Development of indexes of alteration of the hydrologic ...€¦ · to the research carried out. Artur Silva also deserves a word of acknowledgement, given his availability and support

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: Supervisors:

Members of the Commitee:

António Alexandre Trigo Teixeira, PhD Maria Manuela Portela Correia dos Santos Ramos da Silva, PhD Francisca Constança Frutuoso de Aguiar, PhD 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)

iii

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.

iv

v

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.

vi

vii

To my dear grandfather

viii

ix

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/AAC-

AMB/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.

x

xi

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

xii

xiii

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

xiv

xv

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

xvi

xvii

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

Qmod Long-term average of the mean daily flows or, in other words, the modulus (m3/s)

Qmod Natural Natural condition modulus (m3/s)

Qmod Modified Modified condition modulus (m3/s)

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 (km2)

Mean daily flow on Julian day i, for the section respecting to gauging station (m

3/s)

Natural modulus considering gauging station (m

3/s)

xviii

xix

LIST OF APPENDICES

Appendix A. - Results relative to Chapter IV

Appendix B. - Results relative to Chapter V

xx

1

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.

2

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.

3

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.

4

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

5

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 Ecological response

Magnitude and

frequency

Increased variation

(low/high flows; peak flows)

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

Flow stabilization

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

Timing Loss of seasonal flow peaks

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

6

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

Duration

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

Prolonged inundation

Change in vegetation functional type

Tree mortality

Loss of rifle habitat for aquatic species

Rate of change

Rapid changes in river stage

Wash-out and stranding of aquatic species

Decreased germination survival and growth of plants

Low abundance and shifts in waterbird assemblages

Accelerated flood recession 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

7

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.

8

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.

9

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.

10

II.3 INDICATORS OF HYDROLOGIC ALTERATION (IHA)

II.3.1 THE 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).

11

Table II - Outputs returned by IHA Version 7.1 software (for non-parametric analysis).

Single period analysis Pre- and post-impact comparison analysis

Tab

les

Annual summaries table (“ann”)

Scorecard table (“sco”)

Regression table (“lsq”)

Percentile table (“pct”)

EFC daily table (“daily efcs”)

Flow duration curve data table (“fdc”)

Annual summaries table

Scorecard table

RVA table

Box-and-Whisker table

Regression table

Percentile table

EFC daily table

Flow duration curve data table

Gra

ph

ics IHA parameters annual data

EFC parameters annual data

Daily data

Flow duration curves

IHA parameters annual data

EFC parameters annual data

Hydrologic alteration

Monthly averages

Daily data

Flow duration curves

II.3.2 THE 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 Flow regime characteristics Indicators of Hydrologic Alteration, IHAi

1. Magnitude of monthly

water conditions

Magnitude/

timing IHA1 to IHA12 Mean

1 value for each calendar month

2. Magnitude and duration

of annual extreme water

conditions

Magnitude/

duration

IHA13 Annual minima, 1-day mean

IHA14 Annual minima, 3-day means




IHA18 Annual maxima, 1-day mean

IHA19 Annual maxima, 3-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

12

Table III (2/2) - Indicators of Hydrologic Alteration, for one year of daily records.

IHA group Flow regime characteristics Indicators of Hydrologic Alteration, IHAi

4. Frequency and duration of

high/low pulses

Magnitude/

frequency/

duration

IHA27 Number of low pulses

IHA28 Mean1 duration of low pulses (days)

IHA29 Number of high pulses

IHA30 Mean1 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 Description of the indicator

(for a non-parametric analysis)

IHA1 to IHA12 Median flow value for each calendar month

Median daily flow for each calendar month

IHA13 Annual minima, 1-day Minimum flow value of the year

IHA14 Annual minima, 3-day means Minimum value for the mean daily flow of 3 consecutive days of the year




IHA18 Annual maxima, 1-day Maximum flow value of the year

IHA19 Annual maxima, 3-day means Maximum value for the mean daily flow of 3 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

IHA25 Julian date of each annual 1-day minimum Order number of the day of the year when the minimum flow was registered

IHA26 Julian date of each annual 1-day maximum Order number of the day of the year when the maximum flow was registered

IHA27 Number of low pulses Number of times in a year that the flow is lower than the 25% percentile of the flows of the period in analysis

IHA28 Median duration of low pulses (days) Median of the duration of the low pulses

IHA29 Number of high pulses Number of times in a year that the flow is higher than the 75% percentile of the flows of the period in analysis

IHA30 Median duration of high pulses (days) Median of the duration of the high pulses

IHA31 Rise rates Median of all positive differences between consecutive daily values

IHA32 Fall rates Median of all negative differences between consecutive daily values

IHA33 Number of hydrologic reversals Number of times that the tendency of the daily flow changes

13

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

1. Magnitude of

monthly water

conditions

Habitat availability for aquatic organisms

Soil moisture availability for plants

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

2. Magnitude and

duration of annual

extreme water

conditions

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

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 concentrated chemicals in aquatic

environments

Distribution of plant communities in lakes, ponds, floodplains

Duration of high flows for waste disposal, aeration of spawning beds in channel sediments

3. Timing of annual

extreme water

conditions

Compatibility with life cycles of organisms

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

4. Frequency and

duration of high and

low pulses

Frequency and magnitude of soil moisture stress for plants

Frequency and duration of anaerobic stress for plants

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

14

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

alteration. The methodology is summarized in Figure 1.

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.

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 H

ow

to

ch

ara

cte

rize

th

e

nat

ura

l re

gim

e?

Compare the reference condition with the actual state: Define the partial IHA

Ho

w d

o w

e e

valu

ate

th

e a

lte

rati

on

of

the

flo

w r

egi

me

?

