annual flows depths higher than 400 mm the temporal pattern of the flow regime becomes almost the
same, when expressed in a dimensionless form, as showed by Figure 19.
Q/Qmod
b)
4
Q/Qmod
a)
2
4
0
0
100
200
300
Duration (day)
2
Q/Qmod
c)
4
0
0
100
200
300
Duration (day)
2
0
0
100
200
300
Duration (day)
Figure 19 - Mean annual flow duration curves: a) at the 54 Portuguese stream gauging stations (left); and from those
stations at the b) 26 and c) 28 with mean annual flow depths respectively higher and smaller than 400 mm (right)
(reproduced from Portela & Quintela, 2005).
To reconstruct the natural flow regime at the section of Covas station after the construction of Vilarinho das
Furnas dam, the flow records at Fragas da Torre stream gauging station were used. This station is located in
Paiva River and has daily records between the years 1956 and 2004. Table XVIII presents some of its
characteristics along with those of Covas station.
Table XVIII - Important information on Covas and Fragas da Torre gauging stations.
Stream gauging station
Covas
Fragas da Torre
44
SNIRH code
03H/04H
08H/02H
2
A (km )
116
660
̅ (mm)
2212
997
3
Qmod Natural (m /s)
8,87
21,98
The given table includes, among other characteristics, the mean annual flow depths at the watersheds of both
stream gauging stations. There is a clear difference between their values (2212 >> 997), which could suggest
that the procedure was not applicable in this case. However, as their values are higher than 400 mm, according
to Figure 19, the dimensionless form of flow regime for both is almost the same. For that reason, the flow
series verifies the basic conditions to be considered valid.
Figure 20 identifies the time intervals that are important in terms of the reconstruction procedure.
Figure 20 - Scheme including the data suitable for the analysis considering the reconstruction of Covas natural regime
after 1972.
Based on the daily flow records at Fragas da Torre and on the mean annual flow depths at the watersheds of
both stations, the reconstruction of the daily flow regime at the stream gauging station of Covas from 1972 to
2004 utilized equation ( 4 ) applied at a daily level:
(4)
where:
- mean daily flow on Julian day , for the section respecting to
- natural modulus considering
3
gauging station (m /s);
3
gauging station (m /s).
Each non-existent daily flow record at Covas after 1972 is thus obtained by multiplying the daily flow registered
in Fragas da Torre gauging station in the same day by the ratio between the natural modulus at Covas and
Fragas da Torre.
The daily flow data thereby obtained for the natural regime at Covas station after 1972, as well as the one
already available for the same station (either natural, before 1972, or modified, after 1972) are represented in
the chronological diagram of Figure 21 a). The diagram supports the assumption that the reconstruction
procedure is valid, as the reconstructed daily flows after 1972 show a pattern equivalent to the natural regime
prior to 1972. They also clearly show that as a consequence of the dam construction the magnitude of the
daily regime was severely diminished, which is also in accordance to the expected. The same procedure was
adopted for monthly and annual flow data. The resulting diagrams are presented in Figure 21 b) and c) and
their observation corroborate the conclusions taken from the first one.
45
a)
250
Daily flow (m³/s)
200
150
100
50
0
3-Oct-54
20-Dec-62
8-Mar-71
25-May-79
11-Aug-87
28-Oct-95
14-Jan-04
Day
b)
2500
Monthly flow (m³/s)
2000
1500
1000
500
0
Oct-54
Aug-61
Jun-68
Apr-75
Feb-82
Dec-88
Oct-95
Sep-02
Month
c)
6000
Annual flow (m³/s)
5000
4000
3000
2000
1000
0
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
Year
Figure 21 - Daily (a), monthly (b) and annual (c) flows at Covas stream gauging station. Registered and reconstructed
based on Fragas da Torre.
46
The series of daily flows obtained from the reconstruction procedure allow the comparison between the
reconstructed natural daily flow regime after 1972 with the modified one for the same period (post- and postdam comparison). Regarding the concepts introduced in Chapter II, this consists on a temporal analysis. Such
comparison can be added to the ones provided by EDP (upstream and downstream comparison) and Covas
data (pre- and post-dam comparison). These respect to spatial and temporal analysis, respectively. The three
types of comparisons considered for Vilarinho das Furnas case study are summarized in Table XIX.
Table XIX - Vilarinho das Furnas case study. Ratios of alteration for EDP (i), Covas (ii) and for the period after 1972 based
on the reconstructed natural regime and on the registered modified regime (iii).