Obtain the values of the parameters for the altered regime: actual condition

Systematize and simplify: Global alteration indicators

Evaluation of the hydrologic level

Environmental diagnosis

15

Table VI - Parameters for the characterization of the flow regime (adapted from Martínez Santa-María & al., 2010).

Regime component Aspect Parameter

Habitual

data

Monthly or

annual

volumes

Magnitude Average of the annual volumes

Type of

year

Wet year

Normal year

Dry year

Weighted year (P1)

Variability Difference between the maximum and the

minimum monthly volume along the year

Type of

year

Wet year

Normal year

Dry year

Weighted year (P2)

Seasonality Month with the maximum and the minimum

water volume along the year

Type of

year (P3)

Wet year

Normal year

Dry year

Daily flow Variability Difference between the average flows

associated to the percentiles 10% and 90% Q10%-Q90% (P4)

Extreme

data

Maximum

values of the

daily flows

(Floods)

Magnitude

and

frequency

Average of the maximum daily flows along the

year Qc (P5)

Effective discharge QGL (P6)

Connectivity discharge QCONEC (P7)

Flushing flood Q5% (P8)

Variability

Coefficient of variation of the maximum daily

flows along the year CV (Qc) (P9)

Coefficient of variation of the ordinary floods

series CV (Q5%) (P10)

Duration Maximum number of consecutive days

in the year with flow higher than Q5% Flood duration (P11)

Seasonality Average number of days in the month

with flow higher than Q5%

12 values (one for each

month) (P12)

Minimum

values of the

daily flows

(Droughts)

Magnitude

and

frequency

Average minimum daily flows along the year Qs (P13)

Ordinary drought discharge Q95% (P14)

Coefficient of variation of the minimum daily

flows along the year CV (Qs) (P15)

Coefficient of variation of the ordinary

droughts series CV (Q95%) (P16)

Duration

Maximum number of consecutive days in the

year with flow lower than Q95% Droughts duration (P17)

Average number of days in the month with a

daily flow equal to zero


month) (P18)

Seasonality Average number of days in the month

with flow lower than Q95%


month) (P19)

Note: The x% percentile indicates the value below which a given percentage x of observations in a group of observations fall.

16

Table VII - Indicators of Alteration in Rivers for contemporary regimes (adapted from Martínez Santa-María & Fernández

Yuste, 2010).

Aspect IHAR i Description Source

parameter

Habitual

Values

Magnitude IHAR 1 Magnitude of annual volumes

P1 IHAR 2 Magnitude of monthly volumes

Variability IHAR 3 Habitual variability P4

IHAR 4 Extreme variability P2

Seasonality IHAR 5 Seasonality of maximum values

P3 IHAR 6 Seasonality of minimum values

Floods

Magnitude and frequency

IHAR 7 Magnitude of the maximum floods P5

IHAR 8 Magnitude of the effective discharge P6

IHAR 9 Magnitude of the connectivity discharge P7

IHAR 10 Magnitude of the flushing floods P8

Variability IHAR 11 Variability of the maximum floods P9

IHAR 12 Variability of the flushing floods P10

Duration IHAR 13 Floods duration P11

Seasonality IHAR 14 Floods seasonality1 P12

Droughts

Magnitude and frequency IHAR 15 Magnitude of the extreme droughts P13

IHAR 16 Magnitude of the habitual droughts P14

Variability IHAR 17 Variability of the extreme droughts P15

IHAR 18 Variability of the habitual droughts P16

Duration IHAR 19 Droughts duration P17

IHAR 20 Number of days with null flow1 P18

Seasonality IHAR 21 Droughts seasonality1 P19

1 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.

17

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.

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).

Hydraulic energy

Dam Mechanic

energy Turbine

Electric energy

Alternator

18

In this context, nine river reaches affected by an upstream hydropower dam and having daily flow data were

selected (Figure 3).

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.

N

19

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.

Touvedo dam

Alto Lindoso dam

Alto Lindoso powerhouse

N

2 km

20

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.

Vilarinho das Furnas dam

Vilarinho das Furnas powerhouse

N

1 km

21

Legend:

Figure 6 (up) - Case study 4 - Paradela (EDP) and Figure 7 (down) - Case study 5 - Vilar (Comissão Nacional Portuguesa das

Grandes Barragens).

Paradela dam

Vilar dam

Tabuaço powerhouse

Confluence of Douro and Távora

Rivers

N

N

Vila Nova powerhouse

2 km

1 km

22

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.

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.

Caldeirão dam

Confluence of Caldeirão and Mondego Rivers

Caldeirão powerhouse N

200 m

23

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.

Legend:

Figure 10 - Case study 8 - Cabril (Comissão Nacional Portuguesa das Grandes Barragens).

Fronhas dam

Aguieira powerhouse

Confluence of Alva and Mondego Rivers

Cabril dam

N

N

1 km

2 km

24

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.

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).

SystemMain

watershedRiver

Watershed

area (km²)

Starting operation

date

Installed

capacity

(MW)

1 Alto Lindoso Cávado‑Lima Lima Lima River 1525 Energy 1992 630

2 Touvedo Cávado‑Lima Lima Lima River 1700 Energy/i rrigation/flood protection 1993 22

3Vi larinho das

FurnasCávado‑Lima Cávado Homem River 77 Energy 1972 and 1987 125

4 Paradela Cávado‑Lima Cávado Cávado River 168 Energy 1956¹/1958² 54

5 Vi lar Douro Douro Távora River 359 Energy 1965 58

6 Caldeirão Tejo-Mondego Mondego Caldeirão Stream 38 Water supply/i rrigation/energy 1993¹/1994² 40

7 Fronhas Tejo-Mondego Mondego Alva River 652 Energy 1985 -

8 Cabri l Tejo-Mondego Tejo Zêzere River 2340 Energy 1954 108

9 Pracana Tejo-Mondego Tejo Ocreza River 1410 Energy 1944/50 and 1993³ 41

Dam

Uses

Powerhouse

Case study

Pracana dam

Confluence of Ocreza and Tejo Rivers

N

500 m

25

Table VIII - Characteristics of the case studies (2/2).

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.

Water delivered

directly to the river

Water delivered to a

reservoir

1 Alto Lindoso X X4

2 Touvedo X X

3Vi larinho

das FurnasX X

4 Paradela X X

5 Vi lar X X

6 Caldeirão X X

7 Fronhas X X

8 Cabri l X X

9 Pracana X X

Case study Run-of-river or

with small storage

capacity

Reservoir

With storage

capacity

With water transfer between

riversWithout water transfer between rivers

To a reservoir Directly to a riverToe of the dam

powerhouse

Hydraulic circuit relatively long

http://www.edp.pt/

26

Table IX - Years considered for each case study.

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

(m3/s) (m

3/s)

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

1Code 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).

Case study Flow conditions 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Natural 22 54 156 269 326 301 333 347 352 354 333 330 304 356 360

Modified 54 156 270 329 303 335 347 350 344 333 330 304 356 360

Natural 275 365 365 366 365 365 365 366 365 365 333 339 347 346 341 328 335 352 358

Modified 56 156 269 328 300 335 339 347 346 341 328 335 357 359

Natural 366 365 365 365 366 365 365 365

Modified 366 365 365 365 366 365 365 365

Natural 99 269 177 279 328 321 333 332 348 339 342 325 335 351 357

Modified 53 273 177 289 334 323 336 334 348 340 342 325 335 356 358

Natural 366 365 365 365 366 365 365 365

Modified 366 365 365 365 366 365 365 365

Natural 366 365 365 365 366 365 365 365

Modified 366 365 365 365 366 365 365 365

Natural 366 365 365 365 366 365 365 365

Modified 366 365 365 365 366 365 365 365

Natural 366 365 365 365 366 365 365 365

Modified 366 365 365 365 366 365 365 365

Natural 366 365 365 365 366 365 365 365

Modified 366 365 365 365 366 365 365 365

6

7

8

9

1

2

4

3

5

27

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.

28

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.

Covas Stream Gauging Station

Confluence of Homem and Cávado Rivers

Vilarinho das Furnas powerhouse

Vilarinho das Furnas dam N

2 km

29

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 ALTO 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 Inflow (m3/s) Date Inflow (m

3/s)

01-01-2001 499,82 (…)

03-01-2001 451,56 25-12-2011 22,91

04-01-2001 373,2 26-12-2011 30,52

05-01-2001 920,14 27-12-2011 17,93

06-01-2001 FALSE 28-12-2011 24,19

08-01-2001 174,53 29-12-2011 18,98

09-01-2001 240,66 30-12-2011 17,05

10-01-2001 239,3 31-12-2011 23,02

11-01-2001 311,14

12-01-2001 FALSE

13-01-2001 152,99

(…)

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

30

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

Parameter Group #2

1 entrada 1-day minimum 0,43 m3/s 4,372

3-day minimum 1,573 m3/s 1,574

Period of Analysis: 2001-2011 ( 11 years) 7-day minimum 2,659 m3/s 1,035

NormalizationFactor 1 30-day minimum 4,801 m3/s 0,5644

Mean annual flow 39,85 90-day minimum 8,185 m3/s 0,4042

Non-Normalized Mean Flow 39,85 1-day maximum 373,1 m3/s 0,787

Annual C. V. 1,69 3-day maximum 317,6 m3/s 0,6688

Flow predictability 0,44 7-day maximum 244,2 m3/s 0,7492

Constancy/predictability 0,49 30-day maximum 137,1 m3/s 0,6388

% of floods in 60d period 0,32 90-day maximum 87,84 m3/s 0,7071

Flood-free season 45 Number of zero days 0 days 0

Base flow index 0,07111 - 1,049

Medians Coeff. of Disp.

Parameter Group #3

Parameter Group #1 Date of minimum 253 days 0,112

January 34,15 m3/s 2,943 Date of maximum 21 days 0,2896

February 49,01 m3/s 0,9678

March 43,12 m3/s 0,9956 Parameter Group #4

April 26,32 m3/s 1,364 Low pulse count 24 - 0,2917

May 15,96 m3/s 0,7149 Low pulse duration 2 days 0,25

June 13,16 m3/s 0,6648 High pulse count 9 - 0,4444

July 13,78 m3/s 0,5254 High pulse duration 2 days 0,5

August 7,22 m3/s 0,8982 Low Pulse Threshold 9,55

September 6,535 m3/s 0,6128 High Pulse Threshold 43,85

October 15,06 m3/s 2,201

November 28,79 m3/s 1,091 Parameter Group #5

December 30,52 m3/s 1,944 Rise rate 3,7 m3/s 0,373

Fall rate -4,36 m3/s -0,3716

Number of reversals 188 - 0,09574

31

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”).

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.