Type of comparison
Spatial
Indicator
Group
1
2
(i) Source: EDP
0,33
0,33
0,07
0,35
0,28
IHA3 March
IHA4 April
0,09
0,32
0,36
0,09
0,35
0,39
IHA5 May
IHA6 June
0,15
0,47
0,34
0,30
0,49
m³/s
IHA7 July
IHA8 August
0,39
0,22
0,75
0,47
0,43
0,59
0,51
1,00
0,99
IHA9 September
IHA10 October
0,70
0,55
0,98
0,12
0,31
0,44
IHA11 November
IHA12 December
0,10
0,30
0,35
0,08
0,40
0,33
IHA13 Annual minima, 1-day mean
0,05
0,98
0,99
IHA14 Annual minima, 3-day means
0,26
0,99
0,96
IHA15 Annual minima, 7-day means
0,34
0,99
0,94
IHA16 Annual minima, 30-day means
0,86
0,97
0,92
IHA17 Annual minima, 90-day means
0,38
0,63
0,84
0,06
0,41
m³/s
IHA18 Annual maxima, 1-day mean
0,23
0,22
0,05
IHA20 Annual maxima, 7-day means
0,03
0,41
0,23
IHA21 Annual maxima, 30-day means
0,03
0,35
0,26
IHA22 Annual maxima, 90-day means
0,04
0,34
0,28
days
0,58
-
-
--
0,02
0,32
0,30
IHA25 Julian date of each annual 1-day minimum
IHA26 Julian date of each annual 1-day maximum
days
0,28
0,44
0,36
0,41
0,62
IHA19 Annual maxima, 3-day means
IHA27 Number of low pulses
5
(ii) Source: SNIRH
(Covas)
0,05
IHA24 Base flow index
4
Temporal
(iii) Source: SNIRH
(Reconstruction based
on Fragas da Torre)
IHA1 January
IHA2 February
IHA23 Number of zero-flow days
3
Temporal
0,98
0,97
--
0,03
0,67
days
0,06
0,39
--
0,16
IHA30 Median duration of high pulses
days
0,12
0,57
IHA31 Rise rates
m³/s
0,15
0,23
IHA32 Fall rates
m³/s
0,09
--
0,04
IHA28 Median duration of low pulses
IHA29 Number of high pulses
IHA33 Number of hydrologic reversals
Low alteration: RA3 > 0,67;
0,09
0,10
0,61
0,28
0,76
Moderate alteration: 0,33 < RA3 < 0,67;
0,98
0,23
0,99
0,56
0,49
0,56
0,77
0,60
0,56
0,35
0,86
0,70
1,00
0,25
0,42
0,47
0,55
0,94
High alteration: RA3 < 0,33.
A first overall observation of the ratios of alteration shows a notorious difference between natural and
modified regime when EDP data is under consideration, in the table identified by (i). On the contrary, for the
analysis considering Covas stream gauging station in the same table - (ii) -, the majority of values are between
0,33 and 0,67, suggesting a moderate level of alteration. In fact, EDP modified regime refers to the outflow
47
immediately downstream the dam while in the case of Covas it involves records obtained a few kilometres
downstream. Therefore, inflows to the river from tributaries located in intermediate river reach may occur,
eventually justifying part of the differences verified. The ratios obtained for the comparison derived from the
reconstruction of Covas natural regime also suggest that Vilarinho das Furnas induce a moderate level of
alteration in the river flow regime. The similarity of the ratios derived from comparisons identified in Table XIX
by (ii) and (iii) is consistent with the suitability of the reconstruction procedure of the daily regime at Covas
gauging station.
48
CHAPTER VI. CONCLUSIONS AND FUTURE DEVELOPMENTS
In this dissertation, the main goal was to quantify, analyse and characterize dam-induced changes in the
natural flow regime of rivers located in mainland Portugal. The discussion of the results was drawn by linking
the characteristics of dams (type of operation, purposes, layout of the schemes) with the respective hydrologic
alterations. The preliminary bibliographic research on the key-concepts of hydrologic alteration,
methodological approaches for environmental flows definition and ecological responses of aquatic and riparian
communities to altered flows allow summarizing the relevant information for further similar studies:
1.
the hydrologic regime (amount of surface water and its temporal pattern) is a key variable of fluvial
ecosystems, extremely important for the biological components of aquatic ecosystems, contributing
to the geomorphological characteristics of rivers, water quality, and many other river components.
2.
The natural hydrologic regime of rivers in Mediterranean regions has an inherent inter- and
intra-annual variability that assures the integrity of aquatic and riparian ecosystems and preserves
habitats, species, populations and biodiversity.
3.
In Portugal, dams have been constructed for various purposes, but mostly for hydropower production,
urban, industrial and agricultural uses; it is recognized that river regulation by dams induce
disturbances in river flows, and consequently lead to altered fluvial ecosystems.
4.
The flow regimes have five main components - (i) magnitude; ii) frequency; (iii) duration; (iv) timing or
predictability, and (v) rate of change - that define the patterns of natural and altered flows, thus
allowing to quantify and qualify the level of alteration induced by river regulation.
5.
Indicators of hydrologic alteration based on the components of the hydrologic regime may be used to
measure the level of change induced by river damming, and further related with ecological responses
of the fluvial ecosystem.
6.
There is a general agreement on the importance of assuring a minimal discharge downstream the
dams - environmental flows - although in terms of legislation, there is no consensus worldwide when it
comes to its definition and estimation.
7.
The implementation of environmental flows is an important river management issue, addressed in
water legislation, at national and at the European Union levels, being the Water Framework Directive
(EC/2000/60) the most relevant legislative tool to ensure the protection, enhancement and
sustainable use of Europe's freshwaters. Indicators of alteration can be a good support for
environmental flows research and their implementation.
Many difficulties were found along the research studies of this dissertation. The main problems arose in the
beginning of the working plan, with the selection of case studies, given the lack of long-time series of daily
flows from gauging stations upstream and downstream dams. This flow data is required to a detailed and
49
accurate hydrologic study on the characterization of natural and altered flow regimes. Thus, nine case studies
were selected corresponding to diverse types of Portuguese dams, which were further classified according to
the level of alteration they introduced. The calculation and analysis of the indicators for the case studies point
to two main conclusions:
i)
as expected, it was confirmed that dams with a lower flow regulation capacity and with an
operation scheme that ensures discharges just downstream the dam - run-of-river dams - are
those which lead to the most reduced level of hydrologic alteration, whereas dams having a high
flow regulation capacity that function mostly for water transfer are those which induce higher
hydrologic alterations; this information, though predictable, allow having confidence in the flow
data gathered for this study;
ii)
the most interesting and more promising conclusion in terms of research and future applications,
stresses the fact that the calculation of indicators of hydrologic alteration proved to be an useful
approach, capable of focusing, comparing and establishing levels of dam-induced hydrologic
disturbances.
Concerning the comparative study of Vilarinho das Furnas, the flow data from the gauging station of Covas
allowed two different approaches from which the following research outcomes were drawn:
1.
although a dam may reduce extremely the flows downstream, the river may have the capacity of
recovering from that along its course, as the watershed increases, as was observed by the
comparison between Covas and EDP data;
2.
the transposition procedure and the reconstruction of the daily flows at Covas stream gauging
station for the post-dam procedure proved to be a suitable tool for analyzing the dam-induced
changes in the river regime.
Though this study did not intend to relate the ecological responses of biota to flow alterations, it is expectable
that the large differences between natural and modified regimes found for several case studies could cause
high impacts on the ecosystems, stressing the importance of the environmental flow requirements capable of
assuring the sustainability of rivers.
Finally, this study intends to contribute to the knowledge of hydrologic alterations caused by river regulation in
Portugal, a subject insufficiently studied in the country, except for a few exceptions (Martins, 2012). This study
can be a good supporting basis for research in the effects of these dams in biotic components and ecological
quality of rivers and riparian ecosystems. Though the results achieved are specific for the analysed case studies,
some generalizations to other similar dams can be made with caution.
50
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53
54
APPENDICES
APPENDIX A. - RESULTS RELATIVE TO CHAPTER IV
LIST OF APPENDIXES
Appendix A. 1 - Web diagrams for the dimensionless 25% and 75% percentiles for the nine case studies
(followed by the respective legend). ........................................................................................................... iii
Appendix A. 2 - Web diagrams representative of the dimensionless median values for the nine case
studies (followed by the respective legend). ............................................................................................... v
Appendix A. 3 - Dimensionless flow duration curves for the natural and modified regimes for the nine
case studies. ............................................................................................................................................... vii
Appendix A. 4 - Monthly mean daily flows for the natural and modified regimes for the nine case studies.
...................................................................................................................................................................... x
Appendix A. 5 - Ratios of alteration (R3) for the nine case studies. .......................................................... xiii
Appendix A. 1 (1/2) - Web diagrams for the dimensionless 25% and 75% percentiles for the nine case studies (followed by the respective legend).
25% percentile
IHA 12
IHA 11
Case study number 1: Alto
Lindoso
Group 1
Group 2
IHA 1
1,0
IHA 13
1,0
IHA 2
IHA 3
0,5
IHA 10
IHA 24
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 23
IHA 1
1,0
IHA 16
0,6
IHA 30
1,0
0,2
0,5
IHA 28
0,0
IHA 3
0,5
IHA 23
IHA 33
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 12
IHA 22
IHA 27
1,0
IHA 14
IHA 16
IHA 21
IHA 6
IHA 30
0,0
IHA 20
IHA 4
0,0
IHA 5
IHA
12
IHA 1
3,0
IHA
10
0,0
IHA 32
IHA 18
IHA 8
IHA 1
3,0
IHA 31
2,0
0,6
IHA 12
IHA 4
IHA 22
IHA 10
IHA 4
0,0
IHA 22
IHA 16
0,0
IHA 30
0,0
IHA 28
IHA 16
0,0
IHA 27
2,0
IHA 31
2,0
1,5
1,5
1,0
1,0
IHA 30
0,0
IHA 20
IHA 24
0,0
IHA 33
IHA 5
IHA 21
IHA 8
IHA 6
IHA 13
3,0
IHA 29
IHA 27
2,0
IHA 14
IHA 31
2,0
1,5
1,5
2,0
IHA 23
1,0
IHA 15
1,0