IHA Percentile Data

1 entrada

Period of Analysis: 2001-2011 ( 11 years)

Period of Analysis

10% 25% 50% 75% 90%

Parameter Group #1

January 15,92 19,61 34,15 120,1 218,3 m3/s

February 12,07 17,61 49,01 65,04 105,1 m3/s

March 11,17 15,89 43,12 58,82 233,7 m3/s

April 12,62 18,03 26,32 53,92 57,35 m3/s

May 12,95 14,89 15,96 26,3 41,58 m3/s

June 7,864 8,59 13,16 17,34 22,67 m3/s

July 6,012 9,51 13,78 16,75 21,86 m3/s

August 1,314 3,905 7,22 10,39 14,04 m3/s

September 3,259 4,35 6,535 8,354 9,19 m3/s

October 3,544 6,75 15,06 39,89 53,55 m3/s

November 4,096 17,09 28,79 48,51 82,55 m3/s

December 4,786 15,08 30,52 74,41 152,7 m3/s

Parameter Group #2

1-day minimum 0 0,04 0,43 1,92 2,238 m3/s

3-day minimum 0,01667 0,49 1,573 2,967 3,176 m3/s

7-day minimum 0,1857 1,68 2,659 4,431 5,041 m3/s

30-day minimum 1,943 3,389 4,801 6,099 8,573 m3/s

90-day minimum 4,556 6,27 8,185 9,578 12,03 m3/s

1-day maximum 182,7 275,2 373,1 568,9 1004 m3/s

3-day maximum 143,8 226,2 317,6 438,6 761,6 m3/s

7-day maximum 109,8 138,7 244,2 321,7 582,8 m3/s

30-day maximum 49,47 82,02 137,1 169,6 318,4 m3/s

90-day maximum 30,79 39,05 87,84 101,2 241,4 m3/s

Number of zero days 0 0 0 0 6,8 days

Base flow index 0,00692 0,03577 0,07111 0,1104 0,1807 -

Parameter Group #3

Date of minimum 174 225 253 266 286,4 days

Date of maximum 302,6 341 21 81 104,6 days

Parameter Group #4

Low pulse count 15,4 19 24 26 33,4 -

Low pulse duration 1 1,5 2 2 2 days

High pulse count 4,4 8 9 12 15 -

High pulse duration 1,1 2 2 3 4,9 days

Parameter Group #5

Rise rate 2,676 3,16 3,7 4,54 5,684 m3/s

Fall rate -6,417 -5,02 -4,36 -3,4 -3,331 m3/s

Number of reversals 155,6 182 188 200 207,6 -

32

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.

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

25% 50% 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

July 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 15,08 30,52 74,41 0,49 2,44 8,36 21,35 76,59 0,27 2,51

Annual minima, 1-day 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 maxima, 1-day 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




Number of zero-flow days days 0 0 0 - -- 34 69 95 -- --

Base flow index -- 0,04 0,07 0,11 0,50 1,55 0 0 0,03 0,00 0,41

Julian date of each annual 1-day maximum 225 253 266 0,89 1,05 1 41 107 0,00 0,42

Julian date of each annual 1-day minimum 341 21 81 16,24 3,86 364 36 62 17,33 2,95

Number of low pulses -- 19 24 26 0,79 1,08 32 37 46 1,33 1,92

Median duration of low pulses (days) days 1,5 2 2 0,75 1,00 1 2 2 0,50 1,00

Number of high pulses -- 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

Number of hydrologic reversals -- 182 188 200 0,97 1,06 178 184 199 0,95 1,06

Group IHA

Natural regime Modified regime

Percentile Percentile

From the IHA software Dimensionless From the IHA software Dimensionless

4

5

1 m³/s

2

m³/s

3 days

33

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.

Figure 13 - Example, based on Alto Lindoso case study, of the web diagrams for the dimensionless 25% and 75%

percentiles.

Percentile Group 1 Group 2 Group 4 Group 5

25%

75%

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 300,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 300,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

Group Group Group

IHA1 January IHA13 Annual minima, 1-day mean IHA27 Number of low pulses

IHA2 February IHA14 Annual minima, 3-day means IHA28 Mean duration of low pulses (days)

IHA3 March IHA15 Annual minima, 7-day means IHA29 Number of high pulses

IHA4 April IHA16 Annual minima, 30-day means IHA30 Mean duration of high pulses (days)

IHA5 May IHA17 Annual minima, 90-day means IHA31 Rise rates

IHA6 June IHA18 Annual maxima, 1-day mean IHA32 Fall rates

IHA7 July IHA19 Annual maxima, 3-day means IHA33 Number of hydrologic reversals

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

2

IHA

Legend:

Web

ind

ex -

ind

icat

or

corr

esp

on

den

ce

4

5

IHA IHA

1

34

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.

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.

Group Natural regime Modified regime

January 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

December 0,77 0,54

Annual minima, 1-day 0,01 0,00

Annual minima, 3-day means 0,04 0,00




Annual maxima, 1-day 9,36 5,30

Annual maxima, 3-day means 7,97 4,60




Rise rates 0,00 1,73

Fall rates 0,00 0,00

m3/s

IHA

1

2

5

35

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.

Group 1 Groups 2 and 5 (Those envolving flows)

0,0

0,2

0,4

0,6

0,8

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

Group Group

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 IHA17 Annual minima, 90-day means

IHA6 June IHA18 Annual maxima, 1-day mean

IHA7 July IHA19 Annual maxima, 3-day means




IHA11 November IHA31 Rise rates

IHA12 December IHA32 Fall rates5

Legend:

Web

ind

ex -

ind

icat

or

corr

esp

on

den

ce

IHA IHA

1

2

36

Table XVI - Example based on Alto Lindoso case study. Dimensionless flow duration curves for the natural and modified

regimes.