1,0
0,5
0,5
IHA 10
IHA 4
0,0
IHA 9
IHA 17
IHA 20
IHA 7
IHA 22
IHA 16
0,0
IHA 30
0,0
IHA 28
0,0
IHA 12
IHA 11
IHA 1
1,0
IHA 2
IHA 24
IHA 3
0,5
IHA 13
1,0
IHA 8
IHA 27
1,0
IHA 14
IHA 31
2,0
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 22
IHA 21
IHA 6
IHA 20
IHA 12
IHA 11
IHA 24
IHA 3
0,5
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 6
IHA 7
IHA 30
0,0
IHA 22
0,0
IHA 32
IHA 9
IHA 15
IHA 16
IHA 30
1,0
0,2
0,5
0,0
IHA
12
1,5
0,4
IHA 28
1,0
IHA 30
0,0
0,5
IHA 28
0,0
IHA 17
IHA 20
IHA 19
IHA 1
3,0
IHA 13
3,0
IHA 24
IHA 2
IHA 29
IHA 14
2,0
IHA 3
IHA 23
IHA 15
1,0
IHA 27
2,0
IHA 31
2,0
1,5
1,5
1,0
1,0
0,5
IHA
10
IHA 4
0,0
IHA 9
IHA 5
IHA 22
0,5
IHA 16
0,0
IHA 30
IHA 21
0,0
IHA 28
0,0
IHA 17
IHA 33
IHA 6
IHA 7
IHA 32
IHA 18
IHA 7
1,0
IHA 32
1,5
1,0
0,5
IHA 16
0,0
IHA 21
IHA 6
IHA 8
IHA 29
IHA 15
IHA 22
IHA 31
2,0
1,5
IHA 23
2,0
IHA
11
0,0
IHA 33
IHA 18
IHA 19
IHA 27
2,0
IHA 14
IHA 33
IHA 31
2,0
0,8
IHA 17
IHA 20
IHA 5
IHA 8
IHA 14
IHA 21
IHA 13
3,0
1,0
IHA 4
IHA 32
IHA 29
2,0
0,0
IHA 29
0,0
IHA 24
IHA 3
IHA 10
IHA 27
1,0
0,5
IHA 33
IHA 18
0,5
0,6
IHA 23
IHA 2
1,0
IHA 18
IHA 13
1,0
IHA 1
3,0
2,0
IHA 28
IHA 33
IHA 19
IHA 2
IHA 20
IHA 19
IHA 11
1,0
IHA 17
IHA 7
IHA 1
1,0
IHA 16
0,0
IHA 12
1,5
0,4
0,2
IHA 10
IHA 17
0,8
IHA 15
0,5
IHA 21
IHA 6
IHA 7
IHA 29
0,6
IHA 23
IHA 5
IHA 32
IHA 18
IHA 19
IHA 32
IHA 18
IHA 19
IHA 3
0,5
IHA 28
IHA 17
1,0
0,5
IHA 33
Case study number 5: Vilar
IHA 14
0,0
IHA 9
Case study number 4:
Paradela
IHA 13
3,0
IHA 21
IHA 2
IHA 32
IHA 29
0,5
0,2
Case study number 3:
Vilarinho das Furnas
IHA 33
1,0
IHA 11
1,0
IHA 28
0,0
IHA 15
2,0
1,5
0,4
0,0
IHA 18
IHA 23
IHA 6
IHA 27
1,0
IHA 15
IHA 30
IHA 17
IHA 24
IHA 5
IHA 13
1,0
0,5
IHA 16
0,0
2,0
IHA 9
IHA 1
1,0
IHA 23
1,0
0,5
IHA 21
IHA 2
0,0
IHA 7
IHA 3
1,0
IHA 19
IHA 3
IHA 29
0,5
IHA 22
1,0
IHA 33
IHA 14
IHA 15
IHA 20
2,0
IHA
11
IHA 19
IHA 24
1,5
IHA 23
IHA 6
IHA 7
IHA 2
1,5
0,5
IHA 17
IHA 31
2,0
IHA 14
1,0
IHA 9
1,0
0,8
IHA 11
IHA 32
1,5
IHA 28
Group 5
0,5
IHA 10
IHA 31
2,0
0,6
IHA 15
0,0
IHA 24
IHA 7
0,2
IHA 10
IHA 2
2,0
IHA 8
0,4
Case study number 2:
Touvedo
IHA 27
2,0
IHA 3
IHA 29
0,5
IHA 13
3,0
1,0
0,0
0,8
IHA 11
Group 4
IHA 1
3,0
2,0
IHA 18
IHA 13
1,0
Group 2
IHA 11
0,4
IHA 19
IHA 24
IHA 12
1,5
IHA 17
IHA 20
IHA 2
IHA 31
2,0
Group 1
0,8
IHA 15
0,0
IHA 7
IHA 12
IHA 14
IHA 21
IHA 6
Group 5
IHA 27
1,0
0,5
IHA 22
75% percentile
Group 4
IHA 20
IHA 32
IHA 18
IHA 19
IHA 29
iii
Appendix A. 1 (2/2) - Web diagrams for the dimensionless 25% and 75% percentiles for the nine case studies (followed by the respective legend).
25% percentile
IHA 12
75% percentile
Group 1
Group 2
Group 4
IHA 1
1,0
IHA 13
1,0
IHA 27
1,0
IHA 2
IHA 24
IHA 14
Group 5
IHA 31
2,0
IHA
12
0,8
IHA 11
Case study number 6:
Caldeirão
IHA 3
0,5
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 23
IHA 22
IHA 21
IHA 6
IHA 11
IHA 1
1,0
IHA 16
0,0
IHA 30
0,4
1,0
0,2
0,5
IHA 20
IHA 24
IHA 3
0,5
IHA 23
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 12
IHA 11
IHA 1
1,0
IHA 16
0,0
IHA 20
IHA 30
1,5
0,4
1,0
IHA 24
IHA 3
0,5
IHA 23
IHA 15
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 22
IHA 21
IHA 6
1,5
1,0
IHA 20
IHA 11
IHA 1
1,0
IHA 24
IHA 3
0,5
IHA 23
IHA 33
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 6
IHA 7
IHA 22
IHA 27
1,0
IHA 21
IHA 30
IHA 20
IHA 13
3,0
IHA 29
IHA 27
2,0
IHA 31
2,0
IHA 14
1,5
1,5
2,0
IHA 23
1,0
IHA 15
1,0
1,0
IHA 4
IHA 9
0,5
IHA 22
IHA
12
IHA 2
IHA 24
IHA 28
0,0
IHA 32
IHA 13
3,0
IHA 4
0,0
IHA 9
IHA 5
IHA 22
Group
IHA
IHA13 Annual minima, 1-day mean
IHA2 February
IHA14 Annual minima, 3-day means
IHA3 March
IHA15 Annual minima, 7-day means
IHA4 April
IHA16 Annual minima, 30-day means
IHA5 May
IHA17 Annual minima, 90-day means
IHA6 June
IHA18 Annual maxima, 1-day mean
2