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

Natural regime Modified regime Natural regime Modified regime

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

Excendence probability DaysQ (m3/s) Q/Qmod natural

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

)

Days

Natural modified Modified regime

37

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

mean daily flows along the year somehow decreases in the 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:

0

10

20

30

40

50

60

70

80

90

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3/s

)

Month

Natural regime Modified regime

38

{

{

}

( 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

39

patterns of case studies number 1 and 2, which can be explained by the fact that case 2 - Touvedo, of the run-

of-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.

40

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.

41

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 COVAS 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.

42

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 A Qmod Natural Qmod Modified

(km²) (m3/s) (m

3/s)

EDP [1] 1/1/2004 - 31/12/2011 77,00 5,43 0,34

SNIRH (Covas S.G.S.) [2] 1/1/1956 - 31/12/1971

118,15 8,87 -

1/1/1972 - 31/12/2003 - 2,86

Ratio 0,65 0,61 0,12

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

and of the station (approximately 41 km2) 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.

43

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.

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

0 50 100 150 200 250 300 350

Dim

en

sio

nle

ss f

low

(Q

/Qm

od n

atu

ral)

Days

Natural regime (EDP) Natural regime (Covas)

Modified regime (EDP) Modified regime (Covas)

44

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.

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 SNIRH code A (km2) (mm) Qmod Natural (m

3/s)

Covas 03H/04H 116 2212 8,87

Fragas da Torre 08H/02H 660 997 21,98

0

2

4

0 100 200 300

Duration (day)

a)Q/Qmod

0

2

4

0 100 200 300Duration (day)

b)Q/Qmod

0

2

4

0 100 200 300Duration (day)

c)Q/Qmod

45

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 gauging station (m

3/s);

- natural modulus considering gauging station (m

3/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.

46

Figure 21 - Daily (a), monthly (b) and annual (c) flows at Covas stream gauging station. Registered and reconstructed

based on Fragas da Torre.

0

50

100

150

200

250

3-Oct-54 20-Dec-62 8-Mar-71 25-May-79 11-Aug-87 28-Oct-95 14-Jan-04

Dai

ly f

low

(m

³/s)

Day

0

500

1000

1500

2000

2500

Oct-54 Aug-61 Jun-68 Apr-75 Feb-82 Dec-88 Oct-95 Sep-02

Mo

nth

ly f

low

(m

³/s)

Month

0

1000

2000

3000

4000

5000

6000

1955 1960 1965 1970 1975 1980 1985 1990 1995 2000

An

nu

al f

low

(m

³/s)

Year

a)

b)

c)

47

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 post-

dam 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).

Low alteration: RA3 > 0,67; Moderate alteration: 0,33 < RA3 < 0,67; 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

Group

IHA1 January 0,05 0,33 0,33

IHA2 February 0,07 0,35 0,28

IHA3 March 0,09 0,32 0,36

IHA4 April 0,09 0,35 0,39

IHA5 May 0,15 0,47 0,34

IHA6 June 0,30 0,49 0,43

IHA7 July 0,39 0,75 0,59

IHA8 August 0,51 1,00 0,99

IHA9 September 0,70 0,55 0,98

IHA10 October 0,12 0,31 0,44

IHA11 November 0,10 0,30 0,35

IHA12 December 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




IHA18 Annual maxima, 1-day mean 0,06 0,41 0,22

IHA19 Annual maxima, 3-day means 0,05 0,41 0,23




IHA23 Number of zero-flow days days 0,58 - -

IHA24 Base flow index -- 0,02 0,32 0,30

IHA25 Julian date of each annual 1-day minimum 0,28 0,98 0,99

IHA26 Julian date of each annual 1-day maximum 0,44 0,97 0,56

IHA27 Number of low pulses -- 0,03 0,67 0,60

IHA28 Median duration of low pulses days 0,06 0,39 0,35

IHA29 Number of high pulses -- 0,16 0,61 0,86

IHA30 Median duration of high pulses days 0,12 0,57 1,00

IHA31 Rise rates m³/s 0,15 0,23 0,25

IHA32 Fall rates m³/s 0,09 0,28 0,47

IHA33 Number of hydrologic reversals -- 0,04 0,76 0,94

0,55

1

2

3

4

5

0,56

0,420,10

0,09

days

0,49

0,56

0,77

0,70

Type of comparison

Temporal

(iii) Source: SNIRH

(Reconstruction based

on Fragas da Torre)

Indicator

0,980,36

0,23

0,22m³/s

Spatial Temporal

0,47

0,62

(ii) Source: SNIRH

(Covas)(i) Source: EDP

m³/s

48

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.

49

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

50

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.

51

BIBLIOGRAPHY

Alves, M. H. & Bernardo, J. M., 2002. Caudais Ecológicos em Portugal. Instituto da Água. PNA. Lisboa, Portugal.

Arthington, A. H., Bunn, S. H., Poff, N. L. & Naiman, R. J., 2006. The Challenge Of Providing Environmental Flow

Rules To Sustain River Ecosystems. Ecological Applications 16: 1311-1318.

Bejarano M. D., Sordo-Ward A., Marchamalo M. & González del Tánago M., 2012. Geomorphological Controls

on Vegetation Responses to Flow Alterations in a Mediterranean Stream (Central-Western Spain). River

Research and Applications. doi: 10.1002/rra.2608

Belmar Díaz Ó., 2013. Ecological Basis for Assessing Environmental Flow Regimes in the Segura Basin. PhD

Thesis. Universidad de Murcia, Spain.

Belmar Díaz, Ó., Bruno, D., Martínez-Capel, F., Barquín, J. & Velasco, J., 2013. Effects of flow regime alteration

on fluvial habitats and riparian quality in a semiarid Mediterranean basin. Ecological Indicators 30: 52-64.