IHA19 Annual maxima, 3-day means
IHA8 August
IHA20 Annual maxima, 7-day means
IHA9 September
IHA21 Annual maxima, 30-day means
IHA10 October
IHA22 Annual maxima, 90-day means
IHA11 November
IHA23 Number of zero-flow days
IHA12 December
IHA24 Base flow index
IHA
IHA28 Mean duration of low pulses (days)
IHA29 Number of high pulses
IHA30 Mean duration of high pulses (days)
IHA31 Rise rates
5
IHA32 Fall rates
IHA33 Number of hydrologic reversals
Legend:
0,0
1,0
0,5
IHA 28
0,0
IHA 33
IHA 18
IHA27 Number of low pulses
4
IHA 30
IHA 17
IHA 19
Group
IHA 16
0,0
IHA 20
1,5
1,0
0,5
IHA 21
IHA 6
IHA 31
2,0
1,5
1,0
IHA 7
IHA1 January
IHA 27
2,0
IHA 14
IHA 15
1,0
IHA 32
IHA 29
IHA 23
0,5
IHA
10
IHA 33
IHA 18
2,0
IHA 3
0,0
IHA 28
0,0
IHA 19
2,0
IHA
11
IHA 30
IHA 17
IHA 20
IHA 6
IHA 1
3,0
IHA 16
0,0
IHA 21
IHA 5
IHA 8
IHA7 July
IHA 24
IHA 2
IHA 32
0,5
IHA 29
Web index - indicator correspondence
IHA 1
3,0
0,0
IHA 18
1
IHA 28
IHA 18
IHA 19
1,0
IHA 32
IHA 33
IHA
IHA 20
IHA 3
IHA
10
1,0
0,0
IHA 19
0,0
IHA 17
2,0
IHA
11
1,5
IHA 17
Group
iv
IHA
12
0,6
IHA 16
0,5
IHA 30
IHA 33
IHA 31
2,0
0,8
0,4
0,0
1,0
0,0
IHA 7
0,2
Case study number 9: Pracana
1,0
0,5
IHA 16
IHA 21
IHA 6
IHA 8
IHA 15
1,5
IHA 15
IHA 22
IHA 31
2,0
1,5
IHA 23
IHA 5
IHA 29
0,5
IHA 27
2,0
IHA 14
2,0
IHA 4
IHA 32
0,0
0,0
IHA 14
IHA 13
3,0
1,0
0,0
IHA 18
IHA 13
1,0
IHA 24
0,5
0,0
IHA 19
IHA 2
IHA 2
IHA 3
IHA
10
IHA 28
IHA 17
IHA 7
IHA 12
IHA 30
IHA 16
0,0
IHA 1
3,0
2,0
IHA 31
2,0
0,4
0,5
IHA 29
IHA 19
IHA 32
0,6
1,0
IHA 28
IHA 18
IHA 7
0,8
0,0
IHA 17
IHA 20
IHA 6
IHA 8
IHA 27
1,0
IHA 30
IHA 33
IHA 29
0,5
IHA 21
IHA 5
IHA 9
IHA 33
1,5
1,0
0,5
IHA 16
0,0
1,0
0,5
0,2
Case study number 8: Cabril
IHA 9
IHA
11
0,0
IHA 14
IHA 15
IHA 22
IHA 31
2,0
0,0
IHA 18
IHA 13
1,0
IHA 23
IHA 4
Group 5
1,5
1,0
0,0
IHA
12
IHA 28
0,0
IHA 19
IHA 2
IHA 32
0,6
IHA 17
IHA 7
IHA
10
IHA 14
2,0
IHA 3
IHA 31
2,0
0,8
IHA 15
IHA 24
IHA 2
IHA 7
IHA 27
1,0
IHA 14
IHA 21
IHA 6
IHA 27
2,0
IHA 29
0,5
IHA 22
IHA 13
3,0
IHA 8
0,2
Case study number 7: Fronhas
Group 4
IHA 1
3,0
1,0
IHA 18
IHA 13
1,0
Group 2
2,0
IHA
11
0,0
IHA 33
IHA 19
IHA 2
IHA 28
0,0
IHA 17
IHA 7
IHA 12
IHA 15
0,5
1,5
0,6
Group 1
IHA 29
IHA 32
Appendix A. 2 (1/2) - Web diagrams representative of the dimensionless median values for the nine case studies (followed by the
respective legend).
Group 1
IHA 12
IHA 1
1,0
Groups 2 and 5 (Those envolving flows)
IHA 2
IHA 32
0,8
IHA 3
0,4
3,0
IHA 31
IHA 10
1,0
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 22
IHA 21
IHA 6
IHA 1
1,0
IHA 17
IHA 20
IHA 2
IHA 32
IHA 3
IHA 31
1,0
IHA 4
IHA 9
IHA 5
IHA 8
IHA 22
IHA 21
IHA 6
IHA 1
1,0
IHA 17
IHA 20
IHA 2
IHA 32
IHA 3
1,0
IHA 4
0,0
IHA 9
IHA 5
IHA 22
IHA 11
IHA 21
IHA 6
IHA 17
IHA 20
IHA 32
IHA 2
4,0
0,6
3,0
IHA 3
IHA 31
IHA 5
IHA 8
IHA 22
IHA 21
IHA 17
IHA 20
IHA 6
IHA 1
1,0
IHA 18
IHA 19
IHA 2
IHA 32
IHA 13
5,0
0,8
4,0
0,6
3,0
IHA 3
IHA 31
0,4
IHA 9
IHA 5
IHA 6
IHA 7
IHA 15
1,0
IHA 4
0,0
IHA 8
IHA 14
2,0
0,2
IHA 10
IHA 16
0,0
IHA 7
Case study number 5:
Vilar
IHA 15
1,0
IHA 4
IHA 9
IHA 11
IHA 14
2,0
0,0
IHA 12
IHA 13
5,0
0,8
0,2
IHA 10
IHA 18
IHA 19
0,4
Case study number 4:
Paradela
IHA 16
0,0
IHA 7
IHA 1
1,0
IHA 15
2,0
0,2
IHA 12
IHA 14
3,0
IHA 31
0,4
IHA 8
IHA 13
5,0
4,0
0,6
IHA 10
IHA 18
IHA 19
0,8
Case study number 3:
Vilarinho das Furnas
IHA 16
0,0
IHA 7
IHA 11
IHA 15
2,0
0,0
IHA 12
IHA 14
3,0
0,2
IHA 10
IHA 13
5,0
4,0
0,6
0,4
Case study number 2:
Touvedo
IHA 18
IHA 19
0,8
IHA 11
IHA 16
0,0
IHA 7
IHA 12
IHA 15
2,0
0,2
Case study number 1:
Alto Lindoso
IHA 14
4,0
0,6
IHA 11
IHA 13
5,0
IHA 22
IHA 16
0,0
IHA 21
IHA 17
IHA 20
IHA 18
IHA 19
v
Appendix A. 2 (2/2) - Web diagrams representative of the dimensionless median values for the nine case studies (followed by the
respective legend).
Group 1
IHA 1
1,0
IHA 12
Groups 2 and 5 (Those envolving flows)
IHA 2
IHA 32
IHA 13
5,0
IHA 14
4,0
IHA 11
IHA 3
0,5
3,0
IHA 31
IHA 15
2,0
1,0
Case study number 6:
Caldeirão
IHA 10
IHA 4
0,0
IHA 9
IHA 22
IHA 5
IHA 8
IHA 21
IHA 6
IHA 17
IHA 20
IHA 18
IHA 7
IHA 1
1,0
IHA 12
IHA 16
0,0
IHA 19
IHA 2
IHA 32
IHA 13
5,0
IHA 14
4,0
IHA 11
IHA 3
0,5
3,0
IHA 31
IHA 15
2,0
1,0
Case study number 7:
Fronhas
IHA 10
IHA 4
0,0
IHA 9
IHA 22
IHA 5
IHA 8
IHA 21
IHA 6
IHA 17
IHA 20
IHA 18
IHA 7
IHA 1
1,0
IHA 12
IHA 16
0,0
IHA 19
IHA 2
IHA 32
IHA 13
5,0
IHA 14
4,0
IHA 11
IHA 3
0,5
3,0
IHA 31
IHA 15
2,0
1,0
Case study number 8:
Cabril
IHA 10
IHA 4
0,0
IHA 9
IHA 22
IHA 5
IHA 8
IHA 21
IHA 6
IHA 17
IHA 20
IHA 18
IHA 7
IHA 1
1,0
IHA 12
IHA 16
0,0
IHA 19
IHA 2
IHA 32
IHA 13
5,0
IHA 14
4,0
IHA 11
IHA 3
0,5
3,0
IHA 31
IHA 15
2,0
1,0
Case study number 9:
Pracana
IHA 10
IHA 4
0,0
IHA 9
IHA 22
IHA 5
IHA 8
IHA 21
IHA 6
IHA 17
IHA 20
IHA 7
Web index - indicator correspondence
Group
IHA
IHA
IHA1 January
IHA13 Annual minima, 1-day mean
IHA2 February
IHA14 Annual minima, 3-day means
IHA3 March
IHA15 Annual minima, 7-day means
IHA4 April
IHA16 Annual minima, 30-day means
IHA5 May
1
IHA6 June
2
IHA17 Annual minima, 90-day means
IHA18 Annual maxima, 1-day mean
IHA7 July
IHA19 Annual maxima, 3-day means
IHA8 August
IHA20 Annual maxima, 7-day means
IHA9 September
IHA21 Annual maxima, 30-day means
IHA10 October
IHA11 November
IHA12 December
IHA22 Annual maxima, 90-day means
5
IHA31 Rise rates
IHA32 Fall rates
Legend:
vi
IHA 18
IHA 19
Group
IHA 16
0,0
Appendix A. 3 (1/3) - Dimensionless flow duration curves for the natural and modified regimes for the nine case
studies.
Case study number 1: Alto Lindoso
5,00
4,50
Daily flow (m3/s)
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
200
250
300
350
Days
250
300
350
Days
300
350
Days
Case study number 2: Touvedo
5,00
4,50
Daily flow (m3/s
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
200
Case study number 3: Vilarinho das Furnas
5,00
4,50
Daily flow (m3/s
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
200
250
Legend:
vii
Appendix A. 3 (2/3) - Dimensionless flow duration curves for the natural and modified regimes for the nine case
studies.
Case study number 4: Paradela
5,00
4,50
Daily flow (m3/s)
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
200
250
300
350
Days
250
300
350
Days
250
300
350
Days
Case study number 5: Vilar
5,00
4,50
Daily flow (m3/s)
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
200
Case study number 6: Caldeirão
5,00
4,50
Daily flow (m3/s)
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
Legend:
viii
100
150
200
Appendix A. 3 (3/3) - Dimensionless flow duration curves for the natural and modified regimes for the nine case
studies.
Case number 7: Fronhas
5,00
4,50
Daily flow (m3/s)
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
200
250
300
350
Days
250
300
350
Days
250
300
350
Days
Case study number 8: Cabril
5,00
4,50
Daily flow (m3/s)
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
200
Case study number 9: Pracana
5,00
4,50
Daily flow (m3/s)
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
0
50
100
150
200
Legend:
ix
Appendix A. 4 (1/3) - Monthly mean daily flows for the natural and modified regimes for the nine case studies.
Daily flow (m3/s)
Case study number 1: Alto Lindoso
90
80
70
60
50
40
30
20
10
0
1
2
3
4
5
6
7
8
9
10
9
10
11
12
Month
Case study number 2: Touvedo
Daily flow (m3/s)
120
100
80
60
40
20
0
1
2
3
4
5
6
7
8
11
12
Month
Case study number 3: Vilarinho das Furnas
Daily flow (m3/s)
7
6
5
4
3
2
1
0
1
2
3
4
5
6
7
Month
Legend:
x
8
9
10
11
12
Appendix A. 4 (2/3) - Monthly mean daily flows for the natural and modified regimes for the nine case studies.