Bisbane Declaration, 2007. [Online] Available at:

http://www.nature.org/initiatives/freshwater/files/bisbane_declaration_with_organizations_final.pdf

Bonsor, K., 2008. A Discovery Company. [Online]

Available at: http://science.howstuffworks.com/environmental/energy/hydropower-plant2.htm

Braatne, Jeffrey H., Rood, Stewart B., Goater, Lori A., Blair & Charles L., 2008. Analyzing the Impacts of Dams

on Riparian Ecosystems: A Review of Research Strategies and Their Relevance to the Snake River Through Hells

Canyon. Environmental Management 41: 267-281.

Branco, P., Segurado, P., Santos, J. M., Pinheiro, P. & Ferreira, M. T., 2012. Does longitudinal connectivity loss

affect the distribution of freshwater fish? Ecological Engineering 48: 70-78.

Bunn, S. E. & Arthington, A. H., 2002. Basic principles and ecological consequences of altered flow regimes for

aquatic biodiversity. Environmental Management 30: 492-507.

Comissão Nacional Portuguesa das Grandes Barragens [Online] Available at: http://cnpgb.inag.pt/

EDP, 2009. Declaração Ambiental 2009. Aproveitamentos Hidroeléctricos do Centro de Produção Mondego-

Tejo. Cascata da Serra da Estrela, Caldeirão/Aguieira, Raiva. EDP Produção, Portugal.

EDP [Online]

Available at: http://www.edp.pt

European Commission, 2000. Directive 2000/60/EC of the European Parliament and of the Council of 23

October 2000 establishing a framework for community action in the field of water policy. Off J Eur Communities

2000; L327:1-73.

52

Faria, F., 2003. O sistema electroprodutor da EDP. [Online]

Available at: http://www.historia-energia.com/imagens/conteudos/A2(FF).pdf

Greet, J., Coursens, R. D. & Webb, J. A., 2012. Flow regulation affects temporal patterns of riverine plant seed

dispersal: Potential implications for plant recruitment. Freshwater Biology 57: 2568-2579.

Martínez Santa-María, C., Fernández Yuste, J. & Magdaleno Mas, F., 2010. IAHRIS 2.2 Indicators of Hydrologic

Alteration in Rivers. User’s Manual. Gobierno de España, Spain.

Martínez Santa-María, C. & Fernández Yuste, J., 2006. Índices de alteración hidrológica en ecosistemas

fluviales. Mº Medio Ambiente, Spain.

Martins, João. 2012. Avaliação Ecohidrológica de Caudais Modificados e de Caudais Ecológicos em Troços de

Rios Fortemente Modificados. Master Thesis. Instituto Superior de Agronomia, Lisboa, Portugal.

Merritt, D. M., Scott, M. L., Poff, N. L., Auble, G. T. & Lytle, D. A., 2010. Theory, methods and tools for

determining environmental flows for riparian vegetation: riparian vegetation-flow response guilds. Freshwater

Biology: 206-225.

Nilsson, C. & Svedmark, M., 2002. Basic Principles and Ecological Consequences of Changing Water Regimes:

Riparian Plant Communities. Environmental Management 30: 468-480.

Poff, N. L., Allan, J. D., Bain, M. B., Karr, J. R., Prestegaard, K. L., Richter, B. D., Sparks, R. E. & Stromberg, J. C.,

1997. The Natural Flow Regime: A paradigm for river conservation and restoration. BioScience 47: 769-784.

Poff, N. L., Richter, B. D., Arthington, A. H., Bunn, S. E., Naiman, R. J., Kendy, E., Acreman, M., Apse, C.,

Bledsoe, B. P., Freeman, M. C., Henrinksen, J., Jacobson, R. B., Kennen, J. G., Merritt, D. M., O’Keeffe, J. H.,

Olden, J. D., Rogers, K., Tharme, R. E. & Warner, A., 2009. The ecological limits of hydrologic alteration

(ELOHA): a new framework for developing regional environmental flow standards. Freshwater Biology 55: 147-

170.

Poff, N. L. & Zimmerman, J. K. H., 2010. Ecological responses to altered flow regimes: a literature review to

inform the science and management of environmental flows. Freshwater Biology 55: 194-205.

Portela, M. M. & Quintela, A. C., 2005. Estimação de séries de caudais médios diários na ausência de

informação hidrométrica. 7º Simpósio de Hidráulica e Recursos Hídricos dos Países de Língua Oficial

Portuguesa. 7º SILUSBA, Évora, Portugal.

Richter, B. D., Baumgartner, J. V., Powell, J. & Braun, D. P., 1996. A Method for Assessing Hydrologic

Alteration within Ecosystems.Conservation Biology 10: 1163-1174. .

Rood, S. B., Braatne, J. H. & Goater, L. A., 2010. Responses of obligate versus facultative riparian shrubs

following river damming. River Research and Applications 26: 102-117.

53

Stromberg , J. C., Lite, S.J., Marler, R., Paradzick, C., Shafroth, P.B., Shorrock, D., White, J.M. & White, M.S.,

2007. Altered stream-flow regimes and invasive plant species: the Tamarix case. Global Ecology and

Biogeography 16: 381-393.

Tharme, R. E., 2003. A global perspective on environmental flow assessment: Emerging trends in the

development and application of environmental flow methodologies for rivers. River Research and Applications

19: 397-441.

The International Commission on Large Dams - ICOLD [Online]

Available at: http://icold-cigb.net

The Nature Conservancy, 2009. Indicators of Hydrologic Alteration Version 7.1. User's Manual.