Daily flow (m3/s)
Case study number 4: Paradela
9
8
7
6
5
4
3
2
1
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Case study number 5: Vilar
Daily flow (m3/s)
6
5
4
3
2
1
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Daily flow (m3/s)
Case study number 6: Caldeirão
5
5
4
4
3
3
2
2
1
1
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Legend:
xi
Appendix A. 4 (3/3) - Monthly mean daily flows for the natural and modified regimes for the nine case studies.
Case study number 7: Fronhas
Daily flow (m3/s)
35
30
25
20
15
10
5
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Case study number 8: Cabril
Daily flow (m3/s)
70
60
50
40
30
20
10
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Case study number 9: Pracana
Daily flow (m3/s)
30
25
20
15
10
5
0
1
2
3
4
5
6
7
Month
Legend:
xii
8
9
10
11
12
A p p e n di x A. 5 - R a ti o s of alter a tio n ( R 3 ) f or t h e ni n e c a s e st u di e s.
1
Alto
Lindoso
IHA
Group
1
IHA1
IHA2
IHA3
IHA4
IHA5
IHA6
IHA7
IHA8
IHA9
IHA10
IHA11
IHA12
2
IHA13
IHA14
IHA15
IHA16
IHA17
IHA18
IHA19
IHA20
IHA21
IHA22
IHA23
IHA24
January
February
March
April
May
June
July
August
September
October
November
December
Annual minima, 1-day mean
Annual minima, 3-day means
Annual minima, 7-day means
Annual minima, 30-day means
Annual minima, 90-day means
Annual maxima, 1-day mean
Annual maxima, 3-day means
Annual maxima, 7-day means
Annual maxima, 30-day means
Annual maxima, 90-day means
Number of zero-flow days
Base flow index
m³/s
m³/s
days
-
2
Touvedo
3
Vilarinho
das Furnas
4
5
6
7
8
9
Paradela
Vilar
Caldeirão
Fronhas
Cabril
Pracana
0,86
0,94
0,72
0,86
1,00
0,96
0,76
0,64
0,39
0,63
0,96
0,90
0,94
0,91
0,83
0,93
0,65
0,74
0,84
0,81
0,71
0,60
0,76
0,70
0,05
0,07
0,09
0,09
0,15
0,30
0,39
0,51
0,70
0,12
0,10
0,08
0,00
0,00
0,00
0,00
0,00
0,05
0,31
0,84
0,74
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,29
0,12
0,13
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,95
0,76
0,94
0,76
0,66
0,53
0,15
0,10
0,20
0,39
0,80
1,00
0,62
0,74
0,68
0,93
0,14
0,00
0,00
0,00
0,00
0,35
0,79
0,55
0,00
0,00
0,27
0,89
0,74
0,75
0,83
0,81
0,85
0,89
0,01
0,28
0,00
0,00
0,11
0,60
0,72
0,87
1,00
0,98
0,91
0,97
0,02
0,12
0,05
0,26
0,34
0,86
0,38
0,06
0,05
0,03
0,03
0,04
0,58
0,02
0,00
0,00
0,00
0,09
0,12
0,13
0,06
0,07
0,19
0,00
0,00
0,00
0,00
0,00
0,00
0,18
0,15
0,17
0,12
0,07
0,02
0,00
0,00
0,00
0,00
0,00
0,00
0,21
0,14
0,07
0,03
0,02
0,02
0,00
0,00
0,00
0,00
0,00
0,00
0,43
0,61
0,62
0,45
0,35
0,01
0,00
0,00
0,74
0,33
0,31
0,84
0,81
0,79
0,91
0,89
0,28
0,30
0,88
0,14
0,72
0,87
0,90
1,00
0,99
0,51
-
3
IHA25 Julian date of each annual 1-day minimum
IHA26 Julian date of each annual 1-day maximum
days
0,21
0,80
0,31
0,84
0,28
0,44
0,01
0,59
0,01
0,13
0,01
0,42
0,03
0,67
0,45
0,58
0,08
0,79
4
IHA27
IHA28
IHA29
IHA30
Number of low pulses
Median duration of low pulses
Number of high pulses
Median duration of high pulses
days
days
0,62
0,92
0,37
0,59
0,96
0,71
0,96
0,80
0,03
0,06
0,16
0,12
0,00
0,00
0,37
0,87
0,00
0,00
0,09
0,16
0,00
0,00
0,06
0,83
0,00
0,00
0,21
0,64
0,89
1,00
0,46
0,39
0,35
0,22
5
IHA31 Rise rates
IHA32 Fall rates
IHA33 Number of hydrologic reversals
m³/s
m³/s
-
0,30
0,34
0,99
0,99
0,99
0,88
0,15
0,09
0,04
0,78
0,53
0,09
0,06
0,06
0,01
0,04
0,06
0,00
0,08
0,18
0,05
0,31
0,37
0,95
0,14
0,19
0,69
Low alteration: RA3 > 0,67;
Moderate alteration: 0,67 > RA3 > 0,33;
High alteration: RA3 < 0,33
xiii
xiv
APPENDIX B. - RESULTS RELATIVE TO CHAPTER V
LIST OF APPENDICES
Appendix B. 1 - Web diagrams for the dimensionless 25% and 75% percentiles for Covas and EDP data
(followed by respective legend). ................................................................................................................. iii
Appendix B. 2 - Web diagrams representative of the dimensionless median values for Covas and EDP
data (followed by respective legend). ......................................................................................................... iv
Appendix B. 3 - Monthly mean daily flows for the natural and the modified regimes for Covas and EDP
data............................................................................................................................................................... v
Appendix B. 1 - Web diagrams for the dimensionless 25% and 75% percentiles for Covas and EDP data (followed by
respective legend).
Group 2
Group 4
IHA 1
1,0
IHA 13
1,0
IHA 27
1,0
IHA 24
IHA 3
IHA 23
IHA 14
0,5
IHA 31
2,0
0,8
1,5
0,6
IHA 15
1,0
0,4
0,2
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 22
IHA 21
IHA 6
IHA 12
IHA 1
3,0
IHA 30
IHA 20
IHA 2
IHA 33
IHA 3
IHA 32
IHA 29
IHA 13
3,0
IHA 14
2,0
IHA 11
0,0
IHA 18
IHA 19
IHA 24
2,0
0,5
IHA 28
0,0
IHA 17
IHA 7
According to Covas stream gauging station
data
IHA 16
0,0
IHA 23
IHA 27
2,0
IHA 31
2,0
1,5
1,5
1,0
1,0
IHA 15
1,0
1,0
0,5
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 22
IHA 12
IHA 11
IHA 30
IHA 24
IHA 2
IHA 3
0,0
IHA 33
IHA 20
IHA 23
IHA 32
IHA 18
IHA 29
IHA 19
0,5
0,5
IHA 28
0,0
IHA 17
IHA 7
IHA 1
1,0
IHA 16
0,0
IHA 21
IHA 6
25% percentile
IHA 2
0,5
Group 5
75% percentile
IHA 12
IHA 11
Group 1
IHA 13
1,0
IHA 27
1,0
IHA 14
IHA 15
0,5
0,8
IHA 31
2,0
0,6
1,5
0,4
1,0
25% percentile
Vilarinho das Furnas case study
0,2
IHA 10
IHA 4
0,0
IHA 22
IHA 16
0,0
IHA 30
0,5
IHA 28
0,0
0,0
IHA 5
IHA 21
IHA 17
IHA 33
IHA 8
IHA 6
IHA 20
IHA 7
According to EDP data
IHA 12
IHA 1
3,0
IHA 19
IHA 2
IHA 24
2,0
IHA 11
IHA 3
IHA 32
IHA 18
IHA 13
3,0
IHA 29
IHA 27
2,0
IHA 14
IHA 31
2,0
1,5
1,5
2,0
IHA 23
1,0
IHA 15
1,0
1,0
1,0
75% percentile
IHA 9
0,5
0,5
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 6
IHA 22
IHA 21
Web index - indicator correspondence
1
IHA
Group
IHA 20
0,0
IHA 33
IHA 32
IHA 29
IHA 19
IHA
IHA13 Annual minima, 1-day mean
IHA2 February
IHA14 Annual minima, 3-day means
IHA3 March
IHA15 Annual minima, 7-day means
IHA4 April
IHA16 Annual minima, 30-day means
IHA5 May
IHA17 Annual minima, 90-day means
IHA6 June
IHA18 Annual maxima, 1-day mean
2
IHA 28
0,0
IHA 18
IHA1 January
IHA7 July
IHA 30
IHA 17
IHA 7
Group
IHA 16
0,0
IHA19 Annual maxima, 3-day means
IHA8 August
IHA20 Annual maxima, 7-day means
IHA9 September
IHA21 Annual maxima, 30-day means
IHA10 October
IHA22 Annual maxima, 90-day means
IHA11 November
IHA23 Number of zero-flow days
IHA12 December
IHA24 Base flow index
Group
IHA
IHA27 Number of low pulses
4
IHA28 Mean duration of low pulses (days)
IHA29 Number of high pulses
IHA30 Mean duration of high pulses (days)
IHA31 Rise rates
5
IHA32 Fall rates
IHA33 Number of hydrologic reversals
Legend:
iii
Appendix B. 2 - Web diagrams representative of the dimensionless median values for Covas and EDP data (followed by
respective legend).
Vilarinho das Furnas case
study
Group 1
IHA 1
1,0
IHA 12
Groups 2 and 5 (Those envolving flows)
IHA 2
IHA 32
IHA 13
5,0
IHA 14
4,0
IHA 11
IHA 3
0,5
3,0
IHA 31
IHA 15
2,0
According to Covas
stream gauging station
data
1,0
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 22
IHA 21
IHA 6
IHA 17
IHA 20
IHA 7
IHA 1
1,0
IHA 12
IHA 16
0,0
IHA 18
IHA 19
IHA 2
IHA 32
IHA 13
5,0
IHA 14
4,0
IHA 11
IHA 3
0,5
3,0
IHA 31
IHA 15
2,0
1,0
According to EDP data
IHA 10
IHA 4
0,0
IHA 9
IHA 5
IHA 8
IHA 22
IHA 21
IHA 6
IHA 17
IHA 20
IHA 7
Web index - indicator correspondence
Group
IHA
IHA13 Annual minima, 1-day mean
IHA2 February
IHA14 Annual minima, 3-day means
IHA3 March
IHA15 Annual minima, 7-day means
IHA4 April
1
IHA
IHA1 January
IHA5 May
IHA6 June
IHA16 Annual minima, 30-day means
2
IHA17 Annual minima, 90-day means
IHA18 Annual maxima, 1-day mean
IHA7 July
IHA19 Annual maxima, 3-day means
IHA8 August
IHA20 Annual maxima, 7-day means
IHA9 September
IHA21 Annual maxima, 30-day means
IHA10 October
IHA11 November
IHA12 December
IHA22 Annual maxima, 90-day means
5
IHA31 Rise rates
IHA32 Fall rates
Legend:
iv
IHA 18
IHA 19
Group
IHA 16
0,0
Appendix B. 3 - Monthly mean daily flows for the natural and the modified regimes for Covas and EDP data.
Case study: Vilarinho das Furnas according to EDP
Daily flow (m3/s)
7
6
5
4
3
2
1
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Daily flow (m3/s)
Case study: Vilarinho das furnas according to Covas stream gauging station
9
8
7
6
5
4
3
2
1
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Legend:
v
vi