The Nature Conservancy, Nature Conservancy’s Conservation Gateway. [Online]

Available at: http://www.conservationgateway.org

World Bank Group. The World Bank. [Online]

Available at: http://www.worldbank.org/en/topic/water/

World Commission on Dams, 2000. Dams and development. A new framework for decision-making. World

Commission on Dams. Earthscan Publishing, London, UK.

Portuguese Legislation:

Lei n.º 58/2005 de 29 de Dezembro (“Lei da Água”), Diário da República, I Série -A n.º 249: 7280-7310.

Lei n.º 7/2008 de 15 de Fevereiro, Diário da República, 1.ª série, n.º 33: 1024-1032.

Portaria n.º 1450/2007 de 12 de Novembro de 2007, Diário da República, 1.ª série, n.º 217: 8372-8382.

Decreto-Lei n.º 311/2007 de 17 de Setembro de 2007, Diário da República, 1.ª série, n.º 179: 6513-6518.

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

iii

Appendix A. 1 (1/2) - Web diagrams for the dimensionless 25% and 75% percentiles for the nine case studies (followed by the respective legend).

Group 1 Group 2 Group 4 Group 5 Group 1 Group 2 Group 4 Group 5

Case study number 1: Alto

Lindoso

Case study number 2:

Touvedo


Vilarinho das Furnas


Paradela

Case study number 5: Vilar

75% percentile25% percentile

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 300,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 300,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 30 0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 300,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA

10

IHA

11

IHA

12

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA10

IHA11

IHA12

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 300,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 300,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

iv

Appendix A. 1 (2/2) - Web diagrams for the dimensionless 25% and 75% percentiles for the nine case studies (followed by the respective legend).

Group 1 Group 2 Group 4 Group 5 Group 1 Group 2 Group 4 Group 5


Caldeirão

Case study number 7: Fronhas

Case study number 8: Cabril

Case study number 9: Pracana

25% percentile 75% percentile

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA10

IHA11

IHA12

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA10

IHA11

IHA12

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA10

IHA11

IHA12

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA10

IHA11

IHA12

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

Group Group Group













2

IHA

Legend:

Web

ind

ex -

ind

icat

or

corr

esp

on

den

ce

4

5

IHA IHA

1

v

Appendix A. 2 (1/2) - Web diagrams representative of the dimensionless median values for the nine case studies (followed by the

respective legend).



Alto Lindoso


Touvedo


Vilarinho das Furnas


Paradela


Vilar

0,0

0,2

0,4

0,6

0,8

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

0,0

0,2

0,4

0,6

0,8

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

0,0

0,2

0,4

0,6

0,8

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

0,0

0,2

0,4

0,6

0,8

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

0,0

0,2

0,4

0,6

0,8

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

vi

Appendix A. 2 (2/2) - Web diagrams representative of the dimensionless median values for the nine case studies (followed by the

respective legend).



Caldeirão


Fronhas


Cabril


Pracana

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

Group Group













Legend:

Web

ind

ex -

ind

icat

or

corr

esp

on

den

ce

IHA IHA

1

2

vii

Appendix A. 3 (1/3) - Dimensionless flow duration curves for the natural and modified regimes for the nine case

studies.

Legend:

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

)

Days

Case study number 1: Alto Lindoso

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

Days

Case study number 2: Touvedo

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

Days

Case study number 3: Vilarinho das Furnas

viii


studies.

Legend:

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

)

Days

Case study number 4: Paradela

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

)

Days


0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

)

Days

Case study number 6: Caldeirão

ix


studies.

Legend:

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

)

Days

Case number 7: Fronhas

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

)

Days


0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,00

4,50

5,00

0 50 100 150 200 250 300 350

Dai

ly f

low

(m

3/s

)

Days


x

Appendix A. 4 (1/3) - Monthly mean daily flows for the natural and modified regimes for the nine case studies.

Legend:

0102030405060708090

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3/s

)

Month

Case study number 1: Alto Lindoso

0

20

40

60

80

100

120

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3 /s)

Month

Case study number 2: Touvedo

0

1

2

3

4

5

6

7

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3/s

)

Month

Case study number 3: Vilarinho das Furnas

xi


Legend:

0

1

2

3

4

5

6

7

8

9

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3/s

)

Month

Case study number 4: Paradela

0

1

2

3

4

5

6

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3/s

)

Month


01122334455

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3/s

)

Month

Case study number 6: Caldeirão

xii


Legend:

0

5

10

15

20

25

30

35

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3/s

)

Month

Case study number 7: Fronhas

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3/s

)

Month


0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3/s

)

Month


x i i i

A p p e n d i x A . 5 - R a t i o s o f a l t e r a t i o n ( R 3 ) f o r t h e n i n e c a s e s t u d i e s .

Low alteration: RA3 > 0,67;

Moderate alteration: 0,67 > RA3 > 0,33; High alteration: RA3 < 0,33

1 2 3 4 5 6 7 8 9

GroupAlto

LindosoTouvedo

Vilarinho

das FurnasParadela Vilar Caldeirão Fronhas Cabril Pracana

IHA1 January 0,86 0,94 0,05 0,00 0,00 0,00 0,29 0,95 0,62

IHA2 February 0,94 0,91 0,07 0,00 0,00 0,00 0,12 0,76 0,74

IHA3 March 0,72 0,83 0,09 0,00 0,00 0,00 0,13 0,94 0,68

IHA4 April 0,86 0,93 0,09 0,00 0,00 0,00 0,00 0,76 0,93

IHA5 May 1,00 0,65 0,15 0,00 0,00 0,00 0,00 0,66 0,14

IHA6 June 0,96 0,74 0,30 0,05 0,00 0,00 0,00 0,53 0,00

IHA7 July 0,76 0,84 0,39 0,31 0,00 0,00 0,00 0,15 0,00

IHA8 August 0,64 0,81 0,51 0,84 0,00 0,00 0,00 0,10 0,00

IHA9 September 0,39 0,71 0,70 0,74 0,00 0,00 0,00 0,20 0,00

IHA10 October 0,63 0,60 0,12 0,00 0,00 0,00 0,00 0,39 0,35

IHA11 November 0,96 0,76 0,10 0,00 0,00 0,00 0,00 0,80 0,79

IHA12 December 0,90 0,70 0,08 0,00 0,00 0,00 0,00 1,00 0,55

IHA13 Annual minima, 1-day mean 0,00 0,00 0,05 - 0,00 0,00 0,00 - -

IHA14 Annual minima, 3-day means 0,00 0,00 0,26 - 0,00 0,00 0,00 0,00 -

IHA15 Annual minima, 7-day means 0,27 0,11 0,34 0,00 0,00 0,00 0,00 0,74 -

IHA16 Annual minima, 30-day means 0,89 0,60 0,86 0,00 0,00 0,00 0,00 0,33 0,88

IHA17 Annual minima, 90-day means 0,74 0,72 0,38 0,00 0,00 0,00 0,00 0,31 0,14

IHA18 Annual maxima, 1-day mean 0,75 0,87 0,06 0,09 0,18 0,21 0,43 0,84 0,72

IHA19 Annual maxima, 3-day means 0,83 1,00 0,05 0,12 0,15 0,14 0,61 0,81 0,87




IHA23 Number of zero-flow days days 0,01 0,02 0,58 0,19 0,02 0,02 0,01 0,28 0,51

IHA24 Base flow index - 0,28 0,12 0,02 0,00 0,00 0,00 0,00 0,30 -

IHA25 Julian date of each annual 1-day minimum 0,21 0,31 0,28 0,01 0,01 0,01 0,03 0,45 0,08

IHA26 Julian date of each annual 1-day maximum 0,80 0,84 0,44 0,59 0,13 0,42 0,67 0,58 0,79

IHA27 Number of low pulses - 0,62 0,96 0,03 0,00 0,00 0,00 0,00 0,89 -

IHA28 Median duration of low pulses days 0,92 0,71 0,06 0,00 0,00 0,00 0,00 1,00 -

IHA29 Number of high pulses - 0,37 0,96 0,16 0,37 0,09 0,06 0,21 0,46 0,35

IHA30 Median duration of high pulses days 0,59 0,80 0,12 0,87 0,16 0,83 0,64 0,39 0,22

IHA31 Rise rates m³/s 0,30 0,99 0,15 0,78 0,06 0,04 0,08 0,31 0,14

IHA32 Fall rates m³/s 0,34 0,99 0,09 0,53 0,06 0,06 0,18 0,37 0,19

IHA33 Number of hydrologic reversals - 0,99 0,88 0,04 0,09 0,01 0,00 0,05 0,95 0,69

3

4

5

m³/s

m³/s

days

IHA

1

2

x i v

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

iii

Appendix B. 1 - Web diagrams for the dimensionless 25% and 75% percentiles for Covas and EDP data (followed by

respective legend).

25

% p

erce

nti

le7

5%

per

cen

tile

25

% p

erce

nti

le7

5%

per

cen

tile

According to Covas stream gauging station

data

According to EDP data

Group 1 Group 2 Group 4 Group 5Vilarinho das Furnas case study

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 300,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 300,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

0,5

1,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,2

0,4

0,6

0,8

1,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

0,0

1,0

2,0

3,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 23

IHA 24

0,0

0,5

1,0

1,5

2,0IHA 27

IHA 28

IHA 29

IHA 30

0,0

0,5

1,0

1,5

2,0IHA 31

IHA 32IHA 33

Group Group Group













2

IHA

Legend:

Web

ind

ex -

ind

icat

or

corr

esp

on

den

ce

4

5

IHA IHA

1

iv

Appendix B. 2 - Web diagrams representative of the dimensionless median values for Covas and EDP data (followed by

respective legend).

According to Covas

stream gauging station

data

According to EDP data

Group 1 Groups 2 and 5 (Those envolving flows)Vilarinho das Furnas case

study

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

0,0

0,5

1,0IHA 1

IHA 2

IHA 3

IHA 4

IHA 5

IHA 6

IHA 7

IHA 8

IHA 9

IHA 10

IHA 11

IHA 12

0,0

1,0

2,0

3,0

4,0

5,0IHA 13

IHA 14

IHA 15

IHA 16

IHA 17

IHA 18

IHA 19

IHA 20

IHA 21

IHA 22

IHA 31

IHA 32

Group Group













Legend:

Web

ind

ex -

ind

icat

or

corr

esp

on

den

ce

IHA IHA

1

2

v

Appendix B. 3 - Monthly mean daily flows for the natural and the modified regimes for Covas and EDP data.

Legend:

0

1

2

3

4

5

6

7

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3 /s)

Month

Case study: Vilarinho das Furnas according to EDP

0

1

2

3

4

5

6

7

8

9

1 2 3 4 5 6 7 8 9 10 11 12

Dai

ly f

low

(m

3 /s)

Month

Case study: Vilarinho das furnas according to Covas stream gauging station

vi

Documents

Development of indexes of alteration of the hydrologic ...€¦ · to the research carried out. Artur Silva also deserves a word of acknowledgement, given his availability and